Optimal day-ahead operational planning of microgrids

International Nuclear Information System (INIS)

Hosseinnezhad, Vahid; Rafiee, Mansour; Ahmadian, Mohammad; Siano, Pierluigi

2016-01-01

Highlights: • A new multi-objective model for optimal day-ahead operational planning of microgrids is proposed. • A new concept called seamlessness is introduced to control the sustainability of microgrid. • A new method is developed to manage the load and renewable energy resources estimation errors. • A new solution based on a combination of numerical and evolutionary approaches is proposed. - Abstract: Providing a cost-efficient, eco-friendly and sustainable energy is one of the main issues in modern societies. In response to this demand, new features of microgrid technology have provided huge potentials while distributing electricity more effectively, economically and securely. Accordingly, this paper presents a new multi-objective generation management model for optimal day-ahead operational planning of medium voltage microgrids. The proposed model optimizes both pollutant emission and operating cost of a microgrid by using multi-objective optimization. Besides, a seamlessness-selective algorithm is integrated into the model, which can be adopted to achieve the desired self-sufficiency level for microgrids along a specified planning horizon. Furthermore, the model is characterized by a reserve-assessment strategy developed to handle the load and renewable energy resources estimation errors. The introduced model is solved using a combination of numerical and evolutionary methods of species-based quantum particle swarm optimization to find the optimal scheduling scheme and minos-based optimal power flow to optimize the operating cost and emission. In addition, the suggested solution approach also incorporates an efficient mechanism for considering energy storage systems and coding the candidate solutions in the evolutionary algorithm. The proposed model is implemented on a test microgrid and is investigated through simulations to study the different aspects of the problem. The results show significant improvements and benefits which are obtained by

Day-ahead tariffs for the alleviation of distribution grid congestion from electric vehicles

DEFF Research Database (Denmark)

O'Connell, Niamh; Wu, Qiuwei; Østergaard, Jacob

2012-01-01

An economically efficient day-ahead tariff (DT) is proposed with the purpose of preventing the distribution grid congestion resulting from electric vehicle (EV) charging scheduled on a dayahead basis. The DT concept developed herein is derived from the locational marginal price (LMP), in particular...... the congestion cost component of the LMP. A step-wise congestion management structure has been developed whereby the distribution system operator (DSO) predicts congestion for the coming day and publishes DTs prior to the clearing of the day-ahead market. EV fleet operators (FOs) optimize their EV charging...... schedules with respect to the predicted day-ahead prices and the published DTs, thereby avoiding congestion while still minimizing the charging cost. A Danish 400V distribution network is used to carry out case studies to illustrate the effectiveness of the developed concept for the prevention...

Day-ahead wind speed forecasting using f-ARIMA models

International Nuclear Information System (INIS)

Kavasseri, Rajesh G.; Seetharaman, Krithika

2009-01-01

With the integration of wind energy into electricity grids, it is becoming increasingly important to obtain accurate wind speed/power forecasts. Accurate wind speed forecasts are necessary to schedule dispatchable generation and tariffs in the day-ahead electricity market. This paper examines the use of fractional-ARIMA or f-ARIMA models to model, and forecast wind speeds on the day-ahead (24 h) and two-day-ahead (48 h) horizons. The models are applied to wind speed records obtained from four potential wind generation sites in North Dakota. The forecasted wind speeds are used in conjunction with the power curve of an operational (NEG MICON, 750 kW) turbine to obtain corresponding forecasts of wind power production. The forecast errors in wind speed/power are analyzed and compared with the persistence model. Results indicate that significant improvements in forecasting accuracy are obtained with the proposed models compared to the persistence method. (author)

Agent-Based Modeling of Day-Ahead Real Time Pricing in a Pool-Based Electricity Market

Directory of Open Access Journals (Sweden)

Sh. Yousefi

2011-09-01

Full Text Available In this paper, an agent-based structure of the electricity retail market is presented based on which day-ahead (DA energy procurement for customers is modeled. Here, we focus on operation of only one Retail Energy Provider (REP agent who purchases energy from DA pool-based wholesale market and offers DA real time tariffs to a group of its customers. As a model of customer response to the offered real time prices, an hourly acceptance function is proposed in order to represent the hourly changes in the customer’s effective demand according to the prices. Here, Q-learning (QL approach is applied in day-ahead real time pricing for the customers enabling the REP agent to discover which price yields the most benefit through a trial-and-error search. Numerical studies are presented based on New England day-ahead market data which include comparing the results of RTP based on QL approach with that of genetic-based pricing.

Powernext Day-AheadTM statistics - June 30, 2006

International Nuclear Information System (INIS)

2006-01-01

The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead TM since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures TM since 18 June 2004. This document presents in a series of tables and graphics the June 30, 2006 update of Powernext Day-Ahead TM statistics: daily traded volumes and base-load prices from November 2001 to June 2006, monthly overview from June 2005 to June 2006 (volumes and prices), weekly overview from March to June 2006 (volumes and prices), daily and hourly overview and market resilience for June 2006, power consumption in May and June 2006 (average consumption, average forecasted consumption and average price on Powernext Day-Ahead TM ), power consumption on the French hub from July 2005 to May 2006 and Powernext Day-Ahead TM prices, transfer capacities in June 2006 (auction results for France-Germany, France-Belgium, France-UK, France-Spain and France-Italy, and daily capacity allocation for France-Switzerland), temperature variations in France from January 2005 to June 2006 and base-load Powernext Day-Ahead TM prices, and balancing mechanism for April, May and June 2006 (half-hourly imbalance settlement prices). (J.S.)

Hourly Electricity Prices in Day-Ahead Markets

NARCIS (Netherlands)

R. Huisman (Ronald); C. Huurman; R.J. Mahieu (Ronald)

2007-01-01

textabstractThis paper focuses on the characteristics of hourly electricity prices in day-ahead markets. In these markets, quotes for day-ahead delivery of electricity are submitted simultaneously for all hours in the next day. The same information set is used for quoting all hours of the day. The

Risk-constrained dynamic self-scheduling of a pumped-storage plant in the energy and ancillary service markets

International Nuclear Information System (INIS)

Kazempour, S. Jalal; Moghaddam, M. Parsa; Haghifam, M.R.; Yousefi, G.R.

2009-01-01

This work addresses a new framework for self-scheduling of an individual price-taker pumped-storage plant in a day-ahead (DA) market. The goal is achieving the best trade-off between the expected profit and the risks when the plant participates in DA energy, spinning reserve and regulation markets. In this paper, a set of uncertainties including price forecasting errors and also the uncertainty of power delivery requests in the ancillary service markets are contemplated. Considering these uncertainties, a new approach is proposed which is called dynamic self-scheduling (DSS). This risk-constrained dynamic self-scheduling problem is therefore formulated and solved as a mixed integer programming (MIP) problem. Numerical results for a case study are discussed. (author)

Aggregators’ Optimal Bidding Strategy in Sequential Day-Ahead and Intraday Electricity Spot Markets

Directory of Open Access Journals (Sweden)

Xiaolin Ayón

2017-04-01

Full Text Available This paper proposes a probabilistic optimization method that produces optimal bidding curves to be submitted by an aggregator to the day-ahead electricity market and the intraday market, considering the flexible demand of his customers (based in time dependent resources such as batteries and shiftable demand and taking into account the possible imbalance costs as well as the uncertainty of forecasts (market prices, demand, and renewable energy sources (RES generation. The optimization strategy aims to minimize the total cost of the traded energy over a whole day, taking into account the intertemporal constraints. The proposed formulation leads to the solution of different linear optimization problems, following the natural temporal sequence of electricity spot markets. Intertemporal constraints regarding time dependent resources are fulfilled through a scheduling process performed after the day-ahead market clearing. Each of the different problems is of moderate dimension and requires short computation times. The benefits of the proposed strategy are assessed comparing the payments done by an aggregator over a sample period of one year following different deterministic and probabilistic strategies. Results show that probabilistic strategy reports better benefits for aggregators participating in power markets.

Risk-constrained self-scheduling of a fuel and emission constrained power producer using rolling window procedure

International Nuclear Information System (INIS)

Kazempour, S. Jalal; Moghaddam, Mohsen Parsa

2011-01-01

This work addresses a relevant methodology for self-scheduling of a price-taker fuel and emission constrained power producer in day-ahead correlated energy, spinning reserve and fuel markets to achieve a trade-off between the expected profit and the risk versus different risk levels based on Markowitz's seminal work in the area of portfolio selection. Here, a set of uncertainties including price forecasting errors and available fuel uncertainty are considered. The latter uncertainty arises because of uncertainties in being called for reserve deployment in the spinning reserve market and availability of power plant. To tackle the price forecasting errors, variances of energy, spinning reserve and fuel prices along with their covariances which are due to markets correlation are taken into account using relevant historical data. In order to tackle available fuel uncertainty, a framework for self-scheduling referred to as rolling window is proposed. This risk-constrained self-scheduling framework is therefore formulated and solved as a mixed-integer non-linear programming problem. Furthermore, numerical results for a case study are discussed. (author)

How Does Pricing of Day-ahead Electricity Market Affect Put Option Pricing?

Directory of Open Access Journals (Sweden)

H. Raouf Sheybani

2016-09-01

Full Text Available In this paper, impacts of day-ahead market pricing on behavior of producers and consumers in option and day-ahead markets and on option pricing are studied. To this end, two comprehensive equilibrium models for joint put option and day-ahead markets under pay-as-bid and uniform pricing in day-ahead market are presented, respectively. Interaction between put option and day-ahead markets, uncertainty in fuel price, day-ahead market pricing, and elasticity of consumers to strike price, premium price, and day-ahead price are taken into account in these models. By applying the presented models to a test system impact of day-ahead market pricing on equilibrium of joint put option and day-ahead markets are studied.

Powernext Day-AheadTM. Powernext futuresTM. Activity report - 2004

International Nuclear Information System (INIS)

2004-01-01

The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing the French power exchange through an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead TM since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures TM since 18 June 2004. This document is the 2004 activity report of Powernext SA, it presents the key figures of the power market and of Powernext in 2004: - Increasing volumes: Powernext Day-Ahead TM 's traded volumes increased by 89%, from 7.48 to 14.18 TWh. Powernext Futures TM kicks off to a promising debut with 12.86 TWh traded in less than 7 months. - Less volatile prices: During 2004, the base price averaged 28.13 euro/MWh, and the peak prices averaged 33.71 euro/MWh. Compared to 2003, these prices decreased by an average of 3.7% on base-load and 10.9% on peak-load. In comparison to the two previous years, the daily volatility has noticeably settled down with 27% on base-load and 37% on peak-load. - Increasing liquidity: 10 new members joined Powernext Day-Ahead TM in 2004. The activity level of the members remains very high as 89% of them trade on an actual daily basis during 2004. The market resiliency stays strong. In December, an additional market 50 MW order on each hour resulted in a balance price variation of only 0.16 euro/MWh, or 0.53% of this balance price. For a 100 MW order, the resiliency is 0.32 euro/MWh, or 1.07% of the balance price. Thus, in 2004, Powernext Day-Ahead TM consolidates its role as a short term reference price. Moreover, in 2004, Powernext launched a futures market, Powernext Futures TM . This new market segment proposes contracts tradable up to 2 years ahead of delivery

Powernext Day-AheadTM statistics April 30, 2005

International Nuclear Information System (INIS)

2005-04-01

The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead TM since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures TM since 18 June 2004. This document presents in a series of tables and graphics the April 30, 2005 update of Powernext Day-Ahead TM statistics: traded volumes and average prices from November 2001 to April 2005, monthly overview from April 2004 to April 2005 (volumes, prices and price spreads), weekly overview from January to April 2005, daily and hourly overview and market resilience for April 2005, power consumption in March and April 2005 (average consumption, average forecasted consumption and average price on Powernext Day-Ahead TM ), power consumption on the French hub from January to April 2005 and Powernext Day-Ahead TM prices, transfer capacities in April 2005 (daily capacity allocations for France-Germany, France-Switzerland and France-Spain, daily and monthly capacity allocations for France-Belgium, auction on the France-UK Interconnector, daily and yearly capacity allocation for France-Italy), temperature variations in France from November 2004 to April 2005 and average prices on Powernext Day-Ahead TM , and balancing mechanism for March-April 2005 (half-hourly imbalance settlement prices). (J.S.)

Value of Flexible Resources, Virtual Bidding, and Self-Scheduling in Two-Settlement Electricity Markets With Wind Generation – Part I: Principles and Competitive Model

DEFF Research Database (Denmark)

Kazempour, Jalal; Hobbs, Benjamin F.

2017-01-01

Part one of this two-part paper presents new models for evaluating flexible resources in two-settlement electricity markets (day-ahead and real-time) with uncertain net loads (demand minus wind). Physical resources include wind together with fast- and slow-start demand response and thermal...... of certain equivalencies of the four models. We show how virtual bidding enhances market performance, since, together with self-scheduling by slow-start generators, it can help deterministic day-ahead market to choose the most efficient unit commitment....

Deriving Optimal End of Day Storage for Pumped-Storage Power Plants in the Joint Energy and Reserve Day-Ahead Scheduling

Directory of Open Access Journals (Sweden)

Manuel Chazarra

2017-06-01

Full Text Available This paper presents a new methodology to maximise the income and derive the optimal end of day storage of closed-loop and daily-cycle pumped-storage hydropower plants. The plants participate in the day-ahead energy market as a price-taker and in the secondary regulation reserve market as a price-maker, in the context of the Iberian electricity system. The real-time use of the committed reserves is considered in the model formulation. The operation of the plants with the proposed methodology is compared to the ones that use an end of day storage of an empty reservoir or half of the storage capacity. Results show that the proposed methodology increases the maximum theoretical income in all the plants analysed both if they only participate in the day-ahead energy market and if they also participate in the secondary regulation service. It is also shown that the increase in the maximum theoretical income strongly depends on the size of the plant. In addition, it is proven that the end of day storages change notably in the new reserve-driven strategies of pumped-storage hydropower plants and that the proposed methodology is even more recommended if the secondary regulation service is considered.

Stochastic multiobjective self-scheduling of a power producer in joint energy and reserves markets

International Nuclear Information System (INIS)

Vahidinasab, V.; Jadid, S.

2010-01-01

This paper presents a stochastic multiobjective model for self-scheduling of a power producer which participates in the day-ahead joint energy and reserves markets. The objective of a power producer is to compromise the conflicting objectives of payoff maximization and gaseous emissions minimization when committing its generation of thermal units. The proposed schedule will be used by the power producers to decide on emission quota arbitrage opportunities and for strategic bidding to the energy and reserves market. The paper analyzes a scenario-based multiobjective model in which random distributions, such as price forecasting inaccuracies as well as forced outage of generating units are modeled as scenarios tree using a combined fuzzy c-mean/Monte-Carlo simulation (FCM/MCS) method. With the above procedure the stochastic multiobjective self-scheduling problem is converted into corresponding deterministic problems. Then a multiobjective mathematical programming (MMP) approach based on ε-constraint method is implemented for each deterministic scenario. Piecewise linearized fuel and emission cost functions are applied for computational efficiency and the model is formulated as a mixed-integer programming (MIP) problem. Numerical simulations for a power producer with 21 thermal units are discussed to demonstrate the performance of the proposed approach in increasing expected payoffs by adjusting the emission quota arbitrage opportunities. (author)

A Unified Trading Model Based on Robust Optimization for Day-Ahead and Real-Time Markets with Wind Power Integration

DEFF Research Database (Denmark)

Jiang, Yuewen; Chen, Meisen; You, Shi

2017-01-01

In a conventional electricity market, trading is conducted based on power forecasts in the day-ahead market, while the power imbalance is regulated in the real-time market, which is a separate trading scheme. With large-scale wind power connected into the power grid, power forecast errors increase...... in the day-ahead market which lowers the economic efficiency of the separate trading scheme. This paper proposes a robust unified trading model that includes the forecasts of real-time prices and imbalance power into the day-ahead trading scheme. The model is developed based on robust optimization in view...... of the undefined probability distribution of clearing prices of the real-time market. For the model to be used efficiently, an improved quantum-behaved particle swarm algorithm (IQPSO) is presented in the paper based on an in-depth analysis of the limitations of the static character of quantum-behaved particle...

Day-Ahead Probabilistic Model for Scheduling the Operation of a Wind Pumped-Storage Hybrid Power Station: Overcoming Forecasting Errors to Ensure Reliability of Supply to the Grid

Directory of Open Access Journals (Sweden)

Jakub Jurasz

2018-06-01

Full Text Available Variable renewable energy sources (VRES, such as solarphotovoltaic (PV and wind turbines (WT, are starting to play a significant role in several energy systems around the globe. To overcome the problem of their non-dispatchable and stochastic nature, several approaches have been proposed so far. This paper describes a novel mathematical model for scheduling the operation of a wind-powered pumped-storage hydroelectricity (PSH hybrid for 25 to 48 h ahead. The model is based on mathematical programming and wind speed forecasts for the next 1 to 24 h, along with predicted upper reservoir occupancy for the 24th hour ahead. The results indicate that by coupling a 2-MW conventional wind turbine with a PSH of energy storing capacity equal to 54 MWh it is possible to significantly reduce the intraday energy generation coefficient of variation from 31% for pure wind turbine to 1.15% for a wind-powered PSH The scheduling errors calculated based on mean absolute percentage error (MAPE are significantly smaller for such a coupling than those seen for wind generation forecasts, at 2.39% and 27%, respectively. This is even stronger emphasized by the fact that, those for wind generation were calculated for forecasts made for the next 1 to 24 h, while those for scheduled generation were calculated for forecasts made for the next 25 to 48 h. The results clearly show that the proposed scheduling approach ensures the high reliability of the WT–PSH energy source.

Self-Reported Recovery from 2-Week 12-Hour Shift Work Schedules: A 14-Day Follow-Up

NARCIS (Netherlands)

Merkus, S.L.; Holte, K.A.; Huysmans, M.A.; van de Ven, P.M.; van Mechelen, W.; van der Beek, A.J.

2015-01-01

Background Recovery from fatigue is important in maintaining night workers' health. This study compared the course of self-reported recovery after 2-week 12-hour schedules consisting of either night shifts or swing shifts (i.e., 7 night shifts followed by 7 day shifts) to such schedules consisting

Real-time Energy Resource Scheduling considering a Real Portuguese Scenario

DEFF Research Database (Denmark)

Silva, Marco; Sousa, Tiago; Morais, Hugo

2014-01-01

The development in power systems and the introduction of decentralized gen eration and Electric Vehicles (EVs), both connected to distribution networks, represents a major challenge in the planning and operation issues. This new paradigm requires a new energy resources management approach which...... scheduling in smart grids, considering day - ahead, hour - ahead and real - time scheduling. The case study considers a 33 - bus distribution network with high penetration of distributed energy resources . The wind generation profile is base d o n a rea l Portuguese wind farm . Four scenarios are presented...... taking into account 0, 1, 2 and 5 periods (hours or minutes) ahead of the scheduling period in the hour - ahead and real - time scheduling...

A Unified Trading Model Based on Robust Optimization for Day-Ahead and Real-Time Markets with Wind Power Integration

Directory of Open Access Journals (Sweden)

Yuewen Jiang

2017-04-01

Full Text Available In a conventional electricity market, trading is conducted based on power forecasts in the day-ahead market, while the power imbalance is regulated in the real-time market, which is a separate trading scheme. With large-scale wind power connected into the power grid, power forecast errors increase in the day-ahead market which lowers the economic efficiency of the separate trading scheme. This paper proposes a robust unified trading model that includes the forecasts of real-time prices and imbalance power into the day-ahead trading scheme. The model is developed based on robust optimization in view of the undefined probability distribution of clearing prices of the real-time market. For the model to be used efficiently, an improved quantum-behaved particle swarm algorithm (IQPSO is presented in the paper based on an in-depth analysis of the limitations of the static character of quantum-behaved particle swarm algorithm (QPSO. Finally, the impacts of associated parameters on the separate trading and unified trading model are analyzed to verify the superiority of the proposed model and algorithm.

Powernext Day-AheadTM products and market organization

International Nuclear Information System (INIS)

2004-06-01

The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing the French power exchange through an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead TM since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures TM since 18 June 2004. This document presents the principle of the trading of hourly contracts on Powernext Day-Ahead TM , the accessibility of the market, the SAPRI trading platform operated by Nord Pool, the Scandinavian power exchange, the validation of the auction results, the collaboration with LCH.Clearnet SA to secure and facilitate the transactions, and the delivery guarantee implemented by RTE (the French energy transport network). (J.S.)

Optimal day-ahead wind-thermal unit commitment considering statistical and predicted features of wind speeds

International Nuclear Information System (INIS)

Sun, Yanan; Dong, Jizhe; Ding, Lijuan

2017-01-01

Highlights: • A day–ahead wind–thermal unit commitment model is presented. • Wind speed transfer matrix is formed to depict the sequential wind features. • Spinning reserve setting considering wind power accuracy and variation is proposed. • Verified study is performed to check the correctness of the program. - Abstract: The increasing penetration of intermittent wind power affects the secure operation of power systems and leads to a requirement of robust and economic generation scheduling. This paper presents an optimal day–ahead wind–thermal generation scheduling method that considers the statistical and predicted features of wind speeds. In this method, the statistical analysis of historical wind data, which represents the local wind regime, is first implemented. Then, according to the statistical results and the predicted wind power, the spinning reserve requirements for the scheduling period are calculated. Based on the calculated spinning reserve requirements, the wind–thermal generation scheduling is finally conducted. To validate the program, a verified study is performed on a test system. Then, numerical studies to demonstrate the effectiveness of the proposed method are conducted.

Real-time versus day-ahead market power in a hydro-based electricity market

OpenAIRE

Tangerås, Thomas P.; Mauritzen, Johannes

2014-01-01

We analyse in a theoretical framework the link between real-time and day-ahead market performance in a hydro-based and imperfectly competitive wholesale electricity market. Theoretical predictions of the model are tested on data from the Nordic power exchange, Nord Pool Spot (NPS).We reject the hypothesis that prices at NPS were at their competitive levels throughout the period under examination. The empirical approach uses equilibrium prices and quantities and does not rely on bid data nor o...

Assessment of the Impact of Stochastic Day-Ahead SCUC on Economic and Reliability Metrics at Multiple Timescales: Preprint

Energy Technology Data Exchange (ETDEWEB)

Wu, H.; Ela, E.; Krad, I.; Florita, A.; Zhang, J.; Hodge, B. M.; Ibanez, E.; Gao, W.

2015-03-01

This paper incorporates the stochastic day-ahead security-constrained unit commitment (DASCUC) within a multi-timescale, multi-scheduling application with commitment, dispatch, and automatic generation control. The stochastic DASCUC is solved using a progressive hedging algorithm with constrained ordinal optimization to accelerate the individual scenario solution. Sensitivity studies are performed in the RTS-96 system, and the results show how this new scheduling application would impact costs and reliability with a closer representation of timescales of system operations in practice.

Forecasting Nord Pool day-ahead prices with an autoregressive model

International Nuclear Information System (INIS)

Kristiansen, Tarjei

2012-01-01

This paper presents a model to forecast Nord Pool hourly day-ahead prices. The model is based on but reduced in terms of estimation parameters (from 24 sets to 1) and modified to include Nordic demand and Danish wind power as exogenous variables. We model prices across all hours in the analysis period rather than across each single hour of 24 hours. By applying three model variants on Nord Pool data, we achieve a weekly mean absolute percentage error (WMAE) of around 6–7% and an hourly mean absolute percentage error (MAPE) ranging from 8% to 11%. Out of sample results yields a WMAE and an hourly MAPE of around 5%. The models enable analysts and traders to forecast hourly day-ahead prices accurately. Moreover, the models are relatively straightforward and user-friendly to implement. They can be set up in any trading organization. - Highlights: ► Forecasting Nord Pool day-ahead prices with an autoregressive model. ► The model is based on but with the set of parameters reduced from 24 to 1. ► The model includes Nordic demand and Danish wind power as exogenous variables. ► Hourly mean absolute percentage error ranges from 8% to 11%. ► Out of sample results yields a WMAE and an hourly MAPE of around 5%.

What day-ahead reserves are needed in electric grids with high levels of wind power?

International Nuclear Information System (INIS)

Mauch, Brandon; Apt, Jay; Jaramillo, Paulina; Carvalho, Pedro M S

2013-01-01

Day-ahead load and wind power forecasts provide useful information for operational decision making, but they are imperfect and forecast errors must be offset with operational reserves and balancing of (real time) energy. Procurement of these reserves is of great operational and financial importance in integrating large-scale wind power. We present a probabilistic method to determine net load forecast uncertainty for day-ahead wind and load forecasts. Our analysis uses data from two different electric grids in the US with similar levels of installed wind capacity but with large differences in wind and load forecast accuracy, due to geographic characteristics. We demonstrate that the day-ahead capacity requirements can be computed based on forecasts of wind and load. For 95% day-ahead reliability, this required capacity ranges from 2100 to 5700 MW for ERCOT, and 1900 to 4500 MW for MISO (with 10 GW of installed wind capacity), depending on the wind and load forecast values. We also show that for each MW of additional wind power capacity for ERCOT, 0.16–0.30 MW of dispatchable capacity will be used to compensate for wind uncertainty based on day-ahead forecasts. For MISO (with its more accurate forecasts), the requirement is 0.07–0.13 MW of dispatchable capacity for each MW of additional wind capacity. (letter)

Incentive-based demand response programs designed by asset-light retail electricity providers for the day-ahead market

DEFF Research Database (Denmark)

Fotouhi Ghazvini, Mohammad Ali; Faria, Pedro; Ramos, Sergio

2015-01-01

how a REP with light physical assets, such as DG (distributed generation) units and ESS (energy storage systems), can survive in a competitive retail market. The paper discusses the effective risk management strategies for the REPs to deal with the uncertainties of the DAM (day-ahead market) and how...... to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also...... taken into account with a scenario-based approach. The principal advantage of this model for REPs is reducing the risk of financial losses in DAMs, and the main benefit for the whole system is market power mitigation by virtually increasing the price elasticity of demand and reducing the peak demand....

Value of flexible resources, virtual bidding, and self-scheduling in two-settlement electricity markets with wind generation - Part II: ISO Models and Application

DEFF Research Database (Denmark)

Kazempour, Jalal; Hobbs, Benjamin F.

2017-01-01

In Part II of this paper, we present formulations for three two-settlement market models: baseline cost-minimization (Stoch-Opt); and two sequential market models in which an independent system operator (ISO) runs real-time (RT) balancing markets after making day-ahead (DA) generating unit...... commitment decisions based upon deterministic wind forecasts, while virtual bidders arbitrage the two markets (Seq and SeqSS). The latter two models differ in terms of whether some slow-start generators can self-schedule in the DA market while anticipating probabilities of RT prices. Models in Seq and Seq......-SS build on components of the two-settlement equilibrium model (Stoch-MP) defined in Part I of this paper [1]. We then provide numerical results for all four models. A simple single-node case illustrates the economic impacts of flexibility, virtual bidding, and self-schedules, and is followed by a larger...

Optimal operation and forecasting policy for pump storage plants in day-ahead markets

International Nuclear Information System (INIS)

Muche, Thomas

2014-01-01

Highlights: • We investigate unit commitment deploying stochastic and deterministic approaches. • We consider day-ahead markets, its forecast and weekly price based unit commitment. • Stochastic and deterministic unit commitment are identical for the first planning day. • Unit commitment and bidding policy can be based on the deterministic approach. • Robust forecasting models should be estimated based on the whole planning horizon. - Abstract: Pump storage plants are an important electricity storage technology at present. Investments in this technology are expected to increase. The necessary investment valuation often includes expected cash flows from future price-based unit commitment policies. A price-based unit commitment policy has to consider market price uncertainty and the information revealing nature of electricity markets. For this environment stochastic programming models are suggested to derive the optimal unit commitment policy. For the considered day-ahead price electricity market stochastic and deterministic unit commitment policies are comparable suggesting an application of easier implementable deterministic models. In order to identify suitable unit commitment and forecasting policies, deterministic unit commitment models are applied to actual day-ahead electricity prices of a whole year. As a result, a robust forecasting model should consider the unit commitment planning period. This robust forecasting models result in expected cash flows similar to realized ones allowing a reliable investment valuation

Day Ahead Real Time Pricing and Critical Peak Pricing Based Power Scheduling for Smart Homes with Different Duty Cycles

Directory of Open Access Journals (Sweden)

Nadeem Javaid

2018-06-01

Full Text Available In this paper, we propose a demand side management (DSM scheme in the residential area for electricity cost and peak to average ratio (PAR alleviation with maximum users’ satisfaction. For this purpose, we implement state-of-the-art algorithms: enhanced differential evolution (EDE and teacher learning-based optimization (TLBO. Furthermore, we propose a hybrid technique (HT having the best features of both aforementioned algorithms. We consider a system model for single smart home as well as for a community (multiple homes and each home consists of multiple appliances with different priorities. The priority is assigned (to each appliance by electricity consumers and then the proposed scheme finds an optimal solution according to the assigned priorities. Day-ahead real time pricing (DA-RTP and critical peak pricing (CPP are used for electricity cost calculation. To validate our proposed scheme, simulations are carried out and results show that our proposed scheme efficiently achieves the aforementioned objectives. However, when we perform a comparison with existing schemes, HT outperforms other state-of-the-art schemes (TLBO and EDE in terms of electricity cost and PAR reduction while minimizing the average waiting time.

Optimal Resources Planning of Residential Complex Energy System in a Day-ahead Market Based on Invasive Weed Optimization Algorithm

Directory of Open Access Journals (Sweden)

P. Αhmadi

2017-10-01

Full Text Available This paper deals with optimal resources planning in a residential complex energy system, including FC (fuel cell, PV (Photovoltaic panels and the battery. A day-ahead energy management system (EMS based on invasive weed optimization (IWO algorithm is defined for managing different resources to determine an optimal operation schedule for the energy resources at each time interval to minimize the operation cost of a smart residential complex energy system. Moreover, in this paper the impacts of the sell to grid and purchase from grid are also considered. All practical constraints of the each energy resources and utility policies are taken into account. Moreover, sensitivity analysis are conducted on electricity prices and sell to grid factor (SGF, in order to improve understanding the impact of key parameters on residential CHP systems economy. It is shown that proposed system can meet all electrical and thermal demands with economic point of view. Also enhancement of electricity price leads to substantial growth in utilization of proposed CHP system.

Day-ahead optimal dispatch for wind integrated power system considering zonal reserve requirements

International Nuclear Information System (INIS)

Liu, Fan; Bie, Zhaohong; Liu, Shiyu; Ding, Tao

2017-01-01

Highlights: • Analyzing zonal reserve requirements for wind integrated power system. • Modeling day-ahead optimal dispatch solved by chance constrained programming theory. • Determining optimal zonal reserve demand with minimum confidence interval. • Analyzing numerical results on test and large-scale real-life power systems. - Abstract: Large-scale integration of renewable power presents a great challenge for day-ahead dispatch to manage renewable resources while provide available reserve for system security. Considering zonal reserve is an effective way to ensure reserve deliverability when network congested, a random day-ahead dispatch optimization of wind integrated power system for a least operational cost is modeled including zonal reserve requirements and N − 1 security constraints. The random model is transformed into a deterministic one based on the theory of chance constrained programming and a determination method of optimal zonal reserve demand is proposed using the minimum confidence interval. After solving the deterministic model, the stochastic simulation is conducted to verify the validity of solution. Numerical tests and results on the IEEE 39 bus system and a large-scale real-life power system demonstrate the optimal day-ahead dispatch scheme is available and the proposed method is effective for improving reserve deliverability and reducing load shedding after large-capacity power outage.

Robust Optimization-Based Generation Self-Scheduling under Uncertain Price

Directory of Open Access Journals (Sweden)

Xiao Luo

2011-01-01

Full Text Available This paper considers generation self-scheduling in electricity markets under uncertain price. Based on the robust optimization (denoted as RO methodology, a new self-scheduling model, which has a complicated max-min optimization structure, is set up. By using optimal dual theory, the proposed model is reformulated to an ordinary quadratic and quadratic cone programming problems in the cases of box and ellipsoidal uncertainty, respectively. IEEE 30-bus system is used to test the new model. Some comparisons with other methods are done, and the sensitivity with respect to the uncertain set is analyzed. Comparing with the existed uncertain self-scheduling approaches, the new method has twofold characteristics. First, it does not need a prediction of distribution of random variables and just requires an estimated value and the uncertain set of power price. Second, the counterpart of RO corresponding to the self-scheduling is a simple quadratic or quadratic cone programming. This indicates that the reformulated problem can be solved by many ordinary optimization algorithms.

Integration of look-ahead multicast and unicast scheduling for input-queued cell switches

DEFF Research Database (Denmark)

Yu, Hao; Ruepp, Sarah Renée; Berger, Michael Stübert

2012-01-01

This paper presents an integration of multicast and unicast traffic scheduling algorithms for input-queued cell switches. The multi-level round-robin multicast scheduling (ML-RRMS) algorithm with the look-ahead (LA) mechanism provides a highly scalable architecture and is able to reduce the head...... module that filters out the conflicting requests to ensure fairness. Simulation results show that comparing with the scheme using WBA for the multicast scheduling, the scheme proposed in this paper reduces the HOL blocking problem for multicast traffic and provides a significant improvement in terms...

Incentive-based demand response programs designed by asset-light retail electricity providers for the day-ahead market

International Nuclear Information System (INIS)

Fotouhi Ghazvini, Mohammad Ali; Faria, Pedro; Ramos, Sergio; Morais, Hugo; Vale, Zita

2015-01-01

Following the deregulation experience of retail electricity markets in most countries, the majority of the new entrants of the liberalized retail market were pure REP (retail electricity providers). These entities were subject to financial risks because of the unexpected price variations, price spikes, volatile loads and the potential for market power exertion by GENCO (generation companies). A REP can manage the market risks by employing the DR (demand response) programs and using its' generation and storage assets at the distribution network to serve the customers. The proposed model suggests how a REP with light physical assets, such as DG (distributed generation) units and ESS (energy storage systems), can survive in a competitive retail market. The paper discusses the effective risk management strategies for the REPs to deal with the uncertainties of the DAM (day-ahead market) and how to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also taken into account with a scenario-based approach. The principal advantage of this model for REPs is reducing the risk of financial losses in DAMs, and the main benefit for the whole system is market power mitigation by virtually increasing the price elasticity of demand and reducing the peak demand. - Highlights: • Asset-light electricity retail providers subject to financial risks. • Incentive-based demand response program to manage the financial risks. • Maximizing the payoff of electricity retail providers in day-ahead market. • Mixed integer nonlinear programming to manage the risks

Day-ahead economic optimisation of energy storage

NARCIS (Netherlands)

Lampropoulos, I.; Garoufalis, P.; Bosch, van den P.P.J.; Groot, de R.J.W.; Kling, W.L.

2014-01-01

This article addresses the day-ahead economic optimisation of energy storage systems within the setting of electricity spot markets. The case study is about a lithium-ion battery system integrated in a low voltage distribution grid with residential customers and photovoltaic generation in the

Robust optimisation for self-scheduling and bidding strategies of hybrid CSP-fossil power plants

DEFF Research Database (Denmark)

Pousinho, H.M.I.; Contreras, J.; Pinson, P.

2015-01-01

between the molten-salt thermal energy storage (TES) and a fossil-fuel backup to overcome solar irradiation insufficiency, but with emission allowances constrained in the backup system to mitigate carbon footprint. A robust optimisation-based approach is proposed to provide the day-ahead self...

Coordination of bidding strategies in day-ahead energy and spinning reserve markets

International Nuclear Information System (INIS)

Fushuan Wen; David, A.K.

2002-01-01

In this paper, the problem of building optimally coordinated bidding strategies for competitive suppliers in day-ahead energy and spinning reserve markets is addressed. It is assumed that each supplier bids 24 linear energy supply functions and 24 linear spinning reserve supply functions, one for each hour, into the energy and spinning reserve markets, respectively, and each market is cleared separately and simultaneously for all the 24 delivery hours. Each supplier makes decisions on unit commitment and chooses the coefficients in the linear energy and spinning reserve supply functions to maximise total benefits, subject to expectations about how rival suppliers will bid in both markets. Two different bidding schemes have been suggested for each hour, and based on them an overall coordinated bidding strategy in the day-ahead energy and spinning reserve market is then developed. Stochastic optimisation models are first developed to describe these two different bidding schemes and a genetic algorithm (GA) is then used to build the optimally coordinated bidding strategies for each scheme and to develop an overall bidding strategy for the day-ahead energy and spinning reserve markets. A numerical example is utilised to illustrate the essential features of the method. (Author)

Everything you need to know to operate on Day-Ahead{sup TM}; Tout ce que vous devez savoir pour intervenir sur Powernext Day-Ahead{sup TM}

Energy Technology Data Exchange (ETDEWEB)

NONE

2005-05-15

The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing the French power exchange through an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead{sup TM} since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures{sup TM} since 18 June 2004. This document is the user's guide of Powernext Day-Ahead{sup TM}. It presents: 1 - the power exchange in France (market model, Powernext's regulatory environment, general market operations, 2 - Powernext Day-Ahead{sup TM} members (membership, agreement, start-up notification, tariffs, standing obligations, membership termination), 3 - Powernext Day-Ahead{sup TM} products (specifications, management), 4 - trading (connections, system flow chart, ElWeb client installation and daily connections, portfolio-management, single bidding, type of order, submitting, importing, saving, sending, modifying or canceling an order form, transmission problems, block bidding block bid characteristics, sending, saving, transmitting, modifying and canceling a block bid, price calculations, blind auction procedure, example, taking into account block bids, rounding off rules, consulting and saving the results, sample documents, auction validation), 5 - clearing (LCH.Clearnet SA, legal framework, clearing agreement, PP-DPES agreement, market security, initial margin, daily adjustments, additional margin calls, trade-related financial flows, net financial position, value-added tax, settlement statements, general idea, characteristics and transmission method of settlement statements sample Documents, cash calls, settlement, default, sample cash call documents, financial Reports), 6 - delivery (balance responsible entity, file characteristics and transmission, imbalance settlement

A new self-scheduling strategy for integrated operation of wind and pumped-storage power plants in power markets

International Nuclear Information System (INIS)

Varkani, Ali Karimi; Daraeepour, Ali; Monsef, Hassan

2011-01-01

Highlights: → A strategy for integrated operation of wind and pumped-storage plants is proposed. → Participation of both plants in energy and ancillary service markets is modeled. → The uncertainty of wind production is modeled by a novel probabilistic function. → The proposed strategy is tested on a real case in the Spanish electricity market. -- Abstract: Competitive structure of power markets causes various challenges for wind resources to participate in these markets. Indeed, production uncertainty is the main cause of their low income. Thus, they are usually supported by system operators, which is in contrast with the competitive paradigm of power markets. In this paper, a new strategy for increasing the profits of wind resources is proposed. In the suggested strategy, a Generation Company (GenCo), who owns both wind and pumped-storage plants, self-schedules the integrated operation of them regarding the uncertainty of wind power generation. For presenting an integrated self-schedule and obtaining a real added value of the strategy, participation of the GenCo in energy and ancillary service markets is modeled. The self-scheduling strategy is based on stochastic programming techniques. Outputs of the problem include generation offers in day-ahead energy market and ancillary service markets, including spinning and regulation reserve markets. A Neural Network (NN) based technique is used for modeling the uncertainty of wind power production. The proposed strategy is tested on a real wind farm in mainland, Spain. Moreover, added value of the strategy is presented in different conditions of the market.

Real-time energy resources scheduling considering short-term and very short-term wind forecast

Energy Technology Data Exchange (ETDEWEB)

Silva, Marco; Sousa, Tiago; Morais, Hugo; Vale, Zita [Polytechnic of Porto (Portugal). GECAD - Knowledge Engineering and Decision Support Research Center

2012-07-01

This paper proposes an energy resources management methodology based on three distinct time horizons: day-ahead scheduling, hour-ahead scheduling, and real-time scheduling. In each scheduling process the update of generation and consumption operation and of the storage and electric vehicles storage status are used. Besides the new operation conditions, the most accurate forecast values of wind generation and of consumption using results of short-term and very short-term methods are used. A case study considering a distribution network with intensive use of distributed generation and electric vehicles is presented. (orig.)

Everything you need to know to operate on Day-AheadTM

International Nuclear Information System (INIS)

2005-05-01

The introduction of a power exchange in France is a direct response to the opening up of the European electricity markets. Powernext SA is a Multilateral Trading Facility in charge of managing the French power exchange through an optional and anonymous organised exchange offering: - Day-ahead contracts for the management of volume risk on Powernext Day-Ahead TM since 21 November 2001, - Medium term contracts for the management of price risk on Powernext Futures TM since 18 June 2004. This document is the user's guide of Powernext Day-Ahead TM . It presents: 1 - the power exchange in France (market model, Powernext's regulatory environment, general market operations, 2 - Powernext Day-Ahead TM members (membership, agreement, start-up notification, tariffs, standing obligations, membership termination), 3 - Powernext Day-Ahead TM products (specifications, management), 4 - trading (connections, system flow chart, ElWeb client installation and daily connections, portfolio-management, single bidding, type of order, submitting, importing, saving, sending, modifying or canceling an order form, transmission problems, block bidding block bid characteristics, sending, saving, transmitting, modifying and canceling a block bid, price calculations, blind auction procedure, example, taking into account block bids, rounding off rules, consulting and saving the results, sample documents, auction validation), 5 - clearing (LCH.Clearnet SA, legal framework, clearing agreement, PP-DPES agreement, market security, initial margin, daily adjustments, additional margin calls, trade-related financial flows, net financial position, value-added tax, settlement statements, general idea, characteristics and transmission method of settlement statements sample Documents, cash calls, settlement, default, sample cash call documents, financial Reports), 6 - delivery (balance responsible entity, file characteristics and transmission, imbalance settlement, interconnection access), contacts and

The impact of renewable energies on EEX day-ahead electricity prices

International Nuclear Information System (INIS)

Paraschiv, Florentina; Erni, David; Pietsch, Ralf

2014-01-01

In this paper, we analyze the impact of renewable energies, wind and photovoltaic, on the formation of day-ahead electricity prices at EEX. We give an overview of the policy decisions concerning the promotion of renewable energy sources in Germany and discuss their consequences on day-ahead prices. An analysis of electricity spot prices reveals that the introduction of renewable energies enhances extreme price changes. In the frame of a dynamic fundamental model, we show that there has been a continuous electricity price adaption process to market fundamentals. Furthermore, the fundamental drivers of prices differ among hours with different load profiles. Our results imply that renewable energies decrease market spot prices and have implications on the traditional fuel mix for electricity production. However, the prices for the final consumers increased overall because they must pay in addition the feed-in tariffs for the promotion of renewable energy. - Highlights: • We analyze the impact of renewable energies on the day-ahead electricity prices at EEX. • We discuss the impact of renewables on day-ahead prices. • We show a continuous electricity price adaption process to market fundamentals. • Renewable energies decrease market spot prices and shift the merit order curve. • The prices for the final consumers however increased because of feed-in tariffs

PLAStiCC: Predictive Look-Ahead Scheduling for Continuous dataflows on Clouds

Energy Technology Data Exchange (ETDEWEB)

Kumbhare, Alok [Univ. of Southern California, Los Angeles, CA (United States); Simmhan, Yogesh [Indian Inst. of Technology (IIT), Bangalore (India); Prasanna, Viktor K. [Univ. of Southern California, Los Angeles, CA (United States)

2014-05-27

Scalable stream processing and continuous dataflow systems are gaining traction with the rise of big data due to the need for processing high velocity data in near real time. Unlike batch processing systems such as MapReduce and workflows, static scheduling strategies fall short for continuous dataflows due to the variations in the input data rates and the need for sustained throughput. The elastic resource provisioning of cloud infrastructure is valuable to meet the changing resource needs of such continuous applications. However, multi-tenant cloud resources introduce yet another dimension of performance variability that impacts the application’s throughput. In this paper we propose PLAStiCC, an adaptive scheduling algorithm that balances resource cost and application throughput using a prediction-based look-ahead approach. It not only addresses variations in the input data rates but also the underlying cloud infrastructure. In addition, we also propose several simpler static scheduling heuristics that operate in the absence of accurate performance prediction model. These static and adaptive heuristics are evaluated through extensive simulations using performance traces obtained from public and private IaaS clouds. Our results show an improvement of up to 20% in the overall profit as compared to the reactive adaptation algorithm.

Self-Reported Recovery from 2-Week 12-Hour Shift Work Schedules: A 14-Day Follow-Up.

Science.gov (United States)

Merkus, Suzanne L; Holte, Kari Anne; Huysmans, Maaike A; van de Ven, Peter M; van Mechelen, Willem; van der Beek, Allard J

2015-09-01

Recovery from fatigue is important in maintaining night workers' health. This study compared the course of self-reported recovery after 2-week 12-hour schedules consisting of either night shifts or swing shifts (i.e., 7 night shifts followed by 7 day shifts) to such schedules consisting of only day work. Sixty-one male offshore employees-20 night workers, 16 swing shift workers, and 25 day workers-rated six questions on fatigue (sleep quality, feeling rested, physical and mental fatigue, and energy levels; scale 1-11) for 14 days after an offshore tour. After the two night-work schedules, differences on the 1(st) day (main effects) and differences during the follow-up (interaction effects) were compared to day work with generalized estimating equations analysis. After adjustment for confounders, significant main effects were found for sleep quality for night workers (1.41, 95% confidence interval 1.05-1.89) and swing shift workers (1.42, 95% confidence interval 1.03-1.94) when compared to day workers; their interaction terms were not statistically significant. For the remaining fatigue outcomes, no statistically significant main or interaction effects were found. After 2-week 12-hour night and swing shifts, only the course for sleep quality differed from that of day work. Sleep quality was poorer for night and swing shift workers on the 1(st) day off and remained poorer for the 14-day follow-up. This showed that while working at night had no effect on feeling rested, tiredness, and energy levels, it had a relatively long-lasting effect on sleep quality.

A SOM clustering pattern sequence-based next symbol prediction method for day-ahead direct electricity load and price forecasting

International Nuclear Information System (INIS)

Jin, Cheng Hao; Pok, Gouchol; Lee, Yongmi; Park, Hyun-Woo; Kim, Kwang Deuk; Yun, Unil; Ryu, Keun Ho

2015-01-01

Highlights: • A novel pattern sequence-based direct time series forecasting method was proposed. • Due to the use of SOM’s topology preserving property, only SOM can be applied. • SCPSNSP only deals with the cluster patterns not each specific time series value. • SCPSNSP performs better than recently developed forecasting algorithms. - Abstract: In this paper, we propose a new day-ahead direct time series forecasting method for competitive electricity markets based on clustering and next symbol prediction. In the clustering step, pattern sequence and their topology relations are obtained from self organizing map time series clustering. In the next symbol prediction step, with each cluster label in the pattern sequence represented as a pair of its topologically identical coordinates, artificial neural network is used to predict the topological coordinates of next day by training the relationship between previous daily pattern sequence and its next day pattern. According to the obtained topology relations, the nearest nonzero hits pattern is assigned to next day so that the whole time series values can be directly forecasted from the assigned cluster pattern. The proposed method was evaluated on Spanish, Australian and New York electricity markets and compared with PSF and some of the most recently published forecasting methods. Experimental results show that the proposed method outperforms the best forecasting methods at least 3.64%

Comparative analysis of features of Polish and Lithuanian Day-ahead electricity market prices

International Nuclear Information System (INIS)

Bobinaite, Viktorija; Juozapaviciene, Aldona; Staniewski, Marcin; Szczepankowski, Piotr

2013-01-01

The goal of this article is to better understand the processes of electricity market price formation in Poland and Lithuania through an analysis of the features (volatility and spikes) of Lithuanian and Polish day-ahead electricity market prices and to assess how acquired electricity price features could affect the achievement of the main goals of the national energy policy. The following indicators have been calculated to determine electricity market price volatility: the oscillation coefficient, the coefficient of variation, an adjusted coefficient of variation, the standard deviation indicator, the daily velocity indicator (based on the overall average price) and the daily velocity indicator (based on the daily average price). Critical values for electricity market price have been calculated to evaluate price spikes. This analysis reveals that electricity market-price volatility is moderate in Poland and high in Lithuania. Electricity price spikes have been an observable phenomenon both in Lithuanian and in Polish day-ahead electricity markets, but they are more common in Lithuania, encompassing 3.15% of the time period analysed in Poland and 4.68% of the time period analysed in Lithuania. Volatile, spiking and increasing electricity prices in day-ahead electricity markets in Lithuania and Poland create preconditions and substantiate the relevance of implementation of the national energy policies and measures. - Highlights: • Moderate and seasonal volatility. • spiking market price and. • stable average price

A Personalized Rolling Optimal Charging Schedule for Plug-In Hybrid Electric Vehicle Based on Statistical Energy Demand Analysis and Heuristic Algorithm

Directory of Open Access Journals (Sweden)

Fanrong Kong

2017-09-01

Full Text Available To alleviate the emission of greenhouse gas and the dependence on fossil fuel, Plug-in Hybrid Electrical Vehicles (PHEVs have gained an increasing popularity in current decades. Due to the fluctuating electricity prices in the power market, a charging schedule is very influential to driving cost. Although the next-day electricity prices can be obtained in a day-ahead power market, a driving plan is not easily made in advance. Although PHEV owners can input a next-day plan into a charging system, e.g., aggregators, day-ahead, it is a very trivial task to do everyday. Moreover, the driving plan may not be very accurate. To address this problem, in this paper, we analyze energy demands according to a PHEV owner’s historical driving records and build a personalized statistic driving model. Based on the model and the electricity spot prices, a rolling optimization strategy is proposed to help make a charging decision in the current time slot. On one hand, by employing a heuristic algorithm, the schedule is made according to the situations in the following time slots. On the other hand, however, after the current time slot, the schedule will be remade according to the next tens of time slots. Hence, the schedule is made by a dynamic rolling optimization, but it only decides the charging decision in the current time slot. In this way, the fluctuation of electricity prices and driving routine are both involved in the scheduling. Moreover, it is not necessary for PHEV owners to input a day-ahead driving plan. By the optimization simulation, the results demonstrate that the proposed method is feasible to help owners save charging costs and also meet requirements for driving.

Influence of feasibility constrains on the bidding strategy selection in a day-ahead electricity market session

International Nuclear Information System (INIS)

Borghetti, Alberto; Massucco, Stefano; Silvestro, Federico

2009-01-01

Large part of liberalized electricity markets, including the Italian one, features an auction mechanism, called day-ahead energy market, which matches producers' and buyers' simple bids, consisting of energy quantity and price pairs. The match is achieved by a merit-order economic dispatch procedure independently applied for each of the hours of the following day. Power plants operation should, however, take into account several technical constraints, such as maximum and minimum production bounds, ramp constraints and minimum up and downs times, as well as no-load and startup costs. The presence of these constraints forces to adjust the scheduling provided by the market in order to obtain a feasible scheduling. The paper presents an analysis of the possibility and the limits of taking into account the power plants technical constraints in the bidding strategy selection procedure of generating companies (Gencos). The analysis is carried out by using a computer procedure based both on a simple static game-theory approach and on a cost-minimization unit-commitment algorithm. For illustrative purposes, we present the results obtained for a system with three Gencos, each owning several power plants, trying to model the bidding behaviour of every generator in the system. This approach, although complex from the computational point of view, allows an analysis of both price and quantity bidding strategies and appears to be applicable to markets having different rules and features. (author)

Multiple time-scale optimization scheduling for islanded microgrids including PV, wind turbine, diesel generator and batteries

DEFF Research Database (Denmark)

Xiao, Zhao xia; Nan, Jiakai; Guerrero, Josep M.

2017-01-01

A multiple time-scale optimization scheduling including day ahead and short time for an islanded microgrid is presented. In this paper, the microgrid under study includes photovoltaics (PV), wind turbine (WT), diesel generator (DG), batteries, and shiftable loads. The study considers the maximum...... efficiency operation area for the diesel engine and the cost of the battery charge/discharge cycle losses. The day-ahead generation scheduling takes into account the minimum operational cost and the maximum load satisfaction as the objective function. Short-term optimal dispatch is based on minimizing...

Day-ahead electricity prices forecasting by a modified CGSA technique and hybrid WT in LSSVM based scheme

International Nuclear Information System (INIS)

Shayeghi, H.; Ghasemi, A.

2013-01-01

Highlights: • Presenting a hybrid CGSA-LSSVM scheme for price forecasting. • Considering uncertainties for filtering in input data and feature selection to improve efficiency. • Using DWT input featured LSSVM approach to classify next-week prices. • Used three real markets to illustrate performance of the proposed price forecasting model. - Abstract: At the present time, day-ahead electricity market is closely associated with other commodity markets such as fuel market and emission market. Under such an environment, day-ahead electricity price forecasting has become necessary for power producers and consumers in the current deregulated electricity markets. Seeking for more accurate price forecasting techniques, this paper proposes a new combination of a Feature Selection (FS) technique based mutual information (MI) technique and Wavelet Transform (WT) in this study. Moreover, in this paper a new modified version of Gravitational Search Algorithm (GSA) optimization based chaos theory, namely Chaotic Gravitational Search Algorithm (CGSA) is developed to find the optimal parameters of Least Square Support Vector Machine (LSSVM) to predict electricity prices. The performance and price forecast accuracy of the proposed technique is assessed by means of real data from Iran’s, Ontario’s and Spain’s price markets. The simulation results from numerical tables and figures in different cases show that the proposed technique increases electricity price market forecasting accuracy than the other classical and heretical methods in the scientific researches

Application of a Gradient Descent Continuous Actor-Critic Algorithm for Double-Side Day-Ahead Electricity Market Modeling

Directory of Open Access Journals (Sweden)

Huiru Zhao

2016-09-01

Full Text Available An important goal of China’s electric power system reform is to create a double-side day-ahead wholesale electricity market in the future, where the suppliers (represented by GenCOs and demanders (represented by DisCOs compete simultaneously with each other in one market. Therefore, modeling and simulating the dynamic bidding process and the equilibrium in the double-side day-ahead electricity market scientifically is not only important to some developed countries, but also to China to provide a bidding decision-making tool to help GenCOs and DisCOs obtain more profits in market competition. Meanwhile, it can also provide an economic analysis tool to help government officials design the proper market mechanisms and policies. The traditional dynamic game model and table-based reinforcement learning algorithm have already been employed in the day-ahead electricity market modeling. However, those models are based on some assumptions, such as taking the probability distribution function of market clearing price (MCP and each rival’s bidding strategy as common knowledge (in dynamic game market models, and assuming the discrete state and action sets of every agent (in table-based reinforcement learning market models, which are no longer applicable in a realistic situation. In this paper, a modified reinforcement learning method, called gradient descent continuous Actor-Critic (GDCAC algorithm was employed in the double-side day-ahead electricity market modeling and simulation. This algorithm can not only get rid of the abovementioned unrealistic assumptions, but also cope with the Markov decision-making process with continuous state and action sets just like the real electricity market. Meanwhile, the time complexity of our proposed model is only O(n. The simulation result of employing the proposed model in the double-side day-ahead electricity market shows the superiority of our approach in terms of participant’s profit or social welfare

The impact of wind power on APX day-ahead electricity prices in the Netherlands VVM-Intermittency project

Energy Technology Data Exchange (ETDEWEB)

Nieuwenhout, F.D.J. [ECN Policy Studies, Amsterdam (Netherlands); Brand, A.J. [ECN Wind Energy, Petten (Netherlands)

2013-02-15

A detailed analysis was conducted to assess to what extent availability of wind energy has influenced day-ahead electricity prices in the Netherlands over the period 2006-2009. With a meteorological model, time series of day-ahead wind forecasts were generated, and these were compared with APX-ENDEX day-ahead market prices. Wind energy contributes to only 4% of electricity generation in the Netherlands, but was found to depress average day-ahead market prices by about 5%. With the help of the bid curves on the APX-ENDEX day-ahead market for 2009, a model was developed to assess the impact of increasing levels of wind generation on power prices in the Netherlands. One of the main findings is that the future impact on prices will be less than in the past. With an increase of installed wind capacity from 2200 MW to 6000 MW, average day-ahead prices are expected to be depressed by an additional 6% in case no additional conventional generation is assumed. Taking into account existing government policy on wind and ongoing investments in new conventional power plants, prices in 2016 will be only 3% lower.

Day-Ahead Energy Planning with 100% Electric Vehicle Penetration in the Nordic Region by 2050

Directory of Open Access Journals (Sweden)

Zhaoxi Liu

2014-03-01

Full Text Available This paper presents the day-ahead energy planning of passenger cars with 100% electric vehicle (EV penetration in the Nordic region by 2050. EVs will play an important role in the future energy systems which can both reduce the greenhouse gas (GHG emissions from the transport sector and provide the demand side flexibility required by smart grids. On the other hand, the EVs will increase the electricity consumption. In order to quantify the electricity consumption increase due to the 100% EV penetration in the Nordic region to facilitate the power system planning studies, the day-ahead energy planning of EVs has been investigated with different EV charging scenarios. Five EV charging scenarios have been considered in the energy planning analysis which are: uncontrolled charging all day, uncontrolled charging at home, timed charging, spot price based charging all day and spot price based charging at home. The demand profiles of the five charging analysis show that timed charging is the least favorable charging option and the spot priced based EV charging might induce high peak demands. The EV charging demand will have a considerable share of the energy consumption in the future Nordic power system.

Day-Ahead Natural Gas Demand Forecasting Using Optimized ABC-Based Neural Network with Sliding Window Technique: The Case Study of Regional Basis in Turkey

Directory of Open Access Journals (Sweden)

Mustafa Akpinar

2017-06-01

Full Text Available The increase of energy consumption in the world is reflected in the consumption of natural gas. However, this increment requires additional investment. This effect leads imbalances in terms of demand forecasting, such as applying penalties in the case of error rates occurring beyond the acceptable limits. As the forecasting errors increase, penalties increase exponentially. Therefore, the optimal use of natural gas as a scarce resource is important. There are various demand forecast ranges for natural gas and the most difficult range among these demands is the day-ahead forecasting, since it is hard to implement and makes predictions with low error rates. The objective of this study is stabilizing gas tractions on day-ahead demand forecasting using low-consuming subscriber data for minimizing error using univariate artificial bee colony-based artificial neural networks (ANN-ABC. For this purpose, households and low-consuming commercial users’ four-year consumption data between the years of 2011–2014 are gathered in daily periods. Previous consumption values are used to forecast day-ahead consumption values with sliding window technique and other independent variables are not taken into account. Dataset is divided into two parts. First, three-year daily consumption values are used with a seven day window for training the networks, while the last year is used for the day-ahead demand forecasting. Results show that ANN-ABC is a strong, stable, and effective method with a low error rate of 14.9 mean absolute percentage error (MAPE for training utilizing MAPE with a univariate sliding window technique.

Optimal household appliances scheduling under day-ahead pricing and load-shaping demand response strategies

NARCIS (Netherlands)

Paterakis, N.G.; Erdinç, O.; Bakirtzis, A.G.; Catalao, J.P.S.

2015-01-01

In this paper, a detailed home energy management system structure is developed to determine the optimal dayahead appliance scheduling of a smart household under hourly pricing and peak power-limiting (hard and soft power limitation)-based demand response strategies. All types of controllable assets

Powernext Day-Ahead. Powernext Futures. Powernext Carbon. Powernext Weather. 2006 activity assessment; Powernext Day-Ahead. Powernext Futures. Powernext Carbon. Powernext Weather. Bilan d'activite 2006

Energy Technology Data Exchange (ETDEWEB)

NONE

2006-07-01

Powernext SA is a Multilateral Trading Facility which organizes and warrants the transactions on the European power exchange and CO{sub 2} exchange markets. This activity report presents the highlights of the market and of Powernext in 2006: market conditions (prices on the electricity market, prices on the CO{sub 2} emission allowances market, weather conditions, institutional aspects of the CO{sub 2} market, power generation and consumption, situation at the borders, fuel prices), traded volumes on Powernext (Powernext Day-Ahead{sup TM} in the case of day-ahead contracts, Powernext Futures{sup TM} in the case of medium-term contracts, and Powernext Carbon in the case of CO{sub 2}), new active members, and Powernext liquidity on the power market. (J.S.)

MASCEM: EPEX SPOT Day-Ahead market integration and simulation

DEFF Research Database (Denmark)

Santos, Gabriel; Fernandes, Ricardo; Pinto, Tiago

2015-01-01

. It is crucial to MASCEM to have the ability to simulate as many market models and player types as possible, thus enhancing the ability to recreate the electricity markets reality in its maximum possible extent. This paper presents the EPEX Spot Day-Ahead market integration in MASCEM. EPEX Spot SE's mission...

Self-scheduling with Microsoft Excel.

Science.gov (United States)

Irvin, S A; Brown, H N

1999-01-01

Excessive time was being spent by the emergency department (ED) staff, head nurse, and unit secretary on a complex 6-week manual self-scheduling system. This issue, plus inevitable errors and staff dissatisfaction, resulted in a manager-lead initiative to automate elements of the scheduling process using Microsoft Excel. The implementation of this initiative included: common coding of all 8-hour and 12-hour shifts, with each 4-hour period represented by a cell; the creation of a 6-week master schedule using the "count-if" function of Excel based on current staffing guidelines; staff time-off requests then entered by the department secretary; the head nurse, with staff input, then fine-tuned the schedule to provide even unit coverage. Outcomes of these changes included an increase in staff satisfaction, time saved by the head nurse, and staff work time saved because there was less arguing about the schedule. Ultimately, the automated self-scheduling method was expanded to the entire 700-bed hospital.

Powernext Day-Ahead. Powernext Futures. Powernext Carbon. Powernext Weather. Activity assessment first-half 2006; Powernext Day-Ahead. Powernext Futures. Powernext Carbon. Powernext Weather. Bilan d'activite premier semestre 2006

Energy Technology Data Exchange (ETDEWEB)

NONE

2006-07-01

Powernext SA is a Multilateral Trading Facility which organizes and warrants the transactions on the European power exchange and CO{sub 2} exchange markets. This activity report presents the highlights of the market and of Powernext in the first half of 2006: market conditions, prices and traded volumes on Powernext (Powernext Day-Ahead{sup TM} in the case of day-ahead contracts, Powernext Futures{sup TM} in the case of medium-term contracts, and Powernext Carbon in the case of CO{sub 2}), new active members, and liquidity on the power market. (J.S.)

The effect of contingency analysis on the nodal prices in the day-ahead market

International Nuclear Information System (INIS)

Murphy, Frederic H.; Mudrageda, Murthy; Soyster, Allen L.; Saric, Andrija T.; Stankovic, Aleksandar M.

2010-01-01

We look at the effect of modeling branch-outage contingencies on locational marginal prices. To model contingencies in the day-ahead auction, we formulate a two-stage stochastic program. Rather than follow the current practice of including a list of possible contingencies that must be satisfied, we incorporate a larger set of contingencies in the model and allow contingencies to result in load reductions/outages at a cost. The model can be used and interpreted in two ways. One is to look at the tradeoff between reliability and outage costs. Another is to consider the load losses resulting from a contingency to be consumer offers of load reductions in response to line outages as part of the day-ahead auction. In analyzing the model structure, we find that the prices in the model closer in definition to those currently used in the day-ahead auction do not maximize expected surplus because the day-ahead auction produces prices that assume shortages will never occur. This raises issues with the design of auctions with important stochastic elements in the market. We present results for a 68-node grid with 86 branches (lines and transformers) to illustrate how prices and expected values change as the costs of outages are varied.

Powernext Day-Ahead. Powernext Futures. Powernext Carbon. Powernext Weather. 2006 activity assessment

International Nuclear Information System (INIS)

2006-01-01

Powernext SA is a Multilateral Trading Facility which organizes and warrants the transactions on the European power exchange and CO 2 exchange markets. This activity report presents the highlights of the market and of Powernext in 2006: market conditions (prices on the electricity market, prices on the CO 2 emission allowances market, weather conditions, institutional aspects of the CO 2 market, power generation and consumption, situation at the borders, fuel prices), traded volumes on Powernext (Powernext Day-Ahead TM in the case of day-ahead contracts, Powernext Futures TM in the case of medium-term contracts, and Powernext Carbon in the case of CO 2 ), new active members, and Powernext liquidity on the power market. (J.S.)

Demand Response from Day-Ahead Hourly Pricing for Large Customers

International Nuclear Information System (INIS)

Hopper, Nicole; Goldman, Charles; Neenan, Bernie

2006-01-01

Day-ahead default-service RTP for large customers not only improves the linkage between wholesale and retail markets, but also promotes the development of retail competition. The default service sets a standard for competitive alternatives and its structure shapes the types of retail market products that develop. (author)

Combined scheduling of electricity and heat in a microgrid with volatile wind power

DEFF Research Database (Denmark)

Xu, Lizhong; Yang, Guang Ya; Xu, Zhao

2011-01-01

An optimization model is developed for scheduling electricity and heat production in a microgrid under a day-ahead market environment considering the operation constraints and the volatility of wind power generation. The model optimizes the total operation costs from energy and heating consumption...... into a mixed-integer programming (MIP) problem. Numerical simulations present the efficacy of the proposed model for day-ahead scheduling of a microgrid with wind penetration under the deregulated environment. © 2011 State Grid Electrtic Resarch Institute Press....

California LLW disposal site development update: Ahead of milestone schedule

International Nuclear Information System (INIS)

Romano, S.A.; Gaynor, R.K.

1987-01-01

US Ecology has been designated by the State of California to locate, develop and operate a low-level radioactive waste disposal facility. In early 1986, the firm identified eighteen desert basins in southeastern California for siting consideration. Three candidate sites were selected for detailed field characterization work in February, 1987. A preferred site for licensing purposes will be identified in early 1988. California is currently ahead of the siting milestone schedule mandated by the Low-Level Radioactive Waste Policy Amendments Act. It is likely that a license application will be filed before the 1990 milestone date. This paper describes the process undertaken by US Ecology to identify three candidates sites for characterization, and the public involvement program supporting this decision. Future activities leading to final site development are also described

Customer Strategies for Responding to Day-Ahead Market HourlyElectricity Pricing

Energy Technology Data Exchange (ETDEWEB)

Goldman, Chuck; Hopper, Nicole; Bharvirkar, Ranjit; Neenan,Bernie; Boisvert, Dick; Cappers, Peter; Pratt, Donna; Butkins, Kim

2005-08-25

Real-time pricing (RTP) has been advocated as an economically efficient means to send price signals to customers to promote demand response (DR) (Borenstein 2002, Borenstein 2005, Ruff 2002). However, limited information exists that can be used to judge how effectively RTP actually induces DR, particularly in the context of restructured electricity markets. This report describes the second phase of a study of how large, non-residential customers' adapted to default-service day-ahead hourly pricing. The customers are located in upstate New York and served under Niagara Mohawk, A National Grid Company (NMPC)'s SC-3A rate class. The SC-3A tariff is a type of RTP that provides firm, day-ahead notice of hourly varying prices indexed to New York Independent System Operator (NYISO) day-ahead market prices. The study was funded by the California Energy Commission (CEC)'s PIER program through the Demand Response Research Center (DRRC). NMPC's is the first and longest-running default-service RTP tariff implemented in the context of retail competition. The mix of NMPC's large customers exposed to day-ahead hourly prices is roughly 30% industrial, 25% commercial and 45% institutional. They have faced periods of high prices during the study period (2000-2004), thereby providing an opportunity to assess their response to volatile hourly prices. The nature of the SC-3A default service attracted competitive retailers offering a wide array of pricing and hedging options, and customers could also participate in demand response programs implemented by NYISO. The first phase of this study examined SC-3A customers' satisfaction, hedging choices and price response through in-depth customer market research and a Constant Elasticity of Substitution (CES) demand model (Goldman et al. 2004). This second phase was undertaken to answer questions that remained unresolved and to quantify price response to a higher level of granularity. We accomplished these

Powernext Day-Ahead. Powernext Futures. Powernext Carbon. Powernext Weather. Activity assessment first-half 2006

International Nuclear Information System (INIS)

2006-01-01

Powernext SA is a Multilateral Trading Facility which organizes and warrants the transactions on the European power exchange and CO 2 exchange markets. This activity report presents the highlights of the market and of Powernext in the first half of 2006: market conditions, prices and traded volumes on Powernext (Powernext Day-Ahead TM in the case of day-ahead contracts, Powernext Futures TM in the case of medium-term contracts, and Powernext Carbon in the case of CO 2 ), new active members, and liquidity on the power market. (J.S.)

Rolling scheduling of electric power system with wind power based on improved NNIA algorithm

Science.gov (United States)

Xu, Q. S.; Luo, C. J.; Yang, D. J.; Fan, Y. H.; Sang, Z. X.; Lei, H.

2017-11-01

This paper puts forth a rolling modification strategy for day-ahead scheduling of electric power system with wind power, which takes the operation cost increment of unit and curtailed wind power of power grid as double modification functions. Additionally, an improved Nondominated Neighbor Immune Algorithm (NNIA) is proposed for solution. The proposed rolling scheduling model has further improved the operation cost of system in the intra-day generation process, enhanced the system’s accommodation capacity of wind power, and modified the key transmission section power flow in a rolling manner to satisfy the security constraint of power grid. The improved NNIA algorithm has defined an antibody preference relation model based on equal incremental rate, regulation deviation constraints and maximum & minimum technical outputs of units. The model can noticeably guide the direction of antibody evolution, and significantly speed up the process of algorithm convergence to final solution, and enhance the local search capability.

Stochastic coordination of joint wind and photovoltaic systems with energy storage in day-ahead market

International Nuclear Information System (INIS)

Gomes, I.L.R.; Pousinho, H.M.I.; Melício, R.; Mendes, V.M.F.

2017-01-01

This paper presents an optimal bid submission in a day-ahead electricity market for the problem of joint operation of wind with photovoltaic power systems having an energy storage device. Uncertainty not only due to the electricity market price, but also due to wind and photovoltaic powers is one of the main characteristics of this submission. The problem is formulated as a two-stage stochastic programming problem. The optimal bids and the energy flow in the batteries are the first-stage variables and the energy deviation is the second stage variable of the problem. Energy storage is a way to harness renewable energy conversion, allowing the store and discharge of energy at conveniently market prices. A case study with data from the Iberian day-ahead electricity market is presented and a comparison between joint and disjoint operations is discussed. - • Joint wind and PV systems with energy storage. • Electricity markets. • Stochastic optimization. • Day-ahead market.

Predictive densities for day-ahead electricity prices using time-adaptive quantile regression

DEFF Research Database (Denmark)

Jónsson, Tryggvi; Pinson, Pierre; Madsen, Henrik

2014-01-01

A large part of the decision-making problems actors of the power system are facing on a daily basis requires scenarios for day-ahead electricity market prices. These scenarios are most likely to be generated based on marginal predictive densities for such prices, then enhanced with a temporal...... dependence structure. A semi-parametric methodology for generating such densities is presented: it includes: (i) a time-adaptive quantile regression model for the 5%–95% quantiles; and (ii) a description of the distribution tails with exponential distributions. The forecasting skill of the proposed model...

Day-ahead stochastic economic dispatch of wind integrated power system considering demand response of residential hybrid energy system

International Nuclear Information System (INIS)

Jiang, Yibo; Xu, Jian; Sun, Yuanzhang; Wei, Congying; Wang, Jing; Ke, Deping; Li, Xiong; Yang, Jun; Peng, Xiaotao; Tang, Bowen

2017-01-01

Highlights: • Improving the utilization of wind power by the demand response of residential hybrid energy system. • An optimal scheduling of home energy management system integrating micro-CHP. • The scattered response capability of consumers is aggregated by demand bidding curve. • A stochastic day-ahead economic dispatch model considering demand response and wind power. - Abstract: As the installed capacity of wind power is growing, the stochastic variability of wind power leads to the mismatch of demand and generated power. Employing the regulating capability of demand to improve the utilization of wind power has become a new research direction. Meanwhile, the micro combined heat and power (micro-CHP) allows residential consumers to choose whether generating electricity by themselves or purchasing from the utility company, which forms a residential hybrid energy system. However, the impact of the demand response with hybrid energy system contained micro-CHP on the large-scale wind power utilization has not been analyzed quantitatively. This paper proposes an operation optimization model of the residential hybrid energy system based on price response, integrating micro-CHP and smart appliances intelligently. Moreover, a novel load aggregation method is adopted to centralize scattered response capability of residential load. At the power grid level, a day-ahead stochastic economic dispatch model considering demand response and wind power is constructed. Furthermore, simulation is conducted respectively on the modified 6-bus system and IEEE 118-bus system. The results show that with the method proposed, the wind power curtailment of the system decreases by 78% in 6-bus system. In the meantime, the energy costs of residential consumers and the operating costs of the power system reduced by 10.7% and 11.7% in 118-bus system, respectively.

Economic-environmental active and reactive power scheduling of modern distribution systems in presence of wind generations: A distribution market-based approach

International Nuclear Information System (INIS)

Samimi, Abouzar; Kazemi, Ahad; Siano, Pierluigi

2015-01-01

Highlights: • A new market-based approach is proposed to schedule active and reactive powers. • Multi-component reactive power bidding structures for DERs is introduced. • A new economical/environmental operational scheduling method is proposed. • At distribution level, a reactive power market is developed in presence of DERs. - Abstract: Distribution System Operator (DSO) is responsible for active and reactive power scheduling in a distribution system. DSO purchases its active and reactive power requirements from Distributed Energy Resources (DERs) as well as the wholesale electricity market. In this paper, a new economical/environmental operational scheduling method based on sequential day-ahead active and reactive power markets at distribution level is proposed to dispatch active and reactive powers in distribution systems with high penetration of DERs. In the proposed model, after day-ahead active power market was cleared the participants submit their reactive power bids and then the reactive power market will be settled. At distribution level, developing a Var market, in which DERs like synchronous machine-based Distributed Generation (DG) units and Wind Turbines (WTs) could offer their reactive power prices, DERs are motivated to actively participate in the Volt/VAr Control (VVC) problem. To achieve this purpose, based on the capability curves of considered DERs, innovative multi-component reactive power bidding structures for DERs are introduced. Moreover, the effect of reactive power market clearing on the active power scheduling is explicitly considered into the proposed model by rescheduling of active power by usage of energy-balance service bids. On the other hand, environmental concerns that arise from the operation of fossil fuel fired electric generators are included in the proposed model by employing CO_2 emission penalty cost. The suggested reactive power market is cleared through a mixed-integer nonlinear optimization program. The

Risk premiums in the German day-ahead Electricity Market

International Nuclear Information System (INIS)

Viehmann, Johannes

2011-01-01

This paper conducts an empirical analysis of risk premiums in the German day-ahead Electricity Wholesale Market. We compare hourly price data of the European Energy Exchange (EEX) auction and of the continuous over-the-counter (OTC) market which takes place prior to the EEX auction. Data provided by the Energy Exchange Austria (EXAA) has been used as a snapshot of the OTC market two hours prior to the EEX auction. Ex post analysis found market participants are willing to pay both significant positive and negative premiums for hourly contracts. The largest positive premiums were paid for high demand evening peak hours on weekdays during winter months. By contrast, night hours on weekends featuring lowest demand levels display negative premiums. Additionally, ex ante analysis found a strong positive correlation between the expected tightness of the system and positive premiums. For this purpose, a tightness factor has been introduced that includes expectations of fundamental factors such as power plant availability, wind power production and demand. Hence, findings by can be supported that power traders in liberalised markets behave like risk-averse rational economic agents. - Research highlights: →Analysis of hourly risk premiums in the German day-ahead Electricity Wholesale Market. →Market participants are willing to pay both significant positive and negative premiums for hourly contracts. →A strong correlation exists between the expected tightness of the power system and premiums.

Forecasting day ahead electricity spot prices: The impact of the EXAA to other European electricity markets

OpenAIRE

Ziel, Florian; Steinert, Rick; Husmann, Sven

2015-01-01

In our paper we analyze the relationship between the day-ahead electricity price of the Energy Exchange Austria (EXAA) and other day-ahead electricity prices in Europe. We focus on markets, which settle their prices after the EXAA, which enables traders to include the EXAA price into their calculations. For each market we employ econometric models to incorporate the EXAA price and compare them with their counterparts without the price of the Austrian exchange. By employing a forecasting study...

Day-Ahead Energy Planning with 100% Electric Vehicle Penetration in the Nordic Region by 2050

DEFF Research Database (Denmark)

Liu, Zhaoxi; Wu, Qiuwei; Nielsen, Arne Hejde

2014-01-01

This paper presents the day-ahead energy planning of passenger cars with 100% electric vehicle (EV) penetration in the Nordic region by 2050. EVs will play an important role in the future energy systems which can both reduce the greenhouse gas (GHG) emission from the transport sector and provide...... demand side flexibility required by the smart grids. On the other hand, the EVs will increase the electricity consumption. In order to quantify the electricity consumption increase due to the 100% EV penetration in the Nordic region to facilitate the power system planning studies, the day-ahead energy...

Revisiting short-term price and volatility dynamics in day-ahead electricity markets with rising wind power

International Nuclear Information System (INIS)

Li, Yuanjing

2015-01-01

This paper revisits the short-term price and volatility dynamics in day-ahead electricity markets in consideration of an increasing share of wind power, using an example of the Nord Pool day-ahead market and the Danish wind generation. To do so, a GARCH process is applied, and market coupling and the counterbalance effect of hydropower in the Scandinavian countries are additionally accounted for. As results, we found that wind generation weakly dampens spot prices with an elasticity of 0.008 and also reduces price volatility with an elasticity of 0.02 in the Nordic day-ahead market. The results shed lights on the importance of market coupling and interactions between wind power and hydropower in the Nordic system through cross-border exchanges, which play an essential role in price stabilization. Additionally, an EGARCH specification confirms an asymmetric influence of the price innovations, whereby negative shocks produce larger volatility in the Nordic spot market. While considering heavy tails in error distributions can improve model fits significantly, the EGARCH model outperforms the GARCH model on forecast evaluations. (author)

Self-Adaptive Operator Scheduling using the Religion-Based EA

DEFF Research Database (Denmark)

Thomsen, Rene; Krink, Thiemo

2002-01-01

of their application is determined by a constant parameter, such as a fixed mutation rate. However, recent studies have shown that the optimal usage of a variation operator changes during the EA run. In this study, we combined the idea of self-adaptive mutation operator scheduling with the Religion-Based EA (RBEA......), which is an agent model with spatially structured and variable sized subpopulations (religions). In our new model (OSRBEA), we used a selection of different operators, such that each operator type was applied within one specific subpopulation only. Our results indicate that the optimal choice...

Two-Stage Optimal Scheduling of Electric Vehicle Charging based on Transactive Control

DEFF Research Database (Denmark)

Liu, Zhaoxi; Wu, Qiuwei; Ma, Kang

2018-01-01

In this paper, a two-stage optimal charging scheme based on transactive control is proposed for the aggregator to manage day-ahead electricity procurement and real-time EV charging management in order to minimize its total operating cost. The day-ahead electricity procurement considers both the day......-ahead energy cost and expected real-time operation cost. In the real-time charging management, the cost of employing the charging flexibility from the EV owners is explicitly modelled. The aggregator uses a transactive market to manage the real-time charging demand to provide the regulating power. A model...... predictive control (MPC) based method is proposed for the aggregator to clear the transactive market. The realtime charging decisions of the EVs are determined by the clearing of the proposed transactive market according to the realtime requests and preferences of the EV owners. As such, the aggregators...

Modelling a Nurse Shift Schedule with Multiple Preference Ranks for Shifts and Days-Off

Directory of Open Access Journals (Sweden)

Chun-Cheng Lin

2014-01-01

Full Text Available When it comes to nurse shift schedules, it is found that the nursing staff have diverse preferences about shift rotations and days-off. The previous studies only focused on the most preferred work shift and the number of satisfactory days-off of the schedule at the current schedule period but had few discussions on the previous schedule periods and other preference levels for shifts and days-off, which may affect fairness of shift schedules. As a result, this paper proposes a nurse scheduling model based upon integer programming that takes into account constraints of the schedule, different preference ranks towards each shift, and the historical data of previous schedule periods to maximize the satisfaction of all the nursing staff's preferences about the shift schedule. The main contribution of the proposed model is that we consider that the nursing staff’s satisfaction level is affected by multiple preference ranks and their priority ordering to be scheduled, so that the quality of the generated shift schedule is more reasonable. Numerical results show that the planned shifts and days-off are fair and successfully meet the preferences of all the nursing staff.

Simulation of regional day-ahead PV power forecast scenarios

DEFF Research Database (Denmark)

Nuno, Edgar; Koivisto, Matti Juhani; Cutululis, Nicolaos Antonio

2017-01-01

Uncertainty associated with Photovoltaic (PV) generation can have a significant impact on real-time planning and operation of power systems. This obstacle is commonly handled using multiple forecast realizations, obtained using for example forecast ensembles and/or probabilistic forecasts, often...... at the expense of a high computational burden. Alternatively, some power system applications may require realistic forecasts rather than actual estimates; able to capture the uncertainty of weatherdriven generation. To this end, we propose a novel methodology to generate day-ahead forecast scenarios of regional...... PV production matching the spatio-temporal characteristics while preserving the statistical properties of actual records....

How to sell renewable electricity. Interactions of the intraday and day-ahead market under uncertainty

Energy Technology Data Exchange (ETDEWEB)

Knaut, Andreas; Obermueller, Frank

2016-04-15

Uncertainty about renewable production increases the importance of sequential short-term trading in electricity markets. We consider a two-stage market where conventional and renewable producers compete in order to satisfy the demand of consumers. The trading in the first stage takes place under uncertainty about production levels of renewable producers, which can be associated with trading in the day-ahead market. In the second stage, which we consider as the intraday market, uncertainty about the production levels is resolved. Our model is able to capture different levels of flexibility for conventional producers as well as different levels of competition for renewable producers. We find that it is optimal for renewable producers to sell less than the expected production in the day-ahead market. In situations with high renewable production it is even profitable for renewable producers to withhold quantities in the intraday market. However, for an increasing number of renewable producers, the optimal quantity tends towards the expected production level. More competition as well as a more flexible power plant fleet lead to an increase in overall welfare, which can even be further increased by delaying the gate-closure of the day-ahead market or by improving the quality of renewable production forecasts.

Sequential bidding in day-ahead auctions for spot energy and power systems reserve

International Nuclear Information System (INIS)

Swider, Derk J.

2005-01-01

In this paper a novel approach for sequential bidding on day-ahead auction markets for spot energy and power systems reserve is presented. For the spot market a relatively simple method is considered as a competitive market is assumed. For the reserve market one bidder is assumed to behave strategically and the behavior of the competitors is summarized in a probability distribution of the market price. This results in a method for sequential bidding, where the bidding prices and capacities on the spot and reserve markets are calculated by maximizing a stochastic non-linear objective function of expected profit. With an exemplary application is shown that the trading sequence leads to increasing bidding capacities and prices in the reverse rank number of the markets. Hence, the consideration of a defined trading sequence greatly influences the mathematical representation of the optimal bidding behavior under price uncertainty in day-ahead auctions for spot energy and power systems reserve. (Author)

The new building for Linac4 is ready ahead of schedule

CERN Multimedia

Francesco Poppi

2010-01-01

When various teams work together efficiently to achieve a common goal, not only are projects successfully completed but they may ever be ready before the deadline. On 22 October, after two years of civil engineering work and about two months ahead of schedule, the building that will host the new Linac4 was unveiled in the presence of the Director-General and of Steve Myers, Director for Accelerators and Technology.   Entrance to new Linac 4 tunnel. For the time being, the new two-storey 3000 m2 building looks like a huge empty hangar. Very soon, though, the ground floor will start to be filled with the technical equipment and the klystrons. The Linac4 itself will be installed in the tunnel excavated below the ground. “Being 12 metres underground, deep inside what remains of the old “Mount Citron”, the tunnel provides excellent shielding for the new accelerator”, says Maurizio Vretenar, Linac4 Project Leader. The tunnel will be connected to the PS Booster...

A regime-switching copula approach to modeling day-ahead prices in coupled electricity markets

DEFF Research Database (Denmark)

Pircalabu, Anca; Benth, Fred Espen

2017-01-01

significant evidence of tail dependence in all pairs of interconnected areas we consider. As a first application of the proposed model, we consider the pricing of financial transmission rights, and highlight how the choice of marginal distributions and copula impacts prices. As a second application we......The recent price coupling of many European electricity markets has triggered a fundamental change in the interaction of day-ahead prices, challenging additionally the modeling of the joint behavior of prices in interconnected markets. In this paper we propose a regime-switching AR–GARCH copula...... to model pairs of day-ahead electricity prices in coupled European markets. While capturing key stylized facts empirically substantiated in the literature, this model easily allows us to 1) deviate from the assumption of normal margins and 2) include a more detailed description of the dependence between...

Price forecasting of day-ahead electricity markets using a hybrid forecast method

International Nuclear Information System (INIS)

Shafie-khah, M.; Moghaddam, M. Parsa; Sheikh-El-Eslami, M.K.

2011-01-01

Research highlights: → A hybrid method is proposed to forecast the day-ahead prices in electricity market. → The method combines Wavelet-ARIMA and RBFN network models. → PSO method is applied to obtain optimum RBFN structure for avoiding over fitting. → One of the merits of the proposed method is lower need to the input data. → The proposed method has more accurate behavior in compare with previous methods. -- Abstract: Energy price forecasting in a competitive electricity market is crucial for the market participants in planning their operations and managing their risk, and it is also the key information in the economic optimization of the electric power industry. However, price series usually have a complex behavior due to their nonlinearity, nonstationarity, and time variancy. In this paper, a novel hybrid method to forecast day-ahead electricity price is proposed. This hybrid method is based on wavelet transform, Auto-Regressive Integrated Moving Average (ARIMA) models and Radial Basis Function Neural Networks (RBFN). The wavelet transform provides a set of better-behaved constitutive series than price series for prediction. ARIMA model is used to generate a linear forecast, and then RBFN is developed as a tool for nonlinear pattern recognition to correct the estimation error in wavelet-ARIMA forecast. Particle Swarm Optimization (PSO) is used to optimize the network structure which makes the RBFN be adapted to the specified training set, reducing computation complexity and avoiding overfitting. The proposed method is examined on the electricity market of mainland Spain and the results are compared with some of the most recent price forecast methods. The results show that the proposed hybrid method could provide a considerable improvement for the forecasting accuracy.

Price forecasting of day-ahead electricity markets using a hybrid forecast method

Energy Technology Data Exchange (ETDEWEB)

Shafie-khah, M., E-mail: miadreza@gmail.co [Tarbiat Modares University, Tehran (Iran, Islamic Republic of); Moghaddam, M. Parsa, E-mail: parsa@modares.ac.i [Tarbiat Modares University, Tehran (Iran, Islamic Republic of); Sheikh-El-Eslami, M.K., E-mail: aleslam@modares.ac.i [Tarbiat Modares University, Tehran (Iran, Islamic Republic of)

2011-05-15

Research highlights: {yields} A hybrid method is proposed to forecast the day-ahead prices in electricity market. {yields} The method combines Wavelet-ARIMA and RBFN network models. {yields} PSO method is applied to obtain optimum RBFN structure for avoiding over fitting. {yields} One of the merits of the proposed method is lower need to the input data. {yields} The proposed method has more accurate behavior in compare with previous methods. -- Abstract: Energy price forecasting in a competitive electricity market is crucial for the market participants in planning their operations and managing their risk, and it is also the key information in the economic optimization of the electric power industry. However, price series usually have a complex behavior due to their nonlinearity, nonstationarity, and time variancy. In this paper, a novel hybrid method to forecast day-ahead electricity price is proposed. This hybrid method is based on wavelet transform, Auto-Regressive Integrated Moving Average (ARIMA) models and Radial Basis Function Neural Networks (RBFN). The wavelet transform provides a set of better-behaved constitutive series than price series for prediction. ARIMA model is used to generate a linear forecast, and then RBFN is developed as a tool for nonlinear pattern recognition to correct the estimation error in wavelet-ARIMA forecast. Particle Swarm Optimization (PSO) is used to optimize the network structure which makes the RBFN be adapted to the specified training set, reducing computation complexity and avoiding overfitting. The proposed method is examined on the electricity market of mainland Spain and the results are compared with some of the most recent price forecast methods. The results show that the proposed hybrid method could provide a considerable improvement for the forecasting accuracy.

Residential Consumption Scheduling Based on Dynamic User Profiling

Science.gov (United States)

Mangiatordi, Federica; Pallotti, Emiliano; Del Vecchio, Paolo; Capodiferro, Licia

Deployment of household appliances and of electric vehicles raises the electricity demand in the residential areas and the impact of the building's electrical power. The variations of electricity consumption across the day, may affect both the design of the electrical generation facilities and the electricity bill, mainly when a dynamic pricing is applied. This paper focuses on an energy management system able to control the day-ahead electricity demand in a residential area, taking into account both the variability of the energy production costs and the profiling of the users. The user's behavior is dynamically profiled on the basis of the tasks performed during the previous days and of the tasks foreseen for the current day. Depending on the size and on the flexibility in time of the user tasks, home inhabitants are grouped in, one over N, energy profiles, using a k-means algorithm. For a fixed energy generation cost, each energy profile is associated to a different hourly energy cost. The goal is to identify any bad user profile and to make it pay a highest bill. A bad profile example is when a user applies a lot of consumption tasks and low flexibility in task reallocation time. The proposed energy management system automatically schedules the tasks, solving a multi-objective optimization problem based on an MPSO strategy. The goals, when identifying bad users profiles, are to reduce the peak to average ratio in energy demand, and to minimize the energy costs, promoting virtuous behaviors.

Merit-order effects of renewable energy and price divergence in California’s day-ahead and real-time electricity markets

International Nuclear Information System (INIS)

Woo, C.K.; Moore, J.; Schneiderman, B.; Ho, T.; Olson, A.; Alagappan, L.; Chawla, K.; Toyama, N.; Zarnikau, J.

2016-01-01

We answer two policy questions: (1) what are the estimated merit-order effects of renewable energy in the California Independent System Operator’s (CAISO’s) day-ahead market (DAM) and real-time market (RTM)? and (2) what causes the hourly DAM and RTM prices to systematically diverge? The first question is timely and relevant because if the merit-order effect estimates are small, California’s renewable energy development is of limited help in cutting electricity consumers’ bills but also has a lesser adverse impact on the state’s investment incentive for natural-gas-fired generation. The second question is related to the efficient market hypothesis under which the hourly RTM and DAM prices tend to converge. Using a sample of about 21,000 hourly observations of CAISO market prices and their fundamental drivers during 12/12/2012–04/30/2015, we document statistically significant estimates (p-value≤0.01) for the DAM and RTM merit-order effects. This finding lends support to California’s adopted procurement process to provide sufficient investment incentives for natural-gas-fired generation. We document that the RTM-DAM price divergence partly depends on the CASIO’s day-ahead forecast errors for system loads and renewable energy. This finding suggests that improving the performance of the CAISO’s day-ahead forecasts can enhance trading efficiency in California’s DAM and RTM electricity markets. - Highlights: •Estimate the day-ahead and real-time merit-order effects of renewable energy in California. •Document statistically significant merit-order effects of solar and wind energy. •Document the difference between the day-ahead and real-time prices. •Attribute the price differences to forecast errors for load, solar and wind energy. •Discuss the evidence’s implications for California’s energy policy.

A Modified Feature Selection and Artificial Neural Network-Based Day-Ahead Load Forecasting Model for a Smart Grid

OpenAIRE

Ahmad, Ashfaq; Javaid, Nadeem; Alrajeh, Nabil; Khan, Zahoor; Qasim, Umar; Khan, Abid

2015-01-01

In the operation of a smart grid (SG), day-ahead load forecasting (DLF) is an important task. The SG can enhance the management of its conventional and renewable resources with a more accurate DLF model. However, DLF model development is highly challenging due to the non-linear characteristics of load time series in SGs. In the literature, DLF models do exist; however, these models trade off between execution time and forecast accuracy. The newly-proposed DLF model will be able to accurately ...

Two-Stage Multi-Objective Collaborative Scheduling for Wind Farm and Battery Switch Station

Directory of Open Access Journals (Sweden)

Zhe Jiang

2016-10-01

Full Text Available In order to deal with the uncertainties of wind power, wind farm and electric vehicle (EV battery switch station (BSS were proposed to work together as an integrated system. In this paper, the collaborative scheduling problems of such a system were studied. Considering the features of the integrated system, three indices, which include battery swapping demand curtailment of BSS, wind curtailment of wind farm, and generation schedule tracking of the integrated system are proposed. In addition, a two-stage multi-objective collaborative scheduling model was designed. In the first stage, a day-ahead model was built based on the theory of dependent chance programming. With the aim of maximizing the realization probabilities of these three operating indices, random fluctuations of wind power and battery switch demand were taken into account simultaneously. In order to explore the capability of BSS as reserve, the readjustment process of the BSS within each hour was considered in this stage. In addition, the stored energy rather than the charging/discharging power of BSS during each period was optimized, which will provide basis for hour-ahead further correction of BSS. In the second stage, an hour-ahead model was established. In order to cope with the randomness of wind power and battery swapping demand, the proposed hour-ahead model utilized ultra-short term prediction of the wind power and the battery switch demand to schedule the charging/discharging power of BSS in a rolling manner. Finally, the effectiveness of the proposed models was validated by case studies. The simulation results indicated that the proposed model could realize complement between wind farm and BSS, reduce the dependence on power grid, and facilitate the accommodation of wind power.

Probabilistic Price Forecasting for Day-Ahead and Intraday Markets: Beyond the Statistical Model

Directory of Open Access Journals (Sweden)

José R. Andrade

2017-10-01

Full Text Available Forecasting the hourly spot price of day-ahead and intraday markets is particularly challenging in electric power systems characterized by high installed capacity of renewable energy technologies. In particular, periods with low and high price levels are difficult to predict due to a limited number of representative cases in the historical dataset, which leads to forecast bias problems and wide forecast intervals. Moreover, these markets also require the inclusion of multiple explanatory variables, which increases the complexity of the model without guaranteeing a forecasting skill improvement. This paper explores information from daily futures contract trading and forecast of the daily average spot price to correct point and probabilistic forecasting bias. It also shows that an adequate choice of explanatory variables and use of simple models like linear quantile regression can lead to highly accurate spot price point and probabilistic forecasts. In terms of point forecast, the mean absolute error was 3.03 €/MWh for day-ahead market and a maximum value of 2.53 €/MWh was obtained for intraday session 6. The probabilistic forecast results show sharp forecast intervals and deviations from perfect calibration below 7% for all market sessions.

Congestion management of distribution networks with day-ahead dynamic grid tariffs

DEFF Research Database (Denmark)

Huang, Shaojun; Wu, Qiuwei

vehicles (EV) and heat pumps (HP), will be largely deployed in electrical distribution networks. Congestion management will be important in the future active distribution networks. In the IDE4L project, work package 5 is dedicated to develop different kinds of congestion management methods. Demand response...... (DR) is one of the important methods. In this report, as one task of work package 5, the day-ahead dynamic tariff (DADT) method for congestion management in distribution networks is presented. The dynamic tariff (DT) can motivate the flexible demands (EV and HP) to shift their energy consumption...

Ensuring the Reliable Operation of the Power Grid: State-Based and Distributed Approaches to Scheduling Energy and Contingency Reserves

Science.gov (United States)

Prada, Jose Fernando

Keeping a contingency reserve in power systems is necessary to preserve the security of real-time operations. This work studies two different approaches to the optimal allocation of energy and reserves in the day-ahead generation scheduling process. Part I presents a stochastic security-constrained unit commitment model to co-optimize energy and the locational reserves required to respond to a set of uncertain generation contingencies, using a novel state-based formulation. The model is applied in an offer-based electricity market to allocate contingency reserves throughout the power grid, in order to comply with the N-1 security criterion under transmission congestion. The objective is to minimize expected dispatch and reserve costs, together with post contingency corrective redispatch costs, modeling the probability of generation failure and associated post contingency states. The characteristics of the scheduling problem are exploited to formulate a computationally efficient method, consistent with established operational practices. We simulated the distribution of locational contingency reserves on the IEEE RTS96 system and compared the results with the conventional deterministic method. We found that assigning locational spinning reserves can guarantee an N-1 secure dispatch accounting for transmission congestion at a reasonable extra cost. The simulations also showed little value of allocating downward reserves but sizable operating savings from co-optimizing locational nonspinning reserves. Overall, the results indicate the computational tractability of the proposed method. Part II presents a distributed generation scheduling model to optimally allocate energy and spinning reserves among competing generators in a day-ahead market. The model is based on the coordination between individual generators and a market entity. The proposed method uses forecasting, augmented pricing and locational signals to induce efficient commitment of generators based on firm

Evaluation of a twelve-hour/day shift schedule

International Nuclear Information System (INIS)

Lewis, P.M.; Swaim, D.J.

1986-01-01

In April 1985, the operating crews at the Fast Flux Test Facility near Richland, Washington, changed their rotating shift schedule from an 8-hour to a 12-hour a day work schedule. The primary purpose of the change was to reduce the attrition of operators by increasing their job satisfaction. Eighty-four percent of the operators favored the change. A program was established to evaluate the effects on plant performance, operator alertness, attrition, sleep, health, job satisfaction, and off-the-job satisfaction. Preliminary results from that evaluation program indicate that the 12-hour shift schedule is a reasonable alternative to an 8-hour schedule at this facility

New bidding strategy formulation for day-ahead energy and reserve markets based on evolutionary programming

International Nuclear Information System (INIS)

Attaviriyanupap, Pathom; Kita, Hiroyuki; Tanaka, Eiichi; Hasegawa, Jun

2005-01-01

In this paper, a new bidding strategy for a day-ahead market is formulated. The proposed algorithm is developed from the viewpoint of a generation company wishing to maximize a profit as a participant in the deregulated power and reserve markets. Separate power and reserve markets are considered, both are operated by clearing price auction system. The optimal bidding parameters for both markets are determined by solving an optimization problem that takes unit commitment constraints such as generating limits and unit minimum up/down time constraints into account. This is a non-convex and non-differentiable which is difficult to solve by traditional optimization techniques. In this paper, evolutionary programming is used to solve the problem. The algorithm is applied to both single-sided and double-sided auctions, numerical simulations are carried out to demonstrate the performance of the proposed scheme compared with those obtained from a sequential quadratic programming. (author)

Customer response to day-ahead market hourly pricing: Choices and performance

International Nuclear Information System (INIS)

Hopper, Nicole; Goldman, Charles; Bharvirkar, Ranjit; Neenan, Bernie

2006-01-01

Real-time pricing (RTP) has been advocated to address extreme price volatility and market power in electricity markets. This study of Niagara Mohawk Power Corporation's largest customers analyzes their choices and performance in response to day-ahead, default-service RTP. Overall price response is modest: 119 customers are estimated to reduce their peak demand by about 10% at high prices. Manufacturing customers are most responsive with a price elasticity of 0.16, followed by government/education customers (0.11), while commercial/retail, healthcare and public works customers are, at present, relatively unresponsive. Within market segments, individual customer response varies significantly. (author)

A bi-level stochastic scheduling optimization model for a virtual power plant connected to a wind–photovoltaic–energy storage system considering the uncertainty and demand response

International Nuclear Information System (INIS)

Ju, Liwei; Tan, Zhongfu; Yuan, Jinyun; Tan, Qingkun; Li, Huanhuan; Dong, Fugui

2016-01-01

Highlights: • Our research focuses on Virtual Power Plant (VPP). • Virtual Power Plant consists of WPP, PV, CGT, ESSs and DRPs. • Robust optimization theory is introduced to analyze uncertainties. • A bi-level stochastic scheduling optimization model is proposed for VPP. • Models are built to measure the impacts of ESSs and DERPs on VPP operation. - Abstract: To reduce the uncertain influence of wind power and solar photovoltaic power on virtual power plant (VPP) operation, robust optimization theory (ROT) is introduced to build a stochastic scheduling model for VPP considering the uncertainty, price-based demand response (PBDR) and incentive-based demand response (IBDR). First, the VPP components are described including the wind power plant (WPP), photovoltaic generators (PV), convention gas turbine (CGT), energy storage systems (ESSs) and demand resource providers (DRPs). Then, a scenario generation and reduction frame is proposed for analyzing and simulating output stochastics based on the interval method and the Kantorovich distance. Second, a bi-level robust scheduling model is proposed with a double robust coefficient for WPP and PV. In the upper layer model, the maximum VPP operation income is taken as the optimization objective for building the scheduling model with the day-ahead prediction output of WPP and PV. In the lower layer model, the day-ahead scheduling scheme is revised with the actual output of the WPP and PV under the objectives of the minimum system net load and the minimum system operation cost. Finally, the independent micro-grid in a coastal island in eastern China is used for the simulation analysis. The results illustrate that the model can overcome the influence of uncertainty on VPP operations and reduce the system power shortage cost by connecting the day-ahead scheduling with the real-time scheduling. ROT could provide a flexible decision tool for decision makers, effectively addressing system uncertainties. ESSs could

Hourly price elasticity pattern of electricity demand in the German day-ahead market

OpenAIRE

Knaut, Andreas; Paulus, Simon

2016-01-01

System security in electricity markets relies crucially on the interaction between demand and supply over time. However, research on electricity markets has been mainly focusing on the supply side arguing that demand is rather inelastic. Assuming perfectly inelastic demand might lead to delusive statements regarding the price formation in electricity markets. In this article we quantify the short-run price elasticity of electricity demand in the German day-ahead market and show that demand is...

Scheduling reinforcement about once a day.

Science.gov (United States)

Eckerman, D A

1999-04-01

A pigeon earned its daily food by pecking a key according to reinforcement schedules that produced food about once per day. Fixed-interval (FI), Fixed-time (FT), and various complex schedules were arranged to demonstrate the degree to which a scalloped pattern of responding remained. Pausing continued until about an hour before the reinforcer could be earned for FIs of 12, 24, and 48 h. Pausing was not as long for FIs of 18, 19, and 23 h. Pausing of about 24 h was seen for FI 36 h. FT 24 h produced continued responding but at a diminished frequency. The pattern of responding was strongly controlled by the schedule of reinforcement and seemed relatively independent of the cycle of human activity in the surrounding laboratory. Effects of added ratio contingencies and of signaling the availability of reinforcement in FT were also examined. Signaled FTs of 5 min-3 h produced more responding during the signal (autoshaping) than did FTs of 19 or 24 h.

Anodal transcranial direct current stimulation over the primary motor cortex does not enhance the learning benefits of self-controlled feedback schedules.

Science.gov (United States)

Carter, Michael J; Smith, Victoria; Carlsen, Anthony N; Ste-Marie, Diane M

2018-05-01

A distinct learning advantage has been shown when participants control their knowledge of results (KR) scheduling during practice compared to when the same KR schedule is imposed on the learner without choice (i.e., yoked schedules). Although the learning advantages of self-controlled KR schedules are well-documented, the brain regions contributing to these advantages remain unknown. Identifying key brain regions would not only advance our theoretical understanding of the mechanisms underlying self-controlled learning advantages, but would also highlight regions that could be targeted in more applied settings to boost the already beneficial effects of self-controlled KR schedules. Here, we investigated whether applying anodal transcranial direct current stimulation (tDCS) to the primary motor cortex (M1) would enhance the typically found benefits of learning a novel motor skill with a self-controlled KR schedule. Participants practiced a spatiotemporal task in one of four groups using a factorial combination of KR schedule (self-controlled vs. yoked) and tDCS (anodal vs. sham). Testing occurred on two consecutive days with spatial and temporal accuracy measured on both days and learning was assessed using 24-h retention and transfer tests without KR. All groups improved their performance in practice and a significant effect for practicing with a self-controlled KR schedule compared to a yoked schedule was found for temporal accuracy in transfer, but a similar advantage was not evident in retention. There were no significant differences as a function of KR schedule or tDCS for spatial accuracy in retention or transfer. The lack of a significant tDCS effect suggests that M1 may not strongly contribute to self-controlled KR learning advantages; however, caution is advised with this interpretation as typical self-controlled learning benefits were not strongly replicated in the present experiment.

Guidelines for successful self-scheduling on nursing units.

Science.gov (United States)

Russell, Elizabeth; Hawkins, Jenna; Arnold, Kara A

2012-09-01

Self-scheduling programs are an increasingly popular strategy utilized by employers to address the individual and organizational challenges resulting from employee work-life imbalance among the nursing workforce. Certain key components will ensure buy-in and support from staff when self-scheduling programs are developed.

Towards Cost and Comfort Based Hybrid Optimization for Residential Load Scheduling in a Smart Grid

Directory of Open Access Journals (Sweden)

Nadeem Javaid

2017-10-01

Full Text Available In a smart grid, several optimization techniques have been developed to schedule load in the residential area. Most of these techniques aim at minimizing the energy consumption cost and the comfort of electricity consumer. Conversely, maintaining a balance between two conflicting objectives: energy consumption cost and user comfort is still a challenging task. Therefore, in this paper, we aim to minimize the electricity cost and user discomfort while taking into account the peak energy consumption. In this regard, we implement and analyse the performance of a traditional dynamic programming (DP technique and two heuristic optimization techniques: genetic algorithm (GA and binary particle swarm optimization (BPSO for residential load management. Based on these techniques, we propose a hybrid scheme named GAPSO for residential load scheduling, so as to optimize the desired objective function. In order to alleviate the complexity of the problem, the multi dimensional knapsack is used to ensure that the load of electricity consumer will not escalate during peak hours. The proposed model is evaluated based on two pricing schemes: day-ahead and critical peak pricing for single and multiple days. Furthermore, feasible regions are calculated and analysed to develop a relationship between power consumption, electricity cost, and user discomfort. The simulation results are compared with GA, BPSO and DP, and validate that the proposed hybrid scheme reflects substantial savings in electricity bills with minimum user discomfort. Moreover, results also show a phenomenal reduction in peak power consumption.

A Comparison of the Performance of Advanced Statistical Techniques for the Refinement of Day-ahead and Longer NWP-based Wind Power Forecasts

Science.gov (United States)

Zack, J. W.

2015-12-01

Predictions from Numerical Weather Prediction (NWP) models are the foundation for wind power forecasts for day-ahead and longer forecast horizons. The NWP models directly produce three-dimensional wind forecasts on their respective computational grids. These can be interpolated to the location and time of interest. However, these direct predictions typically contain significant systematic errors ("biases"). This is due to a variety of factors including the limited space-time resolution of the NWP models and shortcomings in the model's representation of physical processes. It has become common practice to attempt to improve the raw NWP forecasts by statistically adjusting them through a procedure that is widely known as Model Output Statistics (MOS). The challenge is to identify complex patterns of systematic errors and then use this knowledge to adjust the NWP predictions. The MOS-based improvements are the basis for much of the value added by commercial wind power forecast providers. There are an enormous number of statistical approaches that can be used to generate the MOS adjustments to the raw NWP forecasts. In order to obtain insight into the potential value of some of the newer and more sophisticated statistical techniques often referred to as "machine learning methods" a MOS-method comparison experiment has been performed for wind power generation facilities in 6 wind resource areas of California. The underlying NWP models that provided the raw forecasts were the two primary operational models of the US National Weather Service: the GFS and NAM models. The focus was on 1- and 2-day ahead forecasts of the hourly wind-based generation. The statistical methods evaluated included: (1) screening multiple linear regression, which served as a baseline method, (2) artificial neural networks, (3) a decision-tree approach called random forests, (4) gradient boosted regression based upon an decision-tree algorithm, (5) support vector regression and (6) analog ensemble

An improved charging/discharging strategy of lithium batteries considering depreciation cost in day-ahead microgrid scheduling

International Nuclear Information System (INIS)

Zhang, Zhong; Wang, Jianxue; Wang, Xiuli

2015-01-01

Highlights: • A quantitative depreciation cost model is put forward for lithium batteries. • A practical charging/discharging strategy is applied to battery management. • The depth of discharge of the battery storage is scheduled more rationally. • The proposed strategy improves the cost efficiency of lithium batteries in MGs. - Abstract: An energy storage system is critical for the safe and stable operation of a microgrid (MG) and has a promising prospect in future power system. Economical and safe operation of storage system is of great significance to MGs. This paper presents an improved management strategy for lithium battery storage by establishing a battery depreciation cost model and employing a practical charging/discharging strategy. Firstly, experimental data of lithium battery cycle lives, which are functions of the depth of discharge, are investigated and synthesized. A quantitative depreciation cost model is put forward for lithium batteries from the perspective of cycle life. Secondly, a practical charging/discharging strategy is applied to the lithium battery management in MGs. Then, an optimal scheduling model is developed to minimize MG operational cost including battery depreciation cost. Finally, numerical tests are conducted on a typical grid-connected MG. Results show that the depth of discharge of storage is scheduled more rationally, and operational cost is simultaneously saved for MG under the proposed management strategy. This study helps to improve the cost efficiency and alleviate the aging process for lithium batteries.

Feedback, competition and stochasticity in a day ahead electricity market

International Nuclear Information System (INIS)

Giabardo, Paolo; Zugno, Marco; Pinson, Pierre; Madsen, Henrik

2010-01-01

Major recent changes in electricity markets relate to the process for their deregulation, along with increasing participation of renewable (stochastic) generation e.g. wind power. Our general objective is to model how feedback, competition and stochasticity (on the production side) interact in electricity markets, and eventually assess what their effects are on both the participants and the society. For this, day ahead electricity markets are modeled as dynamic closed loop systems, in which the feedback signal is the market price. In parallel, the Cournot competition model is considered. Mixed portfolios with significant share of renewable energy are based on stochastic threshold cost functions. Regarding trading strategies, it is assumed that generators are looking at optimizing their individual profits. The point of view of the society is addressed by analyzing market behavior and stability. The performed simulations show the beneficial effects of employing long term bidding strategies for both generators and society. Sensitivity analyses are performed in order to evaluate the effects of demand elasticity. It is shown that increase in demand elasticity reduces the possibility for the generators to exploit their market power. Furthermore, the results suggest that introduction of wind power generation in the market is beneficial both for the generators and the society.

Feedback, competition and stochasticity in a day ahead electricity market

Energy Technology Data Exchange (ETDEWEB)

Giabardo, Paolo; Zugno, Marco; Pinson, Pierre; Madsen, Henrik [DTU Informatics, Technical University of Denmark, Richard Petersens Plads 305, DK-2800 Kgs. Lyngby (Denmark)

2010-03-15

Major recent changes in electricity markets relate to the process for their deregulation, along with increasing participation of renewable (stochastic) generation e.g. wind power. Our general objective is to model how feedback, competition and stochasticity (on the production side) interact in electricity markets, and eventually assess what their effects are on both the participants and the society. For this, day ahead electricity markets are modeled as dynamic closed loop systems, in which the feedback signal is the market price. In parallel, the Cournot competition model is considered. Mixed portfolios with significant share of renewable energy are based on stochastic threshold cost functions. Regarding trading strategies, it is assumed that generators are looking at optimizing their individual profits. The point of view of the society is addressed by analyzing market behavior and stability. The performed simulations show the beneficial effects of employing long term bidding strategies for both generators and society. Sensitivity analyses are performed in order to evaluate the effects of demand elasticity. It is shown that increase in demand elasticity reduces the possibility for the generators to exploit their market power. Furthermore, the results suggest that introduction of wind power generation in the market is beneficial both for the generators and the society. (author)

A Modified Feature Selection and Artificial Neural Network-Based Day-Ahead Load Forecasting Model for a Smart Grid

Directory of Open Access Journals (Sweden)

Ashfaq Ahmad

2015-12-01

Full Text Available In the operation of a smart grid (SG, day-ahead load forecasting (DLF is an important task. The SG can enhance the management of its conventional and renewable resources with a more accurate DLF model. However, DLF model development is highly challenging due to the non-linear characteristics of load time series in SGs. In the literature, DLF models do exist; however, these models trade off between execution time and forecast accuracy. The newly-proposed DLF model will be able to accurately predict the load of the next day with a fair enough execution time. Our proposed model consists of three modules; the data preparation module, feature selection and the forecast module. The first module makes the historical load curve compatible with the feature selection module. The second module removes redundant and irrelevant features from the input data. The third module, which consists of an artificial neural network (ANN, predicts future load on the basis of selected features. Moreover, the forecast module uses a sigmoid function for activation and a multi-variate auto-regressive model for weight updating during the training process. Simulations are conducted in MATLAB to validate the performance of our newly-proposed DLF model in terms of accuracy and execution time. Results show that our proposed modified feature selection and modified ANN (m(FS + ANN-based model for SGs is able to capture the non-linearity(ies in the history load curve with 97 . 11 % accuracy. Moreover, this accuracy is achieved at the cost of a fair enough execution time, i.e., we have decreased the average execution time of the existing FS + ANN-based model by 38 . 50 % .

Cultural norm fulfillment, interpersonal belonging, or getting ahead? A large-scale cross-cultural test of three perspectives on the function of self-esteem.

Science.gov (United States)

Gebauer, Jochen E; Sedikides, Constantine; Wagner, Jenny; Bleidorn, Wiebke; Rentfrow, Peter J; Potter, Jeff; Gosling, Samuel D

2015-09-01

What is the function of self-esteem? We classified relevant theoretical work into 3 perspectives. The cultural norm-fulfillment perspective regards self-esteem a result of adherence to cultural norms. The interpersonal-belonging perspective regards self-esteem as a sociometer of interpersonal belonging. The getting-ahead perspective regards self-esteem as a sociometer of getting ahead in the social world, while regarding low anxiety/neuroticism as a sociometer of getting along with others. The 3 perspectives make contrasting predictions on the relation between the Big Five personality traits and self-esteem across cultures. We tested these predictions in a self-report study (2,718,838 participants from 106 countries) and an informant-report study (837,655 informants from 64 countries). We obtained some evidence for cultural norm fulfillment, but the effect size was small. Hence, this perspective does not satisfactorily account for self-esteem's function. We found a strong relation between Extraversion and higher self-esteem, but no such relation between Agreeableness and self-esteem. These 2 traits are pillars of interpersonal belonging. Hence, the results do not fit the interpersonal-belonging perspective either. However, the results closely fit the getting-ahead perspective. The relation between Extraversion and higher self-esteem is consistent with this perspective, because Extraversion is the Big Five driver for getting ahead in the social world. The relation between Agreeableness and lower neuroticism is also consistent with this perspective, because Agreeableness is the Big Five driver for getting along with others. (c) 2015 APA, all rights reserved).

Does self-scheduling increase nurses' job satisfaction? An integrative literature review.

Science.gov (United States)

Koning, Clare

2014-09-25

Flexible work schedules give nurses the freedom and control to manage the demands of work and home, allow organisations to meet their staffing needs and can improve job satisfaction. This article reports the results of an integrative review of published peer-reviewed research and personal narratives that examined nurses' perceptions of the relationship between job satisfaction and a self-scheduling system. Results suggest that self-scheduling is one of a number of factors that influence job satisfaction, but that implementing and sustaining such a system can be challenging. The review also found that self-scheduling programmes underpin more flexible work schedules and can benefit nurses and their organisations.

Collaborative Optimal Pricing and Day-Ahead and Intra-Day Integrative Dispatch of the Active Distribution Network with Multi-Type Active Loads

Directory of Open Access Journals (Sweden)

Chong Chen

2018-04-01

Full Text Available In order to better handle the new features that emerge at both ends of supply and demand, new measures are constantly being introduced, such as demand-side management (DSM and prediction of uncertain output and load. However, the existing DSM strategies, like real-time price (RTP, and dispatch methods are optimized separately, and response models of active loads, such as the interruptible load (IL, are still imperfect, which make it difficult for the active distribution network (ADN to achieve global optimal operation. Therefore, to better manage active loads, the response characteristics including both the response time and the responsibility and compensation model of IL for cluster users, and the real-time demand response model for price based load, were analyzed and established. Then, a collaborative optimization strategy of RTP and optimal dispatch of ADN was proposed, which can realize an economical operation based on mutual benefit and win-win mode of supply and demand sides. Finally, the day-ahead and intra-day integrative dispatch model using different time-scale prediction data was established, which can achieve longer-term optimization while reducing the impact of prediction errors on the dispatch results. With numerical simulations, the effectiveness and superiority of the proposed strategy were verified.

A Market-Based Approach to Multi-factory Scheduling

Science.gov (United States)

Vytelingum, Perukrishnen; Rogers, Alex; MacBeth, Douglas K.; Dutta, Partha; Stranjak, Armin; Jennings, Nicholas R.

In this paper, we report on the design of a novel market-based approach for decentralised scheduling across multiple factories. Specifically, because of the limitations of scheduling in a centralised manner - which requires a center to have complete and perfect information for optimality and the truthful revelation of potentially commercially private preferences to that center - we advocate an informationally decentralised approach that is both agile and dynamic. In particular, this work adopts a market-based approach for decentralised scheduling by considering the different stakeholders representing different factories as self-interested, profit-motivated economic agents that trade resources for the scheduling of jobs. The overall schedule of these jobs is then an emergent behaviour of the strategic interaction of these trading agents bidding for resources in a market based on limited information and their own preferences. Using a simple (zero-intelligence) bidding strategy, we empirically demonstrate that our market-based approach achieves a lower bound efficiency of 84%. This represents a trade-off between a reasonable level of efficiency (compared to a centralised approach) and the desirable benefits of a decentralised solution.

Stochastic Optimization of Economic Dispatch for Microgrid Based on Approximate Dynamic Programming

DEFF Research Database (Denmark)

Shuai, Hang; Fang, Jiakun; Ai, Xiaomeng

2018-01-01

slope updating strategy is employed for the proposed method. With sufficient information extracted from these scenarios and embedded in the PLF function, the proposed ADPED algorithm can not only be used in day-ahead scheduling but also the intra-day optimization process. The algorithm can make full use......-ahead and intra-day operation under uncertainty....

Distributed continuous energy scheduling for dynamic virtual power plants

International Nuclear Information System (INIS)

Niesse, Astrid

2015-01-01

This thesis presents DynaSCOPE as distributed control method for continuous energy scheduling for dynamic virtual power plants (DVPP). DVPPs aggregate the flexibility of distributed energy units to address current energy markets. As an extension of the Virtual Power Plant concept they show high dynamics in aggregation and operation of energy units. Whereas operation schedules are set up for all energy units in a day-ahead planning procedure, incidents may render these schedules infeasible during execution, like deviation from prognoses or outages. Thus, a continuous scheduling process is needed to ensure product fulfillment. With DynaSCOPE, software agents representing single energy units solve this problem in a completely distributed heuristic approach. Using a stepped concept, several damping mechanisms are applied to allow minimum disturbance while continuously trying to fulfill the product as contracted at the market.

Patients' and clinicians' views on the optimum schedules for self-monitoring of blood pressure: a qualitative focus group and interview study.

Science.gov (United States)

Grant, Sabrina; Hodgkinson, James A; Milner, Siobhan L; Martin, Una; Tompson, Alice; Hobbs, Fd Richard; Mant, Jonathan; McManus, Richard J; Greenfield, Sheila M

2016-11-01

Self-monitoring of blood pressure is common but guidance on how it should be carried out varies and it is currently unclear how such guidance is viewed. To explore patients' and healthcare professionals' (HCPs) views and experiences of the use of different self-monitoring regimens to determine what is acceptable and feasible, and to inform future recommendations. Thirteen focus groups and four HCP interviews were held, with a total of 66 participants (41 patients and 25 HCPs) from primary and secondary care with and without experience of self-monitoring. Standard and shortened self-monitoring protocols were both considered. Focus groups and interviews were recorded, transcribed verbatim, and analysed using the constant comparative method. Patients generally supported structured schedules but with sufficient flexibility to allow adaptation to individual routine. They preferred a shorter (3-day) schedule to longer (7-day) regimens. Although HCPs could describe benefits for patients of using a schedule, they were reluctant to recommend a specific schedule. Concerns surrounded the use of different schedules for diagnosis and subsequent monitoring. Appropriate education was seen as vital by all participants to enable a self-monitoring schedule to be followed at home. There is not a 'one size fits all approach' to developing the optimum protocol from the perspective of users and those implementing it. An approach whereby patients are asked to complete the minimum number of readings required for accurate blood pressure estimation in a flexible manner seems most likely to succeed. Informative advice and guidance should incorporate such flexibility for patients and professionals alike. © British Journal of General Practice 2016.

Optimal Day-Ahead Scheduling of a Hybrid Electric Grid Using Weather Forecasts

Science.gov (United States)

2013-12-01

with 214 turbines [22]. In July 2011, the DoD declared that a complete study of 217 wind farm projects proposed in 35 states and Puerto Rico found...14. SUBJECT TERMS Hybrid electric grid , Microgrid , Hybrid renewable energy system , energy management center, optimization, Day...electric grid. In the case of a hybrid electric grid (HEG), or hybrid renewable energy system (HRES) where the microgrid can be connected to the commercial

Constraint-based job shop scheduling with ILOG SCHEDULER

NARCIS (Netherlands)

Nuijten, W.P.M.; Le Pape, C.

1998-01-01

We introduce constraint-based scheduling and discuss its main principles. An approximation algorithm based on tree search is developed for the job shop scheduling problem using ILOG SCHEDULER. A new way of calculating lower bounds on the makespan of the job shop scheduling problem is presented and

SignalGuru: Leveraging mobile phones for collaborative traffic signal schedule advisory

OpenAIRE

Koukoumidis, Emmanouil; Peh, Li-Shiuan; Martonosi, Margaret

2011-01-01

While traffic signals are necessary to safely control competing flows of traffic, they inevitably enforce a stop-and-go movement pattern that increases fuel consumption, reduces traffic flow and causes traffic jams. These side effects can be alleviated by providing drivers and their onboard computational devices (e.g., vehicle computer, smartphone) with information about the schedule of the traffic signals ahead. Based on when the signal ahead will turn green, drivers can then adjust speed so...

Day-Ahead Scheduling of a Photovoltaic Plant by the Energy Management of a Storage System

DEFF Research Database (Denmark)

Marinelli, Mattia; Sossan, Fabrizio; Isleifsson, Fridrik Rafn

2013-01-01

The paper discusses and describes a system for energy management of a 10 kW PV plant coupled with a 15 kW - 190 kWh storage system. The overall idea is, by knowing the meteorological forecast for the next 24h, to dispatch the PV system and to be able to grant the scheduled hourly energy profile...... by a proper management of the storage. Due to forecast inaccuracies, the energy manager controls the storage in order to ensure that the plan for hourly energy production is respected, minimizing the storage itself usage. The experimental study is carried out in SYSLAB, a distributed power system test...

Optimal bidding in Turkey day ahead electricity market for wind energy and pumped storage hydro power plant

Directory of Open Access Journals (Sweden)

Ceyhun Yıldız

2016-10-01

Full Text Available In electrical grid; when the demand power increases energy prices increase, when the demand decreases energy prices decrease. For this reason; to increase the total daily income, it is required to shift generations to the hours that high demand power values occurred. Wind Power Plants (WPP have unstable and uncontrollable generation characteristic. For this reason, energy storage systems are needed to shift the generations of WPPs in time scale. In this study, four wind power plants (WPP which are tied to the Turkish interconnected grid and a pumped hydro storage power plant (PSPP that meets the energy storage requirement of these power plants are investigated in Turkey day ahead energy market. An optimization algorithm is developed using linear programming technique to maximize the day ahead market bids of these plants which are going to generate power together. When incomes and generations of the plants that are operated with optimization strategy is analyzed, it is seen that annual income increased by 2.737% compared with WPPs ‘s alone operation and generations are substantially shifted to the high demand power occurred hours.

Availability Based Tariff and its impact On different Industry Players-A Review

Science.gov (United States)

Holmukhe, R. M.; Pawar, Yogini; Desai, R. S.; Hasarmani, T. S.

2010-10-01

ABT is a performance-based tariff for the supply of electricity by generators owned and controlled by the central government. It is also a new system of scheduling and dispatch, which requires both generators and beneficiaries to commit to day-ahead schedules. It is a system of rewards and penalties seeking to enforce day ahead pre-committed schedules, though variations are permitted if notified One and one half hours in advance. The order emphasizes prompt payment of dues. ABT (Availability Based Tariff) along with the Electricity Act of 2003 is perhaps the most significant and definitive step taken in the Indian power sector so far to bring more efficiency and focus to this vital infrastructure. The ABT mechanism is based on financial principles. ABT scheme is for unscheduled interchange of power. The paper reviews ABT issues, its components, clauses, mechanism, benefits and the impact of grid on different players like generation utilities, grid operator, consumers involved in power generation, transmission and distribution. While the proposed tariff structure has wide implications for each player, this deals exclusively with the technology challenges/opportunities thrown up by ABT.

Thermal energy storage for electricity-driven space heating in a day-ahead electricity market

DEFF Research Database (Denmark)

Pensini, Alessandro

2012-01-01

Thermal Energy Storage (TES) in a space heating (SH) application was investigated. The study aimed to determine the economic benefits of introducing TES into an electricity-driven SH system under a day-ahead electricity market. The performance of the TES was assessed by comparing the cost...... of electricity in a system with a TES unit to the case where no storage is in use and the entire heat requirement is fulfilled by purchasing electricity according to the actual load. The study had two goals: 1. Determining how the size – in terms of electricity input (Pmax) and energy capacity (Emax...

Schedule control in Ling Ao nuclear power project

International Nuclear Information System (INIS)

Xie Ahai

2007-01-01

Ling Ao Nuclear Power Station (LANP) is first one built up by self-reliance in China with power capacity 990x2 MWe. The results of quality control, schedule control and cost control are satisfactory. The commercial operation days of Unit 1 and Unit 2 were 28th May 2002 and 8th Jan. 2003 respectively, which were 48 days and 66 days in advance of the project schedule. This paper presents the practices of self-reliance schedule control system in LANP. The paper includes 10 sections: schedule control system; targets of schedule control; schedule control at early stage of project; construction schedule; scheduling practice; Point curves; schedule control of design and procurement; a good practice of construction schedule control on site; commissioning and startup schedule; schedule control culture. Three figures are attached. The main contents of the self-reliance schedule control system are as follows: to draw up reasonable schedules and targets; to setup management mechanism and procedures; to organize powerful project management team; to establish close monitoring system; to provide timely progress reports and statistics information. Five kinds of schedule control targets are introduced, i.e. bar-chart schedule; milesones; Point curves; interface management; hydraulic test schedule of auxiliary piping loops; EMR/EMC/EESR issuance schedules. Six levels of bar-chart schedules were adopted in LANP, but the bar-chart schedules were not satisfactory for complicated erection condition on site, even using six levels of schedules. So a kind of Point curves was developed and their advantages are explained. Scheduling method of three elements: activity, duration, logic, which was adopted in LANP, is introduced. The duration of each piping activities in LANP level 2 project schedule was calculated based on the relevant working Point quantities. The analysis and adjustment of Point curves are illustrated, i.e. balance of monthly quantities; possible production in the peakload

Generators' bidding behavior in the NYISO day-ahead wholesale electricity market

International Nuclear Information System (INIS)

Zhang, Ning

2009-01-01

This paper proposes a statistical and econometric model to analyze the generators' bidding behavior in the NYISO day-ahead wholesale electricity market. The generator level bidding data show very strong persistence in generators' grouping choices over time. Using dynamic random effect ordered probit model, we find that persistence is characterized by positive state dependence and unobserved heterogeneity and state dependence is more important than unobserved heterogeneity. The finding of true state dependence suggests a scope for economic policy intervention. If NYISO can implement an effective policy to switch generators from higher price groups to lower price groups, the effect is likely to be lasting. As a result, the market price can be lowered in the long-run. Generators' offered capacity is estimated by a two-stage sample selection model. The estimated results show that generators in higher-priced groups tend to withhold their capacity strategically to push up market prices. It further confirms the importance of an effective policy to turn generators into lower price groups in order to mitigate unexpected price spikes. The simulated market prices based on our estimated aggregate supply curve can replicate most volatility of actual DA market prices. Applying our models to different demand assumptions, we find that demand conditions can affect market prices significantly. It validates the importance of introducing demand side management during the restructure of electricity industry. (author)

Breastfeeding: Planning Ahead

Medline Plus

Full Text Available ... your life Partner resources Subscribe To receive Breastfeeding email updates Enter email Submit Planning ahead From choosing the crib to ... Breastfeeding: The #First31 Days Subscribe To receive Breastfeeding email updates Enter email Submit All material contained on ...

Multi-Level Round-Robin Multicast Scheduling with Look-Ahead Mechanism

DEFF Research Database (Denmark)

Yu, Hao; Ruepp, Sarah Renée; Berger, Michael Stübert

2011-01-01

constructs the Traffic Matrix before each cell transmission based on the fan-out vectors of the cells in the queues. A scheduling pointer independently moves on each column of the Traffic Matrix in a round-robin fashion and returns the decision to the Decision Matrix. The sync procedure is carried out...

HOROPLAN: computer-assisted nurse scheduling using constraint-based programming.

Science.gov (United States)

Darmoni, S J; Fajner, A; Mahé, N; Leforestier, A; Vondracek, M; Stelian, O; Baldenweck, M

1995-01-01

Nurse scheduling is a difficult and time consuming task. The schedule has to determine the day to day shift assignments of each nurse for a specified period of time in a way that satisfies the given requirements as much as possible, taking into account the wishes of nurses as closely as possible. This paper presents a constraint-based, artificial intelligence approach by describing a prototype implementation developed with the Charme language and the first results of its use in the Rouen University Hospital. Horoplan implements a non-cyclical constraint-based scheduling, using some heuristics. Four levels of constraints were defined to give a maximum of flexibility: French level (e.g. number of worked hours in a year), hospital level (e.g. specific day-off), department level (e.g. specific shift) and care unit level (e.g. specific pattern for week-ends). Some constraints must always be verified and can not be overruled and some constraints can be overruled at a certain cost. Rescheduling is possible at any time specially in case of an unscheduled absence.

Multi-Time Scale Coordinated Scheduling Strategy with Distributed Power Flow Controllers for Minimizing Wind Power Spillage

Directory of Open Access Journals (Sweden)

Yi Tang

2017-11-01

Full Text Available The inherent variability and randomness of large-scale wind power integration have brought great challenges to power flow control and dispatch. The distributed power flow controller (DPFC has the higher flexibility and capacity in power flow control in the system with wind generation. This paper proposes a multi-time scale coordinated scheduling model with DPFC to minimize wind power spillage. Configuration of DPFCs is initially determined by stochastic method. Afterward, two sequential procedures containing day-head and real-time scales are applied for determining maximum schedulable wind sources, optimal outputs of generating units and operation setting of DPFCs. The generating plan is obtained initially in day-ahead scheduling stage and modified in real-time scheduling model, while considering the uncertainty of wind power and fast operation of DPFC. Numerical simulation results in IEEE-RTS79 system illustrate that wind power is maximum scheduled with the optimal deployment and operation of DPFC, which confirms the applicability and effectiveness of the proposed method.

Optimal Bidding Strategies for Wind Power Producers in the Day-ahead Electricity Market

Directory of Open Access Journals (Sweden)

Xiaolin Liu

2012-11-01

Full Text Available Wind Power Producers (WPPs seek to maximize profit and minimize the imbalance costs when bidding into the day-ahead market, but uncertainties in the hourly available wind and forecasting errors make the bidding risky. This paper assumes that hourly wind power output given by the forecast follows a normal distribution, and proposes three different bidding strategies, i.e., the expected profit-maximization strategy (EPS, the chance-constrained programming-based strategy (CPS and the multi-objective bidding strategy (ECPS. Analytical solutions under the three strategies are obtained. Comparisons among the three strategies are conducted on a hypothetical wind farm which follows the Spanish market rules. Results show that bid under the EPS is highly dependent on market clearing price, imbalance prices, and also the mean value and standard deviation of wind forecast, and that bid under the CPS is largely driven by risk parameters and the mean value and standard deviation of the wind forecast. The ECPS combining both EPS and CPS tends to choose a compromise bid. Furthermore, the ECPS can effectively control the tradeoff between expected profit and target profit for WPPs operating in volatile electricity markets.

Agent-based scheduling for aircraft deicing

NARCIS (Netherlands)

Mao, X.; Ter Mors, A.W.; Roos, N.; Witteveen, C.

2006-01-01

The planning and scheduling of the deicing and anti-icing activities is an important and challenging part of airport departure planning. Deicing planning has to be done in a highly dynamic environment involving several autonomous and self-interested parties. Traditional centralized scheduling

A day-ahead market for electricity in Alberta : is there a case to be made?

International Nuclear Information System (INIS)

Fronimos, P.

2006-01-01

Following the success of the introduction of competition in several heavily regulated industries in the 1980s and 1990s, traditional utilities were broken up and markets were introduced for their respective services. Some of these markets evolved into complex structures with multiple sub-markets for installed capacity, energy, transmission and for all types of reserves. Electricity submarkets now operate in a similar manner in different timeframes comprising two settlement systems: the Day Ahead (DA) market, operating a day ahead of the actual generation and consumption of electricity and one that operates in real time, the Real-Time (RT) or Balancing market. This paper explored the case for a binding DA market for electricity in Alberta, by looking at the challenges facing the marketplace and examining how using a DA market would affect them. This paper hypothesized that a correctly designed and implemented, financially binding DA market would enhance the fidelity of the price signal in Alberta by providing an information rich environment for participants and the system operator. The paper defined and discussed both types of settlement systems. It then discussed the DA market in Alberta in terms of risk management, reliability, price fidelity and demand response. It was noted that some of the benefits of using a DA market could also be achieved by improvements to the existing market. Alberta faces several challenges, such as merit order instability and price volatility which are likely due to market design and operations rather than the inherent inability of a power exchange to address them. 31 refs., 1 tab., 3 figs

Comparative Study on KNN and SVM Based Weather Classification Models for Day Ahead Short Term Solar PV Power Forecasting

Directory of Open Access Journals (Sweden)

Fei Wang

2017-12-01

Full Text Available Accurate solar photovoltaic (PV power forecasting is an essential tool for mitigating the negative effects caused by the uncertainty of PV output power in systems with high penetration levels of solar PV generation. Weather classification based modeling is an effective way to increase the accuracy of day-ahead short-term (DAST solar PV power forecasting because PV output power is strongly dependent on the specific weather conditions in a given time period. However, the accuracy of daily weather classification relies on both the applied classifiers and the training data. This paper aims to reveal how these two factors impact the classification performance and to delineate the relation between classification accuracy and sample dataset scale. Two commonly used classification methods, K-nearest neighbors (KNN and support vector machines (SVM are applied to classify the daily local weather types for DAST solar PV power forecasting using the operation data from a grid-connected PV plant in Hohhot, Inner Mongolia, China. We assessed the performance of SVM and KNN approaches, and then investigated the influences of sample scale, the number of categories, and the data distribution in different categories on the daily weather classification results. The simulation results illustrate that SVM performs well with small sample scale, while KNN is more sensitive to the length of the training dataset and can achieve higher accuracy than SVM with sufficient samples.

Microcomputer-based workforce scheduling for hospital porters.

Science.gov (United States)

Lin, C K

1999-01-01

This paper focuses on labour scheduling for hospital porters who are the major workforce providing routine cleansing of wards, transportation and messenger services. Generating an equitable monthly roster for porters while meeting the daily minimum demand is a tedious task scheduled manually by a supervisor. In considering a variety of constraints and goals, a manual schedule was usually produced in seven to ten days. To be in line with the strategic goal of scientific management of an acute care regional hospital in Hong Kong, a microcomputer-based algorithm was developed to schedule the monthly roster. The algorithm, coded in Digital Visual Fortran 5.0 Professional, could generate a monthly roster in seconds. Implementation has been carried out since September 1998 and the results proved to be useful to hospital administrators and porters. This paper discusses both the technical and human issues involved during the computerization process.

Co-optimization of Energy and Demand-Side Reserves in Day-Ahead Electricity Markets

Science.gov (United States)

Surender Reddy, S.; Abhyankar, A. R.; Bijwe, P. R.

2015-04-01

This paper presents a new multi-objective day-ahead market clearing (DAMC) mechanism with demand-side reserves/demand response (DR) offers, considering realistic voltage-dependent load modeling. The paper proposes objectives such as social welfare maximization (SWM) including demand-side reserves, and load served error (LSE) minimization. In this paper, energy and demand-side reserves are cleared simultaneously through co-optimization process. The paper clearly brings out the unsuitability of conventional SWM for DAMC in the presence of voltage-dependent loads, due to reduction of load served (LS). Under such circumstances multi-objective DAMC with DR offers is essential. Multi-objective Strength Pareto Evolutionary Algorithm 2+ (SPEA 2+) has been used to solve the optimization problem. The effectiveness of the proposed scheme is confirmed with results obtained from IEEE 30 bus system.

Design method for marine direct drive volume control ahead actuator

Directory of Open Access Journals (Sweden)

WANG Haiyang

2018-02-01

Full Text Available [Objectives] In order to reduce the size, weight and auxiliary system configuration of marine ahead actuators, this paper proposes a kind of direct drive volume control electro-hydraulic servo ahead actuator. [Methods] The protruding and indenting control of the servo oil cylinder are realized through the forward and reverse of the bidirectional working gear pump, and the flow matching valve implements the self-locking of the ahead actuator in the target position. The mathematical model of the ahead actuator is established, and an integral separation fuzzy PID controller designed. On this basis, using AMESim software to build a simulation model of the ahead actuator, and combined with testing, this paper completes an analysis of the control strategy research and dynamic and static performance of the ahead actuator. [Results] The experimental results agree well with the simulation results and verify the feasibility of the ahead actuator's design. [Conclusions] The research results of this paper can provide valuable references for the integration and miniaturization design of marine ahead actuators.

Physical Activity and Sedentary Time among Young Children in Full-Day Kindergarten: Comparing Traditional and Balanced Day Schedules

Science.gov (United States)

Vanderloo, Leigh M.; Tucker, Patricia

2017-01-01

Objective: To compare physical activity and sedentary time among young children whose schools adhere to traditional (i.e. three outdoor playtimes = 70 minutes) versus balanced day (i.e. two outdoor playtimes = ~55 minutes) schedules in Ontario full-day kindergarten classrooms. Design: The project was part of a larger, 2-year cross-sectional study.…

Scenario-based stochastic optimal operation of wind, photovoltaic, pump-storage hybrid system in frequency- based pricing

International Nuclear Information System (INIS)

Zare Oskouei, Morteza; Sadeghi Yazdankhah, Ahmad

2015-01-01

Highlights: • Two-stage objective function is proposed for optimization problem. • Hourly-based optimal contractual agreement is calculated. • Scenario-based stochastic optimization problem is solved. • Improvement of system frequency by utilizing PSH unit. - Abstract: This paper proposes the operating strategy of a micro grid connected wind farm, photovoltaic and pump-storage hybrid system. The strategy consists of two stages. In the first stage, the optimal hourly contractual agreement is determined. The second stage corresponds to maximizing its profit by adapting energy management strategy of wind and photovoltaic in coordination with optimum operating schedule of storage device under frequency based pricing for a day ahead electricity market. The pump-storage hydro plant is utilized to minimize unscheduled interchange flow and maximize the system benefit by participating in frequency control based on energy price. Because of uncertainties in power generation of renewable sources and market prices, generation scheduling is modeled by a stochastic optimization problem. Uncertainties of parameters are modeled by scenario generation and scenario reduction method. A powerful optimization algorithm is proposed using by General Algebraic Modeling System (GAMS)/CPLEX. In order to verify the efficiency of the method, the algorithm is applied to various scenarios with different wind and photovoltaic power productions in a day ahead electricity market. The numerical results demonstrate the effectiveness of the proposed approach.

Robust optimization for load scheduling of a smart home with photovoltaic system

International Nuclear Information System (INIS)

Wang, Chengshan; Zhou, Yue; Jiao, Bingqi; Wang, Yamin; Liu, Wenjian; Wang, Dan

2015-01-01

Highlights: • Robust household load scheduling is presented for smart homes with PV system. • A robust counterpart is formulated to deal with PV output uncertainty. • The robust counterpart is finally transformed to a quadratic programming problem. • Load schedules with different robustness can be made by the proposed method. • Feed-in tariff and PV output would affect the significance of the proposed method. - Abstract: In this paper, a robust approach is developed to tackle the uncertainty of PV power output for load scheduling of smart homes integrated with household PV system. Specifically, a robust formulation is proposed and further transformed to an equivalent quadratic programming problem. Day-ahead load schedules with different robustness can be generated by solving the proposed robust formulation with different predefined parameters. The validity and advantage of the proposed approach has been verified by simulation results. Also, the effects of feed-in tariff and PV output have been evaluated

Relationship between shift work schedule and self-reported sleep quality in Chinese employees.

Science.gov (United States)

Ma, Yifei; Wei, Fu; Nie, Guanghui; Zhang, Li'e; Qin, Jian; Peng, Suwan; Xiong, Feng; Zhang, Zhiyong; Yang, Xiaobo; Peng, Xiaowu; Wang, Mingjun; Zou, Yunfeng

2018-02-01

Few studies have reported on the effects of fixed and rotating shift systems on the prevalence of sleep disturbance. Thus, in this study, the relationships between different work schedules and sleep disturbance in Chinese workers were investigated. A total of 2180 workers aged 19-65 years responded to the self-report questionnaire on shift work schedule (fixed day-shift, fixed night-shift, two-shift or three-shift system), working hours a day, and working days a week, physical effort, subjective sleep quality and subjective mental state. It was found that the rotating shift workers, namely, two- and three-shift workers, exhibited higher risks of sleep disturbance than with the fixed day-shift workers did (OR 1.37; 95% CI 1.07to 1.74; and OR 2.19; 95% CI 1.52 to 3.15, respectively). The risk was particularly high among two- or three-shift workers who worked more than 8 hours a day or more than 5 days a week and among three-shift workers who reported both light and heavy physical effort at work. Moreover, the two- and three-shift workers (rotating shift workers) suffered from poorer sleep quality than the fixed night shift workers did (OR 1.84; 95% CI 1.01 to 3.32; and OR 2.94; 95% CI 1.53 to 5.64, respectively). Consequently, rotating shift work (two- and three-shift work) is a risk factor for sleep disturbance, and the fixed work rhythm may contribute to the quality of sleep.

Multi-day activity scheduling reactions to planned activities and future events in a dynamic model of activity-travel behavior

NARCIS (Netherlands)

Nijland, L.; Arentze, T.A.; Timmermans, H.J.P.

2014-01-01

Modeling multi-day planning has received scarce attention in activity-based transport demand modeling so far. However, new dynamic activity-based approaches are being developed at the current moment. The frequency and inflexibility of planned activities and events in activity schedules of

Multi-Day Activity Scheduling Reactions to Planned Activities and Future Events in a Dynamic Model of Activity-Travel Behavior

NARCIS (Netherlands)

Nijland, L.; Arentze, T.; Timmermans, H.

2014-01-01

Modeling multi-day planning has received scarce attention in activity-based transport demand modeling so far. However, new dynamic activity-based approaches are being developed at the current moment. The frequency and inflexibility of planned activities and events in activity schedules of

Stochastic profit-based scheduling of industrial virtual power plant using the best demand response strategy

International Nuclear Information System (INIS)

Nosratabadi, Seyyed Mostafa; Hooshmand, Rahmat-Allah; Gholipour, Eskandar

2016-01-01

Highlights: • VPPs and IVPPs are defined for energy management of aggregated generations. • IVPP can manage industrial microgrid containing some relevant load and generation. • A stochastic modeling is proposed to schedule optimal generations in competition market. • Wind generation and day-ahead and spot market prices are considered to be stochastic. • A new DRL program selection scheme is presented in the scheduling procedure. - Abstract: One of the main classified microgrids in a power system is the industrial microgrid. Due to its behaviors and the heavy loads, its energy management is challengeable. Virtual Power Plant (VPP) can be an important concept in managing such problems in this kind of grids. Here, a transmission power system is considered as a Regional Electric Company (REC) and the VPPs comprising Distributed Generation (DG) units and Demand Response Loads (DRLs) are determined in this system. This paper focuses on Industrial VPP (IVPP) and its management. An IVPP can be determined as a management unit comprising generations and loads in an industrial microgrid. Since the scheduling procedure for these units is very important for their participation in a short-term electric market, a stochastic formulation is proposed for power scheduling in VPPs especially in IVPPs in this paper. By introducing the DRL programs and using the proposed modeling, the operator can select the best DRL program for each VPP in a scheduling procedure. In this regard, a suitable approach is presented to determine the proposed formulation and its solution in a Mixed Integer Non-Linear Programming (MINLP). To validate the performance of the proposed method, the IEEE Reliability Test System (IEEE-RTS) is considered to apply the method on it, while some challenging aspects are presented.

Conception of Self-Construction Production Scheduling System

Science.gov (United States)

Xue, Hai; Zhang, Xuerui; Shimizu, Yasuhiro; Fujimura, Shigeru

With the high speed innovation of information technology, many production scheduling systems have been developed. However, a lot of customization according to individual production environment is required, and then a large investment for development and maintenance is indispensable. Therefore now the direction to construct scheduling systems should be changed. The final objective of this research aims at developing a system which is built by it extracting the scheduling technique automatically through the daily production scheduling work, so that an investment will be reduced. This extraction mechanism should be applied for various production processes for the interoperability. Using the master information extracted by the system, production scheduling operators can be supported to accelerate the production scheduling work easily and accurately without any restriction of scheduling operations. By installing this extraction mechanism, it is easy to introduce scheduling system without a lot of expense for customization. In this paper, at first a model for expressing a scheduling problem is proposed. Then the guideline to extract the scheduling information and use the extracted information is shown and some applied functions are also proposed based on it.

Continuity-Aware Scheduling Algorithm for Scalable Video Streaming

Directory of Open Access Journals (Sweden)

Atinat Palawan

2016-05-01

Full Text Available The consumer demand for retrieving and delivering visual content through consumer electronic devices has increased rapidly in recent years. The quality of video in packet networks is susceptible to certain traffic characteristics: average bandwidth availability, loss, delay and delay variation (jitter. This paper presents a scheduling algorithm that modifies the stream of scalable video to combat jitter. The algorithm provides unequal look-ahead by safeguarding the base layer (without the need for overhead of the scalable video. The results of the experiments show that our scheduling algorithm reduces the number of frames with a violated deadline and significantly improves the continuity of the video stream without compromising the average Y Peek Signal-to-Noise Ratio (PSNR.

Reirradiation of head and neck neoplasms using twice-a-day scheduling

International Nuclear Information System (INIS)

Tercilla, O.F.; Schmidt-Ullrich, R.; Wazer, D.E.

1993-01-01

Between 1985 and 1988, we have explored the value of twice-a-day (BID) irradiation for the retreatment of head and neck neoplasms. In this pilot study of ten patients we used a schedule of BID irradiation at fraction sizes between 1.4 and 1.6 Gy separated by at least 6 h. Of the four patients were treated with curative intent, three patients received 30 Gy in 20 fractions over twelve days followed within ten days by an interstitial/intracavitary Ir-192 implant boost to doses of 30 to 40 Gy and one patient was treated with a 32 Gy BID boost. Four patients were reirradiated with aggressive palliation and received 45 Gy in 30 fractions over 26 days including a break in the third week. The remaining two patients were treated with palliative intent to 30 Gy in 20 fractions over twelve days. Eight patients were treated for recurrent/persistent or second carcinomas, one for a recurrent glomus jugulare tumor. At a median follow-up of 36 months, ranging from six to 61 months, nine of ten patients experienced excellent symptomatic relief. Five patients are alive and free of tumor, one patient is alive with distant metastases, and two each are dead from local or systemic tumor progression. All four patients retreated for cure are alive with no evidence of local disease. The tolerance and tumor control rate of the BID reirradition schedule were good with severe late sequelae in only one patient. (orig.) [de

Self-scheduling and bidding strategies of thermal units with stochastic emission constraints

International Nuclear Information System (INIS)

Laia, R.; Pousinho, H.M.I.; Melíco, R.; Mendes, V.M.F.

2015-01-01

Highlights: • The management of thermal power plants is considered for different emission allowance levels. • The uncertainty on electricity price is considered by a set of scenarios. • A stochastic MILP approach allows devising the bidding strategies and hedging against price uncertainty and emission allowances. - Abstract: This paper is on the self-scheduling problem for a thermal power producer taking part in a pool-based electricity market as a price-taker, having bilateral contracts and emission-constrained. An approach based on stochastic mixed-integer linear programming approach is proposed for solving the self-scheduling problem. Uncertainty regarding electricity price is considered through a set of scenarios computed by simulation and scenario-reduction. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. A requirement on emission allowances to mitigate carbon footprint is modelled by a stochastic constraint. Supply functions for different emission allowance levels are accessed in order to establish the optimal bidding strategy. A case study is presented to illustrate the usefulness and the proficiency of the proposed approach in supporting biding strategies

Constraint-based scheduling

Science.gov (United States)

Zweben, Monte

1993-01-01

The GERRY scheduling system developed by NASA Ames with assistance from the Lockheed Space Operations Company, and the Lockheed Artificial Intelligence Center, uses a method called constraint-based iterative repair. Using this technique, one encodes both hard rules and preference criteria into data structures called constraints. GERRY repeatedly attempts to improve schedules by seeking repairs for violated constraints. The system provides a general scheduling framework which is being tested on two NASA applications. The larger of the two is the Space Shuttle Ground Processing problem which entails the scheduling of all the inspection, repair, and maintenance tasks required to prepare the orbiter for flight. The other application involves power allocation for the NASA Ames wind tunnels. Here the system will be used to schedule wind tunnel tests with the goal of minimizing power costs. In this paper, we describe the GERRY system and its application to the Space Shuttle problem. We also speculate as to how the system would be used for manufacturing, transportation, and military problems.

Neural networks approach to forecast several hour ahead electricity prices and loads in deregulated market

Energy Technology Data Exchange (ETDEWEB)

Mandal, Paras; Senjyu, Tomonobu [Department of Electrical and Electronics, University of the Ryukyus, 1 Senbaru, Nagakami Nishihara, Okinawa 903-0213 (Japan); Funabashi, Toshihisa [Meidensha Corporation, Tokyo 103-8515 (Japan)

2006-09-15

In daily power markets, forecasting electricity prices and loads are the most essential task and the basis for any decision making. An approach to predict the market behaviors is to use the historical prices, loads and other required information to forecast the future prices and loads. This paper introduces an approach for several hour ahead (1-6h) electricity price and load forecasting using an artificial intelligence method, such as a neural network model, which uses publicly available data from the NEMMCO web site to forecast electricity prices and loads for the Victorian electricity market. An approach of selection of similar days is proposed according to which the load and price curves are forecasted by using the information of the days being similar to that of the forecast day. A Euclidean norm with weighted factors is used for the selection of the similar days. Two different ANN models, one for one to six hour ahead load forecasting and another for one to six hour ahead price forecasting have been proposed. The MAPE (mean absolute percentage error) results show a clear increasing trend with the increase in hour ahead load and price forecasting. The sample average of MAPEs for one hour ahead price forecasts is 9.75%. This figure increases to only 20.03% for six hour ahead predictions. Similarly, the one to six hour ahead load forecast errors (MAPE) range from 0.56% to 1.30% only. MAPE results show that several hour ahead electricity prices and loads in the deregulated Victorian market can be forecasted with reasonable accuracy. (author)

Neural networks approach to forecast several hour ahead electricity prices and loads in deregulated market

International Nuclear Information System (INIS)

Mandal, Paras; Senjyu, Tomonobu; Funabashi, Toshihisa

2006-01-01

In daily power markets, forecasting electricity prices and loads are the most essential task and the basis for any decision making. An approach to predict the market behaviors is to use the historical prices, loads and other required information to forecast the future prices and loads. This paper introduces an approach for several hour ahead (1-6 h) electricity price and load forecasting using an artificial intelligence method, such as a neural network model, which uses publicly available data from the NEMMCO web site to forecast electricity prices and loads for the Victorian electricity market. An approach of selection of similar days is proposed according to which the load and price curves are forecasted by using the information of the days being similar to that of the forecast day. A Euclidean norm with weighted factors is used for the selection of the similar days. Two different ANN models, one for one to six hour ahead load forecasting and another for one to six hour ahead price forecasting have been proposed. The MAPE (mean absolute percentage error) results show a clear increasing trend with the increase in hour ahead load and price forecasting. The sample average of MAPEs for one hour ahead price forecasts is 9.75%. This figure increases to only 20.03% for six hour ahead predictions. Similarly, the one to six hour ahead load forecast errors (MAPE) range from 0.56% to 1.30% only. MAPE results show that several hour ahead electricity prices and loads in the deregulated Victorian market can be forecasted with reasonable accuracy

Influence of intravenous self-administered psychomotor stimulants on performance of rhesus monkeys in a multiple schedule paradigm.

Science.gov (United States)

Hoffmeister, F

1980-01-01

Rhesus monkeys were trained to complete three multiple schedules. The schedules consisted of three components: a fixed interval (component 1), a variable interval (component 2), and a fixed ratio (component 3). During components 1 and 2, pressing lever 1 was always reinforced by food delivery. During component 3, pressing lever 2 resulted in either food delivery or intravenous infusions of saline solution, solutions of cocaine, of d-amphetamine, of phenmetrazine, or fenetylline. In schedule I, animals were presented with all three components independent of key-pressing behavior during components 1 and 2. In schedule II the availability of component 2 was dependent on completion of component 1. Component 3 was made available only on completion of component 2. Noncompletion of components 1 or 2 resulted in time-out of 15 and 10 min, respectively. Schedule III was identical with schedule II, except that in schedule III the completion of components was indicated only by a change in the lever lights. The influence of self-administered drugs on behavior in all three components was evaluated. Self-administration of psychomotor stimulants impaired the performance of animals and delayed completion of components 1 and 2 of schedules I, II, and III. The effects on behavior were similar with low drug intake in schedule III, moderate intake in schedule II, and high drug intake in schedule I. These effects were strong with self-administration of phenmetrazine, moderate with self-administration of cocaine and d-amphetamine, and weak with self-administration of fenetylline.

Look-ahead procedures for Lanczos-type product methods based on three-term recurrences

Energy Technology Data Exchange (ETDEWEB)

Gutknecht, M.H.; Ressel, K.J. [Swiss Center for Scientific Computing, Zuerich (Switzerland)

1996-12-31

Lanczos-type product methods for the solution of large sparse non-Hermitian linear systems either square the Lanczos process or combine it with a local minimization of the residual. They inherit from the underlying Lanczos process the danger of breakdown. For various Lanczos-type product methods that are based on the Lanczos three-term recurrence, look-ahead versions are presented, which avoid such breakdowns or near breakdowns with a small computational overhead. Different look-ahead strategies are discussed and their efficiency is demonstrated in several numerical examples.

Segment Fixed Priority Scheduling for Self Suspending Real Time Tasks

Science.gov (United States)

2016-08-11

a compute- intensive system such as a self - driving car that we have recently developed [28]. Such systems run computation-demanding algorithms...Applications. In RTSS, 2012. [12] J. Kim et al. Parallel Scheduling for Cyber-Physical Systems: Analysis and Case Study on a Self - Driving Car . In ICCPS...leveraging GPU can be modeled using a multi-segment self -suspending real-time task model. For example, a planning algorithm for autonomous driving can

Constraint-based scheduling applying constraint programming to scheduling problems

CERN Document Server

Baptiste, Philippe; Nuijten, Wim

2001-01-01

Constraint Programming is a problem-solving paradigm that establishes a clear distinction between two pivotal aspects of a problem: (1) a precise definition of the constraints that define the problem to be solved and (2) the algorithms and heuristics enabling the selection of decisions to solve the problem. It is because of these capabilities that Constraint Programming is increasingly being employed as a problem-solving tool to solve scheduling problems. Hence the development of Constraint-Based Scheduling as a field of study. The aim of this book is to provide an overview of the most widely used Constraint-Based Scheduling techniques. Following the principles of Constraint Programming, the book consists of three distinct parts: The first chapter introduces the basic principles of Constraint Programming and provides a model of the constraints that are the most often encountered in scheduling problems. Chapters 2, 3, 4, and 5 are focused on the propagation of resource constraints, which usually are responsibl...

Optimal operational strategies for a day-ahead electricity market in the presence of market power using multi-objective evolutionary algorithms

Science.gov (United States)

Rodrigo, Deepal

2007-12-01

This dissertation introduces a novel approach for optimally operating a day-ahead electricity market not only by economically dispatching the generation resources but also by minimizing the influences of market manipulation attempts by the individual generator-owning companies while ensuring that the power system constraints are not violated. Since economic operation of the market conflicts with the individual profit maximization tactics such as market manipulation by generator-owning companies, a methodology that is capable of simultaneously optimizing these two competing objectives has to be selected. Although numerous previous studies have been undertaken on the economic operation of day-ahead markets and other independent studies have been conducted on the mitigation of market power, the operation of a day-ahead electricity market considering these two conflicting objectives simultaneously has not been undertaken previously. These facts provided the incentive and the novelty for this study. A literature survey revealed that many of the traditional solution algorithms convert multi-objective functions into either a single-objective function using weighting schemas or undertake optimization of one function at a time. Hence, these approaches do not truly optimize the multi-objectives concurrently. Due to these inherent deficiencies of the traditional algorithms, the use of alternative non-traditional solution algorithms for such problems has become popular and widely used. Of these, multi-objective evolutionary algorithms (MOEA) have received wide acceptance due to their solution quality and robustness. In the present research, three distinct algorithms were considered: a non-dominated sorting genetic algorithm II (NSGA II), a multi-objective tabu search algorithm (MOTS) and a hybrid of multi-objective tabu search and genetic algorithm (MOTS/GA). The accuracy and quality of the results from these algorithms for applications similar to the problem investigated here

Demand side management in a day-ahead wholesale market: A comparison of industrial & social welfare approaches

International Nuclear Information System (INIS)

Jiang, Bo; Farid, Amro M.; Youcef-Toumi, Kamal

2015-01-01

Highlights: • We compare two demand side management in a day-ahead electricity wholesale market. • We develop and reconcile social welfare & industrial DSM mathematical models. • We show the industrial netload has an additional forecast quantity of baseline. • We analytically and numerically show the model equivalence with accurate baseline. • We numerically demonstrate the baseline errors lead to higher and costlier dispatch. - Abstract: The intermittent nature of renewable energy has been discussed in the context of the operational challenges that it brings to electrical grid reliability. Demand side management (DSM) with its ability to allow customers to adjust electricity consumption in response to market signals has often been recognized as an efficient way to mitigate the variable effects of renewable energy as well as to increase system efficiency and reduce system costs. However, the academic & industrial literature have taken divergent approaches to DSM implementation. While the popular approach among academia adopts a social welfare maximization formulation, the industrial practice compensates customers according to their load reduction from a predefined electricity consumption baseline that would have occurred without DSM. This paper rigorously compares these two different approaches in a day-ahead wholesale market context analytically and in a test case using the same system configuration and mathematical formalism. The comparison of the two models showed that a proper reconciliation of the two models might make them mitigate the stochastic netload in fundamentally the same way, but only under very specific conditions which are rarely met in practice. While the social welfare model uses a stochastic net load composed of two terms, the industrial DSM model uses a stochastic net load composed of three terms including the additional baseline term. DSM participants are likely to manipulate the baseline in order to receive greater financial

A Time Scheduling Model of Logistics Service Supply Chain Based on the Customer Order Decoupling Point: A Perspective from the Constant Service Operation Time

Science.gov (United States)

Yang, Yi; Xu, Haitao; Liu, Xiaoyan; Wang, Yijia; Liang, Zhicheng

2014-01-01

In mass customization logistics service, reasonable scheduling of the logistics service supply chain (LSSC), especially time scheduling, is benefit to increase its competitiveness. Therefore, the effect of a customer order decoupling point (CODP) on the time scheduling performance should be considered. To minimize the total order operation cost of the LSSC, minimize the difference between the expected and actual time of completing the service orders, and maximize the satisfaction of functional logistics service providers, this study establishes an LSSC time scheduling model based on the CODP. Matlab 7.8 software is used in the numerical analysis for a specific example. Results show that the order completion time of the LSSC can be delayed or be ahead of schedule but cannot be infinitely advanced or infinitely delayed. Obtaining the optimal comprehensive performance can be effective if the expected order completion time is appropriately delayed. The increase in supply chain comprehensive performance caused by the increase in the relationship coefficient of logistics service integrator (LSI) is limited. The relative concern degree of LSI on cost and service delivery punctuality leads to not only changes in CODP but also to those in the scheduling performance of the LSSC. PMID:24715818

A time scheduling model of logistics service supply chain based on the customer order decoupling point: a perspective from the constant service operation time.

Science.gov (United States)

Liu, Weihua; Yang, Yi; Xu, Haitao; Liu, Xiaoyan; Wang, Yijia; Liang, Zhicheng

2014-01-01

In mass customization logistics service, reasonable scheduling of the logistics service supply chain (LSSC), especially time scheduling, is benefit to increase its competitiveness. Therefore, the effect of a customer order decoupling point (CODP) on the time scheduling performance should be considered. To minimize the total order operation cost of the LSSC, minimize the difference between the expected and actual time of completing the service orders, and maximize the satisfaction of functional logistics service providers, this study establishes an LSSC time scheduling model based on the CODP. Matlab 7.8 software is used in the numerical analysis for a specific example. Results show that the order completion time of the LSSC can be delayed or be ahead of schedule but cannot be infinitely advanced or infinitely delayed. Obtaining the optimal comprehensive performance can be effective if the expected order completion time is appropriately delayed. The increase in supply chain comprehensive performance caused by the increase in the relationship coefficient of logistics service integrator (LSI) is limited. The relative concern degree of LSI on cost and service delivery punctuality leads to not only changes in CODP but also to those in the scheduling performance of the LSSC.

BIM-BASED SCHEDULING OF CONSTRUCTION

DEFF Research Database (Denmark)

Andersson, Niclas; Büchmann-Slorup, Rolf

2010-01-01

The potential of BIM is generally recognized in the construction industry, but the practical application of BIM for management purposes is, however, still limited among contractors. The objective of this study is to review the current scheduling process of construction in light of BIM...... and communicate. Scheduling on the detailed level, on the other hand, follows a stipulated approach to scheduling, i.e. the Last Planner System (LPS), which is characterized by involvement of all actors in the construction phase. Thus, the major challenge when implementing BIM-based scheduling is to improve...

Transactive-Market-Based Operation of Distributed Electrical Energy Storage with Grid Constraints

Directory of Open Access Journals (Sweden)

M. Nazif Faqiry

2017-11-01

Full Text Available In a transactive energy market, distributed energy resources (DERs such as dispatchable distributed generators (DGs, electrical energy storages (EESs, distribution-scale load aggregators (LAs, and renewable energy sources (RESs have to earn their share of supply or demand through a bidding process. In such a market, the distribution system operator (DSO may optimally schedule these resources, first in a forward market, i.e., day-ahead, and in a real-time market later on, while maintaining a reliable and economic distribution grid. In this paper, an efficient day-ahead scheduling of these resources, in the presence of interaction with wholesale market at the locational marginal price (LMP, is studied. Due to inclusion of EES units with integer constraints, a detailed mixed integer linear programming (MILP formulation that incorporates simplified DistFlow equations to account for grid constraints is proposed. Convex quadratic line and transformer apparent power flow constraints have been linearized using an outer approximation. The proposed model schedules DERs based on distribution locational marginal price (DLMP, which is obtained as the Lagrange multiplier of the real power balance constraint at each distribution bus while maintaining physical grid constraints such as line limits, transformer limits, and bus voltage magnitudes. Case studies are performed on a modified IEEE 13-bus system with high DER penetration. Simulation results show the validity and efficiency of the proposed model.

Sharing wind power forecasts in electricity markets: A numerical analysis

DEFF Research Database (Denmark)

Exizidis, Lazaros; Pinson, Pierre; Kazempour, Jalal

2016-01-01

In an electricity pool with significant share of wind power, all generators including conventional and wind power units are generally scheduled in a day-ahead market based on wind power forecasts. Then, a real-time market is cleared given the updated wind power forecast and fixed day......-ahead decisions to adjust power imbalances. This sequential market-clearing process may cope with serious operational challenges such as severe power shortage in real-time due to erroneous wind power forecasts in day-ahead market. To overcome such situations, several solutions can be considered such as adding...... flexible resources to the system. In this paper, we address another potential solution based on information sharing in which market players share their own wind power forecasts with others in day-ahead market. This solution may improve the functioning of sequential market-clearing process through making...

Planning and scheduling - A schedule's performance

International Nuclear Information System (INIS)

Whitman, N.M.

1993-01-01

Planning and scheduling is a process whose time has come to PSI Energy. With an awareness of the challenges ahead, individuals must look for ways to enhance the corporate competitiveness. Working toward this goal means that each individual has to dedicate themselves to this more competitive corporate environment. Being competitive may be defined as the ability of each employee to add value to the corporation's economic well being. The timely and successful implementation of projects greatly enhances competitiveness. Those projects that do not do well often suffer from lack of proper execution - not for lack of talent or strategic vision. Projects are consumers of resources such as cash and people. They produce a return when completed and will generate a better return when properly completed utilizing proven project management techniques. Completing projects on time, within budget and meeting customer expectations is the way a corporation builds it's future. This paper offers suggestions on implementing planning and scheduling and provides a review of results in the form of management reports

On Setting Day-Ahead Equity Trading Risk Limits: VaR Prediction at Market Close or Open?

Directory of Open Access Journals (Sweden)

Ana-Maria Fuertes

2016-09-01

Full Text Available This paper investigates the information content of the ex post overnight return for one-day-ahead equity Value-at-Risk (VaR forecasting. To do so, we deploy a univariate VaR modeling approach that constructs the forecast at market open and, accordingly, exploits the available overnight close-to-open price variation. The benchmark is the bivariate VaR modeling approach proposed by Ahoniemi et al. that constructs the forecast at the market close instead and, accordingly, it models separately the daytime and overnight return processes and their covariance. For a small cap portfolio, the bivariate VaR approach affords superior predictive ability than the ex post overnight VaR approach whereas for a large cap portfolio the results are reversed. The contrast indicates that price discovery at the market open is less efficient for small capitalization, thinly traded stocks.

On the importance of the long-term seasonal component in day-ahead electricity price forecasting

International Nuclear Information System (INIS)

Nowotarski, Jakub; Weron, Rafał

2016-01-01

In day-ahead electricity price forecasting (EPF) the daily and weekly seasonalities are always taken into account, but the long-term seasonal component (LTSC) is believed to add unnecessary complexity to the already parameter-rich models and is generally ignored. Conducting an extensive empirical study involving state-of-the-art time series models we show that (i) decomposing a series of electricity prices into a LTSC and a stochastic component, (ii) modeling them independently and (iii) combining their forecasts can bring – contrary to a common belief – an accuracy gain compared to an approach in which a given time series model is calibrated to the prices themselves. - Highlights: • A new class of Seasonal Component AutoRegressive (SCAR) models is introduced. • Electricity prices are decomposed into a trend-seasonal and a stochastic component. • Both components are modeled independently, their forecasts are combined. • Significant accuracy gains can be achieved compared to commonly used approaches.

Drinking typography established by scheduled induction predicts chronic heavy drinking in a monkey model of ethanol self-administration.

Science.gov (United States)

Grant, Kathleen A; Leng, Xiaoyan; Green, Heather L; Szeliga, Kendall T; Rogers, Laura S M; Gonzales, Steven W

2008-10-01

We have developed an animal model of alcohol self-administration that initially employs schedule-induced polydipsia (SIP) to establish reliable ethanol consumption under open access (22 h/d) conditions with food and water concurrently available. SIP is an adjunctive behavior that is generated by constraining access to an important commodity (e.g., flavored food). The induction schedule and ethanol polydipsia generated under these conditions affords the opportunity to investigate the development of drinking typologies that lead to chronic, excessive alcohol consumption. Adult male cynomolgus monkeys (Macaca fascicularis) were induced to drink water and 4% (w/v in water) ethanol by a Fixed-Time 300 seconds (FT-300 seconds) schedule of banana-flavored pellet delivery. The FT-300 seconds schedule was in effect for 120 consecutive sessions, with daily induction doses increasing from 0.0 to 0.5 g/kg to 1.0 g/kg to 1.5 g/kg every 30 days. Following induction, the monkeys were allowed concurrent access to 4% (w/v) ethanol and water for 22 h/day for 12 months. Drinking typographies during the induction of drinking 1.5 g/kg ethanol emerged that were highly predictive of the daily ethanol intake over the next 12 months. Specifically, the frequency in which monkeys ingested 1.5 g/kg ethanol without a 5-minute lapse in drinking (defined as a bout of drinking) during induction strongly predicted (correlation 0.91) subsequent ethanol intake over the next 12 months of open access to ethanol. Blood ethanol during induction were highly correlated with intake and with drinking typography and ranged from 100 to 160 mg% when the monkeys drank their 1.5 g/kg dose in a single bout. Forty percent of the population became heavy drinkers (mean daily intakes >3.0 g/kg for 12 months) characterized by frequent "spree" drinking (intakes >4.0 g/kg/d). This model of ethanol self-administration identifies early alcohol drinking typographies (gulping the equivalent of 6 drinks) that evolve into

A Hybrid Forecasting Model Based on Bivariate Division and a Backpropagation Artificial Neural Network Optimized by Chaos Particle Swarm Optimization for Day-Ahead Electricity Price

Directory of Open Access Journals (Sweden)

Zhilong Wang

2014-01-01

Full Text Available In the electricity market, the electricity price plays an inevitable role. Nevertheless, accurate price forecasting, a vital factor affecting both government regulatory agencies and public power companies, remains a huge challenge and a critical problem. Determining how to address the accurate forecasting problem becomes an even more significant task in an era in which electricity is increasingly important. Based on the chaos particle swarm optimization (CPSO, the backpropagation artificial neural network (BPANN, and the idea of bivariate division, this paper proposes a bivariate division BPANN (BD-BPANN method and the CPSO-BD-BPANN method for forecasting electricity price. The former method creatively transforms the electricity demand and price to be a new variable, named DV, which is calculated using the division principle, to forecast the day-ahead electricity by multiplying the forecasted values of the DVs and forecasted values of the demand. Next, to improve the accuracy of BD-BPANN, chaos particle swarm optimization and BD-BPANN are synthesized to form a novel model, CPSO-BD-BPANN. In this study, CPSO is utilized to optimize the initial parameters of BD-BPANN to make its output more stable than the original model. Finally, two forecasting strategies are proposed regarding different situations.

Probability-Weighted LMP and RCP for Day-Ahead Energy Markets using Stochastic Security-Constrained Unit Commitment: Preprint

Energy Technology Data Exchange (ETDEWEB)

Ela, E.; O' Malley, M.

2012-06-01

Variable renewable generation resources are increasing their penetration on electric power grids. These resources have weather-driven fuel sources that vary on different time scales and are difficult to predict in advance. These characteristics create challenges for system operators managing the load balance on different timescales. Research is looking into new operational techniques and strategies that show great promise on facilitating greater integration of variable resources. Stochastic Security-Constrained Unit Commitment models are one strategy that has been discussed in literature and shows great benefit. However, it is rarely used outside the research community due to its computational limits and difficulties integrating with electricity markets. This paper discusses how it can be integrated into day-ahead energy markets and especially on what pricing schemes should be used to ensure an efficient and fair market.

PSO-MISMO modeling strategy for multistep-ahead time series prediction.

Science.gov (United States)

Bao, Yukun; Xiong, Tao; Hu, Zhongyi

2014-05-01

Multistep-ahead time series prediction is one of the most challenging research topics in the field of time series modeling and prediction, and is continually under research. Recently, the multiple-input several multiple-outputs (MISMO) modeling strategy has been proposed as a promising alternative for multistep-ahead time series prediction, exhibiting advantages compared with the two currently dominating strategies, the iterated and the direct strategies. Built on the established MISMO strategy, this paper proposes a particle swarm optimization (PSO)-based MISMO modeling strategy, which is capable of determining the number of sub-models in a self-adaptive mode, with varying prediction horizons. Rather than deriving crisp divides with equal-size s prediction horizons from the established MISMO, the proposed PSO-MISMO strategy, implemented with neural networks, employs a heuristic to create flexible divides with varying sizes of prediction horizons and to generate corresponding sub-models, providing considerable flexibility in model construction, which has been validated with simulated and real datasets.

Topology-based hierarchical scheduling using deficit round robin

DEFF Research Database (Denmark)

Yu, Hao; Yan, Ying; Berger, Michael Stubert

2009-01-01

according to the topology. The mapping process could be completed through the network management plane or by manual configuration. Based on the knowledge of the network, the scheduler can manage the traffic on behalf of other less advanced nodes, avoid potential traffic congestion, and provide flow...... protection and isolation. Comparisons between hierarchical scheduling, flow-based scheduling, and class-based scheduling schemes have been carried out under a symmetric tree topology. Results have shown that the hierarchical scheduling scheme provides better flow protection and isolation from attack...

Day and night shift schedules are associated with lower sleep quality in Evening-types.

Science.gov (United States)

Martin, Jeanne Sophie; Laberge, Luc; Sasseville, Alexandre; Bérubé, Marilie; Alain, Samuel; Houle, Jérôme; Hébert, Marc

2015-06-01

Eveningness has been suggested as a facilitating factor in adaptation to shift work, with several studies reporting evening chronotypes (E-types) as better sleepers when on night shifts. Conversely, eveningness has been associated with more sleep complaints during day shifts. However, sleep during day shifts has received limited attention in previous studies assessing chronotypes in shift workers. Environmental light exposure has also been reported to differ between chronotypes in day workers. Activity is also known to provide temporal input to the circadian clock. Therefore, the aim of this study was to compare objective sleep, light exposure and activity levels between chronotypes, both during the night and day shifts. Thirty-nine patrol police patrol officers working on a fast rotating shift schedule (mean age ± SD: 28.9 ± 3.2 yrs; 28 males) participated in this study. All subjects completed the Morningness-Eveningness Questionnaire (MEQ). Sleep and activity were monitored with actigraphy (Actiwatch-L; Mini-Mitter/Respironics, Bend, OR) for four consecutive night shifts and four consecutive day shifts (night work schedule: 00:00 h-07:00 h; day work schedule: 07:00 h-15:00 h). Sleep and activity parameters were calculated with Actiware software. MEQ scores ranged from 26 to 56; no subject was categorized as Morning-type. E-types (n = 13) showed significantly lower sleep efficiency, longer snooze time and spent more time awake after sleep onset than Intermediate-types (I-types, n = 26) for both the night and day shifts. E-types also exhibited shorter and more numerous sleep bouts. Furthermore, when napping was taken into account, E-types had shorter total sleep duration than I-types during the day shifts. E-types were more active during the first hours of their night shift when compared to I-types. Also, all participants spent more time active and had higher amount of activity per minute during day shifts when compared to night shifts. No

Day-Ahead Wind Power Forecasting Using a Two-Stage Hybrid Modeling Approach Based on SCADA and Meteorological Information, and Evaluating the Impact of Input-Data Dependency on Forecasting Accuracy

Directory of Open Access Journals (Sweden)

Dehua Zheng

2017-12-01

Full Text Available The power generated by wind generators is usually associated with uncertainties, due to the intermittency of wind speed and other weather variables. This creates a big challenge for transmission system operators (TSOs and distribution system operators (DSOs in terms of connecting, controlling and managing power networks with high-penetration wind energy. Hence, in these power networks, accurate wind power forecasts are essential for their reliable and efficient operation. They support TSOs and DSOs in enhancing the control and management of the power network. In this paper, a novel two-stage hybrid approach based on the combination of the Hilbert-Huang transform (HHT, genetic algorithm (GA and artificial neural network (ANN is proposed for day-ahead wind power forecasting. The approach is composed of two stages. The first stage utilizes numerical weather prediction (NWP meteorological information to predict wind speed at the exact site of the wind farm. The second stage maps actual wind speed vs. power characteristics recorded by SCADA. Then, the wind speed forecast in the first stage for the future day is fed to the second stage to predict the future day’s wind power. Comparative selection of input-data parameter sets for the forecasting model and impact analysis of input-data dependency on forecasting accuracy have also been studied. The proposed approach achieves significant forecasting accuracy improvement compared with three other artificial intelligence-based forecasting approaches and a benchmark model using the smart persistence method.

Computational Intelligence Techniques Applied to the Day Ahead PV Output Power Forecast: PHANN, SNO and Mixed

Directory of Open Access Journals (Sweden)

Emanuele Ogliari

2018-06-01

Full Text Available An accurate forecast of the exploitable energy from Renewable Energy Sources is extremely important for the stability issues of the electric grid and the reliability of the bidding markets. This paper presents a comparison among different forecasting methods of the photovoltaic output power introducing a new method that mixes some peculiarities of the others: the Physical Hybrid Artificial Neural Network and the five parameters model estimated by the Social Network Optimization. In particular, the day-ahead forecasts evaluated against real data measured for two years in an existing photovoltaic plant located in Milan, Italy, are compared by means both new and the most common error indicators. Results reported in this work show the best forecasting capability of the new “mixed method” which scored the best forecast skill and Enveloped Mean Absolute Error on a yearly basis (47% and 24.67%, respectively.

Knowledge-based scheduling of arrival aircraft

Science.gov (United States)

Krzeczowski, K.; Davis, T.; Erzberger, H.; Lev-Ram, I.; Bergh, C.

1995-01-01

A knowledge-based method for scheduling arrival aircraft in the terminal area has been implemented and tested in real-time simulation. The scheduling system automatically sequences, assigns landing times, and assigns runways to arrival aircraft by utilizing continuous updates of aircraft radar data and controller inputs. The scheduling algorithms is driven by a knowledge base which was obtained in over two thousand hours of controller-in-the-loop real-time simulation. The knowledge base contains a series of hierarchical 'rules' and decision logic that examines both performance criteria, such as delay reduction, as well as workload reduction criteria, such as conflict avoidance. The objective of the algorithms is to devise an efficient plan to land the aircraft in a manner acceptable to the air traffic controllers. This paper will describe the scheduling algorithms, give examples of their use, and present data regarding their potential benefits to the air traffic system.

Breastfeeding: Planning Ahead

Medline Plus

Full Text Available ... and jobs View all pages in this section Home It's Only Natural Planning ahead It's Only Natural Planning ahead Breastfeeding and baby basics Making breastfeeding work for you Addressing breastfeeding myths Overcoming challenges Finding ...

Location-based Scheduling

DEFF Research Database (Denmark)

Andersson, Niclas; Christensen, Knud

on the market. However, CPM is primarily an activity based method that takes the activity as the unit of focus and there is criticism raised, specifically in the case of construction projects, on the method for deficient management of construction work and continuous flow of resources. To seek solutions...... to the identified limitations of the CPM method, an alternative planning and scheduling methodology that includes locations is tested. Location-based Scheduling (LBS) implies a shift in focus, from primarily the activities to the flow of work through the various locations of the project, i.e. the building. LBS uses...... the graphical presentation technique of Line-of-balance, which is adapted for planning and management of work-flows that facilitates resources to perform their work without interruptions caused by other resources working with other activities in the same location. As such, LBS and Lean Construction share...

Model Predictive Control of a Nonlinear System with Known Scheduling Variable

DEFF Research Database (Denmark)

Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik

2012-01-01

Model predictive control (MPC) of a class of nonlinear systems is considered in this paper. We will use Linear Parameter Varying (LPV) model of the nonlinear system. By taking the advantage of having future values of the scheduling variable, we will simplify state prediction. Consequently...... the control problem of the nonlinear system is simplied into a quadratic programming. Wind turbine is chosen as the case study and we choose wind speed as the scheduling variable. Wind speed is measurable ahead of the turbine, therefore the scheduling variable is known for the entire prediction horizon....

Pricing Energy and Ancillary Services in a Day-Ahead Market for a Price-Taker Hydro Generating Company Using a Risk-Constrained Approach

Directory of Open Access Journals (Sweden)

Perica Ilak

2014-04-01

Full Text Available This paper analyzes a price-taker hydro generating company which participates simultaneously in day-ahead energy and ancillary services markets. An approach for deriving marginal cost curves for energy and ancillary services is proposed, taking into consideration price uncertainty and opportunity cost of water, which can later be used to determine hourly bid curves. The proposed approach combines an hourly conditional value-at-risk, probability of occurrence of automatic generation control states and an opportunity cost of water to determine energy and ancillary services marginal cost curves. The proposed approach is in a linear constraint form and is easy to implement in optimization problems. A stochastic model of the hydro-economic river basin is presented, based on the actual Vinodol hydropower system in Croatia, with a complex three-dimensional relationship between the power produced, the discharged water, and the head of associated reservoir.

On the effectiveness of the anti-gaming policy between the day-ahead and real-time electricity markets in The Netherlands

Energy Technology Data Exchange (ETDEWEB)

Boogert, A. [Essent Energy Trading (Netherlands); Dupont, D. [University of Twente (Netherlands). School of Business, Public Administration and Technology

2005-09-01

In the paper, we study the linkage between two related markets for electricity in The Netherlands: the day-ahead market and the real-time market. The Dutch regulator wants to prevent trading across these two markets and has set up a dual pricing system for this purpose. In this paper, we test the effectiveness of this policy by studying the ex post profitability of trading strategies spanning the two markets over various time segments. Our results show that profits generated by these strategies are rarely positive on average and always characterized by very large potential losses, which dwarf the mean profit when the latter is positive. (author)

On the effectiveness of the anti-gaming policy between the day-ahead and real-time electricity markets in The Netherlands

International Nuclear Information System (INIS)

Boogert, A.; Dupont, D.

2005-01-01

In the paper, we study the linkage between two related markets for electricity in The Netherlands: the day-ahead market and the real-time market. The Dutch regulator wants to prevent trading across these two markets and has set up a dual pricing system for this purpose. In this paper, we test the effectiveness of this policy by studying the ex post profitability of trading strategies spanning the two markets over various time segments. Our results show that profits generated by these strategies are rarely positive on average and always characterized by very large potential losses, which dwarf the mean profit when the latter is positive. (author)

Self-Directed Digital Learning: When Do Dental Students Study?

Science.gov (United States)

Jackson, Tate H; Zhong, James; Phillips, Ceib; Koroluk, Lorne D

2018-04-01

The Growth and Development (G&D) curriculum at the University of North Carolina at Chapel Hill School of Dentistry uses self-directed web-based learning modules in the place of lectures and includes scheduled self-study times during the 8 am-5 pm school hours. The aim of this study was to use direct observation to evaluate dental students' access patterns with the self-directed, web-based learning modules in relation to planned self-study time allocated across the curriculum, proximity to course examinations, and course performance. Module access for all 80 students in the DDS Class of 2014 was recorded for date and time across the four G&D courses. Module access data were used to determine likelihood of usage during scheduled time and frequency of usage in three timeframes: >7, 3 to 7, and 0 to 2 days before the final exam. The results showed a statistically significant difference in the likelihood of module access during scheduled time across the curriculum (pstudents, 64% accessed modules at least once during scheduled time in G&D1, but only 10%, 19%, and 18% in G&D2, G&D3, and G&D4, respectively. For all courses, the proportion of module accesses was significantly higher 0-2 days before an exam compared to the other two timeframes. Module access also differed significantly within each timeframe across all four courses (pstudents rarely accessed learning modules during syllabus-budgeted self-study time and accessed modules more frequently as course exams approached.

Sharing wind power forecasts in electricity markets: A numerical analysis

International Nuclear Information System (INIS)

Exizidis, Lazaros; Kazempour, S. Jalal; Pinson, Pierre; Greve, Zacharie de; Vallée, François

2016-01-01

Highlights: • Information sharing among different agents can be beneficial for electricity markets. • System cost decreases by sharing wind power forecasts between different agents. • Market power of wind producer may increase by sharing forecasts with market operator. • Extensive out-of-sample analysis is employed to draw reliable conclusions. - Abstract: In an electricity pool with significant share of wind power, all generators including conventional and wind power units are generally scheduled in a day-ahead market based on wind power forecasts. Then, a real-time market is cleared given the updated wind power forecast and fixed day-ahead decisions to adjust power imbalances. This sequential market-clearing process may cope with serious operational challenges such as severe power shortage in real-time due to erroneous wind power forecasts in day-ahead market. To overcome such situations, several solutions can be considered such as adding flexible resources to the system. In this paper, we address another potential solution based on information sharing in which market players share their own wind power forecasts with others in day-ahead market. This solution may improve the functioning of sequential market-clearing process through making more informed day-ahead schedules, which reduces the need for balancing resources in real-time operation. This paper numerically evaluates the potential value of sharing forecasts for the whole system in terms of system cost reduction. Besides, its impact on each market player’s profit is analyzed. The framework of this study is based on a stochastic two-stage market setup and complementarity modeling, which allows us to gain further insights into information sharing impacts.

Advertisement scheduling on commercial radio station using genetics algorithm

Science.gov (United States)

Purnamawati, S.; Nababan, E. B.; Tsani, B.; Taqyuddin, R.; Rahmat, R. F.

2018-03-01

On the commercial radio station, the advertising schedule is done manually, which resulted in ineffectiveness of ads schedule. Playback time consists of two types such as prime time and regular time. Radio Ads scheduling will be discussed in this research is based on ad playback schedule between 5am until 12am which rules every 15 minutes. It provides 3 slots ads with playback duration per ads maximum is 1 minute. If the radio broadcast time per day is 12 hours, then the maximum number of ads per day which can be aired is 76 ads. The other is the enactment of rules of prime time, namely the hours where the common people (listeners) have the greatest opportunity to listen to the radio, namely between the hours and hours of 4 am - 8 am, 6 pm - 10 pm. The number of screenings of the same ads on one day are limited to prime time ie 5 times, while for regular time is 8 times. Radio scheduling process is done using genetic algorithms which are composed of processes initialization chromosomes, selection, crossover and mutation. Study on chromosome 3 genes, each chromosome will be evaluated based on the value of fitness calculated based on the number of infractions that occurred on each individual chromosome. Where rule 1 is the number of screenings per ads must not be more than 5 times per day and rule 2 is there should never be two or more scheduling ads delivered on the same day and time. After fitness value of each chromosome is acquired, then the do the selection, crossover and mutation. From this research result, the optimal advertising schedule with schedule a whole day and ads data playback time ads with this level of accuracy: the average percentage was 83.79%.

Designing of Vague Logic Based 2-Layered Framework for CPU Scheduler

Directory of Open Access Journals (Sweden)

Supriya Raheja

2016-01-01

Full Text Available Fuzzy based CPU scheduler has become of great interest by operating system because of its ability to handle imprecise information associated with task. This paper introduces an extension to the fuzzy based round robin scheduler to a Vague Logic Based Round Robin (VBRR scheduler. VBRR scheduler works on 2-layered framework. At the first layer, scheduler has a vague inference system which has the ability to handle the impreciseness of task using vague logic. At the second layer, Vague Logic Based Round Robin (VBRR scheduling algorithm works to schedule the tasks. VBRR scheduler has the learning capability based on which scheduler adapts intelligently an optimum length for time quantum. An optimum time quantum reduces the overhead on scheduler by reducing the unnecessary context switches which lead to improve the overall performance of system. The work is simulated using MATLAB and compared with the conventional round robin scheduler and the other two fuzzy based approaches to CPU scheduler. Given simulation analysis and results prove the effectiveness and efficiency of VBRR scheduler.

Project Scheduling Based on Risk of Gas Transmission Pipe

Science.gov (United States)

Silvianita; Nurbaity, A.; Mulyadi, Y.; Suntoyo; Chamelia, D. M.

2018-03-01

The planning of a project has a time limit on which must be completed before or right at a predetermined time. Thus, in a project planning, it is necessary to have scheduling management that is useful for completing a project to achieve maximum results by considering the constraints that will exists. Scheduling management is undertaken to deal with uncertainties and negative impacts of time and cost in project completion. This paper explains about scheduling management in gas transmission pipeline project Gresik-Semarang to find out which scheduling plan is most effectively used in accordance with its risk value. Scheduling management in this paper is assissted by Microsoft Project software to find the critical path of existing project scheduling planning data. Critical path is the longest scheduling path with the fastest completion time. The result is found a critical path on project scheduling with completion time is 152 days. Furthermore, the calculation of risk is done by using House of Risk (HOR) method and it is found that the critical path has a share of 40.98 percent of all causes of the occurence of risk events that will be experienced.

Dental Student Study Strategies: Are Self-Testing and Scheduling Related to Academic Performance?

Science.gov (United States)

McAndrew, Maureen; Morrow, Christina S; Atiyeh, Lindsey; Pierre, Gaëlle C

2016-05-01

Self-testing, a strategy wherein a student actively engages in creating questions and answers from study materials to assist with studying, has been found to be especially advantageous because it enhances future retrieval of information. Studies have found correlations among students' grade point averages (GPAs), self-testing, and rereading study strategies, as well as the spacing of study sessions over time. The aim of this study was to assess relationships among dental students' study strategies, scheduling of study time, and academic achievement. A 16-item survey requesting information on study habits, study schedules, and GPAs was distributed to 358 second-year dental students at New York University College of Dentistry. Additionally, the survey asked students to report the average number of hours per week they devoted to studying for didactic courses and preparing for hands-on preclinical courses. Of the 358 students, 94 (26%) responded to the survey. The vast majority of the respondents reported utilizing self-testing and rereading study strategies. High performers (with higher GPAs) were more likely to use self-testing, especially with flashcards, and to space their studying over multiple sessions. Lower performing students were more likely to highlight or underline their notes and to mass their study sessions or cram. Longer hours devoted to studying and practicing for simulation courses were associated with stronger performance; lower performers reported spending significantly fewer hours practicing for simulation courses. Half of the dental students surveyed said that they felt their studying would be more productive in the morning, although 84% reported doing most of their studying in the evening or late night. Sound study decisions depend on accurate regulation of ongoing learning and appropriate use and timing of evidence-based study strategies, so these results suggest that dental students may require guidance in these areas.

Ophthalmic public health; the way ahead.

Science.gov (United States)

Heidary, F; Rahimi, A; Gharebaghi, R

2012-01-01

Visual sciences have been progressing quickly in recent decades through globalization phenomenon. An enormous change has taken place in ocular health issues, however, there are various problems facing ophthalmic public health worldwide. In the previous years, the World Health Organization and the International Agency for the Prevention of Blindness in partnership launched the global initiative to eradicate avoidable blindness by the year 2020, VISION 2020 the Right to Sight. It has concentrated on the prevention of blindness disability and recognized a health issue-sight as a human right. In view of challenges ahead of visual sciences, close collaboration between international agencies at the global level to implement new strategies and monitor the progress will be mandatory. In these circumstances non-governmental organizations should not be neglected. World Sight Day 2012 would be a great opportunity to be a focus on importance of visual impairment as an important public health issue and discovering new challenges ahead.

Group Elevator Peak Scheduling Based on Robust Optimization Model

Directory of Open Access Journals (Sweden)

ZHANG, J.

2013-08-01

Full Text Available Scheduling of Elevator Group Control System (EGCS is a typical combinatorial optimization problem. Uncertain group scheduling under peak traffic flows has become a research focus and difficulty recently. RO (Robust Optimization method is a novel and effective way to deal with uncertain scheduling problem. In this paper, a peak scheduling method based on RO model for multi-elevator system is proposed. The method is immune to the uncertainty of peak traffic flows, optimal scheduling is realized without getting exact numbers of each calling floor's waiting passengers. Specifically, energy-saving oriented multi-objective scheduling price is proposed, RO uncertain peak scheduling model is built to minimize the price. Because RO uncertain model could not be solved directly, RO uncertain model is transformed to RO certain model by elevator scheduling robust counterparts. Because solution space of elevator scheduling is enormous, to solve RO certain model in short time, ant colony solving algorithm for elevator scheduling is proposed. Based on the algorithm, optimal scheduling solutions are found quickly, and group elevators are scheduled according to the solutions. Simulation results show the method could improve scheduling performances effectively in peak pattern. Group elevators' efficient operation is realized by the RO scheduling method.

Exploiting Flexibility in Coupled Electricity and Natural Gas Markets: A Price-Based Approach

DEFF Research Database (Denmark)

Ordoudis, Christos; Delikaraoglou, Stefanos; Pinson, Pierre

2017-01-01

Natural gas-fired power plants (NGFPPs) are considered a highly flexible component of the energy system and can facilitate the large-scale integration of intermittent renewable generation. Therefore, it is necessary to improve the coordination between electric power and natural gas systems....... Considering a market-based coupling of these systems, we introduce a decision support tool that increases market efficiency in the current setup where day-ahead and balancing markets are cleared sequentially. The proposed approach relies on the optimal adjustment of natural gas price to modify the scheduling...

Management implications for the perioperative surgical home related to inpatient case cancellations and add-on case scheduling on the day of surgery.

Science.gov (United States)

Epstein, Richard H; Dexter, Franklin

2015-07-01

The American Society of Anesthesiologists has embraced the concept of the Perioperative Surgical Home as a means through which anesthesiologists can add value to the health systems in which they practice. One key listed element of the Perioperative Surgical Home is to support "scheduling initiatives to reduce cancellations and increase efficiency." In this study, we explored the potential benefits of the Perioperative Surgical Home with respect to inpatient cancellations and add-on case scheduling. We evaluated 6 hypotheses related to the timing of inpatient cancellations and preoperative anesthesia evaluations. Inpatient cancellations were studied during 26 consecutive 4-week intervals between July 2012 and June 2014 at a tertiary care academic hospital. All timestamps related to scheduling, rescheduling, and cancellation activities were retrieved from the operating room (OR) case scheduling system. Timestamps when patients were seen by anesthesia residents were obtained from the preoperative evaluation system database. Batch mean methods were used to calculate means and SE. For cases cancelled, we determined whether, for "most" (>50%) cancellations, a subsequent procedure (of any type) was performed on the patient within 7 days of the cancellation. Comparisons with most and other fractions were assessed using the 1 group, 1-sided Student t test. We evaluated whether a few procedures were highly represented among the cancelled cases via the Herfindahl (Simpson's) index, comparing it with Data from 24,735 scheduled inpatient cases were assessed. Cases cancelled after 7 AM on the day before or at any time on the scheduled day of surgery accounted for 22.6% ± 0.5% (SE) of the scheduled minutes all scheduled cases, and 26.8% ± 0.4% of the case volume (i.e., number of cases). Most (83.1% ± 0.6%, P 50%, P = 0.12), implying that the indication for the cancelled procedure no longer existed or the patient/family decided not to proceed with surgery. When only

Time of day variation in polyp detection rate for colonoscopies performed on a 3-hour shift schedule.

LENUS (Irish Health Repository)

Munson, Gregory W

2011-03-01

Recent research suggests that the colonoscopy polyp detection rate (PDR) varies by time of day, possibly because of endoscopist fatigue. Mayo Clinic Rochester (MCR) schedules colonoscopies on 3-hour shifts, which should minimize fatigue.

Designing cyclic appointment schedules for outpatient clinics with scheduled and unscheduled patient arrivals

NARCIS (Netherlands)

Kortbeek, Nikky; Zonderland, Maartje E.; Braaksma, Aleida; Vliegen, Ingrid M. H.; Boucherie, Richard J.; Litvak, Nelly; Hans, Erwin W.

2014-01-01

We present a methodology to design appointment systems for outpatient clinics and diagnostic facilities that offer both walk-in and scheduled service. The developed blueprint for the appointment schedule prescribes the number of appointments to plan per day and the moment on the day to schedule the

Designing cyclic appointment schedules for outpatient clinics with scheduled and unscheduled patient arrivals

NARCIS (Netherlands)

Kortbeek, Nikky; Zonderland, Maartje Elisabeth; Boucherie, Richardus J.; Litvak, Nelli; Hans, Elias W.

2011-01-01

We present a methodology to design appointment systems for outpatient clinics and diagnostic facilities that offer both walk-in and scheduled service. The developed blueprint for the appointment schedule prescribes the number of appointments to plan per day and the moment on the day to schedule the

Short time ahead wind power production forecast

International Nuclear Information System (INIS)

Sapronova, Alla; Meissner, Catherine; Mana, Matteo

2016-01-01

An accurate prediction of wind power output is crucial for efficient coordination of cooperative energy production from different sources. Long-time ahead prediction (from 6 to 24 hours) of wind power for onshore parks can be achieved by using a coupled model that would bridge the mesoscale weather prediction data and computational fluid dynamics. When a forecast for shorter time horizon (less than one hour ahead) is anticipated, an accuracy of a predictive model that utilizes hourly weather data is decreasing. That is because the higher frequency fluctuations of the wind speed are lost when data is averaged over an hour. Since the wind speed can vary up to 50% in magnitude over a period of 5 minutes, the higher frequency variations of wind speed and direction have to be taken into account for an accurate short-term ahead energy production forecast. In this work a new model for wind power production forecast 5- to 30-minutes ahead is presented. The model is based on machine learning techniques and categorization approach and using the historical park production time series and hourly numerical weather forecast. (paper)

Short time ahead wind power production forecast

Science.gov (United States)

Sapronova, Alla; Meissner, Catherine; Mana, Matteo

2016-09-01

An accurate prediction of wind power output is crucial for efficient coordination of cooperative energy production from different sources. Long-time ahead prediction (from 6 to 24 hours) of wind power for onshore parks can be achieved by using a coupled model that would bridge the mesoscale weather prediction data and computational fluid dynamics. When a forecast for shorter time horizon (less than one hour ahead) is anticipated, an accuracy of a predictive model that utilizes hourly weather data is decreasing. That is because the higher frequency fluctuations of the wind speed are lost when data is averaged over an hour. Since the wind speed can vary up to 50% in magnitude over a period of 5 minutes, the higher frequency variations of wind speed and direction have to be taken into account for an accurate short-term ahead energy production forecast. In this work a new model for wind power production forecast 5- to 30-minutes ahead is presented. The model is based on machine learning techniques and categorization approach and using the historical park production time series and hourly numerical weather forecast.

Bumpless Transfer between Observer-based Gain Scheduled Controllers

DEFF Research Database (Denmark)

Bendtsen, Jan Dimon; Stoustrup, Jakob; Trangbæk, Klaus

2005-01-01

This paper deals with bumpless transfer between a number of observer-based controllers in a gain scheduling architecture. Linear observer-based controllers are designed for a number of linear approximations of a nonlinear system in a set of operating points, and gain scheduling control can...

Weight loss strategies associated with BMI in overweight adults with type 2 diabetes at entry into the Look AHEAD (Action for Health in Diabetes) trial.

Science.gov (United States)

Raynor, Hollie A; Jeffery, Robert W; Ruggiero, Andrea M; Clark, Jeanne M; Delahanty, Linda M

2008-07-01

Intentional weight loss is recommended for those with type 2 diabetes, but the strategies patients attempt and their effectiveness for weight management are unknown. In this investigation we describe intentional weight loss strategies used and those related to BMI in a diverse sample of overweight participants with type 2 diabetes at enrollment in the Look AHEAD (Action for Health in Diabetes) clinical trial. This was a cross-sectional study of baseline weight loss strategies, including self-weighing frequency, eating patterns, and weight control practices, reported in 3,063 women and 2,082 men aged 45-74 years with BMI > or =25 kg/m(2). Less than half (41.4%) of participants self-weighed > or =1/week. Participants ate breakfast 6.0 +/- 1.8 days/week, ate 5.0 +/- 3.1 meals/snacks per day, and ate 1.9 +/- 2.7 fast food meals/week. The three most common weight control practices (increasing fruits and vegetables, cutting out sweets, and eating less high-carbohydrate foods) were reported by approximately 60% of participants for > or =20 weeks over the previous year. Adjusted models showed that self-weighing less than once per week (B = 0.83), more fast food meals consumed per week (B = 0.14), and fewer breakfast meals consumed per week (B = -0.19) were associated (P < 0.05) with a higher BMI (R(2) = 0.24). Regular self-weighing and breakfast consumption, along with infrequent consumption of fast food, were related to lower BMI in the Look AHEAD study population.

Effects of 14-day treatment with the schedule III anorectic phendimetrazine on choice between cocaine and food in rhesus monkeys.

Science.gov (United States)

Banks, Matthew L; Blough, Bruce E; Negus, S Stevens

2013-08-01

The clinical utility of monoamine releasers such as phenmetrazine or d-amphetamine as candidate agonist medications for cocaine dependence is hindered by their high abuse liability. Phendimetrazine is a clinically available schedule III anorectic that functions as a prodrug for phenmetrazine and thus may have lower abuse liability. This study determined the effects of continuous 14-day treatment with phendimetrazine on cocaine vs. food choice in rhesus monkeys (N=4). Responding was maintained under a concurrent schedule of food delivery (1-g pellets, fixed-ratio 100 schedule) and cocaine injections (0-0.1mg/kg/injection, fixed-ratio 10 schedule). Cocaine choice dose-effect curves were determined daily before and during 14-day periods of continuous intravenous treatment with saline or (+)-phendimetrazine (0.32-1.0mg/kg/h). Effects of 14-day treatment with (+)-phenmetrazine (0.1-0.32 mg/kg/h; N=5) and d-amphetamine (0.032-0.1mg/kg/h; N=6) were also examined for comparison. During saline treatment, food was primarily chosen during availability of low cocaine doses (0, 0.0032, and 0.01 mg/kg/injection), and cocaine was primarily chosen during availability of higher cocaine doses (0.032 and 0.1mg/kg/injection). Phendimetrazine initially decreased overall responding without significantly altering cocaine choice. Over the course of 14 days, tolerance developed to rate decreasing effects, and phendimetrazine dose-dependently decreased cocaine choice (significant at 0.032 mg/kg/injection cocaine). Phenmetrazine and d-amphetamine produced qualitatively similar effects. These results demonstrate that phendimetrazine can produce significant, though modest, reductions in cocaine choice in rhesus monkeys. Phendimetrazine may be especially suitable as a candidate medication for human studies because of its schedule III clinical availability. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Block Scheduling: Restructuring the School Day. Hot Topics Series.

Science.gov (United States)

Flinders, David J., Ed.

The advantages and disadvantages of block scheduling are considered in 24 articles. The editors provide an overview for each section and a conclusion for the anthology. The first section includes articles which examine issues, concepts, and cases: (1) "All around the Block" (Michael D. Rettig and Robert Lynn Canady); (2) "Block Scheduling: A Means…

A stochastic self-scheduling program for compressed air energy storage (CAES) of renewable energy sources (RESs) based on a demand response mechanism

International Nuclear Information System (INIS)

Ghalelou, Afshin Najafi; Fakhri, Alireza Pashaei; Nojavan, Sayyad; Majidi, Majid; Hatami, Hojat

2016-01-01

Highlights: • Optimal stochastic energy management of renewable energy sources (RESs) is proposed. • The compressed air energy storage (CAES) besides RESs is used in the presence of DRP. • Determination charge and discharge of CAES in order to reduce the expected operation cost. • Moreover, demand response program (DRP) is proposed to minimize the operation cost. • The uncertainty modeling of input data are considered in the proposed stochastic framework. - Abstract: In this paper, a stochastic self-scheduling of renewable energy sources (RESs) considering compressed air energy storage (CAES) in the presence of a demand response program (DRP) is proposed. RESs include wind turbine (WT) and photovoltaic (PV) system. Other energy sources are thermal units and CAES. The time-of-use (TOU) rate of DRP is considered in this paper. This DRP shifts the percentage of load from the expensive period to the cheap one in order to flatten the load curve and minimize the operation cost, consequently. The proposed objective function includes minimizing the operation costs of thermal unit and CAES, considering technical and physical constraints. The proposed model is formulated as mixed integer linear programming (MILP) and it is been solved using General Algebraic Modeling System (GAMS) optimization package. Furthermore, CAES and DRP are incorporated in the stochastic self-scheduling problem by a decision maker to reduce the expected operation cost. Meanwhile, the uncertainty models of market price, load, wind speed, temperature and irradiance are considered in the formulation. Finally, to assess the effects of DRP and CAES on self-scheduling problem, four case studies are utilized, and significant results were obtained, which indicate the validity of the proposed stochastic program.

Not All Large Customers are Made Alike: Disaggregating Response to Default-Service Day-Ahead Market Pricing

International Nuclear Information System (INIS)

Hopper, Nicole; Goldman, Charles; Neenan, Bernie

2006-01-01

For decades, policymakers and program designers have gone on the assumption that large customers, particularly industrial facilities, are the best candidates for realtime pricing (RTP). This assumption is based partly on practical considerations (large customers can provide potentially large load reductions) but also on the premise that businesses focused on production cost minimization are most likely to participate and respond to opportunities for bill savings. Yet few studies have examined the actual price response of large industrial and commercial customers in a disaggregated fashion, nor have factors such as the impacts of demand response (DR) enabling technologies, simultaneous emergency DR program participation and price response barriers been fully elucidated. This second-phase case study of Niagara Mohawk Power Corporation (NMPC)'s large customer RTP tariff addresses these information needs. The results demonstrate the extreme diversity of large customers' response to hourly varying prices. While two-thirds exhibit some price response, about 20 percent of customers provide 75-80 percent of the aggregate load reductions. Manufacturing customers are most price-responsive as a group, followed by government/education customers, while other sectors are largely unresponsive. However, individual customer response varies widely. Currently, enabling technologies do not appear to enhance hourly price response; customers report using them for other purposes. The New York Independent System Operator (NYISO)'s emergency DR programs enhance price response, in part by signaling to customers that day-ahead prices are high. In sum, large customers do currently provide moderate price response, but there is significant room for improvement through targeted programs that help customers develop and implement automated load-response strategies

Phase II study of a 3-day schedule with topotecan and cisplatin in patients with previously untreated small cell lung cancer and extensive disease

DEFF Research Database (Denmark)

Sorensen, M.; Lassen, Ulrik Niels; Jensen, Peter Buhl

2008-01-01

INTRODUCTION: Treatment with a topoisomerase I inhibitor in combination with a platinum results in superior or equal survival compared with etoposide-based treatment in extensive disease small cell lung cancer (SCLC). Five-day topotecan is inconvenient and therefore shorter schedules of topotecan...... and cisplatin are needed. The aim of this phase II study was to establish the response rate and response duration in chemo-naive patients with SCLC receiving a 3-day topotecan and cisplatin schedule. METHODS: Simons optimal two-stage design was used. Patients with previously untreated extensive disease SCLC...... age was 59 (range 44-74), 79% had performance status 0 or 1. Thirty-one patients completed all six cycles. Grade 3/4 anemia, neutrocytopenia, and thrombocytopenia were recorded in 9.5%, 66.7%, and 21.4% of patients, respectively. Fourteen percent of patients experienced neutropenic fever. No episodes...

Morning self-efficacy predicts physical activity throughout the day in knee osteoarthritis.

Science.gov (United States)

Zhaoyang, Ruixue; Martire, Lynn M; Sliwinski, Martin J

2017-06-01

The purpose of this study was to examine the within-day and cross-day prospective effects of knee osteoarthritis (OA) patients' self-efficacy to engage in physical activity despite the pain on their subsequent physical activity assessed objectively in their natural environment. Over 22 days, 135 older adults with knee OA reported their morning self-efficacy for being physically active throughout the day using a handheld computer and wore an accelerometer to measure moderate activity and steps. Morning self-efficacy had a significant positive effect on steps and moderate-intensity activity throughout that day, above and beyond the effects of demographic background and other psychosocial factors as well as spouses' support and social control. The lagged effect of morning self-efficacy on the next day's physical activity and the reciprocal lagged effect of physical activity on the next day's self-efficacy were not significant. Positive between-person effects of self-efficacy on physical activity were found. Future research should aim to better understand the mechanisms underlying fluctuations in patients' daily self-efficacy, and target patients' daily self-efficacy as a modifiable psychological mechanism for promoting physical activity. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Day-Ahead Coordination of Vehicle-to-Grid Operation and Wind Power in Security Constraints Unit Commitment (SCUC

Directory of Open Access Journals (Sweden)

Mohammad Javad Abdollahi

2015-08-01

Full Text Available In this paper security constraints unit commitment (SCUC in the presence of wind power resources and electrical vehicles to grid is presented. SCUC operation prepare an optimal time table for generation unit commitment in order to maximize security, minimize operation cost and satisfy the constraints of networks and units in a period of time, as one of the most important research interest in power systems. Today, the relationship between power network and energy storage systems is interested for many researchers and network operators. Using Electrical Vehicles (PEVs and wind power for energy production is one of the newest proposed methods for replacing fossil fuels.One of the effective strategies for analyzing of the effects of Vehicle 2 Grid (V2G and wind power in optimal operation of generation is running of SCUC for power systems that are equipped with V2G and wind power resources. In this paper, game theory method is employed for deterministic solution of day-ahead unit commitment with considering security constraints in the simultaneous presence of V2G and wind power units. This problem for two scenarios of grid-controlled mode and consumer-controlled mode in three different days with light, medium and heavy load profiles is analyzed. Simulation results show the effectiveness of the presence of V2G and wind power for decreasing of generation cost and improving operation indices of power systems.

Day-ahead price forecasting of electricity markets by a new feature selection algorithm and cascaded neural network technique

International Nuclear Information System (INIS)

Amjady, Nima; Keynia, Farshid

2009-01-01

With the introduction of restructuring into the electric power industry, the price of electricity has become the focus of all activities in the power market. Electricity price forecast is key information for electricity market managers and participants. However, electricity price is a complex signal due to its non-linear, non-stationary, and time variant behavior. In spite of performed research in this area, more accurate and robust price forecast methods are still required. In this paper, a new forecast strategy is proposed for day-ahead price forecasting of electricity markets. Our forecast strategy is composed of a new two stage feature selection technique and cascaded neural networks. The proposed feature selection technique comprises modified Relief algorithm for the first stage and correlation analysis for the second stage. The modified Relief algorithm selects candidate inputs with maximum relevancy with the target variable. Then among the selected candidates, the correlation analysis eliminates redundant inputs. Selected features by the two stage feature selection technique are used for the forecast engine, which is composed of 24 consecutive forecasters. Each of these 24 forecasters is a neural network allocated to predict the price of 1 h of the next day. The whole proposed forecast strategy is examined on the Spanish and Australia's National Electricity Markets Management Company (NEMMCO) and compared with some of the most recent price forecast methods.

Robust design of a 2-DOF GMV controller: a direct self-tuning and fuzzy scheduling approach.

Science.gov (United States)

Silveira, Antonio S; Rodríguez, Jaime E N; Coelho, Antonio A R

2012-01-01

This paper presents a study on self-tuning control strategies with generalized minimum variance control in a fixed two degree of freedom structure-or simply GMV2DOF-within two adaptive perspectives. One, from the process model point of view, using a recursive least squares estimator algorithm for direct self-tuning design, and another, using a Mamdani fuzzy GMV2DOF parameters scheduling technique based on analytical and physical interpretations from robustness analysis of the system. Both strategies are assessed by simulation and real plants experimentation environments composed of a damped pendulum and an under development wind tunnel from the Department of Automation and Systems of the Federal University of Santa Catarina. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

A Novel Assembly Line Scheduling Algorithm Based on CE-PSO

Directory of Open Access Journals (Sweden)

Xiaomei Hu

2015-01-01

Full Text Available With the widespread application of assembly line in enterprises, assembly line scheduling is an important problem in the production since it directly affects the productivity of the whole manufacturing system. The mathematical model of assembly line scheduling problem is put forward and key data are confirmed. A double objective optimization model based on equipment utilization and delivery time loss is built, and optimization solution strategy is described. Based on the idea of solution strategy, assembly line scheduling algorithm based on CE-PSO is proposed to overcome the shortcomings of the standard PSO. Through the simulation experiments of two examples, the validity of the assembly line scheduling algorithm based on CE-PSO is proved.

Advance Resource Provisioning in Bulk Data Scheduling

Energy Technology Data Exchange (ETDEWEB)

Balman, Mehmet

2012-10-01

Today?s scientific and business applications generate mas- sive data sets that need to be transferred to remote sites for sharing, processing, and long term storage. Because of increasing data volumes and enhancement in current net- work technology that provide on-demand high-speed data access between collaborating institutions, data handling and scheduling problems have reached a new scale. In this paper, we present a new data scheduling model with ad- vance resource provisioning, in which data movement operations are defined with earliest start and latest comple- tion times. We analyze time-dependent resource assign- ment problem, and propose a new methodology to improve the current systems by allowing researchers and higher-level meta-schedulers to use data-placement as-a-service, so they can plan ahead and submit transfer requests in advance. In general, scheduling with time and resource conflicts is NP-hard. We introduce an efficient algorithm to organize multiple requests on the fly, while satisfying users? time and resource constraints. We successfully tested our algorithm in a simple benchmark simulator that we have developed, and demonstrated its performance with initial test results.

Robust Optimization of the Self- scheduling and Market Involvement for an Electricity Producer

KAUST Repository

Lima, Ricardo

2015-01-01

This work address the optimization under uncertainty of the self-scheduling, forward contracting, and pool involvement of an electricity producer operating a mixed power generation station, which combines thermal, hydro and wind sources, and uses a two-stage adaptive robust optimization approach. In this problem the wind power production and the electricity pool price are considered to be uncertain, and are described by uncertainty convex sets. Two variants of a constraint generation algorithm are proposed, namely a primal and dual version, and they are used to solve two case studies based on two different producers. Their market strategies are investigated for three different scenarios, corresponding to as many instances of electricity price forecasts. The effect of the producers’ approach, whether conservative or more risk prone, is also investigated by solving each instance for multiple values of the so-called budget parameter. It was possible to conclude that this parameter influences markedly the producers’ strategy, in terms of scheduling, profit, forward contracting, and pool involvement. Regarding the computational results, these show that for some instances, the two variants of the algorithms have a similar performance, while for a particular subset of them one variant has a clear superiority

Robust Optimization of the Self- scheduling and Market Involvement for an Electricity Producer

KAUST Repository

Lima, Ricardo

2015-01-07

This work address the optimization under uncertainty of the self-scheduling, forward contracting, and pool involvement of an electricity producer operating a mixed power generation station, which combines thermal, hydro and wind sources, and uses a two-stage adaptive robust optimization approach. In this problem the wind power production and the electricity pool price are considered to be uncertain, and are described by uncertainty convex sets. Two variants of a constraint generation algorithm are proposed, namely a primal and dual version, and they are used to solve two case studies based on two different producers. Their market strategies are investigated for three different scenarios, corresponding to as many instances of electricity price forecasts. The effect of the producers’ approach, whether conservative or more risk prone, is also investigated by solving each instance for multiple values of the so-called budget parameter. It was possible to conclude that this parameter influences markedly the producers’ strategy, in terms of scheduling, profit, forward contracting, and pool involvement. Regarding the computational results, these show that for some instances, the two variants of the algorithms have a similar performance, while for a particular subset of them one variant has a clear superiority

The applicability of knowledge-based scheduling to the utilities industry

International Nuclear Information System (INIS)

Yoshimoto, G.; Gargan, R. Jr.; Duggan, P.

1992-01-01

The Electric Power Research Institute (EPRI), Nuclear Power Division, has identified the three major goals of high technology applications for nuclear power plants. These goals are to enhance power production through increasing power generation efficiency, to increase productivity of the operations, and to reduce the threats to the safety of the plant. Our project responds to the second goal by demonstrating that significant productivity increases can be achieved for outage maintenance operations based on existing knowledge-based scheduling technology. Its use can also mitigate threats to potential safety problems by means of the integration of risk assessment features into the scheduler. The scheduling approach uses advanced techniques enabling the automation of the routine scheduling decision process that previously was handled by people. The process of removing conflicts in scheduling is automated. This is achieved by providing activity representations that allow schedulers to express a variety of different scheduling constraints and by implementing scheduling mechanisms that simulate kinds of processes that humans use to find better solutions from a large number of possible solutions. This approach allows schedulers to express detailed constraints between activities and other activities, resources (material and personnel), and requirements that certain states exist for their execution. Our scheduler has already demonstrated its benefit to improving the shuttle processing flow management at Kennedy Space Center. Knowledge-based scheduling techniques should be examined by utilities industry researchers, developers, operators and management for application to utilities planning problems because of its great cost benefit potential. 4 refs., 4 figs

Investigation by CRE into record high electricity prices on Powernext Day-ahead Auction in October and November 2007. Analysis report

International Nuclear Information System (INIS)

2008-01-01

In October and November 2007, electricity prices hit record highs on the Powernext Day-Ahead Auction trading platform. While, during the first nine months of the year, prices for delivery between 6 pm and 8 pm averaged euros 36 /MWh, rising to a maximum of euros 118 /MWh, they spiked at: - euros 1,236 /MWh for delivery on Monday, 29 October 2007 between 6 pm and 7 pm; - euros 2,500 /MWh for delivery on Monday, 12 November 2007 between 8 pm and 9 pm; - euros 1,762 /MWh for delivery on Thursday, 15 November 2007 between 6 pm and 7 pm. Day ahead prices of electricity have a major effect on the procurement costs of suppliers, and consequently on the formation of selling prices to end consumers. Article 28 of French Act No.2000-108 of 10 February 2000 stipulates that CRE 'shall monitor, for electricity and natural gas, all transactions made between suppliers, brokers and producers, all transactions made on the organised markets and cross-border trading. It shall ensure that bids made by suppliers, brokers and producers are consistent with their financial and technical requirements'. Article 33 of the same Act specifies that, 'In performing the tasks entrusted to it, the French Energy Regulatory Commission (CRE) may gather any information it requires from the Ministers for the Economy and for Energy, from public electricity transmission and distribution system operators, from operators of infrastructures for the natural gas transmission and distribution networks and operators of liquefied natural gas facilities, as well as from any other company involved in the electricity and natural gas market. It may also call upon any person whose evidence it deems necessary for the purposes of its investigations'. In this context, and in application of its duty to monitor the electricity wholesale markets, CRE has undertaken an investigation to analyse the mechanisms underlying the formation of such high prices. To this end, CRE gathered information relative to decisions taken by

PLACEMENT APPLICATIONS SCHEDULING LECTURE IN INTERNATIONAL PROGRAM UNIKOM BASED ANDROID

Directory of Open Access Journals (Sweden)

Andri Sahata Sitanggang

2017-12-01

Full Text Available One who determines life of a classroom namely mapping scheduling courses especially at college. The process scheduling has included time or schedule of a class of available, room available, lecture who is scheduled for, and schedule for lecturer going to teach. Hopefully with a scheduling it will facilitate the students and teachers in obtaining information lecture schedule. With the emergence of the android application ( is implanted in mobile phones , the public can now use the internet so fast that is based .So with that researchers give one a technology based solutions to build android application .This is because one of the technology has given the functions which may make it easier for students and university lecturers in terms of access to information. In building this application used method of the prototype consisting 2 access namely access user and admin , where module user consisting of modules register , login , scheduling module , while for admin given module login , register and arrangement information scheduling courses both the administration and lecturers .Application made will be integrated with internet so that this program is real-time application.

Procedures and practices for day-to-day operation

International Nuclear Information System (INIS)

Distler, K.

1986-01-01

This lecture deals with problems of safe plant operation under day-to-day conditions. Operation, maintenance and surveillance have to be organized in a preventive manner. It will be shown that nearly all expected jobs and proceedings can be done rule-based. The connection of documentation and work preparation will be lined out. Moreover, the need for control and quality assurance for nearly all proceedings will be pointed out. The question of communication and scheduling will be touched. (orig.)

Agent-based transportation planning compared with scheduling heuristics

NARCIS (Netherlands)

Mes, Martijn R.K.; van der Heijden, Matthijs C.; van Harten, Aart

2004-01-01

Here we consider the problem of dynamically assigning vehicles to transportation orders that have di¤erent time windows and should be handled in real time. We introduce a new agent-based system for the planning and scheduling of these transportation networks. Intelligent vehicle agents schedule

Seismic prediction ahead of tunnel construction using Rayleigh-waves

OpenAIRE

Jetschny, Stefan; De Nil, Denise; Bohlen, Thomas

2008-01-01

To increase safety and efficiency of tunnel constructions, online seismic exploration ahead of a tunnel can become a valuable tool. We developed a new forward looking seismic imaging technique e.g. to determine weak and water bearing zones ahead of the constructions. Our approach is based on the excitation and registration of tunnel surface-waves. These waves are excited at the tunnel face behind the cutter head of a tunnel boring machine and travel into drilling direction. Arriving at the fr...

An interpolated activity during the knowledge-of-results delay interval eliminates the learning advantages of self-controlled feedback schedules.

Science.gov (United States)

Carter, Michael J; Ste-Marie, Diane M

2017-03-01

The learning advantages of self-controlled knowledge-of-results (KR) schedules compared to yoked schedules have been linked to the optimization of the informational value of the KR received for the enhancement of one's error-detection capabilities. This suggests that information-processing activities that occur after motor execution, but prior to receiving KR (i.e., the KR-delay interval) may underlie self-controlled KR learning advantages. The present experiment investigated whether self-controlled KR learning benefits would be eliminated if an interpolated activity was performed during the KR-delay interval. Participants practiced a waveform matching task that required two rapid elbow extension-flexion reversals in one of four groups using a factorial combination of choice (self-controlled, yoked) and KR-delay interval (empty, interpolated). The waveform had specific spatial and temporal constraints, and an overall movement time goal. The results indicated that the self-controlled + empty group had superior retention and transfer scores compared to all other groups. Moreover, the self-controlled + interpolated and yoked + interpolated groups did not differ significantly in retention and transfer; thus, the interpolated activity eliminated the typically found learning benefits of self-controlled KR. No significant differences were found between the two yoked groups. We suggest the interpolated activity interfered with information-processing activities specific to self-controlled KR conditions that occur during the KR-delay interval and that these activities are vital for reaping the associated learning benefits. These findings add to the growing evidence that challenge the motivational account of self-controlled KR learning advantages and instead highlights informational factors associated with the KR-delay interval as an important variable for motor learning under self-controlled KR schedules.

Paranoia as an Antecedent and Consequence of Getting Ahead in Organizations: Time-Lagged Effects Between Paranoid Cognitions, Self-Monitoring, and Changes in Span of Control

Directory of Open Access Journals (Sweden)

Niels Van Quaquebeke

2016-09-01

Full Text Available A six-month, time-lagged online survey among 441 employees in diverse industries was conducted to investigate the role paranoia plays as an antecedent and as a consequence of advancement in organizations. The background of the study is the argument that it requires active social sense-making and behavioral adaptability to advance in organizations. The present paper thus explores the extent to which employees’ paranoid cognitions—representative of a heightened albeit suspicious sense-making and behavioral adaptability—link with their advancement in organizations (operationalized as changes in afforded span of control, both as an antecedent and an outcome. Following the strategy to illuminate the process by interaction analysis, both conditions (antecedent and outcome are examined in interaction with employees’ self-monitoring, which is considered representative of a heightened but healthy sense-making and behavioral adaptability. Results support the expected interference interaction between paranoid cognitions and self-monitoring in that each can to some degree compensate for the other in explaining employees’ organizational advancement. Reversely, changes in span of control also affected paranoid cognitions. In particular, low self-monitors, i.e. those low in adaptive sense-making, reacted with heightened paranoid cognitions when demoted. In effect, the present study is thus the first to empirically support that paranoid cognitions can be a consequence but also a prerequisite for getting ahead in organizations. Practical advice should, however, be suspended until it is better understood whether and under what circumstances paranoia may relate not only to personally getting ahead but also to an increased effectiveness for the benefit of the organization.

Validity of self-reported exposure to shift work.

Science.gov (United States)

Härmä, Mikko; Koskinen, Aki; Ropponen, Annina; Puttonen, Sampsa; Karhula, Kati; Vahtera, Jussi; Kivimäki, Mika

2017-03-01

To evaluate the validity of widely used questionnaire items on work schedule using objective registry data as reference. A cohort study of hospital employees who responded to a self-administered questionnaire on work schedule in 2008, 2012 and 2014 and were linked to individual-level pay-roll-based records on work shifts. For predictive validity, leisure-time fatigue was assessed. According to the survey data in 2014 (n=8896), 55% of the day workers had at least 1 year of earlier shift work experience. 8% of the night shift workers changed to day work during the follow-up. Using pay-roll data as reference, questions on 'shift work with night shifts' and 'permanent night work' showed high sensitivity (96% and 90%) and specificity (92% and 97%). Self-reported 'regular day work' showed moderate sensitivity (73%), but high specificity (99%) and 'shift work without night shifts' showed low sensitivity (62%) and moderate specificity (87%). In multivariate logistic regression analysis, the age-adjusted, sex-adjusted and baseline fatigue-adjusted association between 'shift work without night shifts' and leisure-time fatigue was lower for self-reported compared with objective assessment (1.30, 95% CI 0.94 to 1.82, n=1707 vs 1.89, 95% CI 1.06 to 3.39, n=1627). In contrast, shift work with night shifts, compared with permanent day work, was similarly associated with fatigue in the two assessments (2.04, 95% CI 1.62 to 2.57, n=2311 vs 1.82, 95% CI 1.28 to 2.58, n=1804). The validity of self-reported assessment of shift work varies between work schedules. Exposure misclassification in self-reported data may contribute to bias towards the null in shift work without night shifts. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Self-certification and employee training of mail-order distributors of scheduled listed chemical products. Interim final rule with request for comment.

Science.gov (United States)

2011-04-13

On October 12, 2010, the President signed the Combat Methamphetamine Enhancement Act of 2010 (MEA). It establishes new requirements for mail-order distributors of scheduled listed chemical products. Mail-order distributors must now self-certify to DEA in order to sell scheduled listed chemical products at retail. Sales at retail are those sales intended for personal use; mail-order distributors that sell scheduled listed chemical products not intended for personal use, e.g., sale to a university, are not affected by the new law. This self-certification must include a statement that the mail-order distributor understands each of the requirements that apply under part 1314 and agrees to comply with these requirements. Additionally, mail-order distributors are now required to train their employees prior to self certification. DEA is promulgating this rule to incorporate the statutory provisions and make its regulations consistent with the new requirements and other existing regulations related to self-certification.

Optimal trading strategy for GenCo in LMP-based and bilateral ...

African Journals Online (AJOL)

GenCo) in multi-market environment including day-ahead spot and long term bilateral contract markets using self-organising hierarchical particle swarm optimisation with time-varying acceleration coefficients (SPSO-TVAC). The proposed trading ...

Coordinated Volt/Var Control in Distribution Systems with Distributed Generations Based on Joint Active and Reactive Powers Dispatch

Directory of Open Access Journals (Sweden)

Abouzar Samimi

2016-01-01

Full Text Available One of the most significant control schemes in optimal operation of distribution networks is Volt/Var control (VVC. Owing to the radial structure of distribution systems and distribution lines with a small X/R ratio, the active power scheduling affects the VVC issue. A Distribution System Operator (DSO procures its active and reactive power requirements from Distributed Generations (DGs along with the wholesale electricity market. This paper proposes a new operational scheduling method based on a joint day-ahead active/reactive power market at the distribution level. To this end, based on the capability curve, a generic reactive power cost model for DGs is developed. The joint active/reactive power dispatch model presented in this paper motivates DGs to actively participate not only in the energy markets, but also in the VVC scheme through a competitive market. The proposed method which will be performed in an offline manner aims to optimally determine (i the scheduled active and reactive power values of generation units; (ii reactive power values of switched capacitor banks; and (iii tap positions of transformers for the next day. The joint active/reactive power dispatch model for daily VVC is modeled in GAMS and solved with the DICOPT solver. Finally, the plausibility of the proposed scheduling framework is examined on a typical 22-bus distribution test network over a 24-h period.

AHEAD. Advate in HaEmophilia A outcome Database.

Science.gov (United States)

Oldenburg, J; Kurnik, K; Huth-Kühne, A; Zimmermann, R; Abraham, I; Klamroth, R

2010-11-01

The clinical picture of haemophilia A patients is often characterised by recurrent bleedings, in particular joint bleeds. Thus far, long-term data on the outcome of haemophilia A patients are scarce as regards the development of target joints, joint replacement, lost days from school or work due to bleedings, and the quality of life, as most previous studies were limited to the aspects of safety and efficacy. The Baxter-initiated AHEAD (Advate in HaEmophilia A outcome Database) study is a multi-centre, prospective, non-interventional observational study of haemophilia A patients. All patients with a residual FVIII activity of £5% who are being treated with ADVATE are eligible. There are no limitations in terms of patient age or treatment regimen. AHEAD is scientifically supported by a renowned interdisciplinary steering board and is intended to yield data on 500 patients in up to 30 haemophilia centres, collected during a period of four years. The large patient population has been chosen in order to ensure a valid database. The objective of the study is to record haemophilia-related arthropathies, which will be defined based on imaging techniques (e. g. MRI, X-ray, ultrasound) and the judgment of the attending physician. In addition, extensive data will be collected on joint replacement surgeries, pseudotumour development, bleeding-related pain, quality of life (age-related questionnaires: Haem-A-QoL, Haemo-QoL, SF10, SF12v2), risk factors (diabetes mellitus, arterial hypertension, nicotine abuse), blood group, gene mutation, physical activity, and on the efficacy and safety of Advate. The patient data will be entered into an electronic CRF system at the centres. Plausibility checks during data entry, regular monitoring visits, and the option of auditing all serve to ensure a high data quality for AHEAD. The first patient was enrolled in the study in early June 2010; recruitment is planned to continue until the end of 2011. The Ethics Committee of the University

Electric power systems advanced forecasting techniques and optimal generation scheduling

CERN Document Server

Catalão, João P S

2012-01-01

Overview of Electric Power Generation SystemsCláudio MonteiroUncertainty and Risk in Generation SchedulingRabih A. JabrShort-Term Load ForecastingAlexandre P. Alves da Silva and Vitor H. FerreiraShort-Term Electricity Price ForecastingNima AmjadyShort-Term Wind Power ForecastingGregor Giebel and Michael DenhardPrice-Based Scheduling for GencosGovinda B. Shrestha and Songbo QiaoOptimal Self-Schedule of a Hydro Producer under UncertaintyF. Javier Díaz and Javie

Effect of Pre-Construction on Construction Schedule and Client Loyalty

OpenAIRE

Jong Hoon Kim; Hyun-Soo Lee; Moonseo Park; Min Jeong; Inbeom Lee

2016-01-01

Pre-construction is essential in achieving the success of a construction project. Due to the early involvement of project participants in the construction phase, project managers are able to plan ahead and solve issues well in advance leading to the success of the project and the satisfaction of the client. This research utilizes quantitative data derived from construction management projects in order to identify the relationship between pre-construction, construction schedule, and client sat...

Self-management model in the scheduling of successive appointments in rheumatology.

Science.gov (United States)

Castro Corredor, David; Cuadra Díaz, José Luis; Mateos Rodríguez, Javier José; Anino Fernández, Joaquín; Mínguez Sánchez, María Dolores; de Lara Simón, Isabel María; Tébar, María Ángeles; Añó, Encarnación; Sanz, María Dolores; Ballester, María Nieves

2018-01-08

The rheumatology service of Ciudad Real Hospital, located in an autonomous community of that same name that is nearly in the center of Spain, implemented a self-management model of successive appointments more than 10 years ago. Since then, the physicians of the department schedule follow-up visits for their patients depending on the disease, its course and ancillary tests. The purpose of this study is to evaluate and compare the self-management model for successive appointments in the rheumatology service of Ciudad Real Hospital versus the model of external appointment management implemented in 8 of the hospital's 15 medical services. A comparative and multivariate analysis was performed to identify variables with statistically significant differences, in terms of activity and/or performance indicators and quality perceived by users. The comparison involved the self-management model for successive appointments employed in the rheumatology service of Ciudad Real Hospital and the model for external appointment management used in 8 hospital medical services between January 1 and May 31, 2016. In a database with more than 100,000 records of appointments involving the set of services included in the study, the mean waiting time and the numbers of non-appearances and rescheduling of follow-up visits in the rheumatology department were significantly lower than in the other services. The number of individuals treated in outpatient rheumatology services was 7,768, and a total of 280 patients were surveyed (response rate 63.21%). They showed great overall satisfaction, and the incidence rate of claims was low. Our results show that the self-management model of scheduling appointments has better results in terms of activity indicators and in quality perceived by users, despite the intense activity. Thus, this study could be fundamental for decision making in the management of health care organizations. Copyright © 2017 Elsevier España, S.L.U. and Sociedad Española de

Comparing Book- and Tablet-Based Picture Activity Schedules: Acquisition and Preference.

Science.gov (United States)

Giles, Aimee; Markham, Victoria

2017-09-01

Picture activity schedules consist of a sequence of images representing the order of tasks for a person to complete. Although, picture activity schedules have traditionally been presented in a book format, recently picture activity schedules have been evaluated on technological devices such as an iPod™ touch. The present study compared the efficiency of picture activity schedule acquisition on book- and tablet-based modalities. In addition, participant preference for each modality was assessed. Three boys aged below 5 years with a diagnosis of autism participated. Participants were taught to follow the schedules using both modalities. Following mastery of each modality of picture activity schedule, a concurrent-chains preference assessment was conducted to evaluate participant preference for each modality. Differences in acquisition rates across the two modalities were marginal. Preference for book- or tablet-based schedules was idiosyncratic across participants.

Energy resource management under the influence of the weekend transition considering an intensive use of electric vehicles

DEFF Research Database (Denmark)

Sousa, T.; Morais, Hugo; Pinto, T.

2015-01-01

Energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and of massive electric vehicle is envisaged. The present paper proposes a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distri......Energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and of massive electric vehicle is envisaged. The present paper proposes a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use...... of distributed generation and Vehicle-to-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with their owners. It takes into account these contracts, the users' requirements subjected to the VPP, and several discharge price steps...

Multi-time scale energy management of wind farms based on comprehensive evaluation technology

Science.gov (United States)

Xu, Y. P.; Huang, Y. H.; Liu, Z. J.; Wang, Y. F.; Li, Z. Y.; Guo, L.

2017-11-01

A novel energy management of wind farms is proposed in this paper. Firstly, a novel comprehensive evaluation system is proposed to quantify economic properties of each wind farm to make the energy management more economical and reasonable. Then, a combination of multi time-scale schedule method is proposed to develop a novel energy management. The day-ahead schedule optimizes unit commitment of thermal power generators. The intraday schedule is established to optimize power generation plan for all thermal power generating units, hydroelectric generating sets and wind power plants. At last, the power generation plan can be timely revised in the process of on-line schedule. The paper concludes with simulations conducted on a real provincial integrated energy system in northeast China. Simulation results have validated the proposed model and corresponding solving algorithms.

Distributed Research Project Scheduling Based on Multi-Agent Methods

Directory of Open Access Journals (Sweden)

Constanta Nicoleta Bodea

2011-01-01

Full Text Available Different project planning and scheduling approaches have been developed. The Operational Research (OR provides two major planning techniques: CPM (Critical Path Method and PERT (Program Evaluation and Review Technique. Due to projects complexity and difficulty to use classical methods, new approaches were developed. Artificial Intelligence (AI initially promoted the automatic planner concept, but model-based planning and scheduling methods emerged later on. The paper adresses the project scheduling optimization problem, when projects are seen as Complex Adaptive Systems (CAS. Taken into consideration two different approaches for project scheduling optimization: TCPSP (Time- Constrained Project Scheduling and RCPSP (Resource-Constrained Project Scheduling, the paper focuses on a multiagent implementation in MATLAB for TCSP. Using the research project as a case study, the paper includes a comparison between two multi-agent methods: Genetic Algorithm (GA and Ant Colony Algorithm (ACO.

Micro-generation dispatch in a smart residential multi-carrier energy system considering demand forecast error

International Nuclear Information System (INIS)

Sanjari, M.J.; Karami, H.; Gooi, H.B.

2016-01-01

Highlights: • Combination of day-ahead and hour-ahead optimizations to design online controller. • Investigating the effect of load forecast error on the system operating cost. • Proposing effective method for hour-ahead resource re-dispatch. • Using the HSS algorithm as a powerful and effective optimization method. • Combining long-term and short-term strategies for optimal dispatch of resources. - Abstract: This paper deals with a residential hybrid thermal/electrical grid-connected home energy system incorporating real data for the load demand. A day-ahead scheduling (DAS) algorithm for dispatching different resources has been developed in previous studies to determine the optimal operation scheduling for the distributed energy resources at each time interval so that the operational cost of a smart house is minimized. However, demand of houses may be changed in each hour and cannot be exactly predicted one day ahead. System complexity caused by nonlinear dynamics of the fuel cell, as a combined heat and power device, and battery charging and discharging time make it difficult to find the optimal operating point of the system by using the optimization algorithms quickly in online applications. In this paper, the demand forecast error is studied and a near-optimal dispatch strategy by using artificial neural network (ANN) is proposed for the residential energy system when the demand changes are known one hour ahead with respect to the predicted day-ahead values. The day-ahead and hour-ahead optimizations are combined and ANN training inputs are adjusted according to the problem such that the economic dispatch of different energy resources can be achieved by the proposed method compared with previous studies. Using the model of the fuel cell extracted from experimental measurement and real data for the load demand makes the results more applicable in real residential energy systems.

Distributed energy resources scheduling considering real-time resources forecast

DEFF Research Database (Denmark)

Silva, M.; Sousa, T.; Ramos, S.

2014-01-01

grids and considering day-ahead, hour-ahead and realtime time horizons. This method considers that energy resources are managed by a VPP which establishes contracts with their owners. The full AC power flow calculation included in the model takes into account network constraints. In this paper......, distribution function errors are used to simulate variations between time horizons, and to measure the performance of the proposed methodology. A 33-bus distribution network with large number of distributed resources is used....

A stochastic security approach to energy and spinning reserve scheduling considering demand response program

International Nuclear Information System (INIS)

Partovi, Farzad; Nikzad, Mehdi; Mozafari, Babak; Ranjbar, Ali Mohamad

2011-01-01

In this paper a new algorithm for allocating energy and determining the optimum amount of network active power reserve capacity and the share of generating units and demand side contribution in providing reserve capacity requirements for day-ahead market is presented. In the proposed method, the optimum amount of reserve requirement is determined based on network security set by operator. In this regard, Expected Load Not Supplied (ELNS) is used to evaluate system security in each hour. The proposed method has been implemented over the IEEE 24-bus test system and the results are compared with a deterministic security approach, which considers certain and fixed amount of reserve capacity in each hour. This comparison is done from economic and technical points of view. The promising results show the effectiveness of the proposed model which is formulated as mixed integer linear programming (MILP) and solved by GAMS software. -- Highlights: → Determination of optimal spinning reserve capacity requirement in order to satisfy desired security level set by system operator based on stochastic approach. → Scheduling energy and spinning reserve markets simultaneously. → Comparing the stochastic approach with deterministic approach to determine the advantages and disadvantages of each. → Examine the effect of demand response participation in reserve market to provide spinning reserve.

Energy Storage Scheduling with an Advanced Battery Model: A Game–Theoretic Approach

Directory of Open Access Journals (Sweden)

Matthias Pilz

2017-11-01

Full Text Available Energy storage systems will play a key role for individual users in the future smart grid. They serve two purposes: (i handling the intermittent nature of renewable energy resources for a more reliable and efficient system; and (ii preventing the impact of blackouts on users and allowing for more independence from the grid, while saving money through load-shifting. In this paper we investigate the latter scenario by looking at a neighbourhood of 25 households whose demand is satisfied by one utility company. Assuming the users possess lithium-ion batteries, we answer the question of how each household can make the best use of their individual storage system given a real-time pricing policy. To this end, each user is modelled as a player of a non-cooperative scheduling game. The novelty of the game lies in the advanced battery model, which incorporates charging and discharging characteristics of lithium-ion batteries. The action set for each player comprises day-ahead schedules of their respective battery usage. We analyse different user behaviour and are able to obtain a realistic and applicable understanding of the potential of these systems. As a result, we show the correlation between the efficiency of the battery and the outcome of the game.

Adaptive Priority-Based Downlink Scheduling for WiMAX Networks

OpenAIRE

Wu, Shih-Jung; Huang, Shih-Yi; Huang, Kuo-Feng

2012-01-01

Supporting quality of service (QoS) guarantees for diverse multimedia services are the primary concerns for WiMAX (IEEE 802.16) networks. A scheduling scheme that satisfies QoS requirements has become more important for wireless communications. We propose a downlink scheduling scheme called adaptive priority-based downlink scheduling (APDS) for providing QoS guarantees in IEEE 802.16 networks. APDS comprises two major components: priority assignment and resource allocation. Different service-...

An Event-driven, Value-based, Pull Systems Engineering Scheduling Approach

Science.gov (United States)

2012-03-01

combining a services approach to systems engineering with a kanban -based scheduling system. It provides the basis for validating the approach with...agent-based simulations. Keywords-systems engineering; systems engineering process; lean; kanban ; process simulation I. INTRODUCTION AND BACKGROUND...approaches [8], [9], we are investigating the use of flow-based pull scheduling techniques ( kanban systems) in a rapid response development

Backfilling with Fairness and Slack for Parallel Job Scheduling

International Nuclear Information System (INIS)

Sodan, Angela C; Wei Jin

2010-01-01

Parallel job scheduling typically combines a basic policy like FCFS with backfilling, i.e. moving jobs to an earlier than their regular scheduling position if they do not delay the jobs ahead in the queue according to the rules of the backfilling approach applied. Commonly used are conservative and easy backfilling which either have worse response times but better predictability or better response times and poor predictability. The paper proposes a relaxation of conservative backfilling by permitting to shift jobs within certain constraints to backfill more jobs and reduce fragmentation and subsequently obtain better response times. At the same time, deviation from fairness is kept low and predictability remains high. The results of the experimentation evaluation show that the goals are met, with response-time performance lying as expected between conservative and easy backfilling.

Backfilling with Fairness and Slack for Parallel Job Scheduling

Energy Technology Data Exchange (ETDEWEB)

Sodan, Angela C; Wei Jin, E-mail: acsodan@uwindsor.ca [University of Windsor, Computer Science, Windsor, Ontario (Canada)

2010-11-01

Parallel job scheduling typically combines a basic policy like FCFS with backfilling, i.e. moving jobs to an earlier than their regular scheduling position if they do not delay the jobs ahead in the queue according to the rules of the backfilling approach applied. Commonly used are conservative and easy backfilling which either have worse response times but better predictability or better response times and poor predictability. The paper proposes a relaxation of conservative backfilling by permitting to shift jobs within certain constraints to backfill more jobs and reduce fragmentation and subsequently obtain better response times. At the same time, deviation from fairness is kept low and predictability remains high. The results of the experimentation evaluation show that the goals are met, with response-time performance lying as expected between conservative and easy backfilling.

An Online Scheduling Algorithm with Advance Reservation for Large-Scale Data Transfers

Energy Technology Data Exchange (ETDEWEB)

Balman, Mehmet; Kosar, Tevfik

2010-05-20

Scientific applications and experimental facilities generate massive data sets that need to be transferred to remote collaborating sites for sharing, processing, and long term storage. In order to support increasingly data-intensive science, next generation research networks have been deployed to provide high-speed on-demand data access between collaborating institutions. In this paper, we present a practical model for online data scheduling in which data movement operations are scheduled in advance for end-to-end high performance transfers. In our model, data scheduler interacts with reservation managers and data transfer nodes in order to reserve available bandwidth to guarantee completion of jobs that are accepted and confirmed to satisfy preferred time constraint given by the user. Our methodology improves current systems by allowing researchers and higher level meta-schedulers to use data placement as a service where theycan plan ahead and reserve the scheduler time in advance for their data movement operations. We have implemented our algorithm and examined possible techniques for incorporation into current reservation frameworks. Performance measurements confirm that the proposed algorithm is efficient and scalable.

An EV Charging Scheduling Mechanism Based on Price Negotiation

Directory of Open Access Journals (Sweden)

Baocheng Wang

2018-05-01

Full Text Available Scheduling EV user’s charging behavior based on charging price and applying renewable energy resources are the effective methods to release the load pressure of power grids brought about by the large-scale popularity of electric vehicles (EVs. This paper presents a novel approach for EV charging scheduling based on price negotiation. Firstly, the EV charging system framework based on price negotiation and renewable energy resources is discussed. Secondly, the price negotiation model is presented, including the initial price models and the conditions of transactions. Finally, an EV charging scheduling mechanism based on price negotiation (CSM-PN, including the price adjustment strategies of both the operator and EV users is proposed to seek a final transaction during multi-round price negotiation. Simulation results show that this novel approach can effectively improve the charging station operator’s income, reduce the EV users’ costs, and balance the load of the power grid while improving the efficiency of the EV charging system.

Cloud Computing Task Scheduling Based on Cultural Genetic Algorithm

Directory of Open Access Journals (Sweden)

Li Jian-Wen

2016-01-01

Full Text Available The task scheduling strategy based on cultural genetic algorithm(CGA is proposed in order to improve the efficiency of task scheduling in the cloud computing platform, which targets at minimizing the total time and cost of task scheduling. The improved genetic algorithm is used to construct the main population space and knowledge space under cultural framework which get independent parallel evolution, forming a mechanism of mutual promotion to dispatch the cloud task. Simultaneously, in order to prevent the defects of the genetic algorithm which is easy to fall into local optimum, the non-uniform mutation operator is introduced to improve the search performance of the algorithm. The experimental results show that CGA reduces the total time and lowers the cost of the scheduling, which is an effective algorithm for the cloud task scheduling.

Multiprocessor Global Scheduling on Frame-Based DVFS Systems

OpenAIRE

Berten, Vandy; Goossens, Joël

2008-01-01

International audience; In this work, we are interested in multiprocessor energy efficient systems where task durations are not known in advance but are known stochastically. More precisely we consider global scheduling algorithms for frame-based multiprocessor stochastic DVFS (Dynamic Voltage and Frequency Scaling) systems. Moreover we consider processors with a discrete set of available frequencies. We provide a global scheduling algorithm, and formally show that no deadline will ever be mi...

Online multistep-ahead inundation depth forecasts by recurrent NARX networks

Directory of Open Access Journals (Sweden)

H.-Y. Shen

2013-03-01

Full Text Available Various types of artificial neural networks (ANNs have been successfully applied in hydrological fields, but relatively scant on multistep-ahead flood inundation forecasting, which is very difficult to achieve, especially when dealing with forecasts without regular observed data. This study proposes a recurrent configuration of nonlinear autoregressive with exogenous inputs (NARX network, called R-NARX, to forecast multistep-ahead inundation depths in an inundation area. The proposed R-NARX is constructed based on the recurrent neural network (RNN, which is commonly used for modeling nonlinear dynamical systems. The models were trained and tested based on a large number of inundation data generated by a well validated two-dimensional simulation model at thirteen inundation-prone sites in Yilan County, Taiwan. We demonstrate that the R-NARX model can effectively inhibit error growth and accumulation when being applied to online multistep-ahead inundation forecasts over a long lasting forecast period. For comparison, a feedforward time-delay and an online feedback configuration of NARX networks (T-NARX and O-NARX were performed. The results show that (1 T-NARX networks cannot make online forecasts due to unavailable inputs in the constructed networks even though they provide the best performances for reference only; and (2 R-NARX networks consistently outperform O-NARX networks and can be adequately applied to online multistep-ahead forecasts of inundation depths in the study area during typhoon events.

Linear Look-ahead in Conjunctive Cells: An Entorhinal Mechanism for Vector-Based Navigation

Directory of Open Access Journals (Sweden)

John L Kubie

2012-04-01

Full Text Available The crisp organization of the firing bumps of entorhinal grid cells and conjunctive cells leads to the notion that the entorhinal cortex may compute linear navigation routes. Specifically, we propose a process, termed linear look-ahead, by which a stationary animal could compute a series of locations in the direction it is facing. We speculate that this computation could be achieved through learned patterns of connection strengths among entorhinal neurons. This paper has three sections. First, we describe the minimal grid cell properties that will be built into our network. Specifically, the network relies of rigid modules of neurons, where all members have identical grid scale and orientation, but differ in spatial phase. Additionally, these neurons must be densely interconnected with synapses that are modifiable early in the animal’s life. Second, we investigate whether plasticity during short bouts of locomotion could induce patterns of connections amongst grid cells or conjunctive cells. Finally, we run a simulation to test whether the learned connection patterns can exhibit linear look-ahead. Our results are straightforward. A simulated 30-minute walk produces weak strengthening of synapses between grid cells that do not support linear look-ahead. Similar training in a conjunctive-cell module produces a small subset of very strong connections between cells. These strong pairs have three properties: The pre- and post-synaptic cells have similar heading direction. The cell pairs have neighboring grid bumps. Finally, the spatial offset of firing bumps of the cell pair is in the direction of the common heading preference. Such a module can produce strong and accurate linear look ahead starting in any location and extending in any direction. We speculate that this process may: 1. compute linear paths to goals; 2. update grid cell firing during navigation; and 3. stabilize the rigid modules of grid cells and conjunctive cells.

Breastfeeding: Planning Ahead

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ATD-2 Surface Scheduling and Metering Concept

Science.gov (United States)

Coppenbarger, Richard A.; Jung, Yoon Chul; Capps, Richard Alan; Engelland, Shawn A.

2017-01-01

This presentation describes the concept of ATD-2 tactical surface scheduling and metering. The concept is composed of several elements, including data exchange and integration; surface modeling; surface scheduling; and surface metering. The presentation explains each of the elements. Surface metering is implemented to balance demand and capacity• When surface metering is on, target times from surface scheduler areconverted to advisories for throttling demand• Through the scheduling process, flights with CTOTs will not get addedmetering delay (avoids potential for ‘double delay’)• Carriers can designate certain flights as exempt from metering holds• Demand throttle in Phase 1 at CLT is through advisories sent to rampcontrollers for pushback instructions to the flight deck– Push now– Hold for an advised period of time (in minutes)• Principles of surface metering can be more generally applied to otherairports in the NAS to throttle demand via spot-release times (TMATs Strong focus on optimal use of airport resources• Flexibility enables stakeholders to vary the amount of delay theywould like transferred to gate• Addresses practical aspects of executing surface metering in aturbulent real world environment• Algorithms designed for both short term demand/capacityimbalances (banks) or sustained metering situations• Leverage automation to enable surface metering capability withoutrequiring additional positions• Represents first step in Tactical/Strategic fusion• Provides longer look-ahead calculations to enable analysis ofstrategic surface metering potential usage

The relation between self-regulated strategies and individual study time, prepared participation and achievement in a problem-based curriculum

NARCIS (Netherlands)

Hurk, M.M. van den

2006-01-01

In problem-based learning (PBL) students are encouraged to take responsibility for their own self-regulated learning process. The present study focuses on two self-regulated learning strategies, namely time planning and self-monitoring. Time planning involves time management, scheduling and planning

Electricity market clearing with improved dispatch of stochastic production

DEFF Research Database (Denmark)

Morales González, Juan Miguel; Zugno, Marco; Pineda, Salvador

2014-01-01

In this paper, we consider an electricity market that consists of a day-ahead and a balancing settlement, and includes a number of stochastic producers. We first introduce two reference procedures for scheduling and pricing energy in the day-ahead market: on the one hand, a conventional network...... attains higher market efficiency in expectation than the conventional day-ahead auction, it suffers from fundamental drawbacks with a view to its practical implementation. In particular, it requires flexible producers (those that make up for the lack or surplus of stochastic generation) to accept losses...... in some scenarios. Using a bilevel programming framework, we then show that the conventional auction, if combined with a suitable day-ahead dispatch of stochastic producers (generally different from their expected production), can substantially increase market efficiency and emulate the advantageous...

Improved human performance through appropriate work scheduling

International Nuclear Information System (INIS)

Morisseau, D.S.; Lewis, P.M.; Persensky, J.J.

1987-01-01

The Nuclear Regulatory Commission (NRC) has had a policy, Generic Letter 82-12, on hours of work since 1982. The policy states that licensees should establish controls to prevent situations where fatigue could reduce the ability of operating personnel to perform their duties safely (USNRC 1982). While that policy does give guidance on hours of work and overtime, it does not address periods of longer than 7 days or work schedules other than the routine 8-hour day, 40-hour week. Recognizing that NRC policy could provide broader guidance for shift schedules and hours of overtime work, the Division of Human Factors Safety conducted a project with Pacific Northwest Laboratories (PNL) to help the NRC better understand the human factors principles and issues concerning hours of work so that the NRC could consider updating their policy as necessary. The results of this project are recommendations for guidelines and limits for periods of 14 days, 28 days, and 1 year to take into account the cumulative effects of fatigue. In addition, routine 12-hour shifts are addressed. This latter type of shift schedule has been widely adopted in the petroleum and chemical industries and several utilities operating nuclear power plants have adopted it as well. Since this is the case, it is important to consider including guidelines for implementing this type of schedule. This paper discusses the bases for the PNL recommendations which are currently being studied by the NRC

Cbs (Contrastrain Based Schedulling Adalah Faktor Penentu Keberhasilan Perusahanan Printing

Directory of Open Access Journals (Sweden)

Hendra Achmadi

2010-06-01

Full Text Available In a highly competitive industry faces today ranging from small or home-based printing to using machine that can print offset a hundred thousand copies per hour. But, the increasing competition resulted in requiring a faster production time from order entry, print proff until the production process to delivery to customers. Often times in case of orders which will result in the concurrent PPIC will experience vertigo in the setting of production schedules which have concurrent delivery time. Often will end up with no receipt of orders due to difficulties in the production schedule, especially if the orders require the same offset machine and cylinder wear the same length, while the number of cylinders is limited. Therefore, the printing company should be able to do so in the conduct of a penetration timing of production can easily be simulated and implemented on the ground. CBS (Base Constraint scheduling is a technique to do the scheduling of production so that production can be carried out smoothly and quickly that fulfill the promise made to customers. In scheduling, there are several techniques that can be used are: FCFS (First Came First Serve, EDD (Earliest Date, and LCLS (Last Came Last Serve. So, it is required to be able to do way better scheduling to get results quickly in this fast changing schedules.

Seismic prediction ahead of tunnel constructions

Science.gov (United States)

Jetschny, S.; Bohlen, T.; Nil, D. D.; Giese, R.

2007-12-01

To increase safety and efficiency of tunnel constructions, online seismic exploration ahead of a tunnel can become a valuable tool. Within the \\it OnSite project founded by the BMBF (German Ministry of Education and Research) within \\it GeoTechnologien a new forward looking seismic imaging technique is developed to e.g. determine weak and water bearing zones ahead of the constructions. Our approach is based on the excitation and registration of \\it tunnel surface waves. These waves are excited at the tunnel face behind the cutter head of a tunnel boring machine and travel into drilling direction. Arriving at the front face they generate body waves (mainly S-waves) propagating further ahead. Reflected S-waves are back- converted into tunnel surface waves. For a theoretical description of the conversion process and for finding optimal acquisition geometries it is of importance to study the propagation characteristics of tunnel surface waves. 3D seismic finite difference modeling and analytic solutions of the wave equation in cylindric coordinates revealed that at higher frequencies, i.e. if the tunnel diameter is significantly larger than the wavelength of S-waves, these surface waves can be regarded as Rayleigh-waves circulating the tunnel. For smaller frequencies, i.e. when the S-wavelength approaches the tunnel diameter, the propagation characteristics of these surface waves are then similar to S- waves. Field measurements performed by the GeoForschungsZentrum Potsdam, Germany at the Gotthard Base Tunnel (Switzerland) show both effects, i.e. the propagation of Rayleigh- and body-wave like waves along the tunnel. To enhance our understanding of the excitation and propagation characteristics of tunnel surface waves the transition of Rayleigh to tube-waves waves is investigated both analytically and by numerical simulations.

Customer response to day-ahead wholesale market electricity prices: Case study of RTP program experience in New York

Energy Technology Data Exchange (ETDEWEB)

Goldman, C.; Hopper, N.; Sezgen, O.; Moezzi, M.; Bharvirkar, R.; Neenan, B.; Boisvert, R.; Cappers, P.; Pratt, D.

2004-07-01

There is growing interest in policies, programs and tariffs that encourage customer loads to provide demand response (DR) to help discipline wholesale electricity markets. Proposals at the retail level range from eliminating fixed rate tariffs as the default service for some or all customer groups to reinstituting utility-sponsored load management programs with market-based inducements to curtail. Alternative rate designs include time-of-use (TOU), day-ahead real-time pricing (RTP), critical peak pricing, and even pricing usage at real-time market balancing prices. Some Independent System Operators (ISOs) have implemented their own DR programs whereby load curtailment capabilities are treated as a system resource and are paid an equivalent value. The resulting load reductions from these tariffs and programs provide a variety of benefits, including limiting the ability of suppliers to increase spot and long-term market-clearing prices above competitive levels (Neenan et al., 2002; Boren stein, 2002; Ruff, 2002). Unfortunately, there is little information in the public domain to characterize and quantify how customers actually respond to these alternative dynamic pricing schemes. A few empirical studies of large customer RTP response have shown modest results for most customers, with a few very price-responsive customers providing most of the aggregate response (Herriges et al., 1993; Schwarz et al., 2002). However, these studies examined response to voluntary, two-part RTP programs implemented by utilities in states without retail competition.1 Furthermore, the researchers had limited information on customer characteristics so they were unable to identify the drivers to price response. In the absence of a compelling characterization of why customers join RTP programs and how they respond to prices, many initiatives to modernize retail electricity rates seem to be stymied.

Robust Model Predictive Control of a Nonlinear System with Known Scheduling Variable and Uncertain Gain

DEFF Research Database (Denmark)

Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik

2012-01-01

Robust model predictive control (RMPC) of a class of nonlinear systems is considered in this paper. We will use Linear Parameter Varying (LPV) model of the nonlinear system. By taking the advantage of having future values of the scheduling variable, we will simplify state prediction. Because...... of the special structure of the problem, uncertainty is only in the B matrix (gain) of the state space model. Therefore by taking advantage of this structure, we formulate a tractable minimax optimization problem to solve robust model predictive control problem. Wind turbine is chosen as the case study and we...... choose wind speed as the scheduling variable. Wind speed is measurable ahead of the turbine, therefore the scheduling variable is known for the entire prediction horizon....

Opportunistic splitting for scheduling using a score-based approach

KAUST Repository

Rashid, Faraan

2012-06-01

We consider the problem of scheduling a user in a multi-user wireless environment in a distributed manner. The opportunistic splitting algorithm is applied to find the best group of users without reporting the channel state information to the centralized scheduler. The users find the best among themselves while requiring just a ternary feedback from the common receiver at the end of each mini-slot. The original splitting algorithm is modified to handle users with asymmetric channel conditions. We use a score-based approach with the splitting algorithm to introduce time and throughput fairness while exploiting the multi-user diversity of the network. Analytical and simulation results are given to show that the modified score-based splitting algorithm works well as a fair scheduling scheme with good spectral efficiency and reduced feedback. © 2012 IEEE.

Breastfeeding: Planning Ahead

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Breastfeeding: Planning Ahead

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A Convex Model of Risk-Based Unit Commitment for Day-Ahead Market Clearing Considering Wind Power Uncertainty

DEFF Research Database (Denmark)

Zhang, Ning; Kang, Chongqing; Xia, Qing

2015-01-01

The integration of wind power requires the power system to be sufficiently flexible to accommodate its forecast errors. In the market clearing process, the scheduling of flexibility relies on the manner in which the wind power uncertainty is addressed in the unit commitment (UC) model. This paper...... and are considered in both the objective functions and the constraints. The RUC model is shown to be convex and is transformed into a mixed integer linear programming (MILP) problem using relaxation and piecewise linearization. The proposed RUC model is tested using a three-bus system and an IEEE RTS79 system...... that the risk modeling facilitates a strategic market clearing procedure with a reasonable computational expense....

Getting ahead communication skills for business English : learner's book

CERN Document Server

Jones-Macziola, Sarah

1994-01-01

Getting Ahead is a course for students at the pre-intermediate level who want to improve their English for business and professional purposes. It is suitable both for students who are preparing for work and those who are in employment already. At the same time as drawing on the learner's own experience, the course provides activities which give the less experienced learner the opportunity to participate effectively in meaningful communication. The main units are topic-based and focus on such themes as describing a company, welcoming visitors and dealing with problems. All four skills – listening, speaking, reading and writing – are developed. There are controlled practice tasks and meaningful communication activities, and the course as a whole provides a clear structural progression. The Home Study Book provides out-of-class activities which review and expand on what has been done in class. These activities are keyed at the back of the book to aid self-study. The Home Study CD contains all the listening a...

Getting ahead communication skills for business English : teacher's guide

CERN Document Server

Jones-Macziola, Sarah

1993-01-01

Getting Ahead is a course for students at the pre-intermediate level who want to improve their English for business and professional purposes. It is suitable both for students who are preparing for work and those who are in employment already. At the same time as drawing on the learner's own experience, the course provides activities which give the less experienced learner the opportunity to participate effectively in meaningful communication. The main units are topic-based and focus on such themes as describing a company, welcoming visitors and dealing with problems. All four skills – listening, speaking, reading and writing – are developed. There are controlled practice tasks and meaningful communication activities, and the course as a whole provides a clear structural progression. The Home Study Book provides out-of-class activities which review and expand on what has been done in class. These activities are keyed at the back of the book to aid self-study. The Home Study CD contains all the listening a...

Geometric Distribution-Based Readers Scheduling Optimization Algorithm Using Artificial Immune System

Directory of Open Access Journals (Sweden)

Litian Duan

2016-11-01

Full Text Available In the multiple-reader environment (MRE of radio frequency identification (RFID system, multiple readers are often scheduled to interrogate the randomized tags via operating at different time slots or frequency channels to decrease the signal interferences. Based on this, a Geometric Distribution-based Multiple-reader Scheduling Optimization Algorithm using Artificial Immune System (GD-MRSOA-AIS is proposed to fairly and optimally schedule the readers operating from the viewpoint of resource allocations. GD-MRSOA-AIS is composed of two parts, where a geometric distribution function combined with the fairness consideration is first introduced to generate the feasible scheduling schemes for reader operation. After that, artificial immune system (including immune clone, immune mutation and immune suppression quickly optimize these feasible ones as the optimal scheduling scheme to ensure that readers are fairly operating with larger effective interrogation range and lower interferences. Compared with the state-of-the-art algorithm, the simulation results indicate that GD-MRSOA-AIS could efficiently schedules the multiple readers operating with a fairer resource allocation scheme, performing in larger effective interrogation range.

Computer-based irrigation scheduling for cotton crop

International Nuclear Information System (INIS)

Laghari, K.Q.; Memon, H.M.

2008-01-01

In this study a real time irrigation schedule for cotton crop has been tested using mehran model, a computer-based DDS (Decision Support System). The irrigation schedule was set on selected MAD (Management Allowable Depletion) and the current root depth position. The total 451 mm irrigation water applied to the crop field. The seasonal computed crop ET (Evapotranspiration) was estimated 421.32 mm and actual (ET/sub ca/) observed was 413 mm. The model over-estimated seasonal ET by only 1.94. WUE (Water Use Efficiency) for seed-cotton achieved 6.59 Kg (ha mm)/sup -1/. The statistical analysis (R/sup 2/=0.96, ARE%=2.00, T-1.17 and F=550.57) showed good performance of the model in simulated and observed ET values. The designed Mehran model is designed quite versatile for irrigation scheduling and can be successfully used as irrigation DSS tool for various crop types. (author)

Hierarchical Energy Management of Microgrids including Storage and Demand Response

Directory of Open Access Journals (Sweden)

Songli Fan

2018-05-01

Full Text Available Battery energy storage (BES and demand response (DR are considered to be promising technologies to cope with the uncertainty of renewable energy sources (RES and the load in the microgrid (MG. Considering the distinct prediction accuracies of the RES and load at different timescales, it is essential to incorporate the multi-timescale characteristics of BES and DR in MG energy management. Under this background, a hierarchical energy management framework is put forward for an MG including multi-timescale BES and DR to optimize operation with the uncertainty of RES as well as load. This framework comprises three stages of scheduling: day-ahead scheduling (DAS, hour-ahead scheduling (HAS, and real-time scheduling (RTS. In DAS, a scenario-based stochastic optimization model is established to minimize the expected operating cost of MG, while ensuring its safe operation. The HAS is utilized to bridge DAS and RTS. In RTS, a control strategy is proposed to eliminate the imbalanced power owing to the fluctuations of RES and load. Then, a decomposition-based algorithm is adopted to settle the models in DAS and HAS. Simulation results on a seven-bus MG validate the effectiveness of the proposed methodology.

The impact of exposure to shift-based schedules on medical students

Directory of Open Access Journals (Sweden)

David A. Williams

2015-06-01

Full Text Available Background: With new resident duty-hour regulations, resident work schedules have progressively transitioned towards shift-based systems, sometimes resulting in increased team fragmentation. We hypothesized that exposure to shift-based schedules and subsequent team fragmentation would negatively affect medical student experiences during their third-year internal medicine clerkship. Design: As part of a larger national study on duty-hour reform, 67 of 150 eligible third-year medical students completed surveys about career choice, teaching and supervision, assessment, patient care, well-being, and attractiveness of a career in internal medicine after completing their internal medicine clerkship. Students who rotated to hospitals with shift-based systems were compared to those who did not. Non-demographic variables used a five-point Likert scale. Chi-squared and Fisher's exact tests were used to assess the relationships between exposure to shift-based schedules and student responses. Questions with univariate p≤0.1 were included in multivariable logistic regression models. Results: Thirty-six students (54% were exposed to shift-based schedules. Students exposed to shift-based schedules were less likely to perceive that their attendings were committed to teaching (odds ratio [OR] 0.35, 95% confidence interval [CI]: 0.13–0.90, p=0.01 or perceive that residents had sufficient exposure to assess their performance (OR 0.29, 95% CI: 0.09–0.91, p=0.03. However, those students were more likely to feel their interns were able to observe them at the bedside (OR 1.89, 95% CI: 1.08–3.13, p=0.02 and had sufficient exposure to assess their performance (OR 3.00, 95% CI: 1.01–8.86, p=0.05. Conclusions: These findings suggest that shift-based schedules designed in response to duty-hour reform may have important broader implications for the teaching environment.

The impact of exposure to shift-based schedules on medical students.

Science.gov (United States)

Williams, David A; Kogan, Jennifer R; Hauer, Karen E; Yamashita, Traci; Aagaard, Eva M

2015-01-01

With new resident duty-hour regulations, resident work schedules have progressively transitioned towards shift-based systems, sometimes resulting in increased team fragmentation. We hypothesized that exposure to shift-based schedules and subsequent team fragmentation would negatively affect medical student experiences during their third-year internal medicine clerkship. As part of a larger national study on duty-hour reform, 67 of 150 eligible third-year medical students completed surveys about career choice, teaching and supervision, assessment, patient care, well-being, and attractiveness of a career in internal medicine after completing their internal medicine clerkship. Students who rotated to hospitals with shift-based systems were compared to those who did not. Non-demographic variables used a five-point Likert scale. Chi-squared and Fisher's exact tests were used to assess the relationships between exposure to shift-based schedules and student responses. Questions with univariate p ≤ 0.1 were included in multivariable logistic regression models. Thirty-six students (54%) were exposed to shift-based schedules. Students exposed to shift-based schedules were less likely to perceive that their attendings were committed to teaching (odds ratio [OR] 0.35, 95% confidence interval [CI]: 0.13-0.90, p = 0.01) or perceive that residents had sufficient exposure to assess their performance (OR 0.29, 95% CI: 0.09-0.91, p = 0.03). However, those students were more likely to feel their interns were able to observe them at the bedside (OR 1.89, 95% CI: 1.08-3.13, p = 0.02) and had sufficient exposure to assess their performance (OR 3.00, 95% CI: 1.01-8.86, p = 0.05). These findings suggest that shift-based schedules designed in response to duty-hour reform may have important broader implications for the teaching environment.

Baseline Predictors of Missed Visits in the Look AHEAD Study

Science.gov (United States)

Fitzpatrick, Stephanie L.; Jeffery, Robert; Johnson, Karen C.; Roche, Cathy C.; Van Dorsten, Brent; Gee, Molly; Johnson, Ruby Ann; Charleston, Jeanne; Dotson, Kathy; Walkup, Michael P.; Hill-Briggs, Felicia; Brancati, Frederick L.

2013-01-01

Objective To identify baseline attributes associated with consecutively missed data collection visits during the first 48 months of Look AHEAD—a randomized, controlled trial in 5145 overweight/obese adults with type 2 diabetes designed to determine the long-term health benefits of weight loss achieved by lifestyle change. Design and Methods The analyzed sample consisted of 5016 participants who were alive at month 48 and enrolled at Look AHEAD sites. Demographic, baseline behavior, psychosocial factors, and treatment randomization were included as predictors of missed consecutive visits in proportional hazard models. Results In multivariate Cox proportional hazard models, baseline attributes of participants who missed consecutive visits (n=222) included: younger age ( Hazard Ratio [HR] 1.18 per 5 years younger; 95% Confidence Interval 1.05, 1.30), higher depression score (HR 1.04; 1.01, 1.06), non-married status (HR 1.37; 1.04, 1.82), never self-weighing prior to enrollment (HR 2.01; 1.25, 3.23), and randomization to minimal vs. intensive lifestyle intervention (HR 1.46; 1.11, 1.91). Conclusions Younger age, symptoms of depression, non-married status, never self-weighing, and randomization to minimal intervention were associated with a higher likelihood of missing consecutive data collection visits, even in a high-retention trial like Look AHEAD. Whether modifications to screening or retention efforts targeted to these attributes might enhance long-term retention in behavioral trials requires further investigation. PMID:23996977

Breastfeeding: Planning Ahead

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Performance Evaluation of Bidding-Based Multi-Agent Scheduling Algorithms for Manufacturing Systems

Directory of Open Access Journals (Sweden)

Antonio Gordillo

2014-10-01

Full Text Available Artificial Intelligence techniques have being applied to many problems in manufacturing systems in recent years. In the specific field of manufacturing scheduling many studies have been published trying to cope with the complexity of the manufacturing environment. One of the most utilized approaches is (multi agent-based scheduling. Nevertheless, despite the large list of studies reported in this field, there is no resource or scientific study on the performance measure of this type of approach under very common and critical execution situations. This paper focuses on multi-agent systems (MAS based algorithms for task allocation, particularly in manufacturing applications. The goal is to provide a mechanism to measure the performance of agent-based scheduling approaches for manufacturing systems under key critical situations such as: dynamic environment, rescheduling, and priority change. With this mechanism it will be possible to simulate critical situations and to stress the system in order to measure the performance of a given agent-based scheduling method. The proposed mechanism is a pioneering approach for performance evaluation of bidding-based MAS approaches for manufacturing scheduling. The proposed method and evaluation methodology can be used to run tests in different manufacturing floors since it is independent of the workshop configuration. Moreover, the evaluation results presented in this paper show the key factors and scenarios that most affect the market-like MAS approaches for manufacturing scheduling.

Is health, measured by work ability index, affected by 12-hour rotating shift schedules?

Science.gov (United States)

Yong, Mei; Nasterlack, Michael; Pluto, Rolf-Peter; Elmerich, Kathrin; Karl, Dorothee; Knauth, Peter

2010-07-01

Two forms of continuously forward rotating 12-h shift schedules exist at BASF's Ludwigshafen site. These shift schedules were compared with a daytime working system to investigate potential differential effects on employee's health status assessed with the Work Ability Index (WAI). In the 3 x 12 system, a 12-h day shift is followed 24 h later by a 12-h night shift, and after a day off the employee returns to the day shift. The 4 x 12 schedule follows the same pattern except that there are 2 days off between the night and next day shift. A total of 924 participants (278 3 x 12 and 321 4 x 12 shiftworkers and 325 day workers) were recruited. A self-administered questionnaire was used to obtain information about shiftwork schedule, demographic characteristics, and lifestyle and social factors, and the WAI was applied. The outcomes of interest were the WAI sum score and its seven dimensions. In examining the relationship with the WAI categories, a Proportional Odds Model (POM) was used to identify the potential determinants. Logistic regression models were used to estimate the impact of age on single dimensions of WAI after adjustment for potential confounding factors. Increasing age and obesity (BMI > or = 30) were the only significant determinants of poorer WAI. Although a positive association was found linking the second WAI dimension (work ability in relation to job demands) with age, an inverse association was demonstrated consistently between age and the third and fourth WAI dimensions, i.e., number of diagnosed diseases and estimated work impairment due to disease, after adjustment for potential confounders. The age-dependency was moderate overall, but seemed to be stronger among shift- than day workers, although this difference did not reach statistical significance. There was no significant differential impact of the working time systems on the WAI sum score or on the individual WAI dimensions. Thus, there is no indication of an excessive adverse health impact

Medium-dose-rate brachytherapy of cancer of the cervix: preliminary results of a prospectively designed schedule based on the linear-quadratic model

International Nuclear Information System (INIS)

Leborgne, Felix; Fowler, Jack F.; Leborgne, Jose H.; Zubizarreta, Eduardo; Curochquin, Rene

1999-01-01

Purpose: To compare results and complications of our previous low-dose-rate (LDR) brachytherapy schedule for early-stage cancer of the cervix, with a prospectively designed medium-dose-rate (MDR) schedule, based on the linear-quadratic model (LQ). Methods and Materials: A combination of brachytherapy, external beam pelvic and parametrial irradiation was used in 102 consecutive Stage Ib-IIb LDR treated patients (1986-1990) and 42 equally staged MDR treated patients (1994-1996). The planned MDR schedule consisted of three insertions on three treatment days with six 8-Gy brachytherapy fractions to Point A, two on each treatment day with an interfraction interval of 6 hours, plus 18 Gy external whole pelvic dose, and followed by additional parametrial irradiation. The calculated biologically effective dose (BED) for tumor was 90 Gy 10 and for rectum below 125 Gy 3 . Results: In practice the MDR brachytherapy schedule achieved a tumor BED of 86 Gy 10 and a rectal BED of 101 Gy 3 . The latter was better than originally planned due to a reduction from 85% to 77% in the percentage of the mean dose to the rectum in relation to Point A. The mean overall treatment time was 10 days shorter for MDR in comparison with LDR. The 3-year actuarial central control for LDR and MDR was 97% and 98% (p = NS), respectively. The Grades 2 and 3 late complications (scale 0 to 3) were 1% and 2.4%, respectively for LDR (3-year) and MDR (2-year). Conclusions: LQ is a reliable tool for designing new schedules with altered fractionation and dose rates. The MDR schedule has proven to be an equivalent treatment schedule compared with LDR, with an additional advantage of having a shorter overall treatment time. The mean rectal BED Gy 3 was lower than expected

Ahead of the game protocol: a multi-component, community sport-based program targeting prevention, promotion and early intervention for mental health among adolescent males.

Science.gov (United States)

Vella, Stewart A; Swann, Christian; Batterham, Marijka; Boydell, Katherine M; Eckermann, Simon; Fogarty, Andrea; Hurley, Diarmuid; Liddle, Sarah K; Lonsdale, Chris; Miller, Andrew; Noetel, Michael; Okely, Anthony D; Sanders, Taren; Telenta, Joanne; Deane, Frank P

2018-03-21

There is a recognised need for targeted community-wide mental health strategies and interventions aimed specifically at prevention and early intervention in promoting mental health. Young males are a high need group who hold particularly negative attitudes towards mental health services, and these views are detrimental for early intervention and help-seeking. Organised sports provide a promising context to deliver community-wide mental health strategies and interventions to adolescent males. The aim of the Ahead of the Game program is to test the effectiveness of a multi-component, community-sport based program targeting prevention, promotion and early intervention for mental health among adolescent males. The Ahead of the Game program will be implemented within a sample drawn from community sporting clubs and evaluated using a sample drawn from a matched control community. Four programs are proposed, including two targeting adolescents, one for parents, and one for sports coaches. One adolescent program aims to increase mental health literacy, intentions to seek and/or provide help for mental health, and to decrease stigmatising attitudes. The second adolescent program aims to increase resilience. The goal of the parent program is to increase parental mental health literacy and confidence to provide help. The coach program is intended to increase coaches' supportive behaviours (e.g., autonomy supportive behaviours), and in turn facilitate high-quality motivation and wellbeing among adolescents. Programs will be complemented by a messaging campaign aimed at adolescents to enhance mental health literacy. The effects of the program on adolescent males' psychological distress and wellbeing will also be explored. Organised sports represent a potentially engaging avenue to promote mental health and prevent the onset of mental health problems among adolescent males. The community-based design, with samples drawn from an intervention and a matched control community

Straight Ahead in Microgravity

Science.gov (United States)

Wood, S. J.; Vanya, R. D.; Clement, G.

2014-01-01

This joint ESA-NASA study will address adaptive changes in spatial orientation related to the subjective straight ahead, and the use of a vibrotactile sensory aid to reduce perceptual errors. The study will be conducted before and after long-duration expeditions to the International Space Station (ISS) to examine how spatial processing of target location is altered following exposure to microgravity. This project specifically addresses the sensorimotor research gap "What are the changes in sensorimotor function over the course of a mission?" Six ISS crewmembers will be requested to participate in three preflight sessions (between 120 and 60 days prior to launch) and then three postflight sessions on R+0/1 day, R+4 +/-2 days, and R+8 +/-2 days. The three specific aims include: (a) fixation of actual and imagined target locations at different distances; (b) directed eye and arm movements along different spatial reference frames; and (c) the vestibulo-ocular reflex during translation motion with fixation targets at different distances. These measures will be compared between upright and tilted conditions. Measures will then be compared with and without a vibrotactile sensory aid that indicates how far one has tilted relative to the straight-ahead direction. The flight study was been approved by the medical review boards and will be implemented in the upcoming Informed Crew Briefings to solicit flight subject participation. Preliminary data has been recorded on 6 subjects during parabolic flight to examine the spatial coding of eye movements during roll tilt relative to perceived orientations while free-floating during the microgravity phase of parabolic flight or during head tilt in normal gravity. Binocular videographic recordings obtained in darkness allowed us to quantify the mean deviations in gaze trajectories along both horizontal and vertical coordinates relative to the aircraft and head orientations. During some parabolas, a vibrotactile sensory aid provided

Modelling altered fractionation schedules

International Nuclear Information System (INIS)

Fowler, J.F.

1993-01-01

The author discusses the conflicting requirements of hyperfractionation and accelerated fractionation used in radiotherapy, and the development of computer modelling to predict how to obtain an optimum of tumour cell kill without exceeding normal-tissue tolerance. The present trend is to shorten hyperfractionated schedules from 6 or 7 weeks to give overall times of 4 or 5 weeks as in new schedules by Herskovic et al (1992) and Harari (1992). Very high doses are given, much higher than can be given when ultrashort schedules such as CHART (12 days) are used. Computer modelling has suggested that optimum overall times, to yield maximum cell kill in tumours ((α/β = 10 Gy) for a constant level of late complications (α/β = 3 Gy) would be X or X-1 weeks, where X is the doubling time of the tumour cells in days (Fowler 1990). For median doubling times of about 5 days, overall times of 4 or 5 weeks should be ideal. (U.K.)

What's Mine Is Yours: The Crossover of Day-Specific Self-Esteem

Science.gov (United States)

Neff, Angela; Sonnentag, Sabine; Niessen, Cornelia; Unger, Dana

2012-01-01

This diary study examines the daily crossover of self-esteem within working couples. By integrating self-esteem research into the crossover framework, we hypothesized that the day-specific self-esteem experienced by one partner after work crosses over to the other partner. Furthermore, we proposed that this daily crossover process is moderated by…

Forecasting Day-Ahead Electricity Prices : Utilizing Hourly Prices

NARCIS (Netherlands)

E. Raviv (Eran); K.E. Bouwman (Kees); D.J.C. van Dijk (Dick)

2013-01-01

textabstractThe daily average price of electricity represents the price of electricity to be delivered over the full next day and serves as a key reference price in the electricity market. It is an aggregate that equals the average of hourly prices for delivery during each of the 24 individual

A System for Planning Ahead

Science.gov (United States)

2002-01-01

A software system that uses artificial intelligence techniques to help with complex Space Shuttle scheduling at Kennedy Space Center is commercially available. Stottler Henke Associates, Inc.(SHAI), is marketing its automatic scheduling system, the Automated Manifest Planner (AMP), to industries that must plan and project changes many different times before the tasks are executed. The system creates optimal schedules while reducing manpower costs. Using information entered into the system by expert planners, the system automatically makes scheduling decisions based upon resource limitations and other constraints. It provides a constraint authoring system for adding other constraints to the scheduling process as needed. AMP is adaptable to assist with a variety of complex scheduling problems in manufacturing, transportation, business, architecture, and construction. AMP can benefit vehicle assembly plants, batch processing plants, semiconductor manufacturing, printing and textiles, surface and underground mining operations, and maintenance shops. For most of SHAI's commercial sales, the company obtains a service contract to customize AMP to a specific domain and then issues the customer a user license.

Impact of interference on the performance of selection based parallel multiuser scheduling

KAUST Repository

Nam, Sungsik

2012-02-01

In conventional multiuser parallel scheduling schemes, every scheduled user is interfering with every other scheduled user, which limits the capacity and performance of multiuser systems, and the level of interference becomes substantial as the number of scheduled users increases. Based on the above observations, we investigate the trade-off between the system throughput and the number of scheduled users through the exact analysis of the total average sum rate capacity and the average spectral efficiency. Our analytical results can help the system designer to carefully select the appropriate number of scheduled users to maximize the overall throughput while maintaining an acceptable quality of service under certain channel conditions. © 2012 IEEE.

Work happiness among teachers: a day reconstruction study on the role of self-concordance.

Science.gov (United States)

Tadić, Maja; Bakker, Arnold B; Oerlemans, Wido G M

2013-12-01

Self-concordant work motivation arises from one's authentic choices, personal values, and interests. In the present study, we investigated whether self-concordant motivation may fluctuate from one work-related task to the next. On the basis of self-determination theory, we hypothesized that momentary self-concordance buffers the negative impact of momentary work demands on momentary happiness. We developed a modified version of the day reconstruction method to investigate self-concordance, work demands, and happiness during specific work-related tasks on a within-person and within-day level. In total, 132 teachers completed a daily diary on three consecutive work days as well as a background questionnaire. The daily diary resulted in 792 reported work activities and activity-related work demands, self-concordance, and happiness scores. Multilevel analysis showed that-for most work activities-state self-concordant motivation buffered the negative association of work demands with happiness. These findings add to the literature on motivation and well-being by showing that the levels of self-concordance and happiness experienced by employees vary significantly on a within-day level and show a predictable pattern. We discuss theoretical and practical implications of the findings to increase employees' well-being. © 2013.

HOLD MODE BASED DYNAMIC PRIORITY LOAD ADAPTIVE INTERPICONET SCHEDULING FOR BLUETOOTH SCATTERNETS

Directory of Open Access Journals (Sweden)

G.S. Mahalakshmi

2011-09-01

Full Text Available Scheduling in piconets has emerged as a challenging research area. Interpiconet scheduling focuses on when a bridge is switched among various piconets and how a bridge node communicates with the masters in different piconets. This paper proposes an interpiconet scheduling algorithm named, hold mode based dynamic traffic priority load adaptive scheduling. The bridges are adaptively switched between the piconets according to various traffic loads. The main goal is to maximize the utilization of the bridge by reducing the bridge switch wastes, utilize intelligent decision making algorithm, resolve conflict between the masters, and allow negotiation for bridge utilization in HDPLIS using bridge failure-bridge repair procedure . The Hold mode - dynamic traffic - priority based - load adaptive scheduling reduces the number of bridge switch wastes and hence increases the efficiency of the bridge which results in increased performance of the system.

Self-Reported Recovery from 2-Week 12-Hour Shift Work Schedules: A 14-Day Follow-Up

Directory of Open Access Journals (Sweden)

Suzanne L. Merkus

2015-09-01

Conclusion: After 2-week 12-hour night and swing shifts, only the course for sleep quality differed from that of day work. Sleep quality was poorer for night and swing shift workers on the 1st day off and remained poorer for the 14-day follow-up. This showed that while working at night had no effect on feeling rested, tiredness, and energy levels, it had a relatively long-lasting effect on sleep quality.

Breastfeeding: Planning Ahead

Medline Plus

Full Text Available ... we are What we do Programs and activities Work with us Contact Us Blog Popular topics Vision and mission Leadership Programs and activities In your community Funding opportunities Internships and jobs View all pages in this section Home It's Only Natural Planning ahead It's Only Natural ...

PRACTICAL IMPLICATIONS OF LOCATION-BASED SCHEDULING

DEFF Research Database (Denmark)

Andersson, Niclas; Christensen, Knud

2007-01-01

The traditional method for planning, scheduling and controlling activities and resources in construction projects is the CPM-scheduling, which has been the predominant scheduling method since its introduction in the late 1950s. Over the years, CPM has proven to be a very powerful technique...... that will be used in this study. LBS is a scheduling method that rests upon the theories of line-of-balance and which uses the graphic representation of a flowline chart. As such, LBS is adapted for planning and management of workflows and, thus, may provide a solution to the identified shortcomings of CPM. Even...

Multi-day activity scheduling reactions to planned activities and future events in a dynamic model of activity-travel behavior

Science.gov (United States)

Nijland, Linda; Arentze, Theo; Timmermans, Harry

2014-01-01

Modeling multi-day planning has received scarce attention in activity-based transport demand modeling so far. However, new dynamic activity-based approaches are being developed at the current moment. The frequency and inflexibility of planned activities and events in activity schedules of individuals indicate the importance of incorporating those pre-planned activities in the new generation of dynamic travel demand models. Elaborating and combining previous work on event-driven activity generation, the aim of this paper is to develop and illustrate an extension of a need-based model of activity generation that takes into account possible influences of pre-planned activities and events. This paper describes the theory and shows the results of simulations of the extension. The simulation was conducted for six different activities, and the parameter values used were consistent with an earlier estimation study. The results show that the model works well and that the influences of the parameters are consistent, logical, and have clear interpretations. These findings offer further evidence of face and construct validity to the suggested modeling approach.

Perioperative solutions for rapid recovery joint arthroplasty: get ahead and stay ahead.

Science.gov (United States)

Sculco, Peter K; Pagnano, Mark W

2015-04-01

Rapid recovery after total joint arthroplasty requires patients to get ahead and stay ahead or the four impediments to early rehabilitation and discharge: volume depletion, blood loss, pain, and nausea. Adequate volume resuscitation starts before entering the operating room and focuses on intravenous fluids rather than red blood cell transfusion. Tranexamic acid limits blood loss and reduces the need for most other blood management systems. Rapid recovery pain management focuses on minimizing parenteral opioids. A short-acting spinal with a peri-articular local anesthetic injection is reliable, reproducible, and safe. Patients at risk for post-operative nausea are treated with anti-emetic medications and perioperative dexamethasone. These interventions reflect a transition from the sick-patient model to the well-patient model and make rapid recovery joint arthroplasty a reality in 2015. Copyright © 2015 Elsevier Inc. All rights reserved.

A real-time Excel-based scheduling solution for nursing staff reallocation.

Science.gov (United States)

Tuominen, Outi Anneli; Lundgren-Laine, Heljä; Kauppila, Wiveka; Hupli, Maija; Salanterä, Sanna

2016-09-30

Aim This article describes the development and testing of an Excel-based scheduling solution for the flexible allocation and reallocation of nurses to cover sudden, unplanned absences among permanent nursing staff. Method A quasi-experimental, one group, pre- and post-test study design was used ( Box 1 ) with total sampling. Participants (n=17) were selected purposefully by including all ward managers (n=8) and assistant ward managers (n=9) from one university hospital department. The number of sudden absences among the nursing staff was identified during two 4-week data collection periods (pre- and post-test). Results During the use of the paper-based scheduling system, 121 absences were identified; during the use of the Excel-based system, 106 were identified. The main reasons for the use of flexible 'floating' nurses were sick leave (n=66) and workload (n=31). Other reasons (n=29) included patient transfer to another hospital, scheduling errors and the start or end of employment. Conclusion The Excel-based scheduling solution offered better support in obtaining substitute labour inside the organisation, with smaller employment costs. It also reduced the number of tasks ward managers had to carry out during the process of reallocating staff.

Getting ahead communication skills for business English : home study book

CERN Document Server

Jones-Macziola, Sarah

1993-01-01

Getting Ahead is a course for students at the pre-intermediate level who want to improve their English for business and professional purposes. It is suitable both for students who are preparing for work and those who are in employment already. At the same time as drawing on the learner's own experience, the course provides activities which give the less experienced learner the opportunity to participate effectively in meaningful communication. The main units are topic-based and focus on such themes as describing a company, welcoming visitors and dealing with problems. All four skills – listening, speaking, reading and writing – are developed. There are controlled practice tasks and meaningful communication activities, and the course as a whole provides a clear structural progression. The Home Study Book provides out-of-class activities which review and expand on what has been done in class. These activities are keyed at the back of the book to aid self-study. The Home Study CD contains all the listening a...

Excel-based scheduling for reallocation of nursing staff.

Science.gov (United States)

2016-10-19

Outi Annelli Tuominen and colleagues write in Nursing Management about the use of an Excel-based scheduling system for reallocation of nursing staff, which was trialled on ward managers and assistant ward managers.

Compositional schedulability analysis of real-time actor-based systems.

Science.gov (United States)

Jaghoori, Mohammad Mahdi; de Boer, Frank; Longuet, Delphine; Chothia, Tom; Sirjani, Marjan

2017-01-01

We present an extension of the actor model with real-time, including deadlines associated with messages, and explicit application-level scheduling policies, e.g.,"earliest deadline first" which can be associated with individual actors. Schedulability analysis in this setting amounts to checking whether, given a scheduling policy for each actor, every task is processed within its designated deadline. To check schedulability, we introduce a compositional automata-theoretic approach, based on maximal use of model checking combined with testing. Behavioral interfaces define what an actor expects from the environment, and the deadlines for messages given these assumptions. We use model checking to verify that actors match their behavioral interfaces. We extend timed automata refinement with the notion of deadlines and use it to define compatibility of actor environments with the behavioral interfaces. Model checking of compatibility is computationally hard, so we propose a special testing process. We show that the analyses are decidable and automate the process using the Uppaal model checker.

Estimation of Airline Benefits from Avionics Upgrade under Preferential Merge Re-sequence Scheduling

Science.gov (United States)

Kotegawa, Tatsuya; Cayabyab, Charlene Anne; Almog, Noam

2013-01-01

Modernization of the airline fleet avionics is essential to fully enable future technologies and procedures for increasing national airspace system capacity. However in the current national airspace system, system-wide benefits gained by avionics upgrade are not fully directed to aircraft/airlines that upgrade, resulting in slow fleet modernization rate. Preferential merge re-sequence scheduling is a best-equipped-best-served concept designed to incentivize avionics upgrade among airlines by allowing aircraft with new avionics (high-equipped) to be re-sequenced ahead of aircraft without the upgrades (low-equipped) at enroute merge waypoints. The goal of this study is to investigate the potential benefits gained or lost by airlines under a high or low-equipped fleet scenario if preferential merge resequence scheduling is implemented.

Visual straight-ahead preference in saccadic eye movements.

Science.gov (United States)

Camors, Damien; Trotter, Yves; Pouget, Pierre; Gilardeau, Sophie; Durand, Jean-Baptiste

2016-03-15

Ocular saccades bringing the gaze toward the straight-ahead direction (centripetal) exhibit higher dynamics than those steering the gaze away (centrifugal). This is generally explained by oculomotor determinants: centripetal saccades are more efficient because they pull the eyes back toward their primary orbital position. However, visual determinants might also be invoked: elements located straight-ahead trigger saccades more efficiently because they receive a privileged visual processing. Here, we addressed this issue by using both pro- and anti-saccade tasks in order to dissociate the centripetal/centrifugal directions of the saccades, from the straight-ahead/eccentric locations of the visual elements triggering those saccades. Twenty participants underwent alternating blocks of pro- and anti-saccades during which eye movements were recorded binocularly at 1 kHz. The results confirm that centripetal saccades are always executed faster than centrifugal ones, irrespective of whether the visual elements have straight-ahead or eccentric locations. However, by contrast, saccades triggered by elements located straight-ahead are consistently initiated more rapidly than those evoked by eccentric elements, irrespective of their centripetal or centrifugal direction. Importantly, this double dissociation reveals that the higher dynamics of centripetal pro-saccades stem from both oculomotor and visual determinants, which act respectively on the execution and initiation of ocular saccades.

Alternative Work Schedules: Definitions

Science.gov (United States)

Journal of the College and University Personnel Association, 1977

1977-01-01

The term "alternative work schedules" encompasses any variation of the requirement that all permanent employees in an organization or one shift of employees adhere to the same five-day, seven-to-eight-hour schedule. This article defines staggered hours, flexible working hours (flexitour and gliding time), compressed work week, the task system, and…

Network scheduling at Belene NPP construction site

International Nuclear Information System (INIS)

Matveev, A.

2010-01-01

Four types of schedules differing in the level of their detail are singled out to enhance the efficiency of Belene NPP Project implementation planning and monitoring: Level 1 Schedule–Summary Integrated Overall Time Schedule (SIOTS) is an appendix to EPC Contract. The main purpose of SIOTS is the large scale presentation of the current information on the Project implementation. Level 2 Schedule–Integrated Overall Time Schedule (IOTS)is the contract schedule for the Contractor (ASE JSC) and their subcontractors.The principal purpose of IOTS is the work progress planning and monitoring, the analysis of the effect of activities implementation upon the progress of the Project as a whole. IOTS is the reporting schedule at the Employer –Contractor level. Level 3 Schedules, Detail Time Schedules(DTS) are developed by those who actually perform the work and are agreed upon with Atomstroyexport JSC.The main purpose of DTS is the detail planning of Atomstroyexport subcontractor's activities. DTSare the reporting schedules at the level of Contractor-Subcontractor. Level 4 Schedules are the High Detail Time Schedules (HDTS), which are the day-to-day plans of work implementation and are developed, as a rule, for a week's time period.Each lower level time schedule details the activities of the higher level time schedule

Optimal Electric Vehicle Scheduling: A Co-Optimized System and Customer Perspective

Science.gov (United States)

Maigha

Electric vehicles provide a two pronged solution to the problems faced by the electricity and transportation sectors. They provide a green, highly efficient alternative to the internal combustion engine vehicles, thus reducing our dependence on fossil fuels. Secondly, they bear the potential of supporting the grid as energy storage devices while incentivising the customers through their participation in energy markets. Despite these advantages, widespread adoption of electric vehicles faces socio-technical and economic bottleneck. This dissertation seeks to provide solutions that balance system and customer objectives under present technological capabilities. The research uses electric vehicles as controllable loads and resources. The idea is to provide the customers with required tools to make an informed decision while considering the system conditions. First, a genetic algorithm based optimal charging strategy to reduce the impact of aggregated electric vehicle load has been presented. A Monte Carlo based solution strategy studies change in the solution under different objective functions. This day-ahead scheduling is then extended to real-time coordination using a moving-horizon approach. Further, battery degradation costs have been explored with vehicle-to-grid implementations, thus accounting for customer net-revenue and vehicle utility for grid support. A Pareto front, thus obtained, provides the nexus between customer and system desired operating points. Finally, we propose a transactive business model for a smart airport parking facility. This model identifies various revenue streams and satisfaction indices that benefit the parking lot owner and the customer, thus adding value to the electric vehicle.

Real-time integration of optimal generation scheduling with MPC for the energy management of a renewable hydrogen-based microgrid

International Nuclear Information System (INIS)

Petrollese, Mario; Valverde, Luis; Cocco, Daniele; Cau, Giorgio; Guerra, José

2016-01-01

Highlights: • Energy management strategy for a renewable hydrogen-based microgrid. • Integration of optimal generation scheduling with a model predictive control. • Experimental tests are carried out simulating typical summer and winter days. • Effective improvement in performance and reduction in microgrid operating cost are achieved. - Abstract: This paper presents a novel control strategy for the optimal management of microgrids with high penetration of renewable energy sources and different energy storage systems. The control strategy is based on the integration of optimal generation scheduling with a model predictive control in order to achieve both long and short-term optimal planning. In particular, long-term optimization of the various microgrid components is obtained by the adoption of an optimal generation scheduling, in which a statistical approach is used to take into account weather and load forecasting uncertainties. The real-time management of the microgrid is instead entrusted to a model predictive controller, which has the important feature of using the results obtained by the optimal generation scheduling. The proposed control strategy was tested in a laboratory-scale microgrid present at the University of Seville, which is composed of an electronic power source that emulates a photovoltaic system, a battery bank and a hydrogen production and storage system. Two different experimental tests that simulate a summer and a winter day were carried out over a 24-h period to verify the reliability and performance enhancement of the control system. Results show an effective improvement in performance in terms of reduction of the microgrid operating cost and greater involvement of the hydrogen storage system for the maintenance of a spinning reserve in batteries.

Analysis of Issues for Project Scheduling by Multiple, Dispersed Schedulers (distributed Scheduling) and Requirements for Manual Protocols and Computer-based Support

Science.gov (United States)

Richards, Stephen F.

1991-01-01

Although computerized operations have significant gains realized in many areas, one area, scheduling, has enjoyed few benefits from automation. The traditional methods of industrial engineering and operations research have not proven robust enough to handle the complexities associated with the scheduling of realistic problems. To address this need, NASA has developed the computer-aided scheduling system (COMPASS), a sophisticated, interactive scheduling tool that is in wide-spread use within NASA and the contractor community. Therefore, COMPASS provides no explicit support for the large class of problems in which several people, perhaps at various locations, build separate schedules that share a common pool of resources. This research examines the issue of distributing scheduling, as applied to application domains characterized by the partial ordering of tasks, limited resources, and time restrictions. The focus of this research is on identifying issues related to distributed scheduling, locating applicable problem domains within NASA, and suggesting areas for ongoing research. The issues that this research identifies are goals, rescheduling requirements, database support, the need for communication and coordination among individual schedulers, the potential for expert system support for scheduling, and the possibility of integrating artificially intelligent schedulers into a network of human schedulers.

Developing optimal nurses work schedule using integer programming

Science.gov (United States)

Shahidin, Ainon Mardhiyah; Said, Mohd Syazwan Md; Said, Noor Hizwan Mohamad; Sazali, Noor Izatie Amaliena

2017-08-01

Time management is the art of arranging, organizing and scheduling one's time for the purpose of generating more effective work and productivity. Scheduling is the process of deciding how to commit resources between varieties of possible tasks. Thus, it is crucial for every organization to have a good work schedule for their staffs. The job of Ward nurses at hospitals runs for 24 hours every day. Therefore, nurses will be working using shift scheduling. This study is aimed to solve the nurse scheduling problem at an emergency ward of a private hospital. A 7-day work schedule for 7 consecutive weeks satisfying all the constraints set by the hospital will be developed using Integer Programming. The work schedule for the nurses obtained gives an optimal solution where all the constraints are being satisfied successfully.

Long-term home care scheduling

DEFF Research Database (Denmark)

Gamst, Mette; Jensen, Thomas Sejr

In several countries, home care is provided for certain citizens living at home. The long-term home care scheduling problem is to generate work plans spanning several days such that a high quality of service is maintained and the overall cost is kept as low as possible. A solution to the problem...... provides detailed information on visits and visit times for each employee on each of the covered days. We propose a branch-and-price algorithm for the long-term home care scheduling problem. The pricing problem generates one-day plans for an employee, and the master problem merges the plans with respect...

Day of the week lost time occupational injury trends in the US by gender and industry and their implications for work scheduling.

Science.gov (United States)

Brogmus, G E

2007-03-01

While there is a growing body of research on the impact of work schedules on the risk of occupational injuries, there has been little investigation into the impact that the day of the week might have. The present research was completed to explore day of the week trends, reasons for such trends and the corresponding implications for work scheduling. Data for the number of injuries and illnesses involving days away from work (lost time; LT) in 2004 were provided by the US Bureau of Labor Statistics Office of Safety and Health Statistics. Data from the American Time Use Survey database were used to estimate work hours in 2004. From these two data sources, the rate of LT injuries and illnesses (per 200 000 work hours) by day of the week, industry sector and gender were estimated. The analysis revealed clear differences by day of the week, gender and major industry sector. Sundays had the highest rate overall--nearly 37% higher than the average of the remaining days, Monday to Saturday. Mondays had the next highest rate followed closely by Saturdays. This pattern was not the same for males and females. For males, Mondays had the highest LT rate (27% higher than the average of all other days) with all remaining days having essentially the same rate. For females, Sundays and Saturdays had much higher LT rates--122% and 60% higher, respectively, than the average weekday rate. There were also differences by industry and differences between genders by industry. The present analysis suggests that several factors may be contributing to the weekend and Monday trends observed. Lower-tenured (and younger) workers on the weekends, lower female management/supervision and second jobs on the weekend seem to be contributors to the high Saturday and Sunday LT rates. Differences in day of the week employment by industry did not account for the trends observed. Fraud and overtime also could not be confirmed as contributing to these trends. Monday trends were more complex to explain, with

Flexible job-shop scheduling based on genetic algorithm and simulation validation

Directory of Open Access Journals (Sweden)

Zhou Erming

2017-01-01

Full Text Available This paper selects flexible job-shop scheduling problem as the research object, and Constructs mathematical model aimed at minimizing the maximum makespan. Taking the transmission reverse gear production line of a transmission corporation as an example, genetic algorithm is applied for flexible jobshop scheduling problem to get the specific optimal scheduling results with MATLAB. DELMIA/QUEST based on 3D discrete event simulation is applied to construct the physical model of the production workshop. On the basis of the optimal scheduling results, the logical link of the physical model for the production workshop is established, besides, importing the appropriate process parameters to make virtual simulation on the production workshop. Finally, through analyzing the simulated results, it shows that the scheduling results are effective and reasonable.

Changed nursing scheduling for improved safety culture and working conditions - patients' and nurses' perspectives.

Science.gov (United States)

Kullberg, Anna; Bergenmar, Mia; Sharp, Lena

2016-05-01

To evaluate fixed scheduling compared with self-scheduling for nursing staff in oncological inpatient care with regard to patient and staff outcomes. Various scheduling models have been tested to attract and retain nursing staff. Little is known about how these schedules affect staff and patients. Fixed scheduling and self-scheduling have been studied to a small extent, solely from a staff perspective. We implemented fixed scheduling on two of four oncological inpatient wards. Two wards kept self-scheduling. Through a quasi-experimental design, baseline and follow-up measurements were collected among staff and patients. The Safety Attitudes Questionnaire was used among staff, as well as study-specific questions for patients and staff. Fixed scheduling was associated with less overtime and fewer possibilities to change shifts. Self-scheduling was associated with more requests from management for short notice shift changes. The type of scheduling did not affect patient-reported outcomes. Fixed scheduling should be considered in order to lower overtime. Further research is necessary and should explore patient outcomes to a greater extent. Scheduling is a core task for nurse managers. Our study suggests fixed scheduling as a strategy for managers to improve the effective use of resources and safety. © 2016 John Wiley & Sons Ltd.

An immediate go-ahead for nuclear plants

International Nuclear Information System (INIS)

Stubbe, C.

1986-01-01

In the meantime a wealth of court decisions have been reached regarding an immediate go-ahead for nuclear power plants. For all that, it is still not clear - and varying decisions have been made in judgement - according to which criteria the judicial balance is to be made between the interests of the plaintiff in bringing about a stay of the proceedings and the interests of the planner in going ahead with them. The author advocates an examination of the main issue already during suspension proceedings until the court can form a preliminary opinion on the chances of success of the main issue. He also advocates in the Administrative Court Ordinance regulations regarding go-ahead as determined in the commission draft to the Administrative Court of 1978. (orig.) [de

Optimal Scheduling of a Battery Energy Storage System with Electric Vehicles’ Auxiliary for a Distribution Network with Renewable Energy Integration

Directory of Open Access Journals (Sweden)

Yuqing Yang

2015-09-01

Full Text Available With global conventional energy depletion, as well as environmental pollution, utilizing renewable energy for power supply is the only way for human beings to survive. Currently, distributed generation incorporated into a distribution network has become the new trend, with the advantages of controllability, flexibility and tremendous potential. However, the fluctuation of distributed energy resources (DERs is still the main concern for accurate deployment. Thus, a battery energy storage system (BESS has to be involved to mitigate the bad effects of DERs’ integration. In this paper, optimal scheduling strategies for BESS operation have been proposed, to assist with consuming the renewable energy, reduce the active power loss, alleviate the voltage fluctuation and minimize the electricity cost. Besides, the electric vehicles (EVs considered as the auxiliary technique are also introduced to attenuate the DERs’ influence. Moreover, both day-ahead and real-time operation scheduling strategies were presented under the consideration with the constraints of BESS and the EVs’ operation, and the optimization was tackled by a fuzzy mathematical method and an improved particle swarm optimization (IPSO algorithm. Furthermore, the test system for the proposed strategies is a real distribution network with renewable energy integration. After simulation, the proposed scheduling strategies have been verified to be extremely effective for the enhancement of the distribution network characteristics.

Vehicle and driver scheduling for public transit.

Science.gov (United States)

2009-08-01

The problem of driver scheduling involves the construction of a legal set of shifts, including allowance : of overtime, which cover the blocks in a particular vehicle schedule. A shift is the work scheduled to be performed by : a driver in one day, w...

A simple rule based model for scheduling farm management operations in SWAT

Science.gov (United States)

Schürz, Christoph; Mehdi, Bano; Schulz, Karsten

2016-04-01

For many interdisciplinary questions at the watershed scale, the Soil and Water Assessment Tool (SWAT; Arnold et al., 1998) has become an accepted and widely used tool. Despite its flexibility, the model is highly demanding when it comes to input data. At SWAT's core the water balance and the modeled nutrient cycles are plant growth driven (implemented with the EPIC crop growth model). Therefore, land use and crop data with high spatial and thematic resolution, as well as detailed information on cultivation and farm management practices are required. For many applications of the model however, these data are unavailable. In order to meet these requirements, SWAT offers the option to trigger scheduled farm management operations by applying the Potential Heat Unit (PHU) concept. The PHU concept solely takes into account the accumulation of daily mean temperature for management scheduling. Hence, it contradicts several farming strategies that take place in reality; such as: i) Planting and harvesting dates are set much too early or too late, as the PHU concept is strongly sensitivity to inter-annual temperature fluctuations; ii) The timing of fertilizer application, in SWAT this often occurs simultaneously on the same date in in each field; iii) and can also coincide with precipitation events. Particularly, the latter two can lead to strong peaks in modeled nutrient loads. To cope with these shortcomings we propose a simple rule based model (RBM) to schedule management operations according to realistic farmer management practices in SWAT. The RBM involves simple strategies requiring only data that are input into the SWAT model initially, such as temperature and precipitation data. The user provides boundaries of time periods for operation schedules to take place for all crops in the model. These data are readily available from the literature or from crop variety trials. The RBM applies the dates by complying with the following rules: i) Operations scheduled in the

Interactive Dynamic Mission Scheduling for ASCA

Science.gov (United States)

Antunes, A.; Nagase, F.; Isobe, T.

The Japanese X-ray astronomy satellite ASCA (Advanced Satellite for Cosmology and Astrophysics) mission requires scheduling for each 6-month observation phase, further broken down into weekly schedules at a few minutes resolution. Two tools, SPIKE and NEEDLE, written in Lisp and C, use artificial intelligence (AI) techniques combined with a graphic user interface for fast creation and alteration of mission schedules. These programs consider viewing and satellite attitude constraints as well as observer-requested criteria and present an optimized set of solutions for review by the planner. Six-month schedules at 1 day resolution are created for an oversubscribed set of targets by the SPIKE software, originally written for HST and presently being adapted for EUVE, XTE and AXAF. The NEEDLE code creates weekly schedules at 1 min resolution using in-house orbital routines and creates output for processing by the command generation software. Schedule creation on both the long- and short-term scale is rapid, less than 1 day for long-term, and one hour for short-term.

Scheduling of Power System Cells Integrating Stochastic Power Generation

International Nuclear Information System (INIS)

Costa, L.M.

2008-12-01

Energy supply and climate change are nowadays two of the most outstanding problems which societies have to cope with under a context of increasing energy needs. Public awareness of these problems is driving political willingness to take actions for tackling them in a swift and efficient manner. Such actions mainly focus in increasing energy efficiency, in decreasing dependence on fossil fuels, and in reducing greenhouse gas emissions. In this context, power systems are undergoing important changes in the way they are planned and managed. On the one hand, vertically integrated structures are being replaced by market structures in which power systems are un-bundled. On the other, power systems that once relied on large power generation facilities are witnessing the end of these facilities' life-cycle and, consequently, their decommissioning. The role of distributed energy resources such as wind and solar power generators is becoming increasingly important in this context. However, the large-scale integration of such type of generation presents many challenges due, for instance, to the uncertainty associated to the variability of their production. Nevertheless, advanced forecasting tools may be combined with more controllable elements such as energy storage devices, gas turbines, and controllable loads to form systems that aim to reduce the impacts that may be caused by these uncertainties. This thesis addresses the management under market conditions of these types of systems that act like independent societies and which are herewith named power system cells. From the available literature, a unified view of power system scheduling problems is also proposed as a first step for managing sets of power system cells in a multi-cell management framework. Then, methodologies for performing the optimal day-ahead scheduling of single power system cells are proposed, discussed and evaluated under both a deterministic and a stochastic framework that directly integrates the

Effects of Accumulating Work Shifts on Performance-Based Fatigue Using Multiple Strength Measurements in Day and Night Shift Nurses and Aides.

Science.gov (United States)

Thompson, Brennan J; Stock, Matt S; Banuelas, Victoria K

2017-05-01

Objective This study aimed to examine the effects of accumulating nursing work on maximal and rapid strength characteristics in female nurses and compare these effects in day versus night shift workers. Background Nurses exhibit among the highest nonfatal injury rates of all occupations, which may be a consequence of long, cumulative work shift schedules. Fatigue may accumulate across multiple shifts and lead to performance impairments, which in turn may be linked to injury risks. Method Thirty-seven nurses and aides performed isometric strength-based performance testing of three muscle groups, including the knee extensors, knee flexors, and wrist flexors (hand grip), as well as countermovement jumps, at baseline and following exposure to three 12-hour work shifts in a four-day period. Variables included peak torque (PT) and rate of torque development (RTD) from isometric strength testing and jump height and power output. Results The rigorous work period resulted in significant decreases (-7.2% to -19.2%) in a large majority (8/9) of the isometric strength-based measurements. No differences were noted for the day versus night shift workers except for the RTD at 200 millisecond variable, for which the night shift had greater work-induced decreases than the day shift workers. No changes were observed for jump height or power output. Conclusions A compressed nursing work schedule resulted in decreases in strength-based performance abilities, being indicative of performance fatigue. Application Compressed work schedules involving long shifts lead to functional declines in nurse performance capacities that may pose risks for both the nurse and patient quality of care. Fatigue management plans are needed to monitor and regulate increased levels of fatigue.

Project Scheduling Heuristics-Based Standard PSO for Task-Resource Assignment in Heterogeneous Grid

OpenAIRE

Chen, Ruey-Maw; Wang, Chuin-Mu

2011-01-01

The task scheduling problem has been widely studied for assigning resources to tasks in heterogeneous grid environment. Effective task scheduling is an important issue for the performance of grid computing. Meanwhile, the task scheduling problem is an NP-complete problem. Hence, this investigation introduces a named “standard“ particle swarm optimization (PSO) metaheuristic approach to efficiently solve the task scheduling problems in grid. Meanwhile, two promising heuristics based on multimo...

Scheduling nursing personnel on a microcomputer.

Science.gov (United States)

Liao, C J; Kao, C Y

1997-01-01

Suggests that with the shortage of nursing personnel, hospital administrators have to pay more attention to the needs of nurses to retain and recruit them. Also asserts that improving nurses' schedules is one of the most economic ways for the hospital administration to create a better working environment for nurses. Develops an algorithm for scheduling nursing personnel. Contrary to the current hospital approach, which schedules nurses on a person-by-person basis, the proposed algorithm constructs schedules on a day-by-day basis. The algorithm has inherent flexibility in handling a variety of possible constraints and goals, similar to other non-cyclical approaches. But, unlike most other non-cyclical approaches, it can also generate a quality schedule in a short time on a microcomputer. The algorithm was coded in C language and run on a microcomputer. The developed software is currently implemented at a leading hospital in Taiwan. The response to the initial implementation is quite promising.

Forecasting Day-Ahead Electricity Prices: Utilizing Hourly Prices

OpenAIRE

Raviv, Eran; Bouwman, Kees E.; van Dijk, Dick

2013-01-01

This discussion paper led to a publication in 'Energy Economics' , 2015, 50, 227-239. The daily average price of electricity represents the price of electricity to be delivered over the full next day and serves as a key reference price in the electricity market. It is an aggregate that equals the average of hourly prices for delivery during each of the 24 individual hours. This paper demonstrates that the disaggregated hourly prices contain useful predictive information for the daily average ...

Refinery scheduling

Energy Technology Data Exchange (ETDEWEB)

Magalhaes, Marcus V.; Fraga, Eder T. [PETROBRAS, Rio de Janeiro, RJ (Brazil); Shah, Nilay [Imperial College, London (United Kingdom)

2004-07-01

This work addresses the refinery scheduling problem using mathematical programming techniques. The solution adopted was to decompose the entire refinery model into a crude oil scheduling and a product scheduling problem. The envelope for the crude oil scheduling problem is composed of a terminal, a pipeline and the crude area of a refinery, including the crude distillation units. The solution method adopted includes a decomposition technique based on the topology of the system. The envelope for the product scheduling comprises all tanks, process units and products found in a refinery. Once crude scheduling decisions are Also available the product scheduling is solved using a rolling horizon algorithm. All models were tested with real data from PETROBRAS' REFAP refinery, located in Canoas, Southern Brazil. (author)

"Doing our best to keep a routine:" How low-income mothers manage child feeding with unpredictable work and family schedules.

Science.gov (United States)

Agrawal, Tara; Farrell, Tracy Jean; Wethington, Elaine; Devine, Carol M

2018-01-01

Significant changes in work and family conditions over the last three decades have important implications for understanding how young children are fed. The new conditions of work and family have placed pressures on families. The aim of this study was to explore the work and family pressures shaping the ways parents feed their young children on a day-to-day basis. Twenty-two purposively recruited low-income employed mothers of 3-4 year old children from a rural county Head Start program in Upstate New York reported details about the context of their children's eating episodes in a 24-h qualitative dietary recall. Participating mothers were employed and/or in school at least 20 h a week and varied in partner and household characteristics. Interview transcripts were open coded using the constant comparative method for usual ways of feeding children. A typology of three emergent child feeding routines was identified based on mothers' accounts of the recurring ways they fed their child. Mothers' feeding routines were distinguished by a combination of four recurring key strategies - planning ahead, delegating, making trade-offs, and coordinating. Work schedule predictability and other adults helped mothers maintain feeding routines. Unexpected daily events, such as working overtime or waking up late, disrupted child feeding routines and required modifications. These findings suggest that understanding how young children are fed requires recognizing the socio-ecological environments that involve working mothers' daily schedules and household conditions and the multiple ways that mothers manage food and feeding to fit environmental constraints. There is a need to look at more than just family meals to understand parents' daily strategies for feeding young children and their implications for child nutrition. Copyright © 2017 Elsevier Ltd. All rights reserved.

QoS Differentiated and Fair Packet Scheduling in Broadband Wireless Access Networks

Directory of Open Access Journals (Sweden)

Zhang Yan

2009-01-01

Full Text Available This paper studies the packet scheduling problem in Broadband Wireless Access (BWA networks. The key difficulties of the BWA scheduling problem lie in the high variability of wireless channel capacity and the unknown model of packet arrival process. It is difficult for traditional heuristic scheduling algorithms to handle the situation and guarantee satisfying performance in BWA networks. In this paper, we introduce learning-based approach for a better solution. Specifically, we formulate the packet scheduling problem as an average cost Semi-Markov Decision Process (SMDP. Then, we solve the SMDP by using reinforcement learning. A feature-based linear approximation and the Temporal-Difference learning technique are employed to produce a near optimal solution of the corresponding SMDP problem. The proposed algorithm, called Reinforcement Learning Scheduling (RLS, has in-built capability of self-training. It is able to adaptively and timely regulate its scheduling policy according to the instantaneous network conditions. Simulation results indicate that RLS outperforms two classical scheduling algorithms and simultaneously considers: (i effective QoS differentiation, (ii high bandwidth utilization, and (iii both short-term and long-term fairness.

Development of an irrigation scheduling software based on model predicted crop water stress

Science.gov (United States)

Modern irrigation scheduling methods are generally based on sensor-monitored soil moisture regimes rather than crop water stress which is difficult to measure in real-time, but can be computed using agricultural system models. In this study, an irrigation scheduling software based on RZWQM2 model pr...

Mobile Phone-Based Unobtrusive Ecological Momentary Assessment of Day-to-Day Mood: An Explorative Study.

Science.gov (United States)

Asselbergs, Joost; Ruwaard, Jeroen; Ejdys, Michal; Schrader, Niels; Sijbrandij, Marit; Riper, Heleen

2016-03-29

Ecological momentary assessment (EMA) is a useful method to tap the dynamics of psychological and behavioral phenomena in real-world contexts. However, the response burden of (self-report) EMA limits its clinical utility. The aim was to explore mobile phone-based unobtrusive EMA, in which mobile phone usage logs are considered as proxy measures of clinically relevant user states and contexts. This was an uncontrolled explorative pilot study. Our study consisted of 6 weeks of EMA/unobtrusive EMA data collection in a Dutch student population (N=33), followed by a regression modeling analysis. Participants self-monitored their mood on their mobile phone (EMA) with a one-dimensional mood measure (1 to 10) and a two-dimensional circumplex measure (arousal/valence, -2 to 2). Meanwhile, with participants' consent, a mobile phone app unobtrusively collected (meta) data from six smartphone sensor logs (unobtrusive EMA: calls/short message service (SMS) text messages, screen time, application usage, accelerometer, and phone camera events). Through forward stepwise regression (FSR), we built personalized regression models from the unobtrusive EMA variables to predict day-to-day variation in EMA mood ratings. The predictive performance of these models (ie, cross-validated mean squared error and percentage of correct predictions) was compared to naive benchmark regression models (the mean model and a lag-2 history model). A total of 27 participants (81%) provided a mean 35.5 days (SD 3.8) of valid EMA/unobtrusive EMA data. The FSR models accurately predicted 55% to 76% of EMA mood scores. However, the predictive performance of these models was significantly inferior to that of naive benchmark models. Mobile phone-based unobtrusive EMA is a technically feasible and potentially powerful EMA variant. The method is young and positive findings may not replicate. At present, we do not recommend the application of FSR-based mood prediction in real-world clinical settings. Further

Staffing, overtime, and shift scheduling project

International Nuclear Information System (INIS)

Lewis, P.M.

1989-01-01

Recent events at the Peach Bottom nuclear power plant have demonstrated the need to establish a quantifiable basis for assessing the safety significance of long work hours on nuclear power plant operators. The incidents at TMI-2, Chernobyl, and Bhopal, which all occurred during the late evening/night shift, further highlight the importance of the relationship between shift scheduling and performance. The objective of this project is to estimate, using statistical analysis on data from the nuclear industry, the effects on safety of staffing levels, overtime, and shift scheduling for operators and maintenance personnel. Regarding staffing levels, the Nuclear Regulatory Commission (NRC) currently has no explicit regulation concerning the minimum acceptable levels of staffing in a plant that has an operating license. The NRC has no systematic method for collecting data on the number of licensed operators on the operating crews. In 1982 the NRC recommended that plants write into their technical specifications a model policy on overtime. Currently, 77 nuclear power plant units have the model policy or a modification of it written into their technical specifications; 33 units have no policy on overtime. The model policy sets limits on overtime for safety related personnel, although these limits can be exceeded with plant manger approval. The US nuclear power industry has three types of shift schedules: (1) forward-rotating 8-hour/day shift schedules, (2) backward-rotating 8-hour/day schedules, and (3) 12-hour/day schedules

NASA scheduling technologies

Science.gov (United States)

Adair, Jerry R.

1994-01-01

This paper is a consolidated report on ten major planning and scheduling systems that have been developed by the National Aeronautics and Space Administration (NASA). A description of each system, its components, and how it could be potentially used in private industry is provided in this paper. The planning and scheduling technology represented by the systems ranges from activity based scheduling employing artificial intelligence (AI) techniques to constraint based, iterative repair scheduling. The space related application domains in which the systems have been deployed vary from Space Shuttle monitoring during launch countdown to long term Hubble Space Telescope (HST) scheduling. This paper also describes any correlation that may exist between the work done on different planning and scheduling systems. Finally, this paper documents the lessons learned from the work and research performed in planning and scheduling technology and describes the areas where future work will be conducted.

Systematic literature review comparing rapid 3-dose administration of the GSK tick-borne encephalitis vaccine with other primary immunization schedules.

Science.gov (United States)

Galgani, Ilaria; Bunge, Eveline M; Hendriks, Lisa; Schludermann, Christopher; Marano, Cinzia; De Moerlooze, Laurence

2017-09-01

Tick-borne encephalitis (TBE), which is endemic across large regions of Europe and Asia, is most effectively prevented through vaccination. Three-dose primary TBE vaccination schedules are either rapid (0,7,21-days) or conventional (0,28-84-days, 9-12-months). The second dose can also be administered at 14 days for faster priming and sero-protection). Areas covered: We used a three-step selection process to identify 21 publications comparing the immunogenicity and/or safety of different schedules. Expert commentary: Priming with two or three TBE vaccine doses was highly immunogenic. After conventional priming (0-28 days), 95% adults and ≥95% children had neutralization test (NT) titers ≥10 at 14 days post-dose-2 compared with 92% adults and 99% children at 21 days post-dose-3 (rapid schedule). Most subjects retained NT titers ≥10 at day 300. A single booster dose induced a strong immune response in all subjects irrespective of primary vaccination schedule or elapsed time since priming. GMT peaked at 42 days post-dose-1 (i.e., 21 days post-dose 3 [rapid-schedule], or 14-28 days post-dose-2 [conventional-schedule]), and declined thereafter. Adverse events were generally rare and declined with increasing doses. In the absence of data to recommend one particular schedule, the regimen choice will remain at the physician's discretion, based on patient constraints and availability.

Wireless-Uplinks-Based Energy-Efficient Scheduling in Mobile Cloud Computing

Directory of Open Access Journals (Sweden)

Xing Liu

2015-01-01

Full Text Available Mobile cloud computing (MCC combines cloud computing and mobile internet to improve the computational capabilities of resource-constrained mobile devices (MDs. In MCC, mobile users could not only improve the computational capability of MDs but also save operation consumption by offloading the mobile applications to the cloud. However, MCC faces the problem of energy efficiency because of time-varying channels when the offloading is being executed. In this paper, we address the issue of energy-efficient scheduling for wireless uplink in MCC. By introducing Lyapunov optimization, we first propose a scheduling algorithm that can dynamically choose channel to transmit data based on queue backlog and channel statistics. Then, we show that the proposed scheduling algorithm can make a tradeoff between queue backlog and energy consumption in a channel-aware MCC system. Simulation results show that the proposed scheduling algorithm can reduce the time average energy consumption for offloading compared to the existing algorithm.

A self-adaptive chaotic particle swarm algorithm for short term hydroelectric system scheduling in deregulated environment

International Nuclear Information System (INIS)

Jiang Chuanwen; Bompard, Etorre

2005-01-01

This paper proposes a short term hydroelectric plant dispatch model based on the rule of maximizing the benefit. For the optimal dispatch model, which is a large scale nonlinear planning problem with multi-constraints and multi-variables, this paper proposes a novel self-adaptive chaotic particle swarm optimization algorithm to solve the short term generation scheduling of a hydro-system better in a deregulated environment. Since chaotic mapping enjoys certainty, ergodicity and the stochastic property, the proposed approach introduces chaos mapping and an adaptive scaling term into the particle swarm optimization algorithm, which increases its convergence rate and resulting precision. The new method has been examined and tested on a practical hydro-system. The results are promising and show the effectiveness and robustness of the proposed approach in comparison with the traditional particle swarm optimization algorithm

Model-based schedulability analysis of safety critical hard real-time Java programs

DEFF Research Database (Denmark)

Bøgholm, Thomas; Kragh-Hansen, Henrik; Olsen, Petur

2008-01-01

verifiable by the Uppaal model checker [23]. Schedulability analysis is reduced to a simple reachability question, checking for deadlock freedom. Model-based schedulability analysis has been developed by Amnell et al. [2], but has so far only been applied to high level specifications, not actual...

Scheduling algorithm for data relay satellite optical communication based on artificial intelligent optimization

Science.gov (United States)

Zhao, Wei-hu; Zhao, Jing; Zhao, Shang-hong; Li, Yong-jun; Wang, Xiang; Dong, Yi; Dong, Chen

2013-08-01

Optical satellite communication with the advantages of broadband, large capacity and low power consuming broke the bottleneck of the traditional microwave satellite communication. The formation of the Space-based Information System with the technology of high performance optical inter-satellite communication and the realization of global seamless coverage and mobile terminal accessing are the necessary trend of the development of optical satellite communication. Considering the resources, missions and restraints of Data Relay Satellite Optical Communication System, a model of optical communication resources scheduling is established and a scheduling algorithm based on artificial intelligent optimization is put forwarded. According to the multi-relay-satellite, multi-user-satellite, multi-optical-antenna and multi-mission with several priority weights, the resources are scheduled reasonable by the operation: "Ascertain Current Mission Scheduling Time" and "Refresh Latter Mission Time-Window". The priority weight is considered as the parameter of the fitness function and the scheduling project is optimized by the Genetic Algorithm. The simulation scenarios including 3 relay satellites with 6 optical antennas, 12 user satellites and 30 missions, the simulation result reveals that the algorithm obtain satisfactory results in both efficiency and performance and resources scheduling model and the optimization algorithm are suitable in multi-relay-satellite, multi-user-satellite, and multi-optical-antenna recourses scheduling problem.

Inexact stochastic risk-aversion optimal day-ahead dispatch model for electricity system management with wind power under uncertainty

International Nuclear Information System (INIS)

Ji, Ling; Huang, Guo-He; Huang, Lu-Cheng; Xie, Yu-Lei; Niu, Dong-Xiao

2016-01-01

High penetration of wind power generation and deregulated electricity market brings a great challenge to the electricity system operators. It is crucial to make optimal strategy among various generation units and spinning reserve for supporting the system safety operation. By integrating interval two-stage programming and stochastic robust programming, this paper proposes a novel robust model for day-ahead dispatch and risk-aversion management under uncertainties. In the proposed model, the uncertainties are expressed as interval values with different scenario probability. The proposed method requires low computation, and still retains the complete information. A case study is to validate the effectiveness of this approach. Facing the uncertainties of future demand and electricity price, the system operators need to make optimal dispatch strategy for thermal power units and wind turbine, and arrange proper spinning reserve and flexible demand response program to mitigate wind power forecasting error. The optimal strategies provide the system operators with better trade-off between the maximum benefits and the minimum system risk. In additional, two different market rules are compared. The results show that extra financial penalty for the wind power dispatch deviation is another efficient way to enhance the risk consciousness of decision makers and lead to more conservative strategy. - Highlights: • An inexact two-stage stochastic robust programming model for electricity system with wind power penetration. • Uncertainties expressed as discrete intervals and probability distributions. • Demand response program was introduced to adjust the deviation in real-time market. • Financial penalty for imbalance risk from wind power generation was evaluated.

Deadline based scheduling for data-intensive applications in clouds

Institute of Scientific and Technical Information of China (English)

Fu Xiong; Cang Yeliang; Zhu Lipeng; Hu Bin; Deng Song; Wang Dong

2016-01-01

Cloud computing emerges as a new computing pattern that can provide elastic services for any users around the world.It provides good chances to solve large scale scientific problems with fewer efforts.Application deployment remains an important issue in clouds.Appropriate scheduling mechanisms can shorten the total completion time of an application and therefore improve the quality of service (QoS) for cloud users.Unlike current scheduling algorithms which mostly focus on single task allocation,we propose a deadline based scheduling approach for data-intensive applications in clouds.It does not simply consider the total completion time of an application as the sum of all its subtasks' completion time.Not only the computation capacity of virtual machine (VM) is considered,but also the communication delay and data access latencies are taken into account.Simulations show that our proposed approach has a decided advantage over the two other algorithms.

Project Scheduling Heuristics-Based Standard PSO for Task-Resource Assignment in Heterogeneous Grid

Directory of Open Access Journals (Sweden)

Ruey-Maw Chen

2011-01-01

Full Text Available The task scheduling problem has been widely studied for assigning resources to tasks in heterogeneous grid environment. Effective task scheduling is an important issue for the performance of grid computing. Meanwhile, the task scheduling problem is an NP-complete problem. Hence, this investigation introduces a named “standard“ particle swarm optimization (PSO metaheuristic approach to efficiently solve the task scheduling problems in grid. Meanwhile, two promising heuristics based on multimode project scheduling are proposed to help in solving interesting scheduling problems. They are the best performance resource heuristic and the latest finish time heuristic. These two heuristics applied to the PSO scheme are for speeding up the search of the particle and improving the capability of finding a sound schedule. Moreover, both global communication topology and local ring communication topology are also investigated for efficient study of proposed scheme. Simulation results demonstrate that the proposed approach in this investigation can successfully solve the task-resource assignment problems in grid computing and similar scheduling problems.

Cycle 7 outage experience

International Nuclear Information System (INIS)

Gadeken, A.D.

1986-03-01

The scheduled 58-day refueling outage in preparation for the seventh operating cycle of the Fast Flux Test Facility (FFTF) was successfully completed three days ahead of schedule. The planning and execution of the outage was greatly aided by Project/2 automated scheduling capabilities. For example, the use of ''maintenance windows'' and resource loading capabilities was particularly effective. The value of the planning process was demonstrated by the smooth transition into the outage phase after an early shutdown and set the stage for our best outage to date

The operational flight and multi-crew scheduling problem

Directory of Open Access Journals (Sweden)

Stojković Mirela

2005-01-01

Full Text Available This paper introduces a new kind of operational multi-crew scheduling problem which consists in simultaneously modifying, as necessary, the existing flight departure times and planned individual work days (duties for the set of crew members, while respecting predefined aircraft itineraries. The splitting of a planned crew is allowed during a day of operations, where it is more important to cover a flight than to keep planned crew members together. The objective is to cover a maximum number of flights from a day of operations while minimizing changes in both the flight schedule and the next-day planned duties for the considered crew members. A new type of the same flight departure time constraints is introduced. They ensure that a flight which belongs to several personalized duties, where the number of duties is equal to the number of crew members assigned to the flight, will have the same departure time in each of these duties. Two variants of the problem are considered. The first variant allows covering of flights by less than the planned number of crew members, while the second one requires covering of flights by a complete crew. The problem is mathematically formulated as an integer nonlinear multi-commodity network flow model with time windows and supplementary constraints. The optimal solution approach is based on Dantzig-Wolfe decomposition/column generation embedded into a branch-and-bound scheme. The resulting computational times on commercial-size problems are very good. Our new simultaneous approach produces solutions whose quality is far better than that of the traditional sequential approach where the flight schedule has been changed first and then input as a fixed data to the crew scheduling problem.

Sleep duration as a mediator between an alternating day and night shift work schedule and metabolic syndrome among female hospital employees.

Science.gov (United States)

Korsiak, Jill; Tranmer, Joan; Day, Andrew; Aronson, Kristan J

2018-02-01

The main objective was to determine whether sleep duration on work shifts mediates the relationship between a current alternating day and night shift work schedule and metabolic syndrome among female hospital employees. The secondary objective was to assess whether cumulative lifetime shift work exposure was associated with metabolic syndrome. In this cross-sectional study of 294 female hospital employees, sleep duration was measured with the ActiGraph GT3X+. Shift work status was determined through self-report. Investigation of the total, direct and indirect effects between shift work, sleep duration on work shifts and metabolic syndrome was conducted using regression path analysis. Logistic regression was used to determine the association between cumulative shift work exposure and metabolic syndrome. Shift work is strongly associated with metabolic syndrome (OR Total =2.72, 95% CI 1.38 to 5.36), and the relationship is attenuated when work shift sleep duration is added to the model (OR Direct =1.18, 95% CI 0.49 to 2.89). Sleep duration is an important intermediate between shift work and metabolic syndrome (OR Indirect =2.25, 95% CI 1.27 to 4.26). Cumulative shift work exposure is not associated with metabolic syndrome in this population. Sleep duration mediates the association between a current alternating day-night shift work pattern and metabolic syndrome. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

T-L Plane Abstraction-Based Energy-Efficient Real-Time Scheduling for Multi-Core Wireless Sensors

Directory of Open Access Journals (Sweden)

Youngmin Kim

2016-07-01

Full Text Available Energy efficiency is considered as a critical requirement for wireless sensor networks. As more wireless sensor nodes are equipped with multi-cores, there are emerging needs for energy-efficient real-time scheduling algorithms. The T-L plane-based scheme is known to be an optimal global scheduling technique for periodic real-time tasks on multi-cores. Unfortunately, there has been a scarcity of studies on extending T-L plane-based scheduling algorithms to exploit energy-saving techniques. In this paper, we propose a new T-L plane-based algorithm enabling energy-efficient real-time scheduling on multi-core sensor nodes with dynamic power management (DPM. Our approach addresses the overhead of processor mode transitions and reduces fragmentations of the idle time, which are inherent in T-L plane-based algorithms. Our experimental results show the effectiveness of the proposed algorithm compared to other energy-aware scheduling methods on T-L plane abstraction.

Multi-Time Scale Control of Demand Flexibility in Smart Distribution Networks

DEFF Research Database (Denmark)

Bhattarai, Bishnu P.; Myers, Kurt S.; Bak-Jensen, Birgitte

2017-01-01

, and distribution system operator’s perspectives. A hierarchical control architecture (HCA) comprising scheduling, coordinative, and adaptive layers is then designed to realize their coordinative goal. This is realized by integrating multi-time scale controls that work from a day-ahead scheduling up to real-time...... adaptive control. The performance of the developed method is investigated with high EV penetration in a typical residential distribution grid. The simulation results demonstrate that HCA efficiently utilizes demand flexibility stemming from EVs to solve grid unbalancing and congestions with simultaneous...... maximization of economic benefits to the participating actors. This is ensured by enabling EV participation in day-ahead, balancing, and regulation markets. For the given network configuration and pricing structure, HCA ensures the EV owners to get paid up to five times the cost they were paying without...

Assessment and Instruction of Self-Recognition

Science.gov (United States)

Bruce, Susan; Parnell, Elizabeth Pike; Zayyad, Muhammad

2008-01-01

Many teachers of children with disabilities incorporate photographs of people during the school day as part of daily schedules, choice-making, attendance, and turn-taking opportunities. They often hold the expectation that the child with disabilities will be able to discriminate the photographs of others from a self-photograph. It is important to…

Scheduled feeding results in adipogenesis and increased acylated ghrelin

OpenAIRE

Verbaeys, I.; Tolle, V.; SWENNEN, Quirine; Zizzari, P.; Buyse, J.; Epelbaum, J.; Cokelaere, M.

2011-01-01

Ghrelin, known to stimulate adipogenesis, displays an endogenous secretory rhythmicity closely related to meal patterns. Therefore, a chronic imposed feeding schedule might induce modified ghrelin levels and consequently adiposity. Growing Wistar rats were schedule-fed by imposing a particular fixed feeding schedule of 3 meals/day without caloric restriction compared with total daily control intake. After 14 days, their body composition was measured by DEXA and compared with ad libitum-fed co...

Enhanced round robin CPU scheduling with burst time based time quantum

Science.gov (United States)

Indusree, J. R.; Prabadevi, B.

2017-11-01

Process scheduling is a very important functionality of Operating system. The main-known process-scheduling algorithms are First Come First Serve (FCFS) algorithm, Round Robin (RR) algorithm, Priority scheduling algorithm and Shortest Job First (SJF) algorithm. Compared to its peers, Round Robin (RR) algorithm has the advantage that it gives fair share of CPU to the processes which are already in the ready-queue. The effectiveness of the RR algorithm greatly depends on chosen time quantum value. Through this research paper, we are proposing an enhanced algorithm called Enhanced Round Robin with Burst-time based Time Quantum (ERRBTQ) process scheduling algorithm which calculates time quantum as per the burst-time of processes already in ready queue. The experimental results and analysis of ERRBTQ algorithm clearly indicates the improved performance when compared with conventional RR and its variants.

Web-Based Requesting and Scheduling Use of Facilities

Science.gov (United States)

Yeager, Carolyn M.

2010-01-01

Automated User's Training Operations Facility Utilization Request (AutoFUR) is prototype software that administers a Web-based system for requesting and allocating facilities and equipment for astronaut-training classes in conjunction with scheduling the classes. AutoFUR also has potential for similar use in such applications as scheduling flight-simulation equipment and instructors in commercial airplane-pilot training, managing preventive- maintenance facilities, and scheduling operating rooms, doctors, nurses, and medical equipment for surgery. Whereas requesting and allocation of facilities was previously a manual process that entailed examination of documents (including paper drawings) from different sources, AutoFUR partly automates the process and makes all of the relevant information available via the requester s computer. By use of AutoFUR, an instructor can fill out a facility-utilization request (FUR) form on line, consult the applicable flight manifest(s) to determine what equipment is needed and where it should be placed in the training facility, reserve the corresponding hardware listed in a training-hardware inventory database, search for alternative hardware if necessary, submit the FUR for processing, and cause paper forms to be printed. Auto-FUR also maintains a searchable archive of prior FURs.

Hidden power system inflexibilities imposed by traditional unit commitment formulations

International Nuclear Information System (INIS)

Morales-España, Germán; Ramírez-Elizondo, Laura; Hobbs, Benjamin F.

2017-01-01

Highlights: • Quality and accuracy of traditional-energy- and power-based UCs are evaluated. • Real-time performance evaluation simulating “perfect” stochastic UCs. • Ideal energy-based stochastic UC formulations impose hidden system inflexibilities. • A deterministic power-based UC may outperform an ideal energy-based stochastic UC. • Power-based UC overcomes flaws of energy-based UC: lower cost and wind curtailment. - Abstract: Approximations made in traditional day-ahead unit commitment model formulations can result in suboptimal or even infeasible schedules for slow-start units and inaccurate predictions of actual costs and wind curtailment. With increasing wind penetration, these errors will become economically more significant. Here, we consider inaccuracies from three approximations: the use of hourly intervals in which energy production from each generator is modeled as being constant; the disregarding of startup and shutdown energy trajectories; and optimization based on expected wind profiles. The results of unit commitment formulations with those assumptions are compared to models that: (1) use a piecewise-linear power profiles of generation, load and wind, instead of the traditional stepwise energy profiles; (2) consider startup/shutdown trajectories; and (3) include many possible wind trajectories in a stochastic framework. The day-ahead hourly schedules of slow-start generators are then evaluated against actual wind and load profiles using a model real-time dispatch and quick-start unit commitment with a 5 min time step. We find that each simplification usually causes expected generation costs to increase by several percentage points, and results in significant understatement of expected wind curtailment and, in some cases, load interruptions. The inclusion of startup and shutdown trajectories often yielded the largest improvements in schedule performance.

Hour-Ahead Wind Speed and Power Forecasting Using Empirical Mode Decomposition

Directory of Open Access Journals (Sweden)

Ying-Yi Hong

2013-11-01

Full Text Available Operation of wind power generation in a large farm is quite challenging in a smart grid owing to uncertain weather conditions. Consequently, operators must accurately forecast wind speed/power in the dispatch center to carry out unit commitment, real power scheduling and economic dispatch. This work presents a novel method based on the integration of empirical mode decomposition (EMD with artificial neural networks (ANN to forecast the short-term (1 h ahead wind speed/power. First, significant parameters for training the ANN are identified using the correlation coefficients. These significant parameters serve as inputs of the ANN. Owing to the volatile and intermittent wind speed/power, the historical time series of wind speed/power is decomposed into several intrinsic mode functions (IMFs and a residual function through EMD. Each IMF becomes less volatile and therefore increases the accuracy of the neural network. The final forecasting results are achieved by aggregating all individual forecasting results from all IMFs and their corresponding residual functions. Real data related to the wind speed and wind power measured at a wind-turbine generator in Taiwan are used for simulation. The wind speed forecasting and wind power forecasting for the four seasons are studied. Comparative studies between the proposed method and traditional methods (i.e., artificial neural network without EMD, autoregressive integrated moving average (ARIMA, and persistence method are also introduced.

A multi-group and preemptable scheduling of cloud resource based on HTCondor

Science.gov (United States)

Jiang, Xiaowei; Zou, Jiaheng; Cheng, Yaodong; Shi, Jingyan

2017-10-01

Due to the features of virtual machine-flexibility, easy controlling and various system environments, more and more fields utilize the virtualization technology to construct the distributed system with the virtual resources, also including high energy physics. This paper introduce a method used in high energy physics that supports multiple resource group and preemptable cloud resource scheduling, combining virtual machine with HTCondor (a batch system). It makes resource controlling more flexible and more efficient and makes resource scheduling independent of job scheduling. Firstly, the resources belong to different experiment-groups, and the type of user-groups mapping to resource-groups(same as experiment-group) is one-to-one or many-to-one. In order to make the confused group simply to be managed, we designed the permission controlling component to ensure that the different resource-groups can get the suitable jobs. Secondly, for the purpose of elastically allocating resources for suitable resource-group, it is necessary to schedule resources like scheduling jobs. So this paper designs the cloud resource scheduling to maintain a resource queue and allocate an appropriate amount of virtual resources to the request resource-group. Thirdly, in some kind of situations, because of the resource occupied for a long time, resources need to be preempted. This paper adds the preemption function for the resource scheduling that implement resource preemption based on the group priority. Additionally, the way to preempting is soft that when virtual resources are preempted, jobs will not be killed but also be held and rematched later. It is implemented with the help of HTCondor, storing the held job information in scheduler, releasing the job to idle status and doing second matcher. In IHEP (institute of high energy physics), we have built a batch system based on HTCondor with a virtual resources pool based on Openstack. And this paper will show some cases of experiment JUNO

Consensus based scheduling of storage capacities in a virtual microgrid

DEFF Research Database (Denmark)

Brehm, Robert; Top, Søren; Mátéfi-Tempfli, Stefan

2017-01-01

We present a distributed, decentralized method for coordinated scheduling of charge/discharge intervals of storage capacities in a utility grid integrated microgrid. The decentralized algorithm is based on a consensus scheme and solves an optimisation problem with the objective of minimising......, by use of storage capacities, the power flow over a transformer substation from/to the utility grid integrated microgrid. It is shown that when using this coordinated scheduling algorithm, load profile flattening (peak-shaving) for the utility grid is achieved. Additionally, mutual charge...

2007 Wholesale Power Rate Schedules : 2007 General Rate Schedule Provisions.

Energy Technology Data Exchange (ETDEWEB)

United States. Bonneville Power Administration.

2006-11-01

This schedule is available for the contract purchase of Firm Power to be used within the Pacific Northwest (PNW). Priority Firm (PF) Power may be purchased by public bodies, cooperatives, and Federal agencies for resale to ultimate consumers, for direct consumption, and for Construction, Test and Start-Up, and Station Service. Rates in this schedule are in effect beginning October 1, 2006, and apply to purchases under requirements Firm Power sales contracts for a three-year period. The Slice Product is only available for public bodies and cooperatives who have signed Slice contracts for the FY 2002-2011 period. Utilities participating in the Residential Exchange Program (REP) under Section 5(c) of the Northwest Power Act may purchase Priority Firm Power pursuant to the Residential Exchange Program. Rates under contracts that contain charges that escalate based on BPA's Priority Firm Power rates shall be based on the three-year rates listed in this rate schedule in addition to applicable transmission charges. This rate schedule supersedes the PF-02 rate schedule, which went into effect October 1, 2001. Sales under the PF-07 rate schedule are subject to BPA's 2007 General Rate Schedule Provisions (2007 GRSPs). Products available under this rate schedule are defined in the 2007 GRSPs. For sales under this rate schedule, bills shall be rendered and payments due pursuant to BPA's 2007 GRSPs and billing process.

Planning Ahead: Advanced Heart Failure

Science.gov (United States)

... Venous Thromboembolism Aortic Aneurysm More Planning Ahead: Advanced Heart Failure Updated:May 9,2017 An important part of ... Care This content was last reviewed May 2017. Heart Failure • Home • About Heart Failure • Causes and Risks for ...

The Impact of a Rigorous Multiple Work Shift Schedule and Day Versus Night Shift Work on Reaction Time and Balance Performance in Female Nurses: A Repeated Measures Study.

Science.gov (United States)

Thompson, Brennan J; Stock, Matt S; Banuelas, Victoria K; Akalonu, Chibuzo C

2016-07-01

The aim of this study was to determine the impact of a demanding work schedule involving long, cumulative work shifts on response time and balance-related performance outcomes and to evaluate the prevalence of musculoskeletal disorders between day and night shift working nurses. A questionnaire was used to identify the prevalence of past (12-month) and current (7-day) musculoskeletal disorders. Nurses worked three 12-hour work shifts in a 4-day period. Reaction time and balance tests were conducted before and after the work period. The work period induced impairments for reaction time, errors on reaction time tasks, and balance performance, independent of shift type. Musculoskeletal symptom prevalence was high in workers of both work shifts. Compressed work shifts caused performance-based fatigue in nurses. Reaction time and balance tests may be sensitive fatigue identification markers in nurses.

Research on information models for the construction schedule management based on the IFC standard

Directory of Open Access Journals (Sweden)

Weirui Xue

2015-05-01

Full Text Available Purpose: The purpose of this article is to study the description and extension of the Industry Foundation Classes (IFC standard in construction schedule management, which achieves the information exchange and sharing among the different information systems and stakeholders, and facilitates the collaborative construction in the construction projects. Design/methodology/approach: The schedule information processing and coordination are difficult in the complex construction project. Building Information Modeling (BIM provides the platform for exchanging and sharing information among information systems and stakeholders based on the IFC standard. Through analyzing the schedule plan, implementing, check and control, the information flow in the schedule management is reflected based on the IDEF. According to the IFC4, the information model for the schedule management is established, which not only includes the each aspect of the schedule management, but also includes the cost management, the resource management, the quality management and the risk management. Findings: The information requirement for the construction schedule management can be summarized into three aspects: the schedule plan information, the implementing information and the check and control information. The three aspects can be described through the existing and extended entities of IFC4, and the information models are established. Originality/value: The main contribution of the article is to establish the construction schedule management information model, which achieves the information exchange and share in the construction project, and facilitates the development of the application software to meet the requirements of the construction project.

5 CFR 610.406 - Holiday for employees on compressed work schedules.

Science.gov (United States)

2010-01-01

... REGULATIONS HOURS OF DUTY Flexible and Compressed Work Schedules § 610.406 Holiday for employees on compressed work schedules. (a) If a full-time employee is relieved or prevented from working on a day designated... number of hours of the compressed work schedule on that day. (b) If a part-time employee is relieved or...

Traditional/Block Scheduling, Gender, and Test Scores in College Biology Course

Science.gov (United States)

Huelskamp, Diana

2014-01-01

Block scheduling is the reallocation of a school day into longer class sessions to allow for more active teaching strategies and active engagement of students, in the effort to increase student performance. Various types of block scheduling exist. Traditional scheduling is when the school day is divided into six to eight sessions, with each…

A Scheduling Algorithm for Cloud Computing System Based on the Driver of Dynamic Essential Path.

Science.gov (United States)

Xie, Zhiqiang; Shao, Xia; Xin, Yu

2016-01-01

To solve the problem of task scheduling in the cloud computing system, this paper proposes a scheduling algorithm for cloud computing based on the driver of dynamic essential path (DDEP). This algorithm applies a predecessor-task layer priority strategy to solve the problem of constraint relations among task nodes. The strategy assigns different priority values to every task node based on the scheduling order of task node as affected by the constraint relations among task nodes, and the task node list is generated by the different priority value. To address the scheduling order problem in which task nodes have the same priority value, the dynamic essential long path strategy is proposed. This strategy computes the dynamic essential path of the pre-scheduling task nodes based on the actual computation cost and communication cost of task node in the scheduling process. The task node that has the longest dynamic essential path is scheduled first as the completion time of task graph is indirectly influenced by the finishing time of task nodes in the longest dynamic essential path. Finally, we demonstrate the proposed algorithm via simulation experiments using Matlab tools. The experimental results indicate that the proposed algorithm can effectively reduce the task Makespan in most cases and meet a high quality performance objective.

Recommendations to enhance constructivist-based learning in Interprofessional Education using video-based self-assessment

Directory of Open Access Journals (Sweden)

Dahmen, Uta

2016-04-01

Full Text Available Introduction: Interprofessional collaboration is crucial to the optimization of patient care.Aim: This paper aims to provide recommendations for implementing an innovative constructivist educational concept with the core element of video-based self-assessment.Methodology: A course for students in medicine, physiotherapy, and nursing was developed through interprofessional, cross-institutional collaboration. The course consisted of We evaluated the preparation and implementation of the three courses conducted thus far. Concrete recommendations for implementation were made based on evaluation sheets (students, open discussions (tutors, instructors, institutions and recorded meeting minutes (project managers, project participants.Results: Basic recommendations for implementation include: selecting appropriate criteria for self-assessment and a simulated situation that offers members of each professional group an equal opportunity to act in the role play. In terms of administrative implementation we recommend early coordination among the professions and educational institutions regarding the target groups, scheduling and attendance policy to ensure participant recruitment across all professions. Procedural planning should include developing teaching materials, such as the case vignette and treatment scenario, and providing technical equipment that can be operated intuitively in order to ensure efficient recording.Conclusion: These recommendations serve as an aid for implementing an innovative constructivist educational concept with video-based self-assessment at its core.

An Application-Level QoS Control Method Based on Local Bandwidth Scheduling

Directory of Open Access Journals (Sweden)

Yong Wang

2018-01-01

Full Text Available Quality of service (QoS is an important performance indicator for Web applications and bandwidth is a key factor affecting QoS. Current methods use network protocols or ports to schedule bandwidth, which require tedious manual configurations or modifications of the underlying network. Some applications use dynamic ports and the traditional port-based bandwidth control methods cannot deal with them. A new QoS control method based on local bandwidth scheduling is proposed, which can schedule bandwidth at application level in a user-transparent way and it does not require tedious manual configurations. Experimental results indicate that the new method can effectively improve the QoS for applications, and it can be easily integrated into current Web applications without the need to modify the underlying network.

An efficient schedule based data aggregation using node mobility for wireless sensor network

DEFF Research Database (Denmark)

Dnyaneshwar, Mantri; Pawar, Pranav M.; Prasad, Neeli R.

2014-01-01

In the Wireless Sensor Networks, (WSNs) a key challenge is to schedule the activities of the mobile node for improvement in throughput, energy consumption and delay. This paper proposes efficient schedule based data aggregation algorithm using node mobility (SDNM). It considers the cluster...

Coordination between Generation and Transmission Maintenance Scheduling by Means of Multi-agent Technique

Science.gov (United States)

Nagata, Takeshi; Tao, Yasuhiro; Utatani, Masahiro; Sasaki, Hiroshi; Fujita, Hideki

This paper proposes a multi-agent approach to maintenance scheduling in restructured power systems. The restructuring of electric power industry has resulted in market-based approaches for unbundling a multitude of service provided by self-interested entities such as power generating companies (GENCOs), transmission providers (TRANSCOs) and distribution companies (DISCOs). The Independent System Operator (ISO) is responsible for the security of the system operation. The schedule submitted to ISO by GENCOs and TRANSCOs should satisfy security and reliability constraints. The proposed method consists of several GENCO Agents (GAGs), TARNSCO Agents (TAGs) and a ISO Agent(IAG). The IAG’s role in maintenance scheduling is limited to ensuring that the submitted schedules do not cause transmission congestion or endanger the system reliability. From the simulation results, it can be seen the proposed multi-agent approach could coordinate between generation and transmission maintenance schedules.

A new typology of work schedules: Evidence from a cross-sectional study among nurses working in residential elder care.

Science.gov (United States)

Peters, V; de Rijk, A; Engels, J; Heerkens, Y; Nijhuis, F

2016-04-07

Work schedules contribute substantially to the health and well-being of nurses. Too broad typologies are used in research that do not meet the current variety in work schedules. To develop a new typology for nurses' work schedules based on five requirements and to validate the typology. This study is based on a questionnaire returned by 498 nurses (response 51%) including questions regarding nurses' work schedule, socio-demographic, and family characteristics and their appraisal of the work schedule. Frequencies of the different schedules were computed to determine the typology. To validate the typology, differences between the types were tested with ANOVAs, Chi2 and Kruskal-Wallis tests. Five main types can be distinguished based on predetermined requirements and frequencies, namely: (1) fixed early shift, (2) rotating two shift pattern without night shift, (3) rotating three shift pattern, (4) fixed and rotating two shift pattern including night shift, and (5) fixed normal day or afternoon shifts. Nurses in these types of work schedule differed significantly with respect to hours worked, days off between shifts, age, education, years in the job, commuting time, contribution to household income, satisfaction with work schedule and work schedule control. Especially nurses with type 3 schedules differed from other types. A typology of five main types of work schedules is proposed. Content validity of the typology is sufficient and the new typology seems useful for research on work-related aspects of nursing.

Metaheuristic Based Scheduling Meta-Tasks in Distributed Heterogeneous Computing Systems

Directory of Open Access Journals (Sweden)

Hesam Izakian

2009-07-01

Full Text Available Scheduling is a key problem in distributed heterogeneous computing systems in order to benefit from the large computing capacity of such systems and is an NP-complete problem. In this paper, we present a metaheuristic technique, namely the Particle Swarm Optimization (PSO algorithm, for this problem. PSO is a population-based search algorithm based on the simulation of the social behavior of bird flocking and fish schooling. Particles fly in problem search space to find optimal or near-optimal solutions. The scheduler aims at minimizing makespan, which is the time when finishes the latest task. Experimental studies show that the proposed method is more efficient and surpasses those of reported PSO and GA approaches for this problem.

A Bias and Variance Analysis for Multistep-Ahead Time Series Forecasting.

Science.gov (United States)

Ben Taieb, Souhaib; Atiya, Amir F

2016-01-01

Multistep-ahead forecasts can either be produced recursively by iterating a one-step-ahead time series model or directly by estimating a separate model for each forecast horizon. In addition, there are other strategies; some of them combine aspects of both aforementioned concepts. In this paper, we present a comprehensive investigation into the bias and variance behavior of multistep-ahead forecasting strategies. We provide a detailed review of the different multistep-ahead strategies. Subsequently, we perform a theoretical study that derives the bias and variance for a number of forecasting strategies. Finally, we conduct a Monte Carlo experimental study that compares and evaluates the bias and variance performance of the different strategies. From the theoretical and the simulation studies, we analyze the effect of different factors, such as the forecast horizon and the time series length, on the bias and variance components, and on the different multistep-ahead strategies. Several lessons are learned, and recommendations are given concerning the advantages, disadvantages, and best conditions of use of each strategy.

Assessing medical students' self-regulation as aptitude in computer-based learning.

Science.gov (United States)

Song, Hyuksoon S; Kalet, Adina L; Plass, Jan L

2011-03-01

We developed a Self-Regulation Measure for Computer-based learning (SRMC) tailored toward medical students, by modifying Zimmerman's Self-Regulated Learning Interview Schedule (SRLIS) for K-12 learners. The SRMC's reliability and validity were examined in 2 studies. In Study 1, 109 first-year medical students were asked to complete the SRMC. Bivariate correlation analysis results indicated that the SRMC scores had a moderate degree of correlation with student achievement in a teacher-developed test. In Study 2, 58 third-year clerkship students completed the SRMC. Regression analysis results indicated that the frequency of medical students' usage of self-regulation strategies was associated with their general clinical knowledge measured by a nationally standardized licensing exam. These two studies provided evidence for the reliability and concurrent validity of the SRMC to assess medical students' self-regulation as aptitude. Future work should provide evidence to guide and improve instructional design as well as inform educational policy.

Project Robust Scheduling Based on the Scattered Buffer Technology

Directory of Open Access Journals (Sweden)

Nansheng Pang

2018-04-01

Full Text Available The research object in this paper is the sub network formed by the predecessor’s affect on the solution activity. This paper is to study three types of influencing factors from the predecessors that lead to the delay of starting time of the solution activity on the longest path, and to analyze the influence degree on the delay of the solution activity’s starting time from different types of factors. On this basis, through the comprehensive analysis of various factors that influence the solution activity, this paper proposes a metric that is used to evaluate the solution robustness of the project scheduling, and this metric is taken as the optimization goal. This paper also adopts the iterative process to design a scattered buffer heuristics algorithm based on the robust scheduling of the time buffer. At the same time, the resource flow network is introduced in this algorithm, using the tabu search algorithm to solve baseline scheduling. For the generation of resource flow network in the baseline scheduling, this algorithm designs a resource allocation algorithm with the maximum use of the precedence relations. Finally, the algorithm proposed in this paper and some other algorithms in previous literature are taken into the simulation experiment; under the comparative analysis, the experimental results show that the algorithm proposed in this paper is reasonable and feasible.

Adaptive Cost-Based Task Scheduling in Cloud Environment

Directory of Open Access Journals (Sweden)

Mohammed A. S. Mosleh

2016-01-01

Full Text Available Task execution in cloud computing requires obtaining stored data from remote data centers. Though this storage process reduces the memory constraints of the user’s computer, the time deadline is a serious concern. In this paper, Adaptive Cost-based Task Scheduling (ACTS is proposed to provide data access to the virtual machines (VMs within the deadline without increasing the cost. ACTS considers the data access completion time for selecting the cost effective path to access the data. To allocate data access paths, the data access completion time is computed by considering the mean and variance of the network service time and the arrival rate of network input/output requests. Then the task priority is assigned to the removed tasks based data access time. Finally, the cost of data paths are analyzed and allocated based on the task priority. Minimum cost path is allocated to the low priority tasks and fast access path are allocated to high priority tasks as to meet the time deadline. Thus efficient task scheduling can be achieved by using ACTS. The experimental results conducted in terms of execution time, computation cost, communication cost, bandwidth, and CPU utilization prove that the proposed algorithm provides better performance than the state-of-the-art methods.

The intra-day dynamics of affect, self-esteem, tiredness, and suicidality in Major Depression.

Science.gov (United States)

Crowe, Eimear; Daly, Michael; Delaney, Liam; Carroll, Susan; Malone, Kevin M

2018-02-21

Despite growing interest in the temporal dynamics of Major Depressive Disorder (MDD), we know little about the intra-day fluctuations of key symptom constructs. In a study of momentary experience, the Experience Sampling Method captured the within-day dynamics of negative affect, positive affect, self-esteem, passive suicidality, and tiredness across clinical MDD (N= 31) and healthy control groups (N= 33). Ten symptom measures were taken per day over 6 days (N= 2231 observations). Daily dynamics were modeled via intra-day time-trends, variability, and instability in symptoms. MDD participants showed significantly increased variability and instability in negative affect, positive affect, self-esteem, and suicidality. Significantly different time-trends were found in positive affect (increased diurnal variation and an inverted U-shaped pattern in MDD, compared to a positive linear trend in controls) and tiredness (decreased diurnal variation in MDD). In the MDD group only, passive suicidality displayed a negative linear trend and self-esteem displayed a quadratic inverted U trend. MDD and control participants thus showed distinct dynamic profiles in all symptoms measured. As well as the overall severity of symptoms, intra-day dynamics appear to define the experience of MDD symptoms. Copyright © 2018 Elsevier B.V. All rights reserved.

Control and EMS of a Grid-Connected Microgrid with Economical Analysis

Directory of Open Access Journals (Sweden)

Mohamed El-Hendawi

2018-01-01

Full Text Available Recently, significant development has occurred in the field of microgrid and renewable energy systems (RESs. Integrating microgrids and renewable energy sources facilitates a sustainable energy future. This paper proposes a control algorithm and an optimal energy management system (EMS for a grid-connected microgrid to minimize its operating cost. The microgrid includes photovoltaic (PV, wind turbine (WT, and energy storage systems (ESS. The interior search algorithm (ISA optimization technique determines the optimal hour-by-hour scheduling for the microgrid system, while it meets the required load demand based on 24-h ahead forecast data. The control system consists of three stages: EMS, supervisory control and local control. EMS is responsible for providing the control system with the optimum day-ahead scheduling power flow between the microgrid (MG sources, batteries, loads and the main grid based on an economic analysis. The supervisory control stage is responsible for compensating the mismatch between the scheduled power and the real microgrid power. In addition, this paper presents the local control design to regulate the local power, current and DC voltage of the microgrid. For verification, the proposed model was applied on a real case study in Oshawa (Ontario, Canada with various load conditions.

Schedules of Controlled Substances: Temporary Placement of 4-Fluoroisobutyryl Fentanyl into Schedule I. Temporary scheduling order.

Science.gov (United States)

2017-05-03

The Administrator of the Drug Enforcement Administration is issuing this temporary scheduling order to schedule the synthetic opioid, N-(4-fluorophenyl)-N-(1-phenethylpiperidin-4-yl)isobutyramide (4-fluoroisobutyryl fentanyl or para-fluoroisobutyryl fentanyl), and its isomers, esters, ethers, salts and salts of isomers, esters, and ethers, into schedule I pursuant to the temporary scheduling provisions of the Controlled Substances Act. This action is based on a finding by the Administrator that the placement of 4-fluoroisobutyryl fentanyl into schedule I of the Controlled Substances Act is necessary to avoid an imminent hazard to the public safety. As a result of this order, the regulatory controls and administrative, civil, and criminal sanctions applicable to schedule I controlled substances will be imposed on persons who handle (manufacture, distribute, reverse distribute, import, export, engage in research, conduct instructional activities or chemical analysis, or possess), or propose to handle, 4-fluoroisobutyryl fentanyl.

Efficient operation scheduling for adsorption chillers using predictive optimization-based control methods

Science.gov (United States)

Bürger, Adrian; Sawant, Parantapa; Bohlayer, Markus; Altmann-Dieses, Angelika; Braun, Marco; Diehl, Moritz

2017-10-01

Within this work, the benefits of using predictive control methods for the operation of Adsorption Cooling Machines (ACMs) are shown on a simulation study. Since the internal control decisions of series-manufactured ACMs often cannot be influenced, the work focuses on optimized scheduling of an ACM considering its internal functioning as well as forecasts for load and driving energy occurrence. For illustration, an assumed solar thermal climate system is introduced and a system model suitable for use within gradient-based optimization methods is developed. The results of a system simulation using a conventional scheme for ACM scheduling are compared to the results of a predictive, optimization-based scheduling approach for the same exemplary scenario of load and driving energy occurrence. The benefits of the latter approach are shown and future actions for application of these methods for system control are addressed.

Recommendations to enhance constructivist-based learning in Interprofessional Education using video-based self-assessment.

Science.gov (United States)

Dahmen, Uta; Schulze, Christine; Schindler, Claudia; Wick, Katharina; Schwartze, Dominique; Veit, Andrea; Smolenski, Ulrich

2016-01-01

Interprofessional collaboration is crucial to the optimization of patient care. This paper aims to provide recommendations for implementing an innovative constructivist educational concept with the core element of video-based self-assessment. A course for students in medicine, physiotherapy, and nursing was developed through interprofessional, cross-institutional collaboration. The course consisted of drawing on prior knowledge about the work done by each professional group in regard to a specific clinical scenario and an interprofessional treatment situation, filming a role play of this treatment situation, and a structured self-assessment of the role play. We evaluated the preparation and implementation of the three courses conducted thus far. Concrete recommendations for implementation were made based on evaluation sheets (students), open discussions (tutors, instructors, institutions) and recorded meeting minutes (project managers, project participants). Basic recommendations for implementation include: selecting appropriate criteria for self-assessment and a simulated situation that offers members of each professional group an equal opportunity to act in the role play. In terms of administrative implementation we recommend early coordination among the professions and educational institutions regarding the target groups, scheduling and attendance policy to ensure participant recruitment across all professions. Procedural planning should include developing teaching materials, such as the case vignette and treatment scenario, and providing technical equipment that can be operated intuitively in order to ensure efficient recording. These recommendations serve as an aid for implementing an innovative constructivist educational concept with video-based self-assessment at its core.

Gain Scheduling of Observer-Based Controllers with Integral Action

DEFF Research Database (Denmark)

Trangbæk, Klaus; Stoustrup, Jakob; Bendtsen, Jan Dimon

2006-01-01

 This paper presents a method for continuous gain scheduling of  observer-based controllers with integral action. Given two stabilising controllers for a given system, explicit state space formulae are presented, allowing to change gradually from one  controller to the other while preserving...

A preliminary analysis of the reactor-based plutonium disposition alternative deployment schedules

International Nuclear Information System (INIS)

Zurn, R.M.

1997-09-01

This paper discusses the preliminary analysis of the implementation schedules of the reactor-based plutonium disposition alternatives. These schedule analyses are a part of a larger process to examine the nine decision criteria used to determine the most appropriate method of disposing of U.S. surplus weapons plutonium. The preliminary analysis indicates that the mission durations for the reactor-based alternatives range from eleven years to eighteen years and the initial mission fuel assemblies containing surplus weapons-usable plutonium could be loaded into the reactors between nine and fourteen years after the Record of Decision

The application of artificial intelligence to astronomical scheduling problems

Science.gov (United States)

Johnston, Mark D.

1992-01-01

Efficient utilization of expensive space- and ground-based observatories is an important goal for the astronomical community; the cost of modern observing facilities is enormous, and the available observing time is much less than the demand from astronomers around the world. The complexity and variety of scheduling constraints and goals has led several groups to investigate how artificial intelligence (AI) techniques might help solve these kinds of problems. The earliest and most successful of these projects was started at Space Telescope Science Institute in 1987 and has led to the development of the Spike scheduling system to support the scheduling of Hubble Space Telescope (HST). The aim of Spike at STScI is to allocate observations to timescales of days to a week observing all scheduling constraints and maximizing preferences that help ensure that observations are made at optimal times. Spike has been in use operationally for HST since shortly after the observatory was launched in Apr. 1990. Although developed specifically for HST scheduling, Spike was carefully designed to provide a general framework for similar (activity-based) scheduling problems. In particular, the tasks to be scheduled are defined in the system in general terms, and no assumptions about the scheduling timescale are built in. The mechanisms for describing, combining, and propagating temporal and other constraints and preferences are quite general. The success of this approach has been demonstrated by the application of Spike to the scheduling of other satellite observatories: changes to the system are required only in the specific constraints that apply, and not in the framework itself. In particular, the Spike framework is sufficiently flexible to handle both long-term and short-term scheduling, on timescales of years down to minutes or less. This talk will discuss recent progress made in scheduling search techniques, the lessons learned from early HST operations, the application of Spike

Research on logistics scheduling based on PSO

Science.gov (United States)

Bao, Huifang; Zhou, Linli; Liu, Lei

2017-08-01

With the rapid development of e-commerce based on the network, the logistics distribution support of e-commerce is becoming more and more obvious. The optimization of vehicle distribution routing can improve the economic benefit and realize the scientific of logistics [1]. Therefore, the study of logistics distribution vehicle routing optimization problem is not only of great theoretical significance, but also of considerable value of value. Particle swarm optimization algorithm is a kind of evolutionary algorithm, which is based on the random solution and the optimal solution by iteration, and the quality of the solution is evaluated through fitness. In order to obtain a more ideal logistics scheduling scheme, this paper proposes a logistics model based on particle swarm optimization algorithm.

Retail sales of scheduled listed chemical products; self-certification of regulated sellers of scheduled listed chemical products. Interim final rule with request for comment.

Science.gov (United States)

2006-09-26

In March 2006, the President signed the Combat Methamphetamine Epidemic Act of 2005, which establishes new requirements for retail sales of over-the-counter (nonprescription) products containing the List I chemicals ephedrine, pseudoephedrine, and phenylpropanolamine. The three chemicals can be used to manufacture methamphetamine illegally. DEA is promulgating this rule to incorporate the statutory provisions and make its regulations consistent with the new requirements. This action establishes daily and 30-day limits on the sales of scheduled listed chemical products to individuals and requires recordkeeping on most sales.

Designing of vague logic based multilevel feedback queue scheduler

Directory of Open Access Journals (Sweden)

Supriya Raheja

2016-03-01

Full Text Available Multilevel feedback queue scheduler suffers from major issues of scheduling such as starvation for long tasks, fixed number of queues, and static length of time quantum in each queue. These factors directly affect the performance of the scheduler. At many times impreciseness exists in attributes of tasks which make the performance even worse. In this paper, our intent is to improve the performance by providing a solution to these issues. We design a multilevel feedback queue scheduler using a vague set which we call as VMLFQ scheduler. VMLFQ scheduler intelligently handles the impreciseness and defines the optimum number of queues as well as the optimal size of time quantum for each queue. It also resolves the problem of starvation. This paper simulates and analyzes the performance of VMLFQ scheduler with the other multilevel feedback queue techniques using MatLab.

The impact of wind forecast errors on the efficiency of the Ontario electricity market

International Nuclear Information System (INIS)

Ng, H.

2008-01-01

Ontario's Independent System Operator (IESO) is currently involved in a number of wind projects in the province, and has developed both a resource commitment and dispatch timeline in relation to increased wind power penetration in the Ontario electricity grid. This presentation discussed the impacts of wind forecast errors on the province's electricity market. Day-ahead planning is used to commit fossil fuels and gas resources, while 3-hours ahead planning is used to commit generation in real time. Inter-ties are committed 1 hour ahead of dispatch. Over-forecasts for wind can cause market prices to increase in real-time, or cause markets to miss opportunities to schedule cheaper imports. The inefficient scheduling caused by overforecasts can also lead to exports not being purchases at high enough prices. Under-forecasts can cause market prices to decrease, and may cause imports to be scheduled that would not have been economic at lower prices. The scheduling difficulties related to under-forecasting can cause markets to miss opportunities to schedule efficient exports. Wind facility forecast errors typically improve closer to real-time. One-hour ahead wind forecast errors can reach approximately 12 per cent. The annual costs of overforecasting are under $200,000. Underforecasting costs are usually less than $30,000. The costs of the wind forecasting inefficiencies are relatively small in the $10 billion electricity market. It was concluded that system operators will continue to track forecast errors and inefficiencies as wind power capacity in the electric power industry increases. tabs., figs

How do employees prioritise when they schedule their own shifts?

Science.gov (United States)

Nabe-Nielsen, Kirsten; Lund, Henrik; Ajslev, Jeppe Z; Hansen, Åse Marie; Albertsen, Karen; Hvid, Helge; Garde, Anne Helene

2013-01-01

We investigated how employees prioritised when they scheduled their own shifts and whether priorities depended on age, gender, educational level, cohabitation and health status. We used cross-sectional questionnaire data from the follow-up survey of an intervention study investigating the effect of self-scheduling (n = 317). Intervention group participants were asked about their priorities when scheduling their own shifts succeeded by 17 items covering family/private life, economy, job content, health and sleep. At least half of the participants reported that they were giving high priority to their family life, having consecutive time off, leisure-time activities, rest between shifts, sleep, regularity of their everyday life, health and that the work schedule balanced. Thus, employees consider both their own and the workplace's needs when they have the opportunity to schedule their own shifts. Age, gender, cohabitation and health status were all significantly associated with at least one of these priorities. Intervention studies report limited health effects of self-scheduling. Therefore, we investigated to what extent employees prioritise their health and recuperation when scheduling their own shifts. We found that employees not only consider both their health and family but also the workplace's needs when they schedule their own shifts.

Intermittent Metronomic Drug Schedule Is Essential for Activating Antitumor Innate Immunity and Tumor Xenograft Regression

Directory of Open Access Journals (Sweden)

Chong-Sheng Chen

2014-01-01

Full Text Available Metronomic chemotherapy using cyclophosphamide (CPA is widely associated with antiangiogenesis; however, recent studies implicate other immune-based mechanisms, including antitumor innate immunity, which can induce major tumor regression in implanted brain tumor models. This study demonstrates the critical importance of drug schedule: CPA induced a potent antitumor innate immune response and tumor regression when administered intermittently on a 6-day repeating metronomic schedule but not with the same total exposure to activated CPA administered on an every 3-day schedule or using a daily oral regimen that serves as the basis for many clinical trials of metronomic chemotherapy. Notably, the more frequent metronomic CPA schedules abrogated the antitumor innate immune and therapeutic responses. Further, the innate immune response and antitumor activity both displayed an unusually steep dose-response curve and were not accompanied by antiangiogenesis. The strong recruitment of innate immune cells by the 6-day repeating CPA schedule was not sustained, and tumor regression was abolished, by a moderate (25% reduction in CPA dose. Moreover, an ~20% increase in CPA dose eliminated the partial tumor regression and weak innate immune cell recruitment seen in a subset of the every 6-day treated tumors. Thus, metronomic drug treatment must be at a sufficiently high dose but also sufficiently well spaced in time to induce strong sustained antitumor immune cell recruitment. Many current clinical metronomic chemotherapeutic protocols employ oral daily low-dose schedules that do not meet these requirements, suggesting that they may benefit from optimization designed to maximize antitumor immune responses.

Day-ahead load forecast using random forest and expert input selection

International Nuclear Information System (INIS)

Lahouar, A.; Ben Hadj Slama, J.

2015-01-01

Highlights: • A model based on random forests for short term load forecast is proposed. • An expert feature selection is added to refine inputs. • Special attention is paid to customers behavior, load profile and special holidays. • The model is flexible and able to handle complex load signal. • A technical comparison is performed to assess the forecast accuracy. - Abstract: The electrical load forecast is getting more and more important in recent years due to the electricity market deregulation and integration of renewable resources. To overcome the incoming challenges and ensure accurate power prediction for different time horizons, sophisticated intelligent methods are elaborated. Utilization of intelligent forecast algorithms is among main characteristics of smart grids, and is an efficient tool to face uncertainty. Several crucial tasks of power operators such as load dispatch rely on the short term forecast, thus it should be as accurate as possible. To this end, this paper proposes a short term load predictor, able to forecast the next 24 h of load. Using random forest, characterized by immunity to parameter variations and internal cross validation, the model is constructed following an online learning process. The inputs are refined by expert feature selection using a set of if–then rules, in order to include the own user specifications about the country weather or market, and to generalize the forecast ability. The proposed approach is tested through a real historical set from the Tunisian Power Company, and the simulation shows accurate and satisfactory results for one day in advance, with an average error exceeding rarely 2.3%. The model is validated for regular working days and weekends, and special attention is paid to moving holidays, following non Gregorian calendar

One-Step-Ahead Predictive Control for Hydroturbine Governor

Directory of Open Access Journals (Sweden)

Zhihuai Xiao

2015-01-01

Full Text Available The hydroturbine generator regulating system can be considered as one system synthetically integrating water, machine, and electricity. It is a complex and nonlinear system, and its configuration and parameters are time-dependent. A one-step-ahead predictive control based on on-line trained neural networks (NNs for hydroturbine governor with variation in gate position is described in this paper. The proposed control algorithm consists of a one-step-ahead neuropredictor that tracks the dynamic characteristics of the plant and predicts its output and a neurocontroller to generate the optimal control signal. The weights of two NNs, initially trained off-line, are updated on-line according to the scalar error. The proposed controller can thus track operating conditions in real-time and produce the optimal control signal over the wide operating range. Only the inputs and outputs of the generator are measured and there is no need to determine the other states of the generator. Simulations have been performed with varying operating conditions and different disturbances to compare the performance of the proposed controller with that of a conventional PID controller and validate the feasibility of the proposed approach.

Multisensors Cooperative Detection Task Scheduling Algorithm Based on Hybrid Task Decomposition and MBPSO

Directory of Open Access Journals (Sweden)

Changyun Liu

2017-01-01

Full Text Available A multisensor scheduling algorithm based on the hybrid task decomposition and modified binary particle swarm optimization (MBPSO is proposed. Firstly, aiming at the complex relationship between sensor resources and tasks, a hybrid task decomposition method is presented, and the resource scheduling problem is decomposed into subtasks; then the sensor resource scheduling problem is changed into the match problem of sensors and subtasks. Secondly, the resource match optimization model based on the sensor resources and tasks is established, which considers several factors, such as the target priority, detecting benefit, handover times, and resource load. Finally, MBPSO algorithm is proposed to solve the match optimization model effectively, which is based on the improved updating means of particle’s velocity and position through the doubt factor and modified Sigmoid function. The experimental results show that the proposed algorithm is better in terms of convergence velocity, searching capability, solution accuracy, and efficiency.

Simulation-Based Dynamic Passenger Flow Assignment Modelling for a Schedule-Based Transit Network

Directory of Open Access Journals (Sweden)

Xiangming Yao

2017-01-01

Full Text Available The online operation management and the offline policy evaluation in complex transit networks require an effective dynamic traffic assignment (DTA method that can capture the temporal-spatial nature of traffic flows. The objective of this work is to propose a simulation-based dynamic passenger assignment framework and models for such applications in the context of schedule-based rail transit systems. In the simulation framework, travellers are regarded as individual agents who are able to obtain complete information on the current traffic conditions. A combined route selection model integrated with pretrip route selection and entrip route switch is established for achieving the dynamic network flow equilibrium status. The train agent is operated strictly with the timetable and its capacity limitation is considered. A continuous time-driven simulator based on the proposed framework and models is developed, whose performance is illustrated through a large-scale network of Beijing subway. The results indicate that more than 0.8 million individual passengers and thousands of trains can be simulated simultaneously at a speed ten times faster than real time. This study provides an efficient approach to analyze the dynamic demand-supply relationship for large schedule-based transit networks.

Cultural-Based Genetic Tabu Algorithm for Multiobjective Job Shop Scheduling

Directory of Open Access Journals (Sweden)

Yuzhen Yang

2014-01-01

Full Text Available The job shop scheduling problem, which has been dealt with by various traditional optimization methods over the decades, has proved to be an NP-hard problem and difficult in solving, especially in the multiobjective field. In this paper, we have proposed a novel quadspace cultural genetic tabu algorithm (QSCGTA to solve such problem. This algorithm provides a different structure from the original cultural algorithm in containing double brief spaces and population spaces. These spaces deal with different levels of populations globally and locally by applying genetic and tabu searches separately and exchange information regularly to make the process more effective towards promising areas, along with modified multiobjective domination and transform functions. Moreover, we have presented a bidirectional shifting for the decoding process of job shop scheduling. The computational results we presented significantly prove the effectiveness and efficiency of the cultural-based genetic tabu algorithm for the multiobjective job shop scheduling problem.

Information Flow Scheduling in Concurrent Multi-Product Development Based on DSM

Science.gov (United States)

Sun, Qing-Chao; Huang, Wei-Qiang; Jiang, Ying-Jie; Sun, Wei

2017-09-01

Multi-product collaborative development is adopted widely in manufacturing enterprise, while the present multi-project planning models don't take technical/data interactions of multiple products into account. To decrease the influence of technical/data interactions on project progresses, the information flow scheduling models based on the extended DSM is presented. Firstly, information dependencies are divided into four types: series, parallel, coupling and similar. Secondly, different types of dependencies are expressed as DSM units, and the extended DSM model is brought forward, described as a block matrix. Furthermore, the information flow scheduling methods is proposed, which involves four types of operations, where partitioning and clustering algorithm are modified from DSM for ensuring progress of high-priority project, merging and converting is the specific computation of the extended DSM. Finally, the information flow scheduling of two machine tools development is analyzed with example, and different project priorities correspond to different task sequences and total coordination cost. The proposed methodology provides a detailed instruction for information flow scheduling in multi-product development, with specially concerning technical/data interactions.

Proportional fair scheduling algorithm based on traffic in satellite communication system

Science.gov (United States)

Pan, Cheng-Sheng; Sui, Shi-Long; Liu, Chun-ling; Shi, Yu-Xin

2018-02-01

In the satellite communication network system, in order to solve the problem of low system capacity and user fairness in multi-user access to satellite communication network in the downlink, combined with the characteristics of user data service, an algorithm study on throughput capacity and user fairness scheduling is proposed - Proportional Fairness Algorithm Based on Traffic(B-PF). The algorithm is improved on the basis of the proportional fairness algorithm in the wireless communication system, taking into account the user channel condition and caching traffic information. The user outgoing traffic is considered as the adjustment factor of the scheduling priority and presents the concept of traffic satisfaction. Firstly,the algorithm calculates the priority of the user according to the scheduling algorithm and dispatches the users with the highest priority. Secondly, when a scheduled user is the business satisfied user, the system dispatches the next priority user. The simulation results show that compared with the PF algorithm, B-PF can improve the system throughput, the business satisfaction and fairness.

A Frequency-Based Assignment Model under Day-to-Day Information Evolution of Oversaturated Conditions on a Feeder Bus Service

Directory of Open Access Journals (Sweden)

Silin Zhang

2017-02-01

Full Text Available Day-to-day information is increasingly being implemented in transit networks worldwide. Feeder bus service (FBS plays a vital role in a public transit network by providing feeder access to hubs and rails. As a feeder service, a space-time path for frequent passengers is decided by its dynamic strategy procedure, in which a day-to-day information self-learning mechanism is identified and analyzed from our survey data. We formulate a frequency-based assignment model considering day-to-day evolution under oversaturated conditions, which takes into account the residual capacity of bus and the comfort feelings of sitting or standing. The core of our proposed model is to allocate the passengers on each segment belonging to their own paths according to multi-utilities transformed from the time values and parametric demands, such as frequency, bus capacity, seat comfort, and stop layout. The assignment method, albeit general, allows us to formulate an equivalent optimization problem in terms of interaction between the FBS’ operation and frequent passengers’ rational behaviors. Finally, a real application case is generated to test the ability of the modeling framework capturing the theoretical consequents, serving the passengers’ dynamic externalities.

Water requirement and irrigation schedule for tomato in northern guinea savanna zone, Nigeria

Directory of Open Access Journals (Sweden)

Ibraheem Alhassan

2015-06-01

Full Text Available Assessment of water requirement and irrigation schedule for tomato with the support of FAO-CROPWAT simulation model was carried out for Yola, Nigeria with the aim of planning irrigation schedules for tomato and develop recommendations for improve irrigation practices. The climatic data for 2012/2013 and soil properties of the study area were input into the program. Tomato crop properties were updated by the FAO data and three irrigation intervals were tested (7 and 10 days irrigation intervals and irrigation schedule of 10 days interval during initial and development stage and 6 days interval at mid and late season stages of tomato crop. The simulated results analysis for tomato according to the irrigation schedule showed that highest yield reduction of 16.2% was recorded with 10 days irrigation interval treatment and the least of 0.4% with irrigation interval of 10 days at first two growth stages and 6 days at last two stages. FAO-CROPWAT 8.0 can be used in planning proper irrigation schedule for tomato in Yola, Nigeria.

A One-Step-Ahead Smoothing-Based Joint Ensemble Kalman Filter for State-Parameter Estimation of Hydrological Models

KAUST Repository

El Gharamti, Mohamad

2015-11-26

The ensemble Kalman filter (EnKF) recursively integrates field data into simulation models to obtain a better characterization of the model’s state and parameters. These are generally estimated following a state-parameters joint augmentation strategy. In this study, we introduce a new smoothing-based joint EnKF scheme, in which we introduce a one-step-ahead smoothing of the state before updating the parameters. Numerical experiments are performed with a two-dimensional synthetic subsurface contaminant transport model. The improved performance of the proposed joint EnKF scheme compared to the standard joint EnKF compensates for the modest increase in the computational cost.

Experiences with Implementing a Distributed and Self-Organizing Scheduling Algorithm for Energy-Efficient Data Gathering on a Real-Life Sensor Network Platform

NARCIS (Netherlands)

Zhang, Y.; Chatterjea, Supriyo; Havinga, Paul J.M.

2007-01-01

We report our experiences with implementing a distributed and self-organizing scheduling algorithm designed for energy-efficient data gathering on a 25-node multihop wireless sensor network (WSN). The algorithm takes advantage of spatial correlations that exist in readings of adjacent sensor nodes

Survival, Look-Ahead Bias and the Persistence in Hedge Fund Performance

NARCIS (Netherlands)

G. Baquero; J.R. ter Horst (Jenke); M.J.C.M. Verbeek (Marno)

2005-01-01

textabstractWe analyze the performance persistence in hedge funds taking into account look-ahead bias (multi-period sampling bias). We model liquidation of hedge funds by analyzing how it depends upon historical performance. Next, we use a weighting procedure that eliminates look-ahead bias in

A review of metaheuristic scheduling techniques in cloud computing

Directory of Open Access Journals (Sweden)

Mala Kalra

2015-11-01

Full Text Available Cloud computing has become a buzzword in the area of high performance distributed computing as it provides on-demand access to shared pool of resources over Internet in a self-service, dynamically scalable and metered manner. Cloud computing is still in its infancy, so to reap its full benefits, much research is required across a broad array of topics. One of the important research issues which need to be focused for its efficient performance is scheduling. The goal of scheduling is to map tasks to appropriate resources that optimize one or more objectives. Scheduling in cloud computing belongs to a category of problems known as NP-hard problem due to large solution space and thus it takes a long time to find an optimal solution. There are no algorithms which may produce optimal solution within polynomial time to solve these problems. In cloud environment, it is preferable to find suboptimal solution, but in short period of time. Metaheuristic based techniques have been proved to achieve near optimal solutions within reasonable time for such problems. In this paper, we provide an extensive survey and comparative analysis of various scheduling algorithms for cloud and grid environments based on three popular metaheuristic techniques: Ant Colony Optimization (ACO, Genetic Algorithm (GA and Particle Swarm Optimization (PSO, and two novel techniques: League Championship Algorithm (LCA and BAT algorithm.

Full STEAM Ahead: From Earth to Ploonoids

Science.gov (United States)

Runyon, C. R.; Hall, C.; Blackman, C. L.; Royle, M.; Williams, M. N.

2015-12-01

What the heck is a plunoid, you ask? The NASA Solar System Exploration Research Virtual Institute's Education/Public Engagement (EPE) program,from two SSERVI teams (SEEED at Brown/MIT and CLASS at University of Central Florida), is moving full STEAM ahead, engaging the public in the exciting discoveries being made around small bodies, including PLanetary mOONs and asterOIDS (i.e ploonoids). The team has incorporated the arts, from visual representations, storytelling, and music into every facet of the program, to stimulate an affective and personal connection to the content. This past year, the SSERVI STEAM team has participated in numerous public science events, including International Observe the Moon Night, two Astronomy Nights at a local baseball venue, Dark Skies at the US and Canadian National Parks, and Space Day at Camp Happy Days, a camp for children with cancer. Through these events, the team reached over 10000 members of the general public, showcasing current NASA SSERVI research, dispelling myths about our landing and exploring the moon, demonstrating the excitement of STEM through hands-on interactive displays, and providing an outlet for creativity by having multiple ways of representing and explaining scientific information through the arts. Join us on our "ed"venture through the solar system ploonoids.

Need yellow fever vaccine? Plan ahead

Science.gov (United States)

... Submit What's this? Submit Button Past Emails Need yellow fever vaccine? Plan ahead. Language: English (US) Español (Spanish) ... none were from the United States). What is yellow fever? Yellow fever is caused by a virus that ...

Eating meals before wheel-running exercise attenuate high fat diet-driven obesity in mice under two meals per day schedule.

Science.gov (United States)

Sasaki, Hiroyuki; Hattori, Yuta; Ikeda, Yuko; Kamagata, Mayo; Shibata, Shigenobu

2015-06-01

Mice that exercise after meals gain less body weight and visceral fat compared to those that exercised before meals under a one meal/exercise time per day schedule. Humans generally eat two or three meals per day, and rarely have only one meal. To extend our previous observations, we examined here whether a "two meals, two exercise sessions per day" schedule was optimal in terms of maintaining a healthy body weight. In this experiment, "morning" refers to the beginning of the active phase (the "morning" for nocturnal animals). We found that 2-h feeding before 2-h exercise in the morning and evening (F-Ex/F-Ex) resulted in greater attenuation of high fat diet (HFD)-induced weight gain compared to other combinations of feeding and exercise under two daily meals and two daily exercise periods. There were no significant differences in total food intake and total wheel counts, but feeding before exercise in the morning groups (F-Ex/F-Ex and F-Ex/Ex-F) increased the morning wheel counts. These results suggest that habitual exercise after feeding in the morning and evening is more effective for preventing HFD-induced weight gain. We also determined whether there were any correlations between food intake, wheel rotation, visceral fat volume and skeletal muscle volumes. We found positive associations between gastrocnemius muscle volumes and morning wheel counts, as well as negative associations between morning food intake volumes/body weight and morning wheel counts. These results suggest that morning exercise-induced increase of muscle volume may refer to anti-obesity. Evening exercise is negatively associated with fat volume increases, suggesting that this practice may counteract fat deposition. Our multifactorial analysis revealed that morning food intake helps to increase exercise, and that evening exercise reduced fat volumes. Thus, exercise in the morning or evening is important for preventing the onset of obesity.

Intelligent Scheduling of a Grid-Connected Heat Pump in a Danish Detached House

DEFF Research Database (Denmark)

Gianniou, Panagiota; Foteinaki, Kyriaki; Heller, Alfred

This study proposes a methodology for intelligent scheduling of a heat pump installed in a refurbished grid-connected detached house in Denmark. This scheduling is conducted through the coupling of a dynamic building simulation tool with an optimization tool. The optimization of the operation of ...... thermal comfort conditions. The proposed methodology bridges dynamic building modelling with optimization of real-time operation of HVAC systems offering a detailed model for building physics, especially regarding thermal mass and a stochastic price-based control....... of the system is based on a price-signal considering a three-day period for different weather cases. The results show that the optimal scheduling of the system is successful in terms of reducing the peak load during times when electricity prices are high, thus achieving cost savings as well as maintaining good......This study proposes a methodology for intelligent scheduling of a heat pump installed in a refurbished grid-connected detached house in Denmark. This scheduling is conducted through the coupling of a dynamic building simulation tool with an optimization tool. The optimization of the operation...

33 CFR 164.76 - Towline and terminal gear for towing alongside and pushing ahead.

Science.gov (United States)

2010-07-01

... towing alongside and pushing ahead. 164.76 Section 164.76 Navigation and Navigable Waters COAST GUARD... Towline and terminal gear for towing alongside and pushing ahead. The owner, master, or operator of each vessel towing alongside or pushing ahead shall ensure that the face wires, spring lines, and push gear...

A Hybrid Node Scheduling Approach Based on Energy Efficient Chain Routing for WSN

Directory of Open Access Journals (Sweden)

Yimei Kang

2014-04-01

Full Text Available Energy efficiency is usually a significant goal in wireless sensor networks (WSNs. In this work, an energy efficient chain (EEC data routing approach is first presented. The coverage and connectivity of WSNs are discussed based on EEC. A hybrid node scheduling approach is then proposed. It includes sleep scheduling for cyclically monitoring regions of interest in time-driven modes and wakeup scheduling for tracking emergency events in event-driven modes. A failure rate is introduced to the sleep scheduling to improve the reliability of the system. A wakeup sensor threshold and a sleep time threshold are introduced in the wakeup scheduling to reduce the consumption of energy to the possible extent. The results of the simulation show that the proposed algorithm can extend the effective lifetime of the network to twice that of PEAS. In addition, the proposed methods are computing efficient because they are very simple to implement.

Alternative Work Schedules in Office and Nonoffice Work Settings.

Science.gov (United States)

Kirk, Raymond J.; Barton, H. David

A rapidly growing change in the workplace is the replacement of a fixed work schedule with a variety of alternative work schedules (AWS), including both flexible and compressed schedules. Experimenting organizations (N=901) evaluated one of four major categories of AWS in office and nonoffice settings, i.e., a flexible 8-hour day;…

A genetic algorithm-based job scheduling model for big data analytics.

Science.gov (United States)

Lu, Qinghua; Li, Shanshan; Zhang, Weishan; Zhang, Lei

Big data analytics (BDA) applications are a new category of software applications that process large amounts of data using scalable parallel processing infrastructure to obtain hidden value. Hadoop is the most mature open-source big data analytics framework, which implements the MapReduce programming model to process big data with MapReduce jobs. Big data analytics jobs are often continuous and not mutually separated. The existing work mainly focuses on executing jobs in sequence, which are often inefficient and consume high energy. In this paper, we propose a genetic algorithm-based job scheduling model for big data analytics applications to improve the efficiency of big data analytics. To implement the job scheduling model, we leverage an estimation module to predict the performance of clusters when executing analytics jobs. We have evaluated the proposed job scheduling model in terms of feasibility and accuracy.

Hypergraph+: An Improved Hypergraph-Based Task-Scheduling Algorithm for Massive Spatial Data Processing on Master-Slave Platforms

Directory of Open Access Journals (Sweden)

Bo Cheng

2016-08-01

Full Text Available Spatial data processing often requires massive datasets, and the task/data scheduling efficiency of these applications has an impact on the overall processing performance. Among the existing scheduling strategies, hypergraph-based algorithms capture the data sharing pattern in a global way and significantly reduce total communication volume. Due to heterogeneous processing platforms, however, single hypergraph partitioning for later scheduling may be not optimal. Moreover, these scheduling algorithms neglect the overlap between task execution and data transfer that could further decrease execution time. In order to address these problems, an extended hypergraph-based task-scheduling algorithm, named Hypergraph+, is proposed for massive spatial data processing. Hypergraph+ improves upon current hypergraph scheduling algorithms in two ways: (1 It takes platform heterogeneity into consideration offering a metric function to evaluate the partitioning quality in order to derive the best task/file schedule; and (2 It can maximize the overlap between communication and computation. The GridSim toolkit was used to evaluate Hypergraph+ in an IDW spatial interpolation application on heterogeneous master-slave platforms. Experiments illustrate that the proposed Hypergraph+ algorithm achieves on average a 43% smaller makespan than the original hypergraph scheduling algorithm but still preserves high scheduling efficiency.

A risk-based approach to scheduling audits.

Science.gov (United States)

Rönninger, Stephan; Holmes, Malcolm

2009-01-01

The manufacture and supply of pharmaceutical products can be a very complex operation. Companies may purchase a wide variety of materials, from active pharmaceutical ingredients to packaging materials, from "in company" suppliers or from third parties. They may also purchase or contract a number of services such as analysis, data management, audit, among others. It is very important that these materials and services are of the requisite quality in order that patient safety and company reputation are adequately protected. Such quality requirements are ongoing throughout the product life cycle. In recent years, assurance of quality has been derived via audit of the supplier or service provider and by using periodic audits, for example, annually or at least once every 5 years. In the past, companies may have used an audit only for what they considered to be "key" materials or services and used testing on receipt, for example, as their quality assurance measure for "less important" supplies. Such approaches changed as a result of pressure from both internal sources and regulators to the time-driven audit for all suppliers and service providers. Companies recognised that eventually they would be responsible for the quality of the supplied product or service and audit, although providing only a "snapshot in time" seemed a convenient way of demonstrating that they were meeting their obligations. Problems, however, still occur with the supplied product or service and will usually be more frequent from certain suppliers. Additionally, some third-party suppliers will no longer accept routine audits from individual companies, as the overall audit load can exceed one external audit per working day. Consequently a different model is needed for assessing supplier quality. This paper presents a risk-based approach to creating an audit plan and for scheduling the frequency and depth of such audits. The approach is based on the principles and process of the Quality Risk Management

Cost effective shift schedules enhance utility operations

International Nuclear Information System (INIS)

Coleman, R.M.

1995-01-01

This article describes how new shift scheduling concepts can save utility operations millions of dollars every year and yet maintain safety and improve employee morale. The key to scheduling is to define and match the work load. This includes discretionary as well as daily, weekly, and yearly core work loads. In most power plants the overall work load (including maintenance, operations, materials handling, etc.) on day shift is greater than on other shifts, hence an unbalanced schedule would be appropriate

Heuristic algorithm for single resource constrained project scheduling problem based on the dynamic programming

Directory of Open Access Journals (Sweden)

Stanimirović Ivan

2009-01-01

Full Text Available We introduce a heuristic method for the single resource constrained project scheduling problem, based on the dynamic programming solution of the knapsack problem. This method schedules projects with one type of resources, in the non-preemptive case: once started an activity is not interrupted and runs to completion. We compare the implementation of this method with well-known heuristic scheduling method, called Minimum Slack First (known also as Gray-Kidd algorithm, as well as with Microsoft Project.

Simulated Annealing-Based Ant Colony Algorithm for Tugboat Scheduling Optimization

Directory of Open Access Journals (Sweden)

Qi Xu

2012-01-01

Full Text Available As the “first service station” for ships in the whole port logistics system, the tugboat operation system is one of the most important systems in port logistics. This paper formulated the tugboat scheduling problem as a multiprocessor task scheduling problem (MTSP after analyzing the characteristics of tugboat operation. The model considers factors of multianchorage bases, different operation modes, and three stages of operations (berthing/shifting-berth/unberthing. The objective is to minimize the total operation times for all tugboats in a port. A hybrid simulated annealing-based ant colony algorithm is proposed to solve the addressed problem. By the numerical experiments without the shifting-berth operation, the effectiveness was verified, and the fact that more effective sailing may be possible if tugboats return to the anchorage base timely was pointed out; by the experiments with the shifting-berth operation, one can see that the objective is most sensitive to the proportion of the shifting-berth operation, influenced slightly by the tugboat deployment scheme, and not sensitive to the handling operation times.

Study on Cloud Computing Resource Scheduling Strategy Based on the Ant Colony Optimization Algorithm

OpenAIRE

Lingna He; Qingshui Li; Linan Zhu

2012-01-01

In order to replace the traditional Internet software usage patterns and enterprise management mode, this paper proposes a new business calculation mode- cloud computing, resources scheduling strategy is the key technology in cloud computing, Based on the study of cloud computing system structure and the mode of operation, The key research for cloud computing the process of the work scheduling and resource allocation problems based on ant colony algorithm , Detailed analysis and design of the...

Multi-day activity scheduling reactions to planned activities and future events in a dynamic agent-based model of activity-travel behavior

NARCIS (Netherlands)

Nijland, E.W.L.; Arentze, T.A.; Timmermans, H.J.P.

2009-01-01

Modeling multi-day planning has received scarce attention today in activity-based transport demand modeling. Elaborating and combining previous work on event-driven activity generation, the aim of this paper is to develop and illustrate an extension of a need-based model of activity generation that

Resource management and scheduling policy based on grid for AIoT

Science.gov (United States)

Zou, Yiqin; Quan, Li

2017-07-01

This paper has a research on resource management and scheduling policy based on grid technology for Agricultural Internet of Things (AIoT). Facing the situation of a variety of complex and heterogeneous agricultural resources in AIoT, it is difficult to represent them in a unified way. But from an abstract perspective, there are some common models which can express their characteristics and features. Based on this, we proposed a high-level model called Agricultural Resource Hierarchy Model (ARHM), which can be used for modeling various resources. It introduces the agricultural resource modeling method based on this model. Compared with traditional application-oriented three-layer model, ARHM can hide the differences of different applications and make all applications have a unified interface layer and be implemented without distinction. Furthermore, it proposes a Web Service Resource Framework (WSRF)-based resource management method and the encapsulation structure for it. Finally, it focuses on the discussion of multi-agent-based AG resource scheduler, which is a collaborative service provider pattern in multiple agricultural production domains.

Adherence to self-monitoring healthy lifestyle behaviours through mobile phone-based ecological momentary assessments and photographic food records over 6 months in mostly ethnic minority mothers.

Science.gov (United States)

Comulada, W Scott; Swendeman, Dallas; Koussa, Maryann K; Mindry, Deborah; Medich, Melissa; Estrin, Deborah; Mercer, Neil; Ramanathan, Nithya

2018-03-01

Mobile phones can replace traditional self-monitoring tools through cell phone-based ecological momentary assessment (CEMA) of lifestyle behaviours and camera phone-based images of meals, i.e. photographic food records (PFR). Adherence to mobile self-monitoring needs to be evaluated in real-world treatment settings. Towards this goal, we examine CEMA and PFR adherence to the use of a mobile app designed to help mothers self-monitor lifestyle behaviours and stress. Design/Setting In 2012, forty-two mothers recorded CEMA of diet quality, exercise, sleep, stress and mood four times daily and PFR during meals over 6 months in Los Angeles, California, USA. A purposive sample of mothers from mixed ethnicities. Adherence to recording CEMA at least once daily was higher compared with recording PFR at least once daily over the study period (74 v. 11 %); adherence to both types of reports decreased over time. Participants who recorded PFR for more than a day (n 31) were more likely to be obese v. normal- to overweight and to have higher blood pressure, on average (all P<0·05). Based on random-effects regression, CEMA and PFR adherence was highest during weekdays (both P<0·01). Additionally, PFR adherence was associated with older age (P=0·04). CEMA adherence was highest in the morning (P<0·01). PFR recordings occurred throughout the day. Variations in population and temporal characteristics should be considered for mobile assessment schedules. Neither CEMA nor PFR alone is ideal over extended periods.

Automated Scheduling Via Artificial Intelligence

Science.gov (United States)

Biefeld, Eric W.; Cooper, Lynne P.

1991-01-01

Artificial-intelligence software that automates scheduling developed in Operations Mission Planner (OMP) research project. Software used in both generation of new schedules and modification of existing schedules in view of changes in tasks and/or available resources. Approach based on iterative refinement. Although project focused upon scheduling of operations of scientific instruments and other equipment aboard spacecraft, also applicable to such terrestrial problems as scheduling production in factory.

Learning to stay ahead of time

DEFF Research Database (Denmark)

Staunæs, Dorthe; Raffnsøe, Sverre

2014-01-01

In the context of an ongoing change, management is required to take the form of a leadership that must be reignited over and over again. The article examines a new art of leadership that may be viewed as an attempt to keep up with these challenges and stay ahead of time. It emerges from...... a pilgrimage leadership learning laboratory on the road to Santiago de la Compostela. This moving lab creates situations of extraordinary intensity that border on hyperreality and force the leader to find him/herself anew on the verge of him/herself. Conceived as pilgrimage, leadership moves ahead of time...... as it reaches into and anticipates a future still unknown. In this setting, anticipatory affects and the virtual take up a predominant role. As it emerges here, leadership distinguishes itself not only from leadership in the traditional sense, but also from management and governmentality....

Evaluation of the 12-hour shift schedule at the Fast Flux Test Facility

International Nuclear Information System (INIS)

Lewis, P.M.; Swaim, D.J.; Rosa, R.R.; Colligan, M.J.; Booth, R.J.; Swint, M.J.

1986-09-01

The objective of this report are to evaluate the effect of the change to the 12-hour/day schedule on operational performance and safety of FFTF; to evaluate the degree to which the change to the 12-hour/day schedule has met its objectives; and to gather information that may be useful to FFTF management and the US Department of Energy (DOE) in evaluating 8- and 12-hour shift schedules at other facilities. The principal conclusion of this report is that the 12-hour/day shift schedule is a reasonable alternative to an 8-hour/day schedule at FFTF. As a result of the scedule change, it seems clear that plant performance improved in two ways. The operator error rate in keeping the Technical Specification Compliance Logs was already very low on the 8-hour shift. On the 12-hour shift, the rate was even lower. Also, the operator interface with craft personnel resulted in an increase in the productivity of the craft personnel

Improved irrigation scheduling for pear-jujube trees based on trunk ...

African Journals Online (AJOL)

A suitable indicator for scheduling pear-jujube (Ziziphus jujuba Mill.) irrigation in China was developed based on trunk diameter fluctuations (TDF). Parameters derived from TDF responses to variations in soil matrix potential (Ψsoil) were compared under deficit and well irrigation. Maximum daily shrinkage (MDS) increased ...

National contingency plan product schedule data base

International Nuclear Information System (INIS)

Putukian, J.; Hiltabrand, R.R.

1993-01-01

During oil spills there are always proposals by the technical community and industry to use chemical agents to help in oil spill cleanups. Federal Clean Water Act regulations require that any chemical agents that the federal on-scene coordinator (FOSC) wants to use for oil cleanup be listed on the US Environmental Protection Agency (EPA) National Contingency Plan (NCP) Product Schedule. Chemical countermeasures are among the most controversial, complex, and time-critical issues facing decision-making officials choosing response methods to use on coastal oil spills. There are situations in which dispersants are likely to be one of the most appropriate counter-measure strategies. Dispersants are most effective when applied to fresh oil, and their effectiveness dramatically decreases as the oil weathers, which can begin in as little as 24 hours. To logistically implement dispersant use, a decision would need to be made within roughly the first 4 hours after the release. Most of the information that the FOSC needs to make the determination to use a specific chemical agent exists in manuals, EPA bulletins, and the published literature. This information is not in an easy-to-use format under field emergency conditions. Hence the need to collect and disseminate the information in an automated data base. The sources for the information in this data base are the following. Published results of tests performed by Environment Canada; EPA bulletins associated with the NCP Product Schedule; Published results of tests by the chemical industry. The data base resides on a Macintosh computer and contains information about 70 NCP products, including dispersants, surface collecting agents, and biological additives. It contains information on physical properties, toxicity, heavy metal content, safety precautions, use conditions, etc

Decentralized Job Scheduling in the Cloud Based on a Spatially Generalized Prisoner’s Dilemma Game

Directory of Open Access Journals (Sweden)

Gąsior Jakub

2015-12-01

Full Text Available We present in this paper a novel distributed solution to a security-aware job scheduling problem in cloud computing infrastructures. We assume that the assignment of the available resources is governed exclusively by the specialized brokers assigned to individual users submitting their jobs to the system. The goal of this scheme is allocating a limited quantity of resources to a specific number of jobs minimizing their execution failure probability and total completion time. Our approach is based on the Pareto dominance relationship and implemented at an individual user level. To select the best scheduling strategies from the resulting Pareto frontiers and construct a global scheduling solution, we developed a decision-making mechanism based on the game-theoretic model of Spatial Prisoner’s Dilemma, realized by selfish agents operating in the two-dimensional cellular automata space. Their behavior is conditioned by the objectives of the various entities involved in the scheduling process and driven towards a Nash equilibrium solution by the employed social welfare criteria. The performance of the scheduler applied is verified by a number of numerical experiments. The related results show the effectiveness and scalability of the scheme in the presence of a large number of jobs and resources involved in the scheduling process.

Twelve-hour brain lithium concentration in lithium maintenance treatment of manic-depressive disorder: daily versus alternate-day dosing schedule

DEFF Research Database (Denmark)

Jensen, H.V.; Plenge, P; Stensgaard, A

1996-01-01

The 12-h brain lithium concentration was measured by lithium-7 magnetic resonance spectroscopy in ten manic-depressive patients receiving daily or alternate-day lithium carbonate treatment. The median dose of lithium carbonate was 800 mg in the daily treatment group and 1200 mg in the alternate......-day group. Median 12-h serum lithium concentration in the two groups was 0.86 mmol l-1 and 0.55 mmol l-1, respectively, while the corresponding concentration in brain was 0.67 mmol l-1 and 0.52 mmol l-1, respectively. The 12-h brain lithium concentration was independent of lithium dosing schedule (multiple...... linear regression), but correlated significantly with the 12-h serum lithium concentration (P = 0.003; B = 0.53, 95% c.l. 0.24-0.82; beta = 0.83). Thus at identical 12-h serum lithium concentrations the 12-h brain lithium concentration is similar with both treatment regimes. As the risk of manic...

A Multiagent Evolutionary Algorithm for the Resource-Constrained Project Portfolio Selection and Scheduling Problem

Directory of Open Access Journals (Sweden)

Yongyi Shou

2014-01-01

Full Text Available A multiagent evolutionary algorithm is proposed to solve the resource-constrained project portfolio selection and scheduling problem. The proposed algorithm has a dual level structure. In the upper level a set of agents make decisions to select appropriate project portfolios. Each agent selects its project portfolio independently. The neighborhood competition operator and self-learning operator are designed to improve the agent’s energy, that is, the portfolio profit. In the lower level the selected projects are scheduled simultaneously and completion times are computed to estimate the expected portfolio profit. A priority rule-based heuristic is used by each agent to solve the multiproject scheduling problem. A set of instances were generated systematically from the widely used Patterson set. Computational experiments confirmed that the proposed evolutionary algorithm is effective for the resource-constrained project portfolio selection and scheduling problem.

LS1 Report: According to schedule

CERN Multimedia

CERN Bulletin

2013-01-01

The AD’s BHN06 coils have been delivered back to CERN at long last from their repair at a Russian facility. The magnet will be reinstalled underneath the ATRAP experimental area, which has already been partially dismantled to make way for it.   Consolidation of the 7 PS main magnets continues as planned, with 4 magnets already removed from the beam line and delivered to the magnet workshop. A specialised team will be arriving in mid-November (also from Russia) to consolidate the magnets on the surface. The PS Booster’s beam dump replacement project remains ongoing, with the final survey of the beam transfer line currently underway. The SPS’s irradiated cable replacement campaign continues as planned; it will be completed by the end of March 2014. Over at the LHC, the Radiation to Electronics (R2E) campaign is progressing well. These activities are actually a few weeks ahead of schedule at Point 1, where teams have already begun commissioning relocated cryogenic equ...

Self-controlled feedback is effective if it is based on the learner's performance: a replication and extension of Chiviacowsky and Wulf (2005).

Science.gov (United States)

Carter, Michael J; Carlsen, Anthony N; Ste-Marie, Diane M

2014-01-01

The learning advantages of self-controlled feedback schedules compared to yoked schedules have been attributed to motivational influences and/or information processing activities with many researchers adopting the motivational perspective in recent years. Chiviacowsky and Wulf (2005) found that feedback decisions made before (Self-Before) or after a trial (Self-After) resulted in similar retention performance, but superior transfer performance resulted when the decision to receive feedback occurred after a trial. They suggested that the superior skill transfer of the Self-After group likely emerged from information processing activities such as error estimation. However, the lack of yoked groups and a measure of error estimation in their experimental design prevents conclusions being made regarding the underlying mechanisms of why self-controlled feedback schedules optimize learning. Here, we revisited Chiviacowsky and Wulf's (2005) design to investigate the learning benefits of self-controlled feedback schedules. We replicated their Self-Before and Self-After groups, but added a Self-Both group that was able to request feedback before a trial, but could then change or stay with their original choice after the trial. Importantly, yoked groups were included for the three self-controlled groups to address the previously stated methodological limitation and error estimations were included to examine whether self-controlling feedback facilitates a more accurate error detection and correction mechanism. The Self-After and Self-Before groups demonstrated similar accuracy in physical performance and error estimation scores in retention and transfer, and both groups were significantly more accurate than the Self-Before group and their respective Yoked groups (p's 0.05). We suggest these findings further indicate that informational factors associated with the processing of feedback for the development of one's error detection and correction mechanism, rather than

Comparison of buprenorphine and methadone effects on opiate self-administration in primates.

Science.gov (United States)

Mello, N K; Bree, M P; Mendelson, J H

1983-05-01

The effects of ascending and descending doses of buprenorphine (0.014-0.789 mg/kg/day) and methadone (0.179-11.86 mg/kg/day) on opiate and food intake were studied in Macaque monkeys over 195 to 245 days. Food (1-g banana pellets) and i.v. drug self-administration (heroin 0.01 or 0.02 mg/kg/injection or Dilaudid 0.02 mg/kg/injection) were maintained on a second-order schedule of reinforcement [FR 4 (VR 16:S)]. Buprenorphine (0.282-0.789 mg/kg/day) produced a significant suppression of opiate self-administration at 2.5 to 7 times the dose shown to be effective in human opiate abusers (P less than .05-.001). Methadone (1.43-11.86 mg/kg/day) did not suppress opiate self-administration in four of five monkeys across a dose range equivalent to 100 to 800 mg/day in man. The distribution of opiate self-administration across drug sessions did not account for the absence of methadone suppression as monkeys took 43% of the total daily opiate injections during the first daily drug session, 2.5 hr after methadone administration. During buprenorphine maintenance, food intake remained stable or increased significantly above base-line levels. Methadone maintenance was associated with significant decrements in food intake in four of five monkeys. Buprenorphine appeared to be significantly more effective in suppressing opiate self-administration than methadone across the dose range studied. Buprenorphine had none of the toxic side effects (seizures, respiratory depression, profound psychomotor retardation) associated with high doses of methadone over 6 to 8 months of daily drug treatment. These data are consistent with clinical studies of buprenorphine effects on heroin self-administration in human opiate addicts.

Nontraditional work schedules for pharmacists.

Science.gov (United States)

Mahaney, Lynnae; Sanborn, Michael; Alexander, Emily

2008-11-15

Nontraditional work schedules for pharmacists at three institutions are described. The demand for pharmacists and health care in general continues to increase, yet significant material changes are occurring in the pharmacy work force. These changing demographics, coupled with historical vacancy rates and turnover trends for pharmacy staff, require an increased emphasis on workplace changes that can improve staff recruitment and retention. At William S. Middleton Memorial Veterans Affairs Hospital in Madison, Wisconsin, creative pharmacist work schedules and roles are now mainstays to the recruitment and retention of staff. The major challenge that such scheduling presents is the 8 hours needed to prepare a six-week schedule. Baylor Medical Center at Grapevine in Dallas, Texas, has a total of 45 pharmacy employees, and slightly less than half of the 24.5 full-time-equivalent staff work full-time, with most preferring to work one, two, or three days per week. As long as the coverage needs of the facility are met, Envision Telepharmacy in Alpine, Texas, allows almost any scheduling arrangement preferred by individual pharmacists or the pharmacist group covering the facility. Staffing involves a great variety of shift lengths and intervals, with shifts ranging from 2 to 10 hours. Pharmacy leaders must be increasingly aware of opportunities to provide staff with unique scheduling and operational enhancements that can provide for a better work-life balance. Compressed workweeks, job-sharing, and team scheduling were the most common types of alternative work schedules implemented at three different institutions.

Hybrid LSA-ANN Based Home Energy Management Scheduling Controller for Residential Demand Response Strategy

Directory of Open Access Journals (Sweden)

Maytham S. Ahmed

2016-09-01

Full Text Available Demand response (DR program can shift peak time load to off-peak time, thereby reducing greenhouse gas emissions and allowing energy conservation. In this study, the home energy management scheduling controller of the residential DR strategy is proposed using the hybrid lightning search algorithm (LSA-based artificial neural network (ANN to predict the optimal ON/OFF status for home appliances. Consequently, the scheduled operation of several appliances is improved in terms of cost savings. In the proposed approach, a set of the most common residential appliances are modeled, and their activation is controlled by the hybrid LSA-ANN based home energy management scheduling controller. Four appliances, namely, air conditioner, water heater, refrigerator, and washing machine (WM, are developed by Matlab/Simulink according to customer preferences and priority of appliances. The ANN controller has to be tuned properly using suitable learning rate value and number of nodes in the hidden layers to schedule the appliances optimally. Given that finding proper ANN tuning parameters is difficult, the LSA optimization is hybridized with ANN to improve the ANN performances by selecting the optimum values of neurons in each hidden layer and learning rate. Therefore, the ON/OFF estimation accuracy by ANN can be improved. Results of the hybrid LSA-ANN are compared with those of hybrid particle swarm optimization (PSO based ANN to validate the developed algorithm. Results show that the hybrid LSA-ANN outperforms the hybrid PSO based ANN. The proposed scheduling algorithm can significantly reduce the peak-hour energy consumption during the DR event by up to 9.7138% considering four appliances per 7-h period.

The influence of the operating schedule of the Greek Research Reactor on the radiological consequences of the reactor

International Nuclear Information System (INIS)

Kollas, J.G.

1986-04-01

The sensitivity of the radiological consequences of the Greek Research Reactor to the operating schedule of the reactor is assessed in this report. The consequences are due to the occurrence of a postulated accident, a 20% core melt loss of coolant accident. Three different operating schedules are considered: (a) the present 8 hrs/day, 5 days/wk schedule, (b) a 16 hrs/day, 5 days/wk schedule, and (c) a continuous operation schedule. The results of the analysis indicate that there is a direct relation between consequences and duration of operation. (author)

Multi-Agent System-Based Microgrid Operation Strategy for Demand Response

Directory of Open Access Journals (Sweden)

Hee-Jun Cha

2015-12-01

Full Text Available The microgrid and demand response (DR are important technologies for future power grids. Among the variety of microgrid operations, the multi-agent system (MAS has attracted considerable attention. In a microgrid with MAS, the agents installed on the microgrid components operate optimally by communicating with each other. This paper proposes an operation algorithm for the individual agents of a test microgrid that consists of a battery energy storage system (BESS and an intelligent load. A microgrid central controller to manage the microgrid can exchange information with each agent. The BESS agent performs scheduling for maximum benefit in response to the electricity price and BESS state of charge (SOC through a fuzzy system. The intelligent load agent assumes that the industrial load performs scheduling for maximum benefit by calculating the hourly production cost. The agent operation algorithm includes a scheduling algorithm using day-ahead pricing in the DR program and a real-time operation algorithm for emergency situations using emergency demand response (EDR. The proposed algorithm and operation strategy were implemented both by a hardware-in-the-loop simulation test using OPAL-RT and an actual hardware test by connecting a new distribution simulator.

PERFORMANCE ANALYSIS OF AI BASED QOS SCHEDULER FOR MOBILE WIMAX

Directory of Open Access Journals (Sweden)

D. David Neels Pon Kumar

2012-09-01

Full Text Available Interest in broadband wireless access (BWA has been growing due to increased user mobility and the need for data access at all times. IEEE 802.16e based WiMAX networks promise the best available quality of experience for mobile data service users. WiMAX networks incorporate several Quality of Service (QoS mechanisms at the Media Access Control (MAC level for guaranteed services for multimedia viz. data, voice and video. The problem of assuring QoS is how to allocate available resources among users to meet the QoS criteria such as delay, delay jitter, fairness and throughput requirements. IEEE standard does not include a standard scheduling mechanism and leaves it for various implementer differentiations. Although a lot of the real-time and non real-time packet scheduling schemes has been proposed, it needs to be modified to apply to Mobile WiMAX system that supports five kinds of service classes. In this paper, we propose a novel Priority based Scheduling scheme that uses Artificial Intelligence to support various services by considering the QoS constraints of each class. The simulation results show that slow mobility does not affect the performances and faster mobility and the increment in users beyond a particular load have their say in defining average throughput, average per user throughput, fairness index, average end to end delay and average delay jitter. Nevertheless the results are encouraging that the proposed scheme provides QoS support for each class efficiently.

The impact of a social network based intervention on self-management behaviours among patients with type 2 diabetes living in socioeconomically deprived neighbourhoods: a mixed methods approach.

Science.gov (United States)

Vissenberg, Charlotte; Nierkens, Vera; van Valkengoed, Irene; Nijpels, Giel; Uitewaal, Paul; Middelkoop, Barend; Stronks, Karien

2017-08-01

This paper aims to explore the effect of the social network based intervention Powerful Together with Diabetes on diabetes self-management among socioeconomically deprived patients. This 10-month group intervention targeting patients and significant others aimed to improve self-management by stimulating social support and diminishing social influences that hinder self-management. This intervention was evaluated in a quasi-experimental study using a mixed methods approach. Of 131 socioeconomically deprived patients with suboptimal glycaemic control, 69 were assigned to the intervention group and 62 to the control group (standard diabetes education). 27 qualitative in-depth interviews with the participants and 24 with their group leaders were held to study the subjective impact of the intervention. Further, self-management behaviours (medication adherence, diet and physical activity) were assessed at baseline, 10 and 16 months. Data were analysed using framework analyses and a linear mixture model. Qualitative data showed that the intervention group had a better understanding of the way self-management influences diabetes. The intervention group showed more complex self-management behaviours, such as planning ahead, seeking adequate food and physical activity alternatives, and consistently taking their diabetes into consideration when making choices. In participants with complete follow-up data, we found a significant increase in physical activity in the intervention group (3.78 vs. 4.83 days) and no changes in medication adherence and diet. This study indicates that an intensive support group and simultaneously involving significant others might improve diabetes self-management behaviours among socioeconomically deprived patients. More studies are needed to justify further implementation of the intervention. This study is registered in the Dutch Trial Register NTR1886. http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=1886.

A hybrid online scheduling mechanism with revision and progressive techniques for autonomous Earth observation satellite

Science.gov (United States)

Li, Guoliang; Xing, Lining; Chen, Yingwu

2017-11-01

The autonomicity of self-scheduling on Earth observation satellite and the increasing scale of satellite network attract much attention from researchers in the last decades. In reality, the limited onboard computational resource presents challenge for the online scheduling algorithm. This study considered online scheduling problem for a single autonomous Earth observation satellite within satellite network environment. It especially addressed that the urgent tasks arrive stochastically during the scheduling horizon. We described the problem and proposed a hybrid online scheduling mechanism with revision and progressive techniques to solve this problem. The mechanism includes two decision policies, a when-to-schedule policy combining periodic scheduling and critical cumulative number-based event-driven rescheduling, and a how-to-schedule policy combining progressive and revision approaches to accommodate two categories of task: normal tasks and urgent tasks. Thus, we developed two heuristic (re)scheduling algorithms and compared them with other generally used techniques. Computational experiments indicated that the into-scheduling percentage of urgent tasks in the proposed mechanism is much higher than that in periodic scheduling mechanism, and the specific performance is highly dependent on some mechanism-relevant and task-relevant factors. For the online scheduling, the modified weighted shortest imaging time first and dynamic profit system benefit heuristics outperformed the others on total profit and the percentage of successfully scheduled urgent tasks.

A Framework for Uplink Intercell Interference Modeling with Channel-Based Scheduling

KAUST Repository

Tabassum, Hina

2012-12-29

This paper presents a novel framework for modeling the uplink intercell interference(ICI) in a multiuser cellular network. The proposed framework assists in quantifying the impact of various fading channel models and state-of-the-art scheduling schemes on the uplink ICI. Firstly, we derive a semianalytical expression for the distribution of the location of the scheduled user in a given cell considering a wide range of scheduling schemes. Based on this, we derive the distribution and moment generating function (MGF) of the uplink ICI considering a single interfering cell. Consequently, we determine the MGF of the cumulative ICI observed from all interfering cells and derive explicit MGF expressions for three typical fading models. Finally, we utilize the obtained expressions to evaluate important network performance metrics such as the outage probability, ergodic capacity, and average fairness numerically. Monte-Carlo simulation results are provided to demonstrate the efficacy of the derived analytical expressions.

Real-time-service-based Distributed Scheduling Scheme for IEEE 802.16j Networks

OpenAIRE

Kuo-Feng Huang; Shih-Jung Wu

2013-01-01

Supporting Quality of Service (QoS) guarantees for diverse multimedia services is the primary concern for IEEE802.16j networks. A scheduling scheme that satisfies the QoS requirements has become more important for wireless communications. We proposed an adaptive nontransparent-based distributed scheduling scheme (ANDS) for IEEE 802.16j networks. ANDS comprises three major components: Priority Assignment, Resource Allocation, Preserved Bandwidth Adjustment. Different service-type connections p...

Virtual power plant mid-term dispatch optimization

International Nuclear Information System (INIS)

Pandžić, Hrvoje; Kuzle, Igor; Capuder, Tomislav

2013-01-01

Highlights: ► Mid-term virtual power plant dispatching. ► Linear modeling. ► Mixed-integer linear programming applied to mid-term dispatch scheduling. ► Operation profit maximization combining bilateral contracts and the day-ahead market. -- Abstract: Wind power plants incur practically zero marginal costs during their operation. However, variable and uncertain nature of wind results in significant problems when trying to satisfy the contracted quantities of delivered electricity. For this reason, wind power plants and other non-dispatchable power sources are combined with dispatchable power sources forming a virtual power plant. This paper considers a weekly self-scheduling of a virtual power plant composed of intermittent renewable sources, storage system and a conventional power plant. On the one hand, the virtual power plant needs to fulfill its long-term bilateral contracts, while, on the other hand, it acts in the market trying to maximize its overall profit. The optimal dispatch problem is formulated as a mixed-integer linear programming model which maximizes the weekly virtual power plant profit subject to the long-term bilateral contracts and technical constraints. The self-scheduling procedure is based on stochastic programming. The uncertainty of the wind power and solar power generation is settled by using pumped hydro storage in order to provide flexible operation, as well as by having a conventional power plant as a backup. The efficiency of the proposed model is rendered through a realistic case study and analysis of the results is provided. Additionally, the impact of different storage capacities and turbine/pump capacities of pumped storage are analyzed.

Scheduling the scheduling task : a time management perspective on scheduling

NARCIS (Netherlands)

Larco Martinelli, J.A.; Wiers, V.C.S.; Fransoo, J.C.

2013-01-01

Time is the most critical resource at the disposal of schedulers. Hence, an adequate management of time from the schedulers may impact positively on the scheduler’s productivity and responsiveness to uncertain scheduling environments. This paper presents a field study of how schedulers make use of

Day Care Centers for Seniors in Singapore: Looking Back and Looking Ahead.

Science.gov (United States)

Liu, Germaine; Yap, Philip; Wong, Gabriel H Z; Wei, Heng Xiao; Hua, Ee Chye

2015-07-01

The burden of care for frail elderly persons on families and the society is ever real as our population ages. Given the dual-income nature of many working families, day care centers offer a strong alternative to nursing homes for families wishing to provide custodial care and meaningful engagement for seniors while continuing to uphold their filial duties. Recognizing this, several initiatives, such as SPICE (Singapore Programme for Integrated Care for the Elderly) and Weekend Respite Care, have been launched to enhance the services of Singapore's day care centers. This article traces the evolution of this process, distills current challenges, and offers policy recommendations to improve Singapore's day care services for seniors. Copyright © 2015 AMDA - The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.