Supply-demand balance in outward-directed networks and Kleiber's law

Directory of Open Access Journals (Sweden)

Painter Page R

2005-11-01

Full Text Available Abstract Background Recent theories have attempted to derive the value of the exponent α in the allometric formula for scaling of basal metabolic rate from the properties of distribution network models for arteries and capillaries. It has recently been stated that a basic theorem relating the sum of nutrient currents to the specific nutrient uptake rate, together with a relationship claimed to be required in order to match nutrient supply to nutrient demand in 3-dimensional outward-directed networks, leads to Kleiber's law (b = 3/4. Methods The validity of the supply-demand matching principle and the assumptions required to prove the basic theorem are assessed. The supply-demand principle is evaluated by examining the supply term and the demand term in outward-directed lattice models of nutrient and water distribution systems and by applying the principle to fractal-like models of mammalian arterial systems. Results Application of the supply-demand principle to bifurcating fractal-like networks that are outward-directed does not predict 3/4-power scaling, and evaluation of water distribution system models shows that the matching principle does not match supply to demand in such systems. Furthermore, proof of the basic theorem is shown to require that the covariance of nutrient uptake and current path length is 0, an assumption unlikely to be true in mammalian arterial systems. Conclusion The supply-demand matching principle does not lead to a satisfactory explanation for the approximately 3/4-power scaling of mammalian basal metabolic rate.

Demand Response in Low Voltage Distribution Networks with High PV Penetration

DEFF Research Database (Denmark)

Nainar, Karthikeyan; Pokhrel, Basanta Raj; Pillai, Jayakrishnan Radhakrishna

2017-01-01

the required flexibility from the electricity market through an aggregator. The optimum demand response enables consumption of maximum renewable energy within the network constraints. Simulation studies are conducted using Matlab and DigSilent Power factory software on a Danish low-voltage distribution system......In this paper, application of demand response to accommodate maximum PV power in a low-voltage distribution network is discussed. A centralized control based on model predictive control method is proposed for the computation of optimal demand response on an hourly basis. The proposed method uses PV...

Fast demand response in support of the active distribution network

NARCIS (Netherlands)

MacDougall, P.; Heskes, P.; Crolla, P.; Burt, G.; Warmer, C.

2013-01-01

Demand side management has traditionally been investigated for "normal" operation services such as balancing and congestion management. However they potentially could be utilized for Distributed Network Operator (DNO) services. This paper investigates and validates the use of a supply and demand

Multi-Model Prediction for Demand Forecast in Water Distribution Networks

Directory of Open Access Journals (Sweden)

Rodrigo Lopez Farias

2018-03-01

Full Text Available This paper presents a multi-model predictor called Qualitative Multi-Model Predictor Plus (QMMP+ for demand forecast in water distribution networks. QMMP+ is based on the decomposition of the quantitative and qualitative information of the time-series. The quantitative component (i.e., the daily consumption prediction is forecasted and the pattern mode estimated using a Nearest Neighbor (NN classifier and a Calendar. The patterns are updated via a simple Moving Average scheme. The NN classifier and the Calendar are executed simultaneously every period and the most suited model for prediction is selected using a probabilistic approach. The proposed solution for water demand forecast is compared against Radial Basis Function Artificial Neural Networks (RBF-ANN, the statistical Autoregressive Integrated Moving Average (ARIMA, and Double Seasonal Holt-Winters (DSHW approaches, providing the best results when applied to real demand of the Barcelona Water Distribution Network. QMMP+ has demonstrated that the special modelling treatment of water consumption patterns improves the forecasting accuracy.

A Nondominated Genetic Algorithm Procedure for Multiobjective Discrete Network Design under Demand Uncertainty

Directory of Open Access Journals (Sweden)

Bian Changzhi

2015-01-01

Full Text Available This paper addresses the multiobjective discrete network design problem under demand uncertainty. The OD travel demands are supposed to be random variables with the given probability distribution. The problem is formulated as a bilevel stochastic optimization model where the decision maker’s objective is to minimize the construction cost, the expectation, and the standard deviation of total travel time simultaneously and the user’s route choice is described using user equilibrium model on the improved network under all scenarios of uncertain demand. The proposed model generates globally near-optimal Pareto solutions for network configurations based on the Monte Carlo simulation and nondominated sorting genetic algorithms II. Numerical experiments implemented on Nguyen-Dupuis test network show trade-offs among construction cost, the expectation, and standard deviation of total travel time under uncertainty are obvious. Investment on transportation facilities is an efficient method to improve the network performance and reduce risk under demand uncertainty, but it has an obvious marginal decreasing effect.

Designing container shipping network under changing demand and freight rates

Directory of Open Access Journals (Sweden)

C. Chen

2010-03-01

Full Text Available This paper focuses on the optimization of container shipping network and its operations under changing cargo demand and freight rates. The problem is formulated as a mixed integer non-linear programming problem (MINP with an objective of maximizing the average unit ship-slot profit at three stages using analytical methodology. The issues such as empty container repositioning, ship-slot allocating, ship sizing, and container configuration are simultaneously considered based on a series of the matrices of demand for a year. To solve the model, a bi-level genetic algorithm based method is proposed. Finally, numerical experiments are provided to illustrate the validity of the proposed model and algorithms. The obtained results show that the suggested model can provide a more realistic solution to the issues on the basis of changing demand and freight rates and arrange a more effective approach to the optimization of container shipping network structures and operations than does the model based on the average demand.

Function-Oriented Networking and On-Demand Routing System in Network Using Ant Colony Optimization Algorithm

Directory of Open Access Journals (Sweden)

Young-Bo Sim

2017-11-01

Full Text Available In this paper, we proposed and developed Function-Oriented Networking (FON, a platform for network users. It has a different philosophy as opposed to technologies for network managers of Software-Defined Networking technology, OpenFlow. It is a technology that can immediately reflect the demands of the network users in the network, unlike the existing OpenFlow and Network Functions Virtualization (NFV, which do not reflect directly the needs of the network users. It allows the network user to determine the policy of the direct network, so it can be applied more precisely than the policy applied by the network manager. This is expected to increase the satisfaction of the service users when the network users try to provide new services. We developed FON function that performs on-demand routing for Low-Delay Required service. We analyzed the characteristics of the Ant Colony Optimization (ACO algorithm and found that the algorithm is suitable for low-delay required services. It was also the first in the world to implement the routing software using ACO Algorithm in the real Ethernet network. In order to improve the routing performance, several algorithms of the ACO Algorithm have been developed to enable faster path search-routing and path recovery. The relationship between the network performance index and the ACO routing parameters is derived, and the results are compared and analyzed. Through this, it was possible to develop the ACO algorithm.

Information system design for demand-driven supply networks

OpenAIRE

Selk, Bernhard

2004-01-01

Information system design for demand-driven supply networks : integrating CRM & SCM / B. Selk, K. Turowski, C. Winnewisser. - In: EIS : Fourth International ICSC Symposium on Engineering of Intelligent Systems, EIS 2004. [Elektronische Ressource]. - Millet, Alberta : ICSC Interdisciplinary Research Canada, 2004. - 8 S. auf CD-ROM

Impact of Demand Side Management in Active Distribution Networks

DEFF Research Database (Denmark)

Ponnaganti, Pavani; Bak-Jensen, Birgitte; Pillai, Jayakrishnan Radhakrishna

2017-01-01

Demand Side Management (DSM) is an efficient flexible program which helps distribution network operators to meet the future critical peak demand. It is executed in cases of not only technical issues like voltage sag or swell, transformer burdening, cable congestions, but also to increase the degree...... of visibility in the electricity markets. The aim of this paper is to find the optimal flexible demands that can be shifted to another time in order to operate the active distribution system within secure operating limits. A simple mechanism is proposed for finding the flexibility of the loads where electric...

Revenue Improvement Through Demand-Dependent Pricing of Network Services

National Research Council Canada - National Science Library

Sanders, David

2000-01-01

... of the expectation of rewards based upon variable demands. This work shows that revenue improvement can occur in this network environment when a dynamic pricing policy is applied as opposed to optimal static pricing...

Identifying demand effects in a large network of product categories

NARCIS (Netherlands)

Gelper, S.E.C.; Wilms, I.; Croux, C.

2016-01-01

Planning marketing mix strategies requires retailers to understand within- as well as cross-category demand effects. Most retailers carry products in a large variety of categories, leading to a high number of such demand effects to be estimated. At the same time, we do not expect cross-category

Demand Forecasting Methods in Accommodation Establishments: A Research with Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Ebru ULUCAN

2018-05-01

Full Text Available As it being seen in every sector, demand forecasting in tourism is been conducted with various qualitative and quantitative methods. In recent years, artificial neural network models, which have been developed as an alternative to these forecasting methods, give the nearest values in forecasting with the smallest failure percentage. This study aims to reveal that accomodation establishments can use the neural network models as an alternative while forecasting their demand. With this aim, neural network models have been tested by using the sold room values between the period of 2013-2016 of a five star hotel in Istanbul and it is found that the results acquired from the testing models are the nearest values comparing the realized figures. In the light of these results, tourism demand of the hotel for 2017 and 2018 has been forecasted.

Urban development control based on transportation carrying capacity

Science.gov (United States)

Miharja, M.; Sjafruddin, A. H.

2017-06-01

Severe transportation problems in Indonesian urban areas are stimulated by one fundamental factor, namely lack of awareness on transportation carrying capacity in these areas development control. Urban land use development towards more physical coverage is typically not related with the capability of transportation system to accommodate additional trips volume. Lack of clear connection between development permit with its implication on the transportation side has led to a phenomenon of exceeding transport demand over supply capacity. This paper discusses the concept of urban land use development control which will be related with transport carrying capacity. The discussion would cover both supply and demand sides of transportation. From supply side, the analysis regarding the capacity of transport system would take both existing as well as potential road network capacity could be developed. From demand side, the analysis would be through the control of a maximum floor area and public transport provision. Allowed maximum floor area for development would be at the level of generating traffic at reasonable volume. Ultimately, the objective of this paper is to introduce model to incorporate transport carrying capacity in Indonesian urban land use development control.

Definition of Distribution Network Tariffs Considering Distribution Generation and Demand Response

DEFF Research Database (Denmark)

Soares, Tiago; Faria, Pedro; Vale, Zita

2014-01-01

The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits for the wh......The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits...... the determination of topological distribution factors, and consequent application of the MW-mile method. The application of the proposed tariffs definition methodology is illustrated in a distribution network with 33 buses, 66 DG units, and 32 consumers with DR capacity...

Performance Analysis of On-Demand Routing Protocols in Wireless Mesh Networks

Directory of Open Access Journals (Sweden)

Arafatur RAHMAN

2009-01-01

Full Text Available Wireless Mesh Networks (WMNs have recently gained a lot of popularity due to their rapid deployment and instant communication capabilities. WMNs are dynamically self-organizing, self-configuring and self-healing with the nodes in the network automatically establishing an adiej hoc network and preserving the mesh connectivity. Designing a routing protocol for WMNs requires several aspects to consider, such as wireless networks, fixed applications, mobile applications, scalability, better performance metrics, efficient routing within infrastructure, load balancing, throughput enhancement, interference, robustness etc. To support communication, various routing protocols are designed for various networks (e.g. ad hoc, sensor, wired etc.. However, all these protocols are not suitable for WMNs, because of the architectural differences among the networks. In this paper, a detailed simulation based performance study and analysis is performed on the reactive routing protocols to verify the suitability of these protocols over such kind of networks. Ad Hoc On-Demand Distance Vector (AODV, Dynamic Source Routing (DSR and Dynamic MANET On-demand (DYMO routing protocol are considered as the representative of reactive routing protocols. The performance differentials are investigated using varying traffic load and number of source. Based on the simulation results, how the performance of each protocol can be improved is also recommended.

A multi-period distribution network design model under demand uncertainty

Science.gov (United States)

Tabrizi, Babak H.; Razmi, Jafar

2013-05-01

Supply chain management is taken into account as an inseparable component in satisfying customers' requirements. This paper deals with the distribution network design (DND) problem which is a critical issue in achieving supply chain accomplishments. A capable DND can guarantee the success of the entire network performance. However, there are many factors that can cause fluctuations in input data determining market treatment, with respect to short-term planning, on the one hand. On the other hand, network performance may be threatened by the changes that take place within practicing periods, with respect to long-term planning. Thus, in order to bring both kinds of changes under control, we considered a new multi-period, multi-commodity, multi-source DND problem in circumstances where the network encounters uncertain demands. The fuzzy logic is applied here as an efficient tool for controlling the potential customers' demand risk. The defuzzifying framework leads the practitioners and decision-makers to interact with the solution procedure continuously. The fuzzy model is then validated by a sensitivity analysis test, and a typical problem is solved in order to illustrate the implementation steps. Finally, the formulation is tested by some different-sized problems to show its total performance.

Transport energy demand modeling of South Korea using artificial neural network

International Nuclear Information System (INIS)

Geem, Zong Woo

2011-01-01

Artificial neural network models were developed to forecast South Korea's transport energy demand. Various independent variables, such as GDP, population, oil price, number of vehicle registrations, and passenger transport amount, were considered and several good models (Model 1 with GDP, population, and passenger transport amount; Model 2 with GDP, number of vehicle registrations, and passenger transport amount; and Model 3 with oil price, number of vehicle registrations, and passenger transport amount) were selected by comparing with multiple linear regression models. Although certain regression models obtained better R-squared values than neural network models, this does not guarantee the fact that the former is better than the latter because root mean squared errors of the former were much inferior to those of the latter. Also, certain regression model had structural weakness based on P-value. Instead, neural network models produced more robust results. Forecasted results using the neural network models show that South Korea will consume around 37 MTOE of transport energy in 2025. - Highlights: → Transport energy demand of South Korea was forecasted using artificial neural network. → Various variables (GDP, population, oil price, number of registrations, etc.) were considered. → Results of artificial neural network were compared with those of multiple linear regression.

Prediction of energy demands using neural network with model identification by global optimization

Energy Technology Data Exchange (ETDEWEB)

Yokoyama, Ryohei; Wakui, Tetsuya; Satake, Ryoichi [Department of Mechanical Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Naka-ku, Sakai, Osaka 599-8531 (Japan)

2009-02-15

To operate energy supply plants properly from the viewpoints of stable energy supply, and energy and cost savings, it is important to predict energy demands accurately as basic conditions. Several methods of predicting energy demands have been proposed, and one of them is to use neural networks. Although local optimization methods such as gradient ones have conventionally been adopted in the back propagation procedure to identify the values of model parameters, they have the significant drawback that they can derive only local optimal solutions. In this paper, a global optimization method called ''Modal Trimming Method'' proposed for non-linear programming problems is adopted to identify the values of model parameters. In addition, the trend and periodic change are first removed from time series data on energy demand, and the converted data is used as the main input to a neural network. Furthermore, predicted values of air temperature and relative humidity are considered as additional inputs to the neural network, and their effect on the prediction of energy demand is investigated. This approach is applied to the prediction of the cooling demand in a building used for a bench mark test of a variety of prediction methods, and its validity and effectiveness are clarified. (author)

Delivery of video-on-demand services using local storages within passive optical networks.

Science.gov (United States)

Abeywickrama, Sandu; Wong, Elaine

2013-01-28

At present, distributed storage systems have been widely studied to alleviate Internet traffic build-up caused by high-bandwidth, on-demand applications. Distributed storage arrays located locally within the passive optical network were previously proposed to deliver Video-on-Demand services. As an added feature, a popularity-aware caching algorithm was also proposed to dynamically maintain the most popular videos in the storage arrays of such local storages. In this paper, we present a new dynamic bandwidth allocation algorithm to improve Video-on-Demand services over passive optical networks using local storages. The algorithm exploits the use of standard control packets to reduce the time taken for the initial request communication between the customer and the central office, and to maintain the set of popular movies in the local storage. We conduct packet level simulations to perform a comparative analysis of the Quality-of-Service attributes between two passive optical networks, namely the conventional passive optical network and one that is equipped with a local storage. Results from our analysis highlight that strategic placement of a local storage inside the network enables the services to be delivered with improved Quality-of-Service to the customer. We further formulate power consumption models of both architectures to examine the trade-off between enhanced Quality-of-Service performance versus the increased power requirement from implementing a local storage within the network.

Modelling and Forecasting Cruise Tourism Demand to İzmir by Different Artificial Neural Network Architectures

Directory of Open Access Journals (Sweden)

Murat Cuhadar

2014-03-01

Full Text Available Abstract Cruise ports emerged as an important sector for the economy of Turkey bordered on three sides by water. Forecasting cruise tourism demand ensures better planning, efficient preparation at the destination and it is the basis for elaboration of future plans. In the recent years, new techniques such as; artificial neural networks were employed for developing of the predictive models to estimate tourism demand. In this study, it is aimed to determine the forecasting method that provides the best performance when compared the forecast accuracy of Multi-layer Perceptron (MLP, Radial Basis Function (RBF and Generalized Regression neural network (GRNN to estimate the monthly inbound cruise tourism demand to İzmir via the method giving best results. We used the total number of foreign cruise tourist arrivals as a measure of inbound cruise tourism demand and monthly cruise tourist arrivals to İzmir Cruise Port in the period of January 2005 ‐December 2013 were utilized to appropriate model. Experimental results showed that radial basis function (RBF neural network outperforms multi-layer perceptron (MLP and the generalised regression neural networks (GRNN in terms of forecasting accuracy. By the means of the obtained RBF neural network model, it has been forecasted the monthly inbound cruise tourism demand to İzmir for the year 2014.

A demand assignment control in international business satellite communications network

Science.gov (United States)

Nohara, Mitsuo; Takeuchi, Yoshio; Takahata, Fumio; Hirata, Yasuo

An experimental system is being developed for use in an international business satellite (IBS) communications network based on demand-assignment (DA) and TDMA techniques. This paper discusses its system design, in particular from the viewpoints of a network configuration, a DA control, and a satellite channel-assignment algorithm. A satellite channel configuration is also presented along with a tradeoff study on transmission rate, HPA output power, satellite resource efficiency, service quality, and so on.

Limitations of demand- and pressure-driven modeling for large deficient networks

Science.gov (United States)

Braun, Mathias; Piller, Olivier; Deuerlein, Jochen; Mortazavi, Iraj

2017-10-01

The calculation of hydraulic state variables for a network is an important task in managing the distribution of potable water. Over the years the mathematical modeling process has been improved by numerous researchers for utilization in new computer applications and the more realistic modeling of water distribution networks. But, in spite of these continuous advances, there are still a number of physical phenomena that may not be tackled correctly by current models. This paper will take a closer look at the two modeling paradigms given by demand- and pressure-driven modeling. The basic equations are introduced and parallels are drawn with the optimization formulations from electrical engineering. These formulations guarantee the existence and uniqueness of the solution. One of the central questions of the French and German research project ResiWater is the investigation of the network resilience in the case of extreme events or disasters. Under such extraordinary conditions where models are pushed beyond their limits, we talk about deficient network models. Examples of deficient networks are given by highly regulated flow, leakage or pipe bursts and cases where pressure falls below the vapor pressure of water. These examples will be presented and analyzed on the solvability and physical correctness of the solution with respect to demand- and pressure-driven models.

The Use of Artificial Neural Networks for Forecasting the Electric Demand of Stand-Alone Consumers

Science.gov (United States)

Ivanin, O. A.; Direktor, L. B.

2018-05-01

The problem of short-term forecasting of electric power demand of stand-alone consumers (small inhabited localities) situated outside centralized power supply areas is considered. The basic approaches to modeling the electric power demand depending on the forecasting time frame and the problems set, as well as the specific features of such modeling, are described. The advantages and disadvantages of the methods used for the short-term forecast of the electric demand are indicated, and difficulties involved in the solution of the problem are outlined. The basic principles of arranging artificial neural networks are set forth; it is also shown that the proposed method is preferable when the input information necessary for prediction is lacking or incomplete. The selection of the parameters that should be included into the list of the input data for modeling the electric power demand of residential areas using artificial neural networks is validated. The structure of a neural network is proposed for solving the problem of modeling the electric power demand of residential areas. The specific features of generation of the training dataset are outlined. The results of test modeling of daily electric demand curves for some settlements of Kamchatka and Yakutia based on known actual electric demand curves are provided. The reliability of the test modeling has been validated. A high value of the deviation of the modeled curve from the reference curve obtained in one of the four reference calculations is explained. The input data and the predicted power demand curves for the rural settlement of Kuokuiskii Nasleg are provided. The power demand curves were modeled for four characteristic days of the year, and they can be used in the future for designing a power supply system for the settlement. To enhance the accuracy of the method, a series of measures based on specific features of a neural network's functioning are proposed.

Efficient network resource management for multimedia-on-demand services

Science.gov (United States)

Kuo, Chinhwa; Chiu, Jui-Hwa; Wu, Jong-Jyh; Chen, Dxo-Shin

1998-08-01

A Multimedia Instruction on Demand (MID) serves the purpose of providing an environment for lecture design, lecture annotation, and lecture review over networks. In order to support real-time multimedia interactive playback for such an application, the underlying networks are required to provide network resource management mechanism to enforce the reservation policy. In our design, the MID server and MID gateway consist of the following mechanisms, namely, resource management agent, admission control agent, packet classifier, and packet scheduler. We make use of the framework of the ReSerVation Protocol to devise and implement a network resource management mechanism, which control end-to-end packet delays and bandwidth allocation for the designed MID system. In the present paper, our contributions are as follows: (1) a network resource management scheme is designed to support real-time multimedia over the Internet and (2) an experimental test bed is established to measure the system performance. The developed scheme is currently being implemented in the Multimedia Information Networking laboratory at Tamkang University.

Contracting for Competitive Supply Chains under Network Externalities and Demand Uncertainty

Directory of Open Access Journals (Sweden)

Xiaojing Liu

2016-01-01

Full Text Available Based on network externalities and demand uncertainty environment, supply chain competition model is built; we identify the valid mechanism for the alternative range of profit-sharing contracts and also analyze the effect of product substitutability coefficient and network externalities on the alliance and profit-sharing contract. The results show that the vertical alliance contributes profit improvement to both the manufacturer and the retailer when the impact of network externalities on the product substitutability is not strong. However, vertical alliance will be out of operation when the effect of network externalities on the product substitutability is strong.

Pollution source localization in an urban water supply network based on dynamic water demand.

Science.gov (United States)

Yan, Xuesong; Zhu, Zhixin; Li, Tian

2017-10-27

Urban water supply networks are susceptible to intentional, accidental chemical, and biological pollution, which pose a threat to the health of consumers. In recent years, drinking-water pollution incidents have occurred frequently, seriously endangering social stability and security. The real-time monitoring for water quality can be effectively implemented by placing sensors in the water supply network. However, locating the source of pollution through the data detection obtained by water quality sensors is a challenging problem. The difficulty lies in the limited number of sensors, large number of water supply network nodes, and dynamic user demand for water, which leads the pollution source localization problem to an uncertainty, large-scale, and dynamic optimization problem. In this paper, we mainly study the dynamics of the pollution source localization problem. Previous studies of pollution source localization assume that hydraulic inputs (e.g., water demand of consumers) are known. However, because of the inherent variability of urban water demand, the problem is essentially a fluctuating dynamic problem of consumer's water demand. In this paper, the water demand is considered to be stochastic in nature and can be described using Gaussian model or autoregressive model. On this basis, an optimization algorithm is proposed based on these two dynamic water demand change models to locate the pollution source. The objective of the proposed algorithm is to find the locations and concentrations of pollution sources that meet the minimum between the analogue and detection values of the sensor. Simulation experiments were conducted using two different sizes of urban water supply network data, and the experimental results were compared with those of the standard genetic algorithm.

Video-on-demand network design and maintenance using fuzzy optimization.

Science.gov (United States)

Abadpour, Arash; Alfa, Attahiru Sule; Diamond, Jeff

2008-04-01

Video-on-demand (VoD) is the entertainment source that, in the future, will likely overtake regular television in many aspects. Although many companies have deployed working VoD services, some aspects of the VoD should still undergo further improvement in order for it to reach to the foreseen potentials. An important aspect of a VoD system is the underlying network in which it operates. According to the huge number of customers in this network, it should be carefully designed to fulfill certain performance criteria. This process should be capable of finding optimal locations for the nodes of the network as well as determining the content that should be cached in each one. While this problem is categorized in the general group of network optimization problems, its specific characteristics demand a new solution to be sought for it. In this paper, which is inspired by the successful use of fuzzy optimization in similar problems in other fields, a fuzzy objective function that is heuristically shown to minimize the communication cost in a VoD network is derived while also controlling the storage cost. Then, an iterative algorithm is proposed to find a locally optimal solution to the proposed objective function. Capitalizing on the unrepeatable tendency of the proposed algorithm, a heuristic method for picking a good solution from a bundle of solutions produced by the proposed algorithm is also suggested. This paper includes a formal statement of the problem and its mathematical analysis. In addition, different scenarios in which the proposed algorithm can be utilized are discussed.

The development and work procedures to super speed network for the growing demands for the network

International Nuclear Information System (INIS)

Nosaki, Nobuhisa; Aoki, Kazuhisa

2001-01-01

Following the recently growing demands for the network, the modification of Local Area Network (LAN) and Wide Area Network (WAN) to super speed network have been reviewed in the Japan Nuclear Cycle Development Institute (JNC). Though the modification of the LAN to super speed network is being developed this year in Heisei 13 fiscal year, it of the WAN was developed in Heisei 12 fiscal year. In spite of various issues, technical reviews and etc., there are a lot of benefits and merit for the super speed network of the WAN and though the modification of it and reduction of the running cost are contradictory to each other, both of those have been achieved in the JNC. This paper introduces the development and work procedures for the WAN. (author)

Managing the growing energy demand - The case of Egypt

Energy Technology Data Exchange (ETDEWEB)

El-Kholy, Hosni; Faried, Ragy

2010-09-15

The electric energy consumption rate in Egypt has an average increase of 7% per year through the last three decades. In order to satisfy the ever increasing energy demand, several actions were, and have to be taken. These actions have to be carried out in parallel. The one having the greatest effect is the measures carried out for energy conservation and loss reduction. Diversifying the energy source such as utilization of Renewable Energy technologies can contribute to satisfying the demand and extending the hydro-carbon reserves life. Regional integration of electrical networks will save expenditures used to build additional power plants.

Exploring the Impact of Network Structure and Demand Collaboration on the Dynamics of a Supply Chain Network Using a Robust Control Approach

Directory of Open Access Journals (Sweden)

Yongchang Wei

2015-01-01

uncertain environment. The impact of network structure and collaboration on the dynamics and robustness of supply chain network, however, remains to be explored. In this paper, a unified state space model for a two-layer supply chain network composed of multiple distributors and multiple retailers is developed. A robust control algorithm is advocated to reduce both order and demand fluctuations for unknown demand. Numerical simulations demonstrate that the robust control approach has the advantage to reduce both inventory and order fluctuations. In the simulation experiment, it is interesting to notice that complex network structure and collaborations might contribute to the reduction of inventory and order oscillations. This paper yields new insights into the overestimated bullwhip effect problem and helps us understand the complexities of supply chain networks.

Dynamic Vehicle Scheduling for Working Service Network with Dual Demands

Directory of Open Access Journals (Sweden)

Bing Li

2017-01-01

Full Text Available This study aims to develop some models to aid in making decisions on the combined fleet size and vehicle assignment in working service network where the demands include two types (minimum demands and maximum demands, and vehicles themselves can act like a facility to provide services when they are stationary at one location. This type of problem is named as the dynamic working vehicle scheduling with dual demands (DWVS-DD and formulated as a mixed integer programming (MIP. Instead of a large integer program, the problem is decomposed into small local problems that are guided by preset control parameters. The approach for preset control parameters is given. By introducing them into the MIP formulation, the model is reformulated as a piecewise form. Further, a piecewise method by updating preset control parameters is proposed for solving the reformulated model. Numerical experiments show that the proposed method produces better solution within reasonable computing time.

Robustness of the Drinking Water Distribution Network under Changing Future Demand

NARCIS (Netherlands)

Agudelo-Vera, C.; Blokker, M.; Vreeburg, J.; Bongard, T.; Hillegers, S.; Van der Hoek, J.P.

2014-01-01

A methodology to determine the robustness of the drinking water distribution system is proposed. The performance of three networks under ten future demand scenarios was tested, using head loss and residence time as indicators. The scenarios consider technological and demographic changes. Daily

Equilibrium Model of Discrete Dynamic Supply Chain Network with Random Demand and Advertisement Strategy

Directory of Open Access Journals (Sweden)

Guitao Zhang

2014-01-01

Full Text Available The advertisement can increase the consumers demand; therefore it is one of the most important marketing strategies in the operations management of enterprises. This paper aims to analyze the impact of advertising investment on a discrete dynamic supply chain network which consists of suppliers, manufactures, retailers, and demand markets associated at different tiers under random demand. The impact of advertising investment will last several planning periods besides the current period due to delay effect. Based on noncooperative game theory, variational inequality, and Lagrange dual theory, the optimal economic behaviors of the suppliers, the manufactures, the retailers, and the consumers in the demand markets are modeled. In turn, the supply chain network equilibrium model is proposed and computed by modified project contraction algorithm with fixed step. The effectiveness of the model is illustrated by numerical examples, and managerial insights are obtained through the analysis of advertising investment in multiple periods and advertising delay effect among different periods.

On-demand virtual optical network access using 100 Gb/s Ethernet.

Science.gov (United States)

Ishida, Osamu; Takamichi, Toru; Arai, Sachine; Kawate, Ryusuke; Toyoda, Hidehiro; Morita, Itsuro; Araki, Soichiro; Ichikawa, Toshiyuki; Hoshida, Takeshi; Murai, Hitoshi

2011-12-12

Our Terabit LAN initiatives attempt to enhance the scalability and utilization of lambda resources. This paper describes bandwidth-on-demand virtualized 100GE access to WDM networks on a field fiber test-bed using multi-domain optical-path provisioning. © 2011 Optical Society of America

Flexible Demand Control to Enhance the Dynamic Operation of Low Voltage Networks

DEFF Research Database (Denmark)

Diaz de Cerio Mendaza, Iker; Szczesny, Ireneusz Grzegorz; Pillai, Jayakrishnan Radhakrishna

2015-01-01

Moving towards a carbon free energy system has become an objective for many countries nowadays. Among other changes, the electrification of strategic sectors such as heating and transportation is inevitable. As a consequence, the current power system load will substantially increase...... for controlling the demand response of a low voltage grid. This is designed to; i) maximize the grid utilization, thereby reducing the need for reinforcement, ii) accommodate the maximum number of flexible loads and iii) satisfy the power and comfort requirements from each of the consumers in the network....... In this context, the nature of the expected loads (heat pumps, plug-in electric vehicles, etc.) makes the low voltage networks specially targeted. A promising solution to overcome the challenges resulting from their grid integration, is demand response. This paper introduces a hierarchical structure...

Building energy demand aggregation and simulation tools

DEFF Research Database (Denmark)

Gianniou, Panagiota; Heller, Alfred; Rode, Carsten

2015-01-01

to neighbourhoods and cities. Buildings occupy a key place in the development of smart cities as they represent an important potential to integrate smart energy solutions. Building energy consumption affects significantly the performance of the entire energy network. Therefore, a realistic estimation...... of the aggregated building energy use will not only ensure security of supply but also enhance the stabilization of national energy balances. In this study, the aggregation of building energy demand was investigated for a real case in Sønderborg, Denmark. Sixteen single-family houses -mainly built in the 1960s......- were examined, all connected to the regional district heating network. The aggregation of building energy demands was carried out according to typologies, being represented by archetype buildings. These houses were modelled with dynamic energy simulation software and with a simplified simulation tool...

Home Network Technologies and Automating Demand Response

Energy Technology Data Exchange (ETDEWEB)

McParland, Charles

2009-12-01

Over the past several years, interest in large-scale control of peak energy demand and total consumption has increased. While motivated by a number of factors, this interest has primarily been spurred on the demand side by the increasing cost of energy and, on the supply side by the limited ability of utilities to build sufficient electricity generation capacity to meet unrestrained future demand. To address peak electricity use Demand Response (DR) systems are being proposed to motivate reductions in electricity use through the use of price incentives. DR systems are also be design to shift or curtail energy demand at critical times when the generation, transmission, and distribution systems (i.e. the 'grid') are threatened with instabilities. To be effectively deployed on a large-scale, these proposed DR systems need to be automated. Automation will require robust and efficient data communications infrastructures across geographically dispersed markets. The present availability of widespread Internet connectivity and inexpensive, reliable computing hardware combined with the growing confidence in the capabilities of distributed, application-level communications protocols suggests that now is the time for designing and deploying practical systems. Centralized computer systems that are capable of providing continuous signals to automate customers reduction of power demand, are known as Demand Response Automation Servers (DRAS). The deployment of prototype DRAS systems has already begun - with most initial deployments targeting large commercial and industrial (C & I) customers. An examination of the current overall energy consumption by economic sector shows that the C & I market is responsible for roughly half of all energy consumption in the US. On a per customer basis, large C & I customers clearly have the most to offer - and to gain - by participating in DR programs to reduce peak demand. And, by concentrating on a small number of relatively

Measuring the impact of negative demand shocks on car dealer networks

NARCIS (Netherlands)

Albuquerque, P.; Bronnenberg, B.J.

2012-01-01

The goal of this paper is to study the behavior of consumers, dealers, and manufacturers in the car sector and present an approach that can be used by managers and policy makers to investigate the impact of significant demand shocks on profits, prices, and dealer networks. More specifically, we

Geospatial Analysis of the Building Heat Demand and Distribution Losses in a District Heating Network

Directory of Open Access Journals (Sweden)

Tobias Törnros

2016-11-01

Full Text Available The district heating (DH demand of various systems has been simulated in several studies. Most studies focus on the temporal aspects rather than the spatial component. In this study, the DH demand for a medium-sized DH network in a city in southern Germany is simulated and analyzed in a spatially explicit approach. Initially, buildings are geo-located and attributes obtained from various sources including building type, ground area, and number of stories are merged. Thereafter, the annual primary energy demand for heating and domestic hot water is calculated for individual buildings. Subsequently, the energy demand is aggregated on the segment level of an existing DH network and the water flow is routed through the system. The simulation results show that the distribution losses are overall the highest at the end segments (given in percentage terms. However, centrally located pipes with a low throughflow are also simulated to have high losses. The spatial analyses are not only useful when addressing the current demand. Based on a scenario taking into account the refurbishment of buildings and a decentralization of energy production, the future demand was also addressed. Due to lower demand, the distribution losses given in percentage increase under such conditions.

Competitive closed-loop supply chain network design with price-dependent demands

DEFF Research Database (Denmark)

Rezapour, Shabnam; Farahani, Reza Zanjirani; Fahimnia, Behnam

2015-01-01

Abstract This paper presents a bi-level model for the strategic reverse network design (upper level) and tactical/operational planning (lower level) of a closed-loop single-period supply chain operating in a competitive environment with price-dependent market demand. An existing supply chain (SC...... for the supply of new and remanufactured products. The performance behaviors of both SCs are evaluated with specific focus placed on investigating the impacts of the strategic facility location decisions of the new SC on the tactical/operational transport and inventory decisions of the overall network. The bi...

Deep Neural Network Based Demand Side Short Term Load Forecasting

Directory of Open Access Journals (Sweden)

Seunghyoung Ryu

2016-12-01

Full Text Available In the smart grid, one of the most important research areas is load forecasting; it spans from traditional time series analyses to recent machine learning approaches and mostly focuses on forecasting aggregated electricity consumption. However, the importance of demand side energy management, including individual load forecasting, is becoming critical. In this paper, we propose deep neural network (DNN-based load forecasting models and apply them to a demand side empirical load database. DNNs are trained in two different ways: a pre-training restricted Boltzmann machine and using the rectified linear unit without pre-training. DNN forecasting models are trained by individual customer’s electricity consumption data and regional meteorological elements. To verify the performance of DNNs, forecasting results are compared with a shallow neural network (SNN, a double seasonal Holt–Winters (DSHW model and the autoregressive integrated moving average (ARIMA. The mean absolute percentage error (MAPE and relative root mean square error (RRMSE are used for verification. Our results show that DNNs exhibit accurate and robust predictions compared to other forecasting models, e.g., MAPE and RRMSE are reduced by up to 17% and 22% compared to SNN and 9% and 29% compared to DSHW.

Peak load demand forecasting using two-level discrete wavelet decomposition and neural network algorithm

Science.gov (United States)

Bunnoon, Pituk; Chalermyanont, Kusumal; Limsakul, Chusak

2010-02-01

This paper proposed the discrete transform and neural network algorithms to obtain the monthly peak load demand in mid term load forecasting. The mother wavelet daubechies2 (db2) is employed to decomposed, high pass filter and low pass filter signals from the original signal before using feed forward back propagation neural network to determine the forecasting results. The historical data records in 1997-2007 of Electricity Generating Authority of Thailand (EGAT) is used as reference. In this study, historical information of peak load demand(MW), mean temperature(Tmean), consumer price index (CPI), and industrial index (economic:IDI) are used as feature inputs of the network. The experimental results show that the Mean Absolute Percentage Error (MAPE) is approximately 4.32%. This forecasting results can be used for fuel planning and unit commitment of the power system in the future.

Co-Planning of Demand Response and Distributed Generators in an Active Distribution Network

Directory of Open Access Journals (Sweden)

Yi Yu

2018-02-01

Full Text Available The integration of renewables is fast-growing, in light of smart grid technology development. As a result, the uncertain nature of renewables and load demand poses significant technical challenges to distribution network (DN daily operation. To alleviate such issues, price-sensitive demand response and distributed generators can be coordinated to accommodate the renewable energy. However, the investment cost for demand response facilities, i.e., load control switch and advanced metering infrastructure, cannot be ignored, especially when the responsive demand is large. In this paper, an optimal coordinated investment for distributed generator and demand response facilities is proposed, based on a linearized, price-elastic demand response model. To hedge against the uncertainties of renewables and load demand, a two-stage robust investment scheme is proposed, where the investment decisions are optimized in the first stage, and the demand response participation with the coordination of distributed generators is adjusted in the second stage. Simulations on the modified IEEE 33-node and 123-node DN demonstrate the effectiveness of the proposed model.

Better Water Demand and Pipe Description Improve the Distribution Network Modeling Results

Science.gov (United States)

Distribution system modeling simplifies pipe network in skeletonization and simulates the flow and water quality by using generalized water demand patterns. While widely used, the approach has not been examined fully on how it impacts the modeling fidelity. This study intends to ...

Natural gas demand forecast system based on the application of artificial neural networks

International Nuclear Information System (INIS)

Sanfeliu, J.M.; Doumanian, J.E.

1997-01-01

Gas Natural BAN, as a distribution gas company since 1993 in the north and west area of Buenos Aires Argentina, with 1,000,000 customers, had to develop a gas demand forecast system which should comply with the following basic requirements: Be able to do reliable forecasts with short historical information (2 years); Distinguish demands in areas of different characteristics, i.e. mainly residential, mainly industrial; Self-learning capability. To accomplish above goals, Gas Natural BAN chose in view of its own necessities, an artificial intelligence application (neural networks). 'SANDRA', the gas demand forecast system for gas distribution used by Gas Natural BAN, has the following features: Daily gas demand forecast, Hourly gas demand forecast and Breakdown of both forecast for each of the 3 basic zones in which the distribution area of Gas Natural BAN is divided. (au)

A Nondominated Genetic Algorithm Procedure for Multiobjective Discrete Network Design under Demand Uncertainty

OpenAIRE

Changzhi, Bian

2015-01-01

This paper addresses the multiobjective discrete network design problem under demand uncertainty. The OD travel demands are supposed to be random variables with the given probability distribution. The problem is formulated as a bilevel stochastic optimization model where the decision maker’s objective is to minimize the construction cost, the expectation, and the standard deviation of total travel time simultaneously and the user’s route choice is described using user equilibrium model on the...

Structuring energy supply and demand networks in a general equilibrium model to simulate global warming control strategies

International Nuclear Information System (INIS)

Hamilton, S.; Veselka, T.D.; Cirillo, R.R.

1991-01-01

Global warming control strategies which mandate stringent caps on emissions of greenhouse forcing gases can substantially alter a country's demand, production, and imports of energy products. Although there is a large degree of uncertainty when attempting to estimate the potential impact of these strategies, insights into the problem can be acquired through computer model simulations. This paper presents one method of structuring a general equilibrium model, the ENergy and Power Evaluation Program/Global Climate Change (ENPEP/GCC), to simulate changes in a country's energy supply and demand balance in response to global warming control strategies. The equilibrium model presented in this study is based on the principle of decomposition, whereby a large complex problem is divided into a number of smaller submodules. Submodules simulate energy activities and conversion processes such as electricity production. These submodules are linked together to form an energy supply and demand network. Linkages identify energy and fuel flows among various activities. Since global warming control strategies can have wide reaching effects, a complex network was constructed. The network represents all energy production, conversion, transportation, distribution, and utilization activities. The structure of the network depicts interdependencies within and across economic sectors and was constructed such that energy prices and demand responses can be simulated. Global warming control alternatives represented in the network include: (1) conservation measures through increased efficiency; and (2) substitution of fuels that have high greenhouse gas emission rates with fuels that have lower emission rates. 6 refs., 4 figs., 4 tabs

First field trial of Virtual Network Operator oriented network on demand (NoD) service provisioning over software defined multi-vendor OTN networks

Science.gov (United States)

Li, Yajie; Zhao, Yongli; Zhang, Jie; Yu, Xiaosong; Chen, Haoran; Zhu, Ruijie; Zhou, Quanwei; Yu, Chenbei; Cui, Rui

2017-01-01

A Virtual Network Operator (VNO) is a provider and reseller of network services from other telecommunications suppliers. These network providers are categorized as virtual because they do not own the underlying telecommunication infrastructure. In terms of business operation, VNO can provide customers with personalized services by leasing network infrastructure from traditional network providers. The unique business modes of VNO lead to the emergence of network on demand (NoD) services. The conventional network provisioning involves a series of manual operation and configuration, which leads to high cost in time. Considering the advantages of Software Defined Networking (SDN), this paper proposes a novel NoD service provisioning solution to satisfy the private network need of VNOs. The solution is first verified in the real software defined multi-domain optical networks with multi-vendor OTN equipment. With the proposed solution, NoD service can be deployed via online web portals in near-real time. It reinvents the customer experience and redefines how network services are delivered to customers via an online self-service portal. Ultimately, this means a customer will be able to simply go online, click a few buttons and have new services almost instantaneously.

Negative autoregulation matches production and demand in synthetic transcriptional networks.

Science.gov (United States)

Franco, Elisa; Giordano, Giulia; Forsberg, Per-Ola; Murray, Richard M

2014-08-15

We propose a negative feedback architecture that regulates activity of artificial genes, or "genelets", to meet their output downstream demand, achieving robustness with respect to uncertain open-loop output production rates. In particular, we consider the case where the outputs of two genelets interact to form a single assembled product. We show with analysis and experiments that negative autoregulation matches the production and demand of the outputs: the magnitude of the regulatory signal is proportional to the "error" between the circuit output concentration and its actual demand. This two-device system is experimentally implemented using in vitro transcriptional networks, where reactions are systematically designed by optimizing nucleic acid sequences with publicly available software packages. We build a predictive ordinary differential equation (ODE) model that captures the dynamics of the system and can be used to numerically assess the scalability of this architecture to larger sets of interconnected genes. Finally, with numerical simulations we contrast our negative autoregulation scheme with a cross-activation architecture, which is less scalable and results in slower response times.

A source-initiated on-demand routing algorithm based on the Thorup-Zwick theory for mobile wireless sensor networks.

Science.gov (United States)

Mao, Yuxin; Zhu, Ping

2013-01-01

The unreliability and dynamics of mobile wireless sensor networks make it hard to perform end-to-end communications. This paper presents a novel source-initiated on-demand routing mechanism for efficient data transmission in mobile wireless sensor networks. It explores the Thorup-Zwick theory to achieve source-initiated on-demand routing with time efficiency. It is able to find out shortest routing path between source and target in a network and transfer data in linear time. The algorithm is easy to be implemented and performed in resource-constrained mobile wireless sensor networks. We also evaluate the approach by analyzing its cost in detail. It can be seen that the approach is efficient to support data transmission in mobile wireless sensor networks.

Pseudo dynamic transitional modeling of building heating energy demand using artificial neural network

NARCIS (Netherlands)

Paudel, S.; Elmtiri, M.; Kling, W.L.; Corre, le O.; Lacarriere, B.

2014-01-01

This paper presents the building heating demand prediction model with occupancy profile and operational heating power level characteristics in short time horizon (a couple of days) using artificial neural network. In addition, novel pseudo dynamic transitional model is introduced, which consider

Supply-demand balance in outward-directed networks and Kleiber's law

OpenAIRE

Painter Page R

2005-01-01

Abstract Background Recent theories have attempted to derive the value of the exponent α in the allometric formula for scaling of basal metabolic rate from the properties of distribution network models for arteries and capillaries. It has recently been stated that a basic theorem relating the sum of nutrient currents to the specific nutrient uptake rate, together with a relationship claimed to be required in order to match nutrient supply to nutrient demand in 3-dimensional outward-directed n...

Categorical and continuous - disentangling the neural correlates of the carry effect in multi-digit addition

Directory of Open Access Journals (Sweden)

Dressel Katharina

2010-11-01

Full Text Available Abstract Background Recently it was suggested that the carry effect observed in addition involves both categorical and continuous processing characteristics. Methods In the present study, we aimed at identifying the specific neural correlates associated with processing either categorical or continuous aspects of the carry effect in an fMRI study on multi-digit addition. Results In line with our expectations, we observed two distinct parts of the fronto-parietal network subserving numerical cognition to be associated with either one of these two characteristics. On the one hand, the categorical aspect of the carry effect was associated with left-hemispheric language areas and the basal ganglia probably reflecting increased demands on procedural and problem solving processes. Complementarily, the continuous aspect of the carry effect was associated with increased intraparietal activation indicating increasing demands on magnitude processing as well as place-value integration with increasing unit sum. Conclusions In summary, the findings suggest representations and processes underlying the carry effect in multi-digit addition to be more complex and interactive than assumed previously.

Utilizing artificial neural networks to predict demand for weather-sensitive products at retail stores

OpenAIRE

Taghizadeh, Elham

2017-01-01

One key requirement for effective supply chain management is the quality of its inventory management. Various inventory management methods are typically employed for different types of products based on their demand patterns, product attributes, and supply network. In this paper, our goal is to develop robust demand prediction methods for weather sensitive products at retail stores. We employ historical datasets from Walmart, whose customers and markets are often exposed to extreme weather ev...

Strategic and Tactical Design of Competing Decentralized Supply Chain Networks with Risk-Averse Participants for Markets with Uncertain Demand

Directory of Open Access Journals (Sweden)

Ashkan Hafezalkotob

2011-01-01

Full Text Available An integrated equilibrium model for tactical decisions in network design is developed. We consider a decentralized supply chain network operating in markets under uncertain demands when there is a rival decentralized chain. The primary assumption is that two chains provide partial substitutable products to the markets, and markets' demands are affected by tactical decisions such as price, service level, and advertising expenditure. Each chain consists of one risk-averse manufacturer and a set of risk-averse retailers. The strategic decisions are frequently taking precedence over tactical ones. Therefore, we first find equilibrium of tactical decisions for each possible scenario of supply chain network. Afterwards, we find optimal distribution network of the new supply chain by the scenario evaluation method. Numerical example, including sensitivity analysis will illustrate how the conservative behaviors of chains' members affect expected demand, profit, and utility of each distribution scenario.

An Automation System for Optimizing a Supply Chain Network Design under the Influence of Demand Uncertainty

OpenAIRE

Polany, Rany

2012-01-01

This research develops and applies an integrated hierarchical framework for modeling a multi-echelon supply chain network design, under the influence of demand uncertainty. The framework is a layered integration of two levels: macro, high-level scenario planning combined with micro, low-level Monte Carlo simulation of uncertainties in demand. To facilitate rapid simulation of the effects of demand uncertainty, the integrated framework was implemented as a dashboard automation system using Mic...

MQARR-AODV: A NOVEL MULTIPATH QOS AWARE RELIABLE REVERSE ON-DEMAND DISTANCE VECTOR ROUTING PROTOCOL FOR MOBILE AD-HOC NETWORKS

Directory of Open Access Journals (Sweden)

K.G. Santhiya

2012-12-01

Full Text Available MANET (Mobile Ad-hoc Network is an infra structure less wireless ad-hoc network that does not require any basic central control. The topology of the network changes drastically due to very fast mobility of nodes. So an adaptive routing protocol is needed for routing in MANET. AODV (Ad-hoc On-demand Distance Vector routing is the effective and prominent on-demand Ad-hoc routing protocols. During route establishment phase in traditional AODV, only one route reply message will be sent in the reverse path to establish routing path. The high mobility of nodes may affect the reply messages which lead to the retransmission of route request message by the sender which in turn leads to higher communication delay, power consumption and the reduction in the ratio of packets delivered. Sending multiple route reply messages and establishing multiple paths in a single path discovery will reduce the routing overhead involved in maintaining the connection between source and destination nodes. Multipath routing can render high scalability, end-to-end throughput and provide load balancing in MANET. The new proposed novel Multipath QoS aware reliable routing protocol establishes two routes of maximum node disjoint paths and the data transfer is carried out in the two paths simultaneously. To select best paths, the new proposed protocol uses three parameters Link Eminence, MAC overhead and node residual energy. The experimental values prove that the MQARR-AODV protocol achieves high reliability, stability, low latency and outperforms AODV by the less energy consumption, overhead and delay.

The General Evolving Model for Energy Supply-Demand Network with Local-World

Science.gov (United States)

Sun, Mei; Han, Dun; Li, Dandan; Fang, Cuicui

2013-10-01

In this paper, two general bipartite network evolving models for energy supply-demand network with local-world are proposed. The node weight distribution, the "shifting coefficient" and the scaling exponent of two different kinds of nodes are presented by the mean-field theory. The numerical results of the node weight distribution and the edge weight distribution are also investigated. The production's shifted power law (SPL) distribution of coal enterprises and the installed capacity's distribution of power plants in the US are obtained from the empirical analysis. Numerical simulations and empirical results are given to verify the theoretical results.

The energy demand of fast neuronal network oscillations: insights from brain slice preparations

Directory of Open Access Journals (Sweden)

Oliver eKann

2012-01-01

Full Text Available Fast neuronal network oscillations in the gamma range (30-100 Hz in the cerebral cortex have been implicated in higher cognitive functions such as sensual perception, working memory, and, perhaps, consciousness. However, little is known about the energy demand of gamma oscillations. This is mainly caused by technical limitations that are associated with simultaneous recordings of neuronal activity and energy metabolism in small neuronal networks and at the level of mitochondria in vivo. Thus recent studies have focused on brain slice preparations to address the energy demand of gamma oscillations in vitro. Here, reports will be summarized and discussed that combined electrophysiological recordings, oxygen sensor microelectrodes and live-cell fluorescence imaging in acutely prepared slices and organotypic slice cultures of the hippocampus from both, mouse and rat. These reports consistently show that gamma oscillations can be reliably induced in hippocampal slice preparations by different pharmacological tools. They suggest that gamma oscillations are associated with high energy demand, requiring both rapid adaptation of oxidative energy metabolism and sufficient supply with oxygen and nutrients. These findings might help to explain the exceptional vulnerability of higher cognitive functions during pathological processes of the brain, such as circulatory disturbances, genetic mitochondrial diseases, and neurodegeneration.

77 FR 3544 - Meeting and Webinar on the Active Traffic and Demand Management and Intelligent Network Flow...

Science.gov (United States)

2012-01-24

... Intelligent Network Flow Optimization Operational Concepts; Notice of Public Meeting AGENCY: Research and... Demand Management (ADTM) and Intelligent Network Flow Optimization (INFLO) operational concepts. The ADTM... infrastructure. The vision for ATDM research is to allow transportation agencies to increase traffic flow...

Forecasting Electricity Demand in Thailand with an Artificial Neural Network Approach

Directory of Open Access Journals (Sweden)

Karin Kandananond

2011-08-01

Full Text Available Demand planning for electricity consumption is a key success factor for the development of any countries. However, this can only be achieved if the demand is forecasted accurately. In this research, different forecasting methods—autoregressive integrated moving average (ARIMA, artificial neural network (ANN and multiple linear regression (MLR—were utilized to formulate prediction models of the electricity demand in Thailand. The objective was to compare the performance of these three approaches and the empirical data used in this study was the historical data regarding the electricity demand (population, gross domestic product: GDP, stock index, revenue from exporting industrial products and electricity consumption in Thailand from 1986 to 2010. The results showed that the ANN model reduced the mean absolute percentage error (MAPE to 0.996%, while those of ARIMA and MLR were 2.80981 and 3.2604527%, respectively. Based on these error measures, the results indicated that the ANN approach outperformed the ARIMA and MLR methods in this scenario. However, the paired test indicated that there was no significant difference among these methods at α = 0.05. According to the principle of parsimony, the ARIMA and MLR models might be preferable to the ANN one because of their simple structure and competitive performance

A robust optimization model for green regional logistics network design with uncertainty in future logistics demand

Directory of Open Access Journals (Sweden)

Dezhi Zhang

2015-12-01

Full Text Available This article proposes a new model to address the design problem of a sustainable regional logistics network with uncertainty in future logistics demand. In the proposed model, the future logistics demand is assumed to be a random variable with a given probability distribution. A set of chance constraints with regard to logistics service capacity and environmental impacts is incorporated to consider the sustainability of logistics network design. The proposed model is formulated as a two-stage robust optimization problem. The first-stage problem before the realization of future logistics demand aims to minimize a risk-averse objective by determining the optimal location and size of logistics parks with CO2 emission taxes consideration. The second stage after the uncertain logistics demand has been determined is a scenario-based stochastic logistics service route choices equilibrium problem. A heuristic solution algorithm, which is a combination of penalty function method, genetic algorithm, and Gauss–Seidel decomposition approach, is developed to solve the proposed model. An illustrative example is given to show the application of the proposed model and solution algorithm. The findings show that total social welfare of the logistics system depends very much on the level of uncertainty in future logistics demand, capital budget for logistics parks, and confidence levels of the chance constraints.

Strategic and Tactical Design of Competing Decentralized Supply Chain Networks with Risk-Averse Participants for Markets with Uncertain Demand

OpenAIRE

Hafezalkotob, Ashkan; Makui, Ahmad; Sadjadi, Seyed Jafar

2011-01-01

An integrated equilibrium model for tactical decisions in network design is developed. We consider a decentralized supply chain network operating in markets under uncertain demands when there is a rival decentralized chain. The primary assumption is that two chains provide partial substitutable products to the markets, and markets' demands are affected by tactical decisions such as price, service level, and advertising expenditure. Each chain consists of one risk-averse manufacturer and a set...

Exergy and Energy Analysis of Low Temperature District Heating Network

DEFF Research Database (Denmark)

Li, Hongwei; Svendsen, Svend

is in line with a pilot project that is carrying out in Denmark with network supply/return temperature at 55oC/25 oC. The consumer domestic hot water (DHW) demand is supplied with a special designed district heating (DH) storage tank. The space heating (SH) demand is supplied with a low temperature radiator......Low temperature district heating (LTDH) with reduced network supply and return temperature provides better match of the low quality building thermal demand and the low quality waste heat supply. In this paper, an exemplary LTDH network was designed for 30 low energy demand residential houses, which....... The network thermal and hydraulic conditions were simulated under steady state with an in-house district heating network design and simulation code. Through simulation, the overall system energetic and exergetic efficiencies were calculated and the exergy losses for the major district heating system...

Optimizing Bus Frequencies under Uncertain Demand: Case Study of the Transit Network in a Developing City

Directory of Open Access Journals (Sweden)

Zhengfeng Huang

2013-01-01

Full Text Available Various factors can make predicting bus passenger demand uncertain. In this study, a bilevel programming model for optimizing bus frequencies based on uncertain bus passenger demand is formulated. There are two terms constituting the upper-level objective. The first is transit network cost, consisting of the passengers’ expected travel time and operating costs, and the second is transit network robustness performance, indicated by the variance in passenger travel time. The second term reflects the risk aversion of decision maker, and it can make the most uncertain demand be met by the bus operation with the optimal transit frequency. With transit link’s proportional flow eigenvalues (mean and covariance obtained from the lower-level model, the upper-level objective is formulated by the analytical method. In the lower-level model, the above two eigenvalues are calculated by analyzing the propagation of mean transit trips and their variation in the optimal strategy transit assignment process. The genetic algorithm (GA used to solve the model is tested in an example network. Finally, the model is applied to determining optimal bus frequencies in the city of Liupanshui, China. The total cost of the transit system in Liupanshui can be reduced by about 6% via this method.

Integration of V2H/V2G Hybrid System for Demand Response in Distribution Network

Energy Technology Data Exchange (ETDEWEB)

Wang, Yubo; Sheikh, Omar; Hu, Boyang; Chu, Chi-Cheng; Gadh, Rajit

2014-11-03

Integration of Electrical Vehicles (EVs) with power grid not only brings new challenges for load management, but also opportunities for distributed storage and generation in distribution network. With the introduction of Vehicle-to-Home (V2H) and Vehicle-to-Grid (V2G), EVs can help stabilize the operation of power grid. This paper proposed and implemented a hybrid V2H/V2G system with commercialized EVs, which is able to support both islanded AC/DC load and the power grid with one single platform. Standard industrial communication protocols are implemented for a seamless respond to remote Demand Respond (DR) signals. Simulation and implementation are carried out to validate the proposed design. Simulation and implementation results showed that the hybrid system is capable of support critical islanded DC/AC load and quickly respond to the remote DR signal for V2G within 1.5kW of power range.

A Multi-Objective Demand Side Management Considering ENS Cost in Smart Grids

DEFF Research Database (Denmark)

Yousefi Khanghah, Babak; Ghassemzadeh, Saeid; Hosseini, Seyed Hossein

2017-01-01

In this paper a new method is presented to achieve economic exploitation and proper usage of network capacity by exerting controlling actions over flexible loads and energy storage (ES) equipment. Multi-objective planning for demand response programs (DRP) and battery management policies is carried...... out by considering energy not supplied (ENS). In order to achieve an optimal scheduling, charge/discharge control for batteries, demand response programs and dispatch of controllable distributed generations (DGs) are also considered. Then, the balanced cost and benefits of participants are evaluated...

On-Demand Telemetry

Data.gov (United States)

National Aeronautics and Space Administration — AFRC has previously investigated the use of Network Based Telemetry. We will be building on that research to enable On-Demand Telemetry. On-Demand Telemetry is a way...

Receiver-Based Ad Hoc On Demand Multipath Routing Protocol for Mobile Ad Hoc Networks.

Science.gov (United States)

Al-Nahari, Abdulaziz; Mohamad, Mohd Murtadha

2016-01-01

Decreasing the route rediscovery time process in reactive routing protocols is challenging in mobile ad hoc networks. Links between nodes are continuously established and broken because of the characteristics of the network. Finding multiple routes to increase the reliability is also important but requires a fast update, especially in high traffic load and high mobility where paths can be broken as well. The sender node keeps re-establishing path discovery to find new paths, which makes for long time delay. In this paper we propose an improved multipath routing protocol, called Receiver-based ad hoc on demand multipath routing protocol (RB-AOMDV), which takes advantage of the reliability of the state of the art ad hoc on demand multipath distance vector (AOMDV) protocol with less re-established discovery time. The receiver node assumes the role of discovering paths when finding data packets that have not been received after a period of time. Simulation results show the delay and delivery ratio performances are improved compared with AOMDV.

An adaptive network-based fuzzy inference system for short-term natural gas demand estimation: Uncertain and complex environments

International Nuclear Information System (INIS)

Azadeh, A.; Asadzadeh, S.M.; Ghanbari, A.

2010-01-01

Accurate short-term natural gas (NG) demand estimation and forecasting is vital for policy and decision-making process in energy sector. Moreover, conventional methods may not provide accurate results. This paper presents an adaptive network-based fuzzy inference system (ANFIS) for estimation of NG demand. Standard input variables are used which are day of the week, demand of the same day in previous year, demand of a day before and demand of 2 days before. The proposed ANFIS approach is equipped with pre-processing and post-processing concepts. Moreover, input data are pre-processed (scaled) and finally output data are post-processed (returned to its original scale). The superiority and applicability of the ANFIS approach is shown for Iranian NG consumption from 22/12/2007 to 30/6/2008. Results show that ANFIS provides more accurate results than artificial neural network (ANN) and conventional time series approach. The results of this study provide policy makers with an appropriate tool to make more accurate predictions on future short-term NG demand. This is because the proposed approach is capable of handling non-linearity, complexity as well as uncertainty that may exist in actual data sets due to erratic responses and measurement errors.

WATER DEMAND PREDICTION USING ARTIFICIAL NEURAL ...

African Journals Online (AJOL)

This paper presents Hourly water demand prediction at the demand nodes of a water distribution network using NeuNet Pro 2.3 neural network software and the monitoring and control of water distribution using supervisory control. The case study is the Laminga Water Treatment Plant and its water distribution network, Jos.

Enhancing On-Demand Multicast Routing Protocols using Mobility Prediction in Mobile Ad-hoc Network

Directory of Open Access Journals (Sweden)

Nermin Makhlouf

2014-08-01

Full Text Available A Mobile Ad hoc Network (MANET is a self-organizing wireless communication network in which mobile devices are based on no infrastructure like base stations or access points. Minimal configuration and quick deployment make ad hoc networks suitable for emergency situations like disaster recovery or military conflict. Since node mobility may cause links to be broken frequently, a very important issue for routing in MANETs is how to set reliable paths which can last as long as possible. To solve this problem, non-random behaviors for the mobility patterns that mobile users exhibit are exploited. This paper introduces a scheme to improve On-Demand Multicast Routing Protocol (ODMRP performances by using mobility prediction. 

DReAM: Demand Response Architecture for Multi-level District Heating and Cooling Networks

Energy Technology Data Exchange (ETDEWEB)

Bhattacharya, Saptarshi; Chandan, Vikas; Arya, Vijay; Kar, Koushik

2017-05-19

In this paper, we exploit the inherent hierarchy of heat exchangers in District Heating and Cooling (DHC) networks and propose DReAM, a novel Demand Response (DR) architecture for Multi-level DHC networks. DReAM serves to economize system operation while still respecting comfort requirements of individual consumers. Contrary to many present day DR schemes that work on a consumer level granularity, DReAM works at a level of hierarchy above buildings, i.e. substations that supply heat to a group of buildings. This improves the overall DR scalability and reduce the computational complexity. In the first step of the proposed approach, mathematical models of individual substations and their downstream networks are abstracted into appropriately constructed low-complexity structural forms. In the second step, this abstracted information is employed by the utility to perform DR optimization that determines the optimal heat inflow to individual substations rather than buildings, in order to achieve the targeted objectives across the network. We validate the proposed DReAM framework through experimental results under different scenarios on a test network.

Energy and exergy analysis of low temperature district heating network

DEFF Research Database (Denmark)

Li, Hongwei; Svendsen, Svend

2012-01-01

is designed to supply heating for 30 low energy detached residential houses. The network operational supply/return temperature is set as 55 °C/25 °C, which is in line with a pilot project carried out in Denmark. Two types of in-house substations are analyzed to supply the consumer domestic hot water demand...... energy/exergy losses and increase the quality match between the consumer heating demand and the district heating supply.......Low temperature district heating with reduced network supply and return temperature provides better match of the low quality building heating demand and the low quality heating supply from waste heat or renewable energy. In this paper, a hypothetical low temperature district heating network...

Neural network controller for Active Demand-Side Management with PV energy in the residential sector

International Nuclear Information System (INIS)

Matallanas, E.; Castillo-Cagigal, M.; Gutiérrez, A.; Monasterio-Huelin, F.; Caamaño-Martín, E.; Masa, D.; Jiménez-Leube, J.

2012-01-01

Highlights: ► We have developed a neural controller for Active Demand-Side Management. ► The controller consists of Multilayer Perceptrons evolved with a genetic algorithm. ► The architecture of the controller is distributed and modular. ► The simulations show that the electrical local behavior improves. ► Active Demand-Side Management helps users to control his energy behaviour. -- Abstract: In this paper, we describe the development of a control system for Demand-Side Management in the residential sector with Distributed Generation. The electrical system under study incorporates local PV energy generation, an electricity storage system, connection to the grid and a home automation system. The distributed control system is composed of two modules: a scheduler and a coordinator, both implemented with neural networks. The control system enhances the local energy performance, scheduling the tasks demanded by the user and maximizing the use of local generation.

Social Demand of New Generation Information Network: Introduction to High Spectral Density Optical Communication Technology

Science.gov (United States)

Kamiya, Takeshi; Miyazaki, Tetsuya; Kubota, Fumito

In this section, first, current situation of traffic growth and penetration of broadband services are described. Then social demand, technical issues, and research trend for future information network in the United States, Europe, and Japan are described. Finally, a detailed construction of this book is introduced.

Hybrid Forecasting Approach Based on GRNN Neural Network and SVR Machine for Electricity Demand Forecasting

Directory of Open Access Journals (Sweden)

Weide Li

2017-01-01

Full Text Available Accurate electric power demand forecasting plays a key role in electricity markets and power systems. The electric power demand is usually a non-linear problem due to various unknown reasons, which make it difficult to get accurate prediction by traditional methods. The purpose of this paper is to propose a novel hybrid forecasting method for managing and scheduling the electricity power. EEMD-SCGRNN-PSVR, the proposed new method, combines ensemble empirical mode decomposition (EEMD, seasonal adjustment (S, cross validation (C, general regression neural network (GRNN and support vector regression machine optimized by the particle swarm optimization algorithm (PSVR. The main idea of EEMD-SCGRNN-PSVR is respectively to forecast waveform and trend component that hidden in demand series to substitute directly forecasting original electric demand. EEMD-SCGRNN-PSVR is used to predict the one week ahead half-hour’s electricity demand in two data sets (New South Wales (NSW and Victorian State (VIC in Australia. Experimental results show that the new hybrid model outperforms the other three models in terms of forecasting accuracy and model robustness.

An On-Demand Emergency Packet Transmission Scheme for Wireless Body Area Networks.

Science.gov (United States)

Al Ameen, Moshaddique; Hong, Choong Seon

2015-12-04

The rapid developments of sensor devices that can actively monitor human activities have given rise to a new field called wireless body area network (BAN). A BAN can manage devices in, on and around the human body. Major requirements of such a network are energy efficiency, long lifetime, low delay, security, etc. Traffic in a BAN can be scheduled (normal) or event-driven (emergency). Traditional media access control (MAC) protocols use duty cycling to improve performance. A sleep-wake up cycle is employed to save energy. However, this mechanism lacks features to handle emergency traffic in a prompt and immediate manner. To deliver an emergency packet, a node has to wait until the receiver is awake. It also suffers from overheads, such as idle listening, overhearing and control packet handshakes. An external radio-triggered wake up mechanism is proposed to handle prompt communication. It can reduce the overheads and improve the performance through an on-demand scheme. In this work, we present a simple-to-implement on-demand packet transmission scheme by taking into considerations the requirements of a BAN. The major concern is handling the event-based emergency traffic. The performance analysis of the proposed scheme is presented. The results showed significant improvements in the overall performance of a BAN compared to state-of-the-art protocols in terms of energy consumption, delay and lifetime.

An On-Demand Emergency Packet Transmission Scheme for Wireless Body Area Networks

Directory of Open Access Journals (Sweden)

Moshaddique Al Ameen

2015-12-01

Full Text Available The rapid developments of sensor devices that can actively monitor human activities have given rise to a new field called wireless body area network (BAN. A BAN can manage devices in, on and around the human body. Major requirements of such a network are energy efficiency, long lifetime, low delay, security, etc. Traffic in a BAN can be scheduled (normal or event-driven (emergency. Traditional media access control (MAC protocols use duty cycling to improve performance. A sleep-wake up cycle is employed to save energy. However, this mechanism lacks features to handle emergency traffic in a prompt and immediate manner. To deliver an emergency packet, a node has to wait until the receiver is awake. It also suffers from overheads, such as idle listening, overhearing and control packet handshakes. An external radio-triggered wake up mechanism is proposed to handle prompt communication. It can reduce the overheads and improve the performance through an on-demand scheme. In this work, we present a simple-to-implement on-demand packet transmission scheme by taking into considerations the requirements of a BAN. The major concern is handling the event-based emergency traffic. The performance analysis of the proposed scheme is presented. The results showed significant improvements in the overall performance of a BAN compared to state-of-the-art protocols in terms of energy consumption, delay and lifetime.

Devising a New Model of Demand-Based Learning Integrated with Social Networks and Analyses of its Performance

Directory of Open Access Journals (Sweden)

Bekim Fetaji

2018-02-01

Full Text Available The focus of the research study is to devise a new model for demand based learning that will be integrated with social networks such as Facebook, twitter and other. The study investigates this by reviewing the published literature and realizes a case study analyses in order to analyze the new models’ analytical perspectives of practical implementation. The study focuses on analyzing demand-based learning and investigating how it can be improved by devising a specific model that incorporates social network use. Statistical analyses of the results of the questionnaire through research of the raised questions and hypothesis showed that there is a need for introducing new models in the teaching process. The originality stands on the prologue of the social login approach to an educational environment, whereas the approach is counted as a contribution of developing a demand-based web application, which aims to modernize the educational pattern of communication, introduce the social login approach, and increase the process of knowledge transfer as well as improve learners’ performance and skills. Insights and recommendations are provided, argumented and discussed.

Software Defined Networking for Next Generation Converged Metro-Access Networks

Science.gov (United States)

Ruffini, M.; Slyne, F.; Bluemm, C.; Kitsuwan, N.; McGettrick, S.

2015-12-01

While the concept of Software Defined Networking (SDN) has seen a rapid deployment within the data center community, its adoption in telecommunications network has progressed slowly, although the concept has been swiftly adopted by all major telecoms vendors. This paper presents a control plane architecture for SDN-driven converged metro-access networks, developed through the DISCUS European FP7 project. The SDN-based controller architecture was developed in a testbed implementation targeting two main scenarios: fast feeder fiber protection over dual-homed Passive Optical Networks (PONs) and dynamic service provisioning over a multi-wavelength PON. Implementation details and results of the experiment carried out over the second scenario are reported in the paper, showing the potential of SDN in providing assured on-demand services to end-users.

Emergency response network design for hazardous materials transportation with uncertain demand

Directory of Open Access Journals (Sweden)

Kamran Shahanaghi

2012-10-01

Full Text Available Transportation of hazardous materials play an essential role on keeping a friendly environment. Every day, a substantial amount of hazardous materials (hazmats, such as flammable liquids and poisonous gases, need to be transferred prior to consumption or disposal. Such transportation may result in unsuitable events for people and environment. Emergency response network is designed for this reason where specialist responding teams resolve any issue as quickly as possible. This study proposes a new multi-objective model to locate emergency response centers for transporting the hazardous materials. Since many real-world applications are faced with uncertainty in input parameters, the proposed model of this paper also assumes that reference and demand to such centre is subject to uncertainty, where demand is fuzzy random. The resulted problem formulation is modelled as nonlinear non-convex mixed integer programming and we used NSGAII method to solve the resulted problem. The performance of the proposed model is examined with several examples using various probability distribution and they are compared with the performance of other existing method.

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

Directory of Open Access Journals (Sweden)

Bishnu P. Bhattarai

2017-01-01

Full Text Available This paper presents a multi-timescale control strategy to deploy electric vehicle (EV demand flexibility for simultaneously providing power balancing, grid congestion management, and economic benefits to participating actors. First, an EV charging problem is investigated from consumer, aggregator, 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 control.

Demanding Dynamics - Demand articulation of intermediary organisations in emerging pharmaceutical innovations

NARCIS (Netherlands)

Boon, W.P.C.

2008-01-01

User involvement in emerging technological fields is carried by so-called demand articulation processes. These demand articulation processes are interactive learning processes in which stakeholders try to address what they perceive as important characteristics of, and to unravel preferences for an

A multi-stage stochastic program for supply chain network redesign problem with price-dependent uncertain demands

DEFF Research Database (Denmark)

Fattahi, Mohammad; Govindan, Kannan; Keyvanshokooh, Esmaeil

2018-01-01

In this paper, we address a multi-period supply chain network redesign problem in which customer zones have price-dependent stochastic demand for multiple products. A novel multi-stage stochastic program is proposed to simultaneously make tactical decisions including products' prices and strategic...... redesign decisions. Existing uncertainty in potential demands of customer zones is modeled through a finite set of scenarios, described in the form of a scenario tree. The scenarios are generated using a Latin Hypercube Sampling method and then a forward scenario construction technique is employed...

Large-Scale Demand Driven Design of a Customized Bus Network: A Methodological Framework and Beijing Case Study

Directory of Open Access Journals (Sweden)

Jihui Ma

2017-01-01

Full Text Available In recent years, an innovative public transportation (PT mode known as the customized bus (CB has been proposed and implemented in many cities in China to efficiently and effectively shift private car users to PT to alleviate traffic congestion and traffic-related environmental pollution. The route network design activity plays an important role in the CB operation planning process because it serves as the basis for other operation planning activities, for example, timetable development, vehicle scheduling, and crew scheduling. In this paper, according to the demand characteristics and operational purpose, a methodological framework that includes the elements of large-scale travel demand data processing and analysis, hierarchical clustering-based route origin-destination (OD region division, route OD region pairing, and a route selection model is proposed for CB network design. Considering the operating cost and social benefits, a route selection model is proposed and a branch-and-bound-based solution method is developed. In addition, a computer-aided program is developed to analyze a real-world Beijing CB route network design problem. The results of the case study demonstrate that the current CB network of Beijing can be significantly improved, thus demonstrating the effectiveness of the proposed methodology.

Anticipation of Traffic Demands to Guarantee QoS in IP/Optical Networks

Directory of Open Access Journals (Sweden)

Carolina Pinart

2010-09-01

Full Text Available Traffic in the Internet backbone is expected to grow above a few Tbit/s in 2020. To cope with this, operators are moving to IP/optical network architectures, where IP is the convergence layer for all services. On the other hand, the quality of service (QoS requirements of future applications encompasses the individualization of services and the assurance of stricter quality parameters such as latency, jitter or capacity. In other words, future optical networks will not only transport more IP data, but they will also have to offer differentiated QoS requirements to services. Finally, some emerging applications, e.g., grid computing, need greater flexibility in the usage of network resources, which involves establishing and releasing connections as if they were virtualized resources controlled by other elements or layers. In this context, traffic-driven lightpath provisioning and service-plane approaches arise as very interesting candidate solutions to solve the main challenges described above. This work reviews the concepts of service-oriented and self-managed networks and relates them to propose an integrated approach to assure QoS by offering flow-aware networking in the sense that traffic demands will be anticipated in a suitable way, lightpaths will be established taking into account QoS information (i.e., impairments and complex services will be decomposed into optical connections so that the above techniques can be employed to assure QoS for any service.

Distribution network design under demand uncertainty using genetic algorithm and Monte Carlo simulation approach: a case study in pharmaceutical industry

Science.gov (United States)

Izadi, Arman; Kimiagari, Ali Mohammad

2014-05-01

Distribution network design as a strategic decision has long-term effect on tactical and operational supply chain management. In this research, the location-allocation problem is studied under demand uncertainty. The purposes of this study were to specify the optimal number and location of distribution centers and to determine the allocation of customer demands to distribution centers. The main feature of this research is solving the model with unknown demand function which is suitable with the real-world problems. To consider the uncertainty, a set of possible scenarios for customer demands is created based on the Monte Carlo simulation. The coefficient of variation of costs is mentioned as a measure of risk and the most stable structure for firm's distribution network is defined based on the concept of robust optimization. The best structure is identified using genetic algorithms and 14 % reduction in total supply chain costs is the outcome. Moreover, it imposes the least cost variation created by fluctuation in customer demands (such as epidemic diseases outbreak in some areas of the country) to the logistical system. It is noteworthy that this research is done in one of the largest pharmaceutical distribution firms in Iran.

Energy Efficiency in Self Organising Networks

DEFF Research Database (Denmark)

Kisielius, Edvinas; Popovska Avramova, Andrijana; Zakrzewska, Anna

2013-01-01

We evaluate the performance of an energy efficient algorithm that controls power emissions and the number of powered cell sites (eNBs) in overlaid Long Term Evolution (LTE) networks. Simulations are carried out in OPNET Modeler and we investigate cells cites designed to meet peak hours trac demand...

Comprehensive Forecast of Urban Water-Energy Demand Based on a Neural Network Model

Directory of Open Access Journals (Sweden)

Ziyi Yin

2018-03-01

Full Text Available Water-energy nexus has been a popular topic of rese arch in recent years. The relationships between the demand for water resources and energy are intense and closely connected in urban areas. The primary, secondary, and tertiary industry gross domestic product (GDP, the total population, the urban population, annual precipitation, agricultural and industrial water consumption, tap water supply, the total discharge of industrial wastewater, the daily sewage treatment capacity, total and domestic electricity consumption, and the consumption of coal in industrial enterprises above the designed size were chosen as input indicators. A feedforward artificial neural network model (ANN based on a back-propagation algorithm with two hidden layers was constructed to combine urban water resources with energy demand. This model used historical data from 1991 to 2016 from Wuxi City, eastern China. Furthermore, a multiple linear regression model (MLR was introduced for comparison with the ANN. The results show the following: (a The mean relative error values of the forecast and historical urban water-energy demands are 1.58 % and 2.71%, respectively; (b The predicted water-energy demand value for 2020 is 4.843 billion cubic meters and 47.561 million tons of standard coal equivalent; (c The predicted water-energy demand value in the year 2030 is 5.887 billion cubic meters and 60.355 million tons of standard coal equivalent; (d Compared with the MLR, the ANN performed better in fitting training data, which achieved a more satisfactory accuracy and may provide a reference for urban water-energy supply planning decisions.

Fiber to the home: next generation network

Science.gov (United States)

Yang, Chengxin; Guo, Baoping

2006-07-01

Next generation networks capable of carrying converged telephone, television (TV), very high-speed internet, and very high-speed bi-directional data services (like video-on-demand (VOD), Game etc.) strategy for Fiber To The Home (FTTH) is presented. The potential market is analyzed. The barriers and some proper strategy are also discussed. Several technical problems like various powering methods, optical fiber cables, and different network architecture are discussed too.

Reduction of peak energy demand based on smart appliances energy consumption adjustment

Science.gov (United States)

Powroźnik, P.; Szulim, R.

2017-08-01

In the paper the concept of elastic model of energy management for smart grid and micro smart grid is presented. For the proposed model a method for reducing peak demand in micro smart grid has been defined. The idea of peak demand reduction in elastic model of energy management is to introduce a balance between demand and supply of current power for the given Micro Smart Grid in the given moment. The results of the simulations studies were presented. They were carried out on real household data available on UCI Machine Learning Repository. The results may have practical application in the smart grid networks, where there is a need for smart appliances energy consumption adjustment. The article presents a proposal to implement the elastic model of energy management as the cloud computing solution. This approach of peak demand reduction might have application particularly in a large smart grid.

Demand Modelling in Telecommunications

Directory of Open Access Journals (Sweden)

M. Chvalina

2009-01-01

Full Text Available This article analyses the existing possibilities for using Standard Statistical Methods and Artificial Intelligence Methods for a short-term forecast and simulation of demand in the field of telecommunications. The most widespread methods are based on Time Series Analysis. Nowadays, approaches based on Artificial Intelligence Methods, including Neural Networks, are booming. Separate approaches will be used in the study of Demand Modelling in Telecommunications, and the results of these models will be compared with actual guaranteed values. Then we will examine the quality of Neural Network models. 

Sustainability Analysis and Market Demand Estimation in the Retail Industry through a Convolutional Neural Network

Directory of Open Access Journals (Sweden)

Luyao Wang

2018-05-01

Full Text Available The Chinese retail industry is expected to grow dramatically over the next few years, owing to the rapid increase in purchasing power of Chinese consumers. Retail managers should analyze the market demands and avoid dull sales to promote the sustainable development of the retail industry. Economic sustainability in the retail industry, which refers to a suitable return of investment, requires the implementation of precise product allocation strategies in different regions. This study proposed a hybrid model to evaluate economic sustainability in the preparation of goods of retail shops on the basis of market demand evaluation. Through a grid-based convolutional neural network, a regression model was first established to model the relationship between consumer distribution and the potential market demand. Then, another model was proposed to evaluate the sustainability among regions based on their supply-demand analysis. An experiment was conducted based on the actual sales data of retail shops in Guiyang, China. Results showed an immense diversity of sustainability in the entire city and three classes of regions were distinguished, namely, high, moderate, and limited. Our model was proven to be effective in the sustainability evaluation of supply and demand in the retail industry after validation showed that its accuracy reached 92.8%.

Cloudification of mmwave-based and packet-based fronthaul for future heterogeneous mobile networks

DEFF Research Database (Denmark)

Artuso, Matteo; Marcano, Andrea; Christiansen, Henrik Lehrmann

2015-01-01

is seen as an enabler for next-generation heterogeneous mobile networks. This allows for simpler base stations and savings in deployment costs, but introduces challenges in the fronthaul network connecting the sites to the processing pool. The fronthaul needs to have very low latency and high capacity......, but the traditional architecture of this network uses point-to-point links between each site and the pool, thus making it impossible to share capacity as the demands change. To address these challenges, a flexible network architecture for the fronthaul is presented that is based on Ethernet to carry the baseband......Current deployments of mobile networks are seriously challenged by increasing capacity demands, and traditional solutions are no longer practical. The use of small cells is considered as a viable technique to meet these demands. In this context, the use of centralized signal processing in a pool...

Prediction of Tourism Demand in Iran by Using Artificial Neural Network (ANN and Supporting Vector Machine (SVR

Directory of Open Access Journals (Sweden)

Seyedehelham Sadatiseyedmahalleh

2016-02-01

Full Text Available This research examines and proves this effectiveness connected with artificial neural networks (ANNs as an alternative approach to the use of Support Vector Machine (SVR in the tourism research. This method can be used for the tourism industry to define the turism’s demands in Iran. The outcome reveals the use of ANNs in tourism research might result in better quotations when it comes to prediction bias and accuracy. Even more applications of ANNs in the context of tourism demand evaluation is needed to establish and validate the effects.

Ad hoc laser networks component technology for modular spacecraft

Science.gov (United States)

Huang, Xiujun; Shi, Dele; Shen, Jingshi

2017-10-01

Distributed reconfigurable satellite is a new kind of spacecraft system, which is based on a flexible platform of modularization and standardization. Based on the module data flow analysis of the spacecraft, this paper proposes a network component of ad hoc Laser networks architecture. Low speed control network with high speed load network of Microwave-Laser communication mode, no mesh network mode, to improve the flexibility of the network. Ad hoc Laser networks component technology was developed, and carried out the related performance testing and experiment. The results showed that ad hoc Laser networks components can meet the demand of future networking between the module of spacecraft.

Applying demand side management using a generalised grid supportive approach

NARCIS (Netherlands)

Blaauwbroek, N.; Nguyen, H.P.; Slootweg, J.G.

2017-01-01

Demand side management is often seen as a promising tool for distribution network operators to mitigate network operation limit violations. Many demand side management applications have been proposed, each with their own objectives and methodology. Quite often, these demand side management

Implementation of IGMP v3 and its application to IPTV carrying network

Science.gov (United States)

Zhou, Min; Dong, Ximing

2008-11-01

IGMP is a host-router signaling protocol, and it is used to manage the membership of Internet Protocol multicast groups for IPv4. IGMPv3 adds "source filtering" function required to support SSM. Firstly, this paper analyses the improvements and implementation of IGMPv3. Secondly, it points out the problems when applying IGMPv3 to IPTV carrying network. Then it presents the solutions by improving IGMPv3 protocol to reduce channel zapping time which is one of the important metrics affecting the QoE in IPTV service. Method to realize the end user authentication, authorization and accounting in the IP multicast security and authentication area by extending the IGMPv3 protocol is described at last.

Demand response: Social welfare maximisation in an unbundled energy market - Case study for the low-voltage networks of a distribution network operator in the Netherlands

NARCIS (Netherlands)

Nijhuis, M.; Babar, M.; Gibescu, M.; Cobben, J.F.G.

2017-01-01

With the introduction of smart meters, dynamic pricing and home energy management systems, residential customers are able to react to changes in electricity prices. In an unbundled market, the energy supplier and the network operator may have conflicting interests with respect to demand response

Demand response : social welfare maximisation in an unbundled energy market : case study for the low-voltage networks of a distribution network operator in the Netherlands

NARCIS (Netherlands)

Nijhuis, M.; Babar, M.; Gibescu, M.; Cobben, J.F.G.

2015-01-01

With the introduction of smart meters, dynamic pricing and home energy management systems, residential customers are able to react to changes in electricity prices. In an unbundled market, the energy supplier and the network operator may have conflicting interests with respect to demand response

INDIA’S ELECTRICITY DEMAND FORECAST USING REGRESSION ANALYSIS AND ARTIFICIAL NEURAL NETWORKS BASED ON PRINCIPAL COMPONENTS

Directory of Open Access Journals (Sweden)

S. Saravanan

2012-07-01

Full Text Available Power System planning starts with Electric load (demand forecasting. Accurate electricity load forecasting is one of the most important challenges in managing supply and demand of the electricity, since the electricity demand is volatile in nature; it cannot be stored and has to be consumed instantly. The aim of this study deals with electricity consumption in India, to forecast future projection of demand for a period of 19 years from 2012 to 2030. The eleven input variables used are Amount of CO2 emission, Population, Per capita GDP, Per capita gross national income, Gross Domestic savings, Industry, Consumer price index, Wholesale price index, Imports, Exports and Per capita power consumption. A new methodology based on Artificial Neural Networks (ANNs using principal components is also used. Data of 29 years used for training and data of 10 years used for testing the ANNs. Comparison made with multiple linear regression (based on original data and the principal components and ANNs with original data as input variables. The results show that the use of ANNs with principal components (PC is more effective.

Smart control for minimizing distribution network reinforcement cost due to electrification

International Nuclear Information System (INIS)

Pudjianto, Danny; Djapic, Predrag; Aunedi, Marko; Gan, Chin Kim; Strbac, Goran; Huang, Sikai; Infield, David

2013-01-01

Electrification of transport fleets and heating sectors is seen as one of the key strategies to further reduce the use of fossil fuels and the resulting greenhouse gas emissions. However, it will potentially cause a significant increase of electricity peak demand and have adverse consequences on the electricity system, in particular on distribution networks. This paper will address the benefits of various applications of smart network control and demand response technologies for enhancing the integration of these future load categories, and for improvements in operation management and efficient use of distribution network assets. A range of numerical simulations have been carried out on different distribution network topologies (rural and urban networks) to identify the need and the cost of network reinforcement required to accommodate future load under various operating strategies such as Business as Usual (passive demand and passive network) against the smart grid approach. Applications of smart Plug-in vehicle (PiV) charging, smart heat pumps, and optimised control of network voltage regulators to reduce network investment have been studied, and selected key results of our studies on evaluating the benefits of implementing these technologies for Great Britain's distribution networks are presented and discussed in this paper. - Highlights: ► Growth of electricity loads driven by electrification of transport and heat will be significant. ► It will increase the electricity peak demand up to 2–3 times and cost tens of billion pounds if we maintain Business as Usual approach. ► A coordinated application of smart demand technologies can significantly reduce this cost. ► It requires sets of policies and regulations to facilitate timely deployment of such technologies.

Impacts of climate change on electricity network business

International Nuclear Information System (INIS)

Auvinen, O.; Martikainen, A.

2006-01-01

In this project the impact of climate change on electricity network business was study. The results are based on RCAO climate model scenarios. The climate predictions were composed to the period 2016- 2045. The period 1960-1990 was used as a control period. The climate predictions were composed for precipitation, temperature, hoarfrost, thunder, ground frost and wind. Impacts of the change of the climate variables on electricity network business were estimated from technical and economical points of view. It is expected that climate change will cause more damages than benefits on the electricity network business. The increase of the number of network faults will be the most significant and demanding disadvantage caused by climate change in distribution network. If networks are not improved to be more resistant for faults, then thunder, heavy snow and wind cause more damages especially to overhead lines in medium voltage network. Increasing precipitation and decreasing amount of ground frost weaken the strength of soil. The construction work will be more difficult with the present vehicles because wet and unfrozen ground can not carry heavy vehicles. As a consequence of increasing temperature, the demand of heating energy will decrease and the demand of cooling energy will increase. This is significant for the electricity consumption and the peak load of temperature-dependent electricity users. (orig.)

Cost and Demand Characteristics of Telecom Networks

DEFF Research Database (Denmark)

Falch, Morten

1997-01-01

The Chapter presents the general characteristics of the cost and demand profiles for telecommunication services and identifies the barriers towards a free competitive market for telecommunication services related to these characteristics.......The Chapter presents the general characteristics of the cost and demand profiles for telecommunication services and identifies the barriers towards a free competitive market for telecommunication services related to these characteristics....

Capacity planning of a wide-sense nonblocking generalized survivable network

Science.gov (United States)

Ho, Kwok Shing; Cheung, Kwok Wai

2006-06-01

Generalized survivable networks (GSNs) have two interesting properties that are essential attributes for future backbone networks--full survivability against link failures and support for dynamic traffic demands. GSNs incorporate the nonblocking network concept into the survivable network models. Given a set of nodes and a topology that is at least two-edge connected, a certain minimum capacity is required for each edge to form a GSN. The edge capacity is bounded because each node has an input-output capacity limit that serves as a constraint for any allowable traffic demand matrix. The GSN capacity planning problem is nondeterministic polynomial time (NP) hard. We first give a rigorous mathematical framework; then we offer two different solution approaches. The two-phase approach is fast, but the joint optimization approach yields a better bound. We carried out numerical computations for eight networks with different topologies and found that the cost of a GSN is only a fraction (from 52% to 89%) more than that of a static survivable network.

Software Defined Networking Demands on Software Technologies

DEFF Research Database (Denmark)

Galinac Grbac, T.; Caba, Cosmin Marius; Soler, José

2015-01-01

Software Defined Networking (SDN) is a networking approach based on a centralized control plane architecture with standardised interfaces between control and data planes. SDN enables fast configuration and reconfiguration of the network to enhance resource utilization and service performances....... This new approach enables a more dynamic and flexible network, which may adapt to user needs and application requirements. To this end, systemized solutions must be implemented in network software, aiming to provide secure network services that meet the required service performance levels. In this paper......, we review this new approach to networking from an architectural point of view, and identify and discuss some critical quality issues that require new developments in software technologies. These issues we discuss along with use case scenarios. Here in this paper we aim to identify challenges...

A Novel approach for predicting monthly water demand by combining singular spectrum analysis with neural networks

Science.gov (United States)

Zubaidi, Salah L.; Dooley, Jayne; Alkhaddar, Rafid M.; Abdellatif, Mawada; Al-Bugharbee, Hussein; Ortega-Martorell, Sandra

2018-06-01

Valid and dependable water demand prediction is a major element of the effective and sustainable expansion of municipal water infrastructures. This study provides a novel approach to quantifying water demand through the assessment of climatic factors, using a combination of a pretreatment signal technique, a hybrid particle swarm optimisation algorithm and an artificial neural network (PSO-ANN). The Singular Spectrum Analysis (SSA) technique was adopted to decompose and reconstruct water consumption in relation to six weather variables, to create a seasonal and stochastic time series. The results revealed that SSA is a powerful technique, capable of decomposing the original time series into many independent components including trend, oscillatory behaviours and noise. In addition, the PSO-ANN algorithm was shown to be a reliable prediction model, outperforming the hybrid Backtracking Search Algorithm BSA-ANN in terms of fitness function (RMSE). The findings of this study also support the view that water demand is driven by climatological variables.

Integrated Strategic Planning of Global Production Networks and Financial Hedging under Uncertain Demands and Exchange Rates

Directory of Open Access Journals (Sweden)

Achim Koberstein

2013-11-01

Full Text Available In this paper, we present a multi-stage stochastic programming model that integrates financial hedging decisions into the planning of strategic production networks under uncertain exchange rates and product demands. This model considers the expenses of production plants and the revenues of markets in different currency areas. Financial portfolio planning decisions for two types of financial instruments, forward contracts and options, are represented explicitly by multi-period decision variables and a multi-stage scenario tree. Using an illustrative example, we analyze the impact of exchange-rate and demand volatility, the level of investment expenses and interest rate spreads on capacity location and dimensioning decisions. In particular, we show that, in the illustrative example, the exchange-rate uncertainty cannot be completely eliminated by financial hedging in the presence of demand uncertainty. In this situation, we find that the integrated model can result in better strategic planning decisions for a risk-averse decision maker compared to traditional modeling approaches.

Forecasting water demand using back propagation networks in the operation of reservoirs in the citarum cascade, west java, indonesia

Directory of Open Access Journals (Sweden)

Mulya R. Mashudi

2017-11-01

Full Text Available This study investigates the use of Neural Networks (NN as a potential means of more accurately forecasting water demand in the Citarum River basin cascade. Neural Networks have the ability to recognise nonlinear patterns when sufficiently trained with historical data. The study constructs a NN model of the cascade, based on Back Propagation Networks (BPN. Data representing physical characteristics and meteorological conditions in the Citarum River basin from 1989 through 1995 were used to train the BPN. Nonlinear activation functions (sigmoid, tangent, and gaussian functions and hidden layers in the BPN were chosen for the study.

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...

Demand Response Design and Use Based on Network Locational Marginal Prices

DEFF Research Database (Denmark)

Morais, Hugo; Faria, Pedro; Vale, Zita

2014-01-01

Power systems have been experiencing huge changes mainly due to the substantial increase of distributed generation (DG) and the operation in competitive environments. Virtual Power Players (VPP) can aggregate several players, namely a diversity of energy resources, including distributed generation...... (DG) based on several technologies, electric storage systems (ESS) and demand response (DR). Energy resources management gains an increasing relevance in this competitive context. This makes the DR use more interesting and flexible, giving place to a wide range of new opportunities. This paper...... proposes a methodology to support VPPs in the DR programs’ management, considering all the existing energy resources (generation and storage units) and the distribution network. The proposed method is based on locational marginal prices (LMP) values. The evaluation of the impact of using DR specific...

Advanced Communication Technology Satellite (ACTS) Very Small Aperture Terminal (VSAT) Network Control Performance

Science.gov (United States)

Coney, T. A.

1996-01-01

This paper discusses the performance of the network control function for the Advanced Communications Technology Satellite (ACTS) very small aperture terminal (VSAT) full mesh network. This includes control of all operational activities such as acquisition, synchronization, timing and rain fade compensation as well as control of all communications activities such as on-demand integrated services (voice, video, and date) connects and disconnects Operations control is provided by an in-band orderwire carried in the baseboard processor (BBP) control burst, the orderwire burst, the reference burst, and the uplink traffic burst. Communication services are provided by demand assigned multiple access (DAMA) protocols. The ACTS implementation of DAMA protocols ensures both on-demand and integrated voice, video and data services. Communications services control is also provided by the in-band orderwire but uses only the reference burst and the uplink traffic burst. The performance of the ACTS network control functions have been successfully tested during on-orbit checkout and in various VSAT networks in day to day operations. This paper discusses the network operations and services control performance.

Energy and exergy analysis of low temperature district heating network

International Nuclear Information System (INIS)

Li, Hongwei; Svendsen, Svend

2012-01-01

Low temperature district heating with reduced network supply and return temperature provides better match of the low quality building heating demand and the low quality heating supply from waste heat or renewable energy. In this paper, a hypothetical low temperature district heating network is designed to supply heating for 30 low energy detached residential houses. The network operational supply/return temperature is set as 55 °C/25 °C, which is in line with a pilot project carried out in Denmark. Two types of in-house substations are analyzed to supply the consumer domestic hot water demand. The space heating demand is supplied through floor heating in the bathroom and low temperature radiators in the rest of rooms. The network thermal and hydraulic conditions are simulated under steady state. A district heating network design and simulation code is developed to incorporate the network optimization procedure and the network simultaneous factor. Through the simulation, the overall system energy and exergy efficiencies are calculated and the exergy losses for the major district heating system components are identified. Based on the results, suggestions are given to further reduce the system energy/exergy losses and increase the quality match between the consumer heating demand and the district heating supply. -- Highlights: ► Exergy and energy analysis for low and medium temperature district heating systems. ► Different district heating network dimensioning methods are analyzed. ► Major exergy losses are identified in the district heating network and the in-house substations. ► Advantages to apply low temperature district heating are highlighted through exergy analysis. ► The influence of thermal by-pass on system exergy/energy performance is analyzed.

Real-Time Congestion Management in Distribution Networks by Flexible Demand Swap

DEFF Research Database (Denmark)

Huang, Shaojun; Wu, Qiuwei

2017-01-01

In addition to the day-ahead congestion management in distribution networks, the real-time congestion management is very important because many unforeseen events can occur at the real operation time, e.g. loss of generation of distributed energy resources (DERs) or inaccurate forecast of energy...... pumps (HPs) for real time congestion management. The swap method can maintain the power balance of the system and avoid the imbalance cost of activating the flexibility service. An algorithm for forming swaps through optimal power flow (OPF) and mixed integer linear programming (MILP) is proposed...... consumption or production. Flexibility service from demand will be a good option to solve the real-time congestions if the cost of activating the flexibility service is fully addressed. This paper proposes a new method, namely “swap”, to employ the flexibility service from electric vehicles (EVs) and heat...

Managing Disasters Using Pressure Dependent Demand Analysis – Case Study of Shirpur Town

Directory of Open Access Journals (Sweden)

Madhuri Mulay

2016-12-01

Full Text Available Water is the most essential component for sustaining lives of humans and other living creatures. Supplying potable water with adequate residual pressure is a fundamental responsibility of city administration, which they do during normal conditions. But sometimes, abnormal conditions are formed resulting pressure deficient conditions during the daily operations of water distribution networks. These are caused due to common occurrences such as pump failure, pipe bursts, and isolation of major pipes from the system for planned maintenance work and excessive firefighting demands. Total water stop conditions may arise, when the major source supplying water to the city fails in natural disaster such as floods, Tsunami, earthquake or manmade disaster such as terrorist attack. Unlike the pipe failure, longer time is required for restoring water in case of source failure condition. In such situations, the quantity of water is generally decreased and the water distribution systems (WDS may not be able to satisfy all consumers’ demands. In this context, the assumption that all demands are fully satisfied regardless of the pressure in the system becomes unreasonable. A realistic behavior of the network performance can only be attained by considering demands to be pressure dependent. This paper aims to describe how pressure dependent demand analysis is useful for the simulation of disaster scenario due to source failure of the Shirpur town. The simulation of failure scenario is carried out using WaterGEMs software. The paper also aims to prepare the action plans for the recovery of water supply in such crisis conditions.

Influence of road network and population demand assumptions in evacuation modeling for distant tsunamis

Science.gov (United States)

Henry, Kevin; Wood, Nathan J.; Frazier, Tim G.

2017-01-01

Tsunami evacuation planning in coastal communities is typically focused on local events where at-risk individuals must move on foot in a matter of minutes to safety. Less attention has been placed on distant tsunamis, where evacuations unfold over several hours, are often dominated by vehicle use and are managed by public safety officials. Traditional traffic simulation models focus on estimating clearance times but often overlook the influence of varying population demand, alternative modes, background traffic, shadow evacuation, and traffic management alternatives. These factors are especially important for island communities with limited egress options to safety. We use the coastal community of Balboa Island, California (USA), as a case study to explore the range of potential clearance times prior to wave arrival for a distant tsunami scenario. We use a first-in–first-out queuing simulation environment to estimate variations in clearance times, given varying assumptions of the evacuating population (demand) and the road network over which they evacuate (supply). Results suggest clearance times are less than wave arrival times for a distant tsunami, except when we assume maximum vehicle usage for residents, employees, and tourists for a weekend scenario. A two-lane bridge to the mainland was the primary traffic bottleneck, thereby minimizing the effect of departure times, shadow evacuations, background traffic, boat-based evacuations, and traffic light timing on overall community clearance time. Reducing vehicular demand generally reduced clearance time, whereas improvements to road capacity had mixed results. Finally, failure to recognize non-residential employee and tourist populations in the vehicle demand substantially underestimated clearance time.

Robust On-Demand Multipath Routing with Dynamic Path Upgrade for Delay-Sensitive Data over Ad Hoc Networks

Directory of Open Access Journals (Sweden)

Sunil Kumar

2013-01-01

Full Text Available Node mobility in mobile ad hoc networks (MANETs causes frequent route breakages and intermittent link stability. In this paper, we introduce a robust routing scheme, known as ad hoc on-demand multipath distance vector with dynamic path update (AOMDV-DPU, for delay-sensitive data transmission over MANET. The proposed scheme improves the AOMDV scheme by incorporating the following features: (i a routing metric based on the combination of minimum hops and received signal strength indicator (RSSI for discovery of reliable routes; (ii a local path update mechanism which strengthens the route, reduces the route breakage frequency, and increases the route longevity; (iii a keep alive mechanism for secondary route maintenance which enables smooth switching between routes and reduces the route discovery frequency; (iv a packet salvaging scheme to improve packet delivery in the event of a route breakage; and (v low HELLO packet overhead. The simulations are carried out in ns-2 for varying node speeds, number of sources, and traffic load conditions. Our AOMDV-DPU scheme achieves significantly higher throughput, lower delay, routing overhead, and route discovery frequency and latency compared to AOMDV. For H.264 compressed video traffic, AOMDV-DPU scheme achieves 3 dB or higher PSNR gain over AOMDV at both low and high node speeds.

POLARIS: Agent-based modeling framework development and implementation for integrated travel demand and network and operations simulations

Energy Technology Data Exchange (ETDEWEB)

Auld, Joshua; Hope, Michael; Ley, Hubert; Sokolov, Vadim; Xu, Bo; Zhang, Kuilin

2016-03-01

This paper discusses the development of an agent-based modelling software development kit, and the implementation and validation of a model using it that integrates dynamic simulation of travel demand, network supply and network operations. A description is given of the core utilities in the kit: a parallel discrete event engine, interprocess exchange engine, and memory allocator, as well as a number of ancillary utilities: visualization library, database IO library, and scenario manager. The overall framework emphasizes the design goals of: generality, code agility, and high performance. This framework allows the modeling of several aspects of transportation system that are typically done with separate stand-alone software applications, in a high-performance and extensible manner. The issue of integrating such models as dynamic traffic assignment and disaggregate demand models has been a long standing issue for transportation modelers. The integrated approach shows a possible way to resolve this difficulty. The simulation model built from the POLARIS framework is a single, shared-memory process for handling all aspects of the integrated urban simulation. The resulting gains in computational efficiency and performance allow planning models to be extended to include previously separate aspects of the urban system, enhancing the utility of such models from the planning perspective. Initial tests with case studies involving traffic management center impacts on various network events such as accidents, congestion and weather events, show the potential of the system.

Operations of electric taxis to serve advance reservations by trip chaining: Sensitivity analysis on network size, customer demand and number of charging stations

Directory of Open Access Journals (Sweden)

Hao Wang

2016-10-01

Full Text Available This research investigated the performance of an Electric Taxi (ET fleet that catered solely for customers with advance reservations. In a previously related research, a customized Paired Pickup and Delivery Problem with Time Window and Charging Station (PPDPTWCS had been formulated to solve for the minimum number of taxis that would serve a fixed set of customer demand. The concept behind this fleet optimization was to chain multiple customer trips and trips to Charging Stations (CSs to form a route and assigned to a taxi driver. In this paper the sensitivity of the ET fleet’s operations with respect to network sizes, customer demand densities and number of CSs have been investigated. It also analyzed the market shares of the CSs and the occupancy of a CS over time. The results showed that, (1 the expansion of network size or the increase in customer demand density led to increase in fleet size, number of trips to the CSs and maximum occupancies at the CSs but these performance measures grew at different rates; (2 when the network size and number of CSs were fixed, an increase in customer demand density led to a better utilization of taxis in terms of more customers served per taxi and higher average revenue per taxi; (3 given the same network size and demand density, the ET fleet’s performance was relatively insensitive to the number of CSs; and (4 the usage of individual CS was affected by the number of CS and their locations; and (5 when all the ETs were fully charged at the beginning of the same shift hour, they visited the CSs in bunches when their batteries were about to run out. These findings contribute to a better understanding of the operations of the ET fleet and the CSs. They could be used for making better decisions in the planning of ET operations.

Experimental demonstration of bandwidth on demand (BoD) provisioning based on time scheduling in software-defined multi-domain optical networks

Science.gov (United States)

Zhao, Yongli; Li, Yajie; Wang, Xinbo; Chen, Bowen; Zhang, Jie

2016-09-01

A hierarchical software-defined networking (SDN) control architecture is designed for multi-domain optical networks with the Open Daylight (ODL) controller. The OpenFlow-based Control Virtual Network Interface (CVNI) protocol is deployed between the network orchestrator and the domain controllers. Then, a dynamic bandwidth on demand (BoD) provisioning solution is proposed based on time scheduling in software-defined multi-domain optical networks (SD-MDON). Shared Risk Link Groups (SRLG)-disjoint routing schemes are adopted to separate each tenant for reliability. The SD-MDON testbed is built based on the proposed hierarchical control architecture. Then the proposed time scheduling-based BoD (Ts-BoD) solution is experimentally demonstrated on the testbed. The performance of the Ts-BoD solution is evaluated with respect to blocking probability, resource utilization, and lightpath setup latency.

Robust total energy demand estimation with a hybrid Variable Neighborhood Search – Extreme Learning Machine algorithm

International Nuclear Information System (INIS)

Sánchez-Oro, J.; Duarte, A.; Salcedo-Sanz, S.

2016-01-01

Highlights: • The total energy demand in Spain is estimated with a Variable Neighborhood algorithm. • Socio-economic variables are used, and one year ahead prediction horizon is considered. • Improvement of the prediction with an Extreme Learning Machine network is considered. • Experiments are carried out in real data for the case of Spain. - Abstract: Energy demand prediction is an important problem whose solution is evaluated by policy makers in order to take key decisions affecting the economy of a country. A number of previous approaches to improve the quality of this estimation have been proposed in the last decade, the majority of them applying different machine learning techniques. In this paper, the performance of a robust hybrid approach, composed of a Variable Neighborhood Search algorithm and a new class of neural network called Extreme Learning Machine, is discussed. The Variable Neighborhood Search algorithm is focused on obtaining the most relevant features among the set of initial ones, by including an exponential prediction model. While previous approaches consider that the number of macroeconomic variables used for prediction is a parameter of the algorithm (i.e., it is fixed a priori), the proposed Variable Neighborhood Search method optimizes both: the number of variables and the best ones. After this first step of feature selection, an Extreme Learning Machine network is applied to obtain the final energy demand prediction. Experiments in a real case of energy demand estimation in Spain show the excellent performance of the proposed approach. In particular, the whole method obtains an estimation of the energy demand with an error lower than 2%, even when considering the crisis years, which are a real challenge.

Analysis of Environmental Carrying Capacity with Emergy Perspective of Jeju Island

Directory of Open Access Journals (Sweden)

Chanhoon Jung

2018-05-01

Full Text Available Jeju Island experienced an approximately 42% increase in energy consumption from 2006 to 2015 and the demand for energy consumption is expected to continue to increase. Thus, Jeju Island is planning a project entitled “Carbon Free Island by 2030” to promote sustainable development and is required to estimate the environmental carrying capacity for future energy demand changes. The purpose of this study was to calculate the emergy inherent in Jeju Island’s energy, materials, and information in 2015 using the emergy analysis method and local characteristics. In addition, this study aimed to estimate the emergy indices to evaluate the environmental carrying capacity for sustainable development in 2005, 2015, and 2030 considering the future energy demand. This study’s outputs provide the environmental carrying capacity with emergy indices, such as the percent renewable (%Renew, emergy yield ratio (EYR, environmental loading ratio (ELR, sustainability index (SI, and carrying capacity of the population (CCP for social and economic activities on Jeju Island, which are expected to be saturated. These findings show regions with heavy tourism require development strategies, including the concept of environmental carrying capacity.

Flexible investment under uncertainty in smart distribution networks with demand side response: Assessment framework and practical implementation

International Nuclear Information System (INIS)

Schachter, Jonathan A.; Mancarella, Pierluigi; Moriarty, John; Shaw, Rita

2016-01-01

Classical deterministic models applied to investment valuation in distribution networks may not be adequate for a range of real-world decision-making scenarios as they effectively ignore the uncertainty found in the most important variables driving network planning (e.g., load growth). As greater uncertainty is expected from growing distributed energy resources in distribution networks, there is an increasing risk of investing in too much or too little network capacity and hence causing the stranding and inefficient use of network assets; these costs are then passed on to the end-user. An alternative emerging solution in the context of smart grid development is to release untapped network capacity through Demand-Side Response (DSR). However, to date there is no approach able to quantify the value of ‘smart’ DSR solutions against ‘conventional’ asset-heavy investments. On these premises, this paper presents a general real options framework and a novel probabilistic tool for the economic assessment of DSR for smart distribution network planning under uncertainty, which allows the modeling and comparison of multiple investment strategies, including DSR and capacity reinforcements, based on different cost and risk metrics. In particular the model provides an explicit quantification of the economic value of DSR against alternative investment strategies. Through sensitivity analysis it is able to indicate the maximum price payable for DSR service such that DSR remains economically optimal against these alternatives. The proposed model thus provides Regulators with clear insights for overseeing DSR contractual arrangements. Further it highlights that differences exist in the economic perspective of the regulated DNO business and of customers. Our proposed model is therefore capable of highlighting instances where a particular investment strategy is favorable to the DNO but not to its customers, or vice-versa, and thus aspects of the regulatory framework which may

VuFind: eBooks on Demand Suchmaschine

OpenAIRE

Gstrein, Silvia

2011-01-01

The eBooks-on-Demand (EOD) network provides a trans-European digital document delivery service for end-users from all over the world offering digitization on demand of the public domain holdings of participating libraries. Currently the EOD network comprises over 30 libraries from 12 European countries. The service is offered through „EOD buttons“ placed at each record in the different library catalogues. Already in the first years of the service a common interface to search for all books off...

GLIF – striving towards a high-performance on-demand network

CERN Multimedia

Kristina Gunne

2010-01-01

If you were passing through the Mezzanine in the Main Building a couple of weeks ago, you probably noticed the large tiled panel display showing an ultra-high resolution visualization model of dark matter, developed by Cosmogrid. The display was one of the highlights of the 10th Annual Global Lambda Grid Workshop demo session, together with the first ever transfer of over 35 Gbit/second from one PC to another between the SARA Computing Centre in Amsterdam and CERN.   GLIF display. The transfer of such large amounts of data at this speed has been made possible thanks to the GLIF community's vision of a new computing paradigm, in which the central architectural element is an end-to-end path built on optical network wavelengths (so called lambdas). You may think of this as an on-demand private highway for data transfer: by using it you avoid the normal internet exchange points and “traffic jams”. GLIF is a virtual international organization managed as a cooperative activity, wi...

Quality-on-Demand Compression of EEG Signals for Telemedicine Applications Using Neural Network Predictors

Directory of Open Access Journals (Sweden)

N. Sriraam

2011-01-01

Full Text Available A telemedicine system using communication and information technology to deliver medical signals such as ECG, EEG for long distance medical services has become reality. In either the urgent treatment or ordinary healthcare, it is necessary to compress these signals for the efficient use of bandwidth. This paper discusses a quality on demand compression of EEG signals using neural network predictors for telemedicine applications. The objective is to obtain a greater compression gains at a low bit rate while preserving the clinical information content. A two-stage compression scheme with a predictor and an entropy encoder is used. The residue signals obtained after prediction is first thresholded using various levels of thresholds and are further quantized and then encoded using an arithmetic encoder. Three neural network models, single-layer and multi-layer perceptrons and Elman network are used and the results are compared with linear predictors such as FIR filters and AR modeling. The fidelity of the reconstructed EEG signal is assessed quantitatively using parameters such as PRD, SNR, cross correlation and power spectral density. It is found from the results that the quality of the reconstructed signal is preserved at a low PRD thereby yielding better compression results compared to results obtained using lossless scheme.

New Method for Leakage Detection by Using Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Mohammad Attari

2018-03-01

Full Text Available Nowadays water loss has been turned into a global concern and on the other hand the demand for water is increasing. This problem has made the demand management and consumption pattern reform necessary. One of the most important methods for managing water consumption is to decrease the water loss. In this study by using neural networks, a new method is presented to specify the location and quantity of leakages in water distribution networks.  In this method, by producing the training data and applying it to neural network, the network is able to determine approximate location and quantity of nodal leakage with receiving the nodal pressure. Production of training data is carried out by applying assumed leakage to specific nodes in the network and calculating the new nodal pressures. The results show that by minimum use of hydraulic data taken from pressures, not only this method can determine the location of nodal leakages, but also it can specify the amount of leakage on each node with reasonable accuracy.

Influence of network demands on power plant operation

International Nuclear Information System (INIS)

Spalthoff, F.J.

1974-01-01

The demands which are made by the user on an energy generation system are investigated and thoughts on the provision of the energy needed as well as procuring the supply are put forward. The consequences these user demands upon generating units in power plants have and the technical possibilities to meet these requirements are explained. The study ends with prospects of feasible developments through modern information systems. (orig./RW) [de

Notification: Follow-Up on OIG Report 12-P-0417, Weaknesses in EPA’s Management of the Radiation Network System Demand Attention

Science.gov (United States)

Project #OPE-FY14-0010, January 2, 2014. The EPA OIG is beginning preliminary research on the EPA's actions to address the recommendations in the Apr 19, 2012, OIG Report, Weaknesses in EPA's Management of the Radiation Network System Demand Attention.

Accreditation and training on internal dosimetry in a laboratory network in Brazil: an increasing demand.

Science.gov (United States)

Dantas, B M; Dantas, A L A; Acar, M E D; Cardoso, J C S; Julião, L M Q C; Lima, M F; Taddei, M H T; Arine, D R; Alonso, T; Ramos, M A P; Fajgelj, A

2011-03-01

In recent years, Brazilian Nuclear Programme has been reviewed and updated by government authorities in face of the demand for energy supply and its associated environmental constraints. The immediate impact of new national programmes and projects in nuclear field is the increase in the number of exposed personnel and the consequent need for reliable dosimetry services in the country. Several Technical Documents related to internal dosimetry have been released by the International Atomic Energy Agency and International Commission on Radiological Protection. However, standard bioassay procedures and methodologies for bioassay data interpretation are still under discussion and, in some cases, both in routine and emergency internal monitoring, procedures can vary from one laboratory to another and responses may differ markedly among Dosimetry Laboratories. Thus, it may be difficult to interpret and use bioassay data generated from different laboratories of a network. The main goal of this work is to implement a National Network of Laboratories aimed to provide reliable internal monitoring services in Brazil. The establishment of harmonised in vivo and in vitro radioanalytical techniques, dose assessment methods and the implementation of the ISO/IEC 17025 requirements will result in the recognition of technical competence of the network.

Minimum cost connection networks

DEFF Research Database (Denmark)

Hougaard, Jens Leth; Tvede, Mich

2015-01-01

In the present paper we consider the allocation of costs in connection networks. Agents have connection demands in form of pairs of locations they want to have connected. Connections between locations are costly to build. The problem is to allocate costs of networks satisfying all connection...... demands. We use a few axioms to characterize allocation rules that truthfully implement cost minimizing networks satisfying all connection demands in a game where: (1) a central planner announces an allocation rule and a cost estimation rule; (2) every agent reports her own connection demand as well...... as all connection costs; (3) the central planner selects a cost minimizing network satisfying reported connection demands based on the estimated costs; and, (4) the planner allocates the true costs of the selected network. It turns out that an allocation rule satisfies the axioms if and only if relative...

The 30/20 GHz communications satellite trunking network study

Science.gov (United States)

Kolb, W.

1981-01-01

Alternative transmission media for a CONUS-wide trunking network in the years 1990 and 2000 are examined. The alternative technologies comprised fiber optic cable, conventional C- and Ku-band satellites, and 30/20 GHz satellites. Three levels of implementation were considered - a 10-city network, a 20-city network, and a 40-city network. The cities selected were the major metropolitan areas with the greatest communications demand. All intercity voice, data, and video traffic carried more than 40 miles was included in the analysis. In the optimized network, traffic transmitted less than 500 miles was found to be better served by fiber optic cable in 1990. By the year 2000, the crossover point would be down to 200 miles, assuming availability of 30/20 GHz satellites.

A mismatch between supply and demand of social support in dementia care: a qualitative study on the perspectives of spousal caregivers and their social network members.

Science.gov (United States)

Dam, Alieske E H; Boots, Lizzy M M; van Boxtel, Martin P J; Verhey, Frans R J; de Vugt, Marjolein E

2017-06-13

Access to social support contributes to feelings of independence and better social health. This qualitative study aims to investigate multi-informant perspectives on informal social support in dementia care networks. Ten spousal caregivers of people with dementia (PwD) completed an ecogram, a social network card and a semi-structured interview. The ecogram aimed to trigger subjective experiences regarding social support. Subsequently, 17 network members were interviewed. The qualitative analyses identified codes, categories, and themes. Sixth themes emerged: (1) barriers to ask for support; (2) facilitators to ask for support; (3) barriers to offer support; (4) facilitators to offer support; (5) a mismatch between supply and demand of social support; and (6) openness in communication to repair the imbalance. Integrating social network perspectives resulted in a novel model identifying a mismatch between the supply and demand of social support, strengthened by a cognitive bias: caregivers reported to think for other social network members and vice versa. Openness in communication in formal and informal care systems might repair this mismatch.

Comparison of neural network applications for channel assignment in cellular TDMA networks and dynamically sectored PCS networks

Science.gov (United States)

Hortos, William S.

1997-04-01

The use of artificial neural networks (NNs) to address the channel assignment problem (CAP) for cellular time-division multiple access and code-division multiple access networks has previously been investigated by this author and many others. The investigations to date have been based on a hexagonal cell structure established by omnidirectional antennas at the base stations. No account was taken of the use of spatial isolation enabled by directional antennas to reduce interference between mobiles. Any reduction in interference translates into increased capacity and consequently alters the performance of the NNs. Previous studies have sought to improve the performance of Hopfield- Tank network algorithms and self-organizing feature map algorithms applied primarily to static channel assignment (SCA) for cellular networks that handle uniformly distributed, stationary traffic in each cell for a single type of service. The resulting algorithms minimize energy functions representing interference constraint and ad hoc conditions that promote convergence to optimal solutions. While the structures of the derived neural network algorithms (NNAs) offer the potential advantages of inherent parallelism and adaptability to changing system conditions, this potential has yet to be fulfilled the CAP for emerging mobile networks. The next-generation communication infrastructures must accommodate dynamic operating conditions. Macrocell topologies are being refined to microcells and picocells that can be dynamically sectored by adaptively controlled, directional antennas and programmable transceivers. These networks must support the time-varying demands for personal communication services (PCS) that simultaneously carry voice, data and video and, thus, require new dynamic channel assignment (DCA) algorithms. This paper examines the impact of dynamic cell sectoring and geometric conditioning on NNAs developed for SCA in omnicell networks with stationary traffic to improve the metrics

Batch sequencing of oil derivates in pipeline networks; Sequenciamento de bateladas de derivados leves de petroleo numa rede dutoviaria

Energy Technology Data Exchange (ETDEWEB)

Bonacin, Mario Vicente; Oliveira, Daniel Rossato de; Czaikowski, Daniel Irineu; Polli, Helton Luis; Magatao, Leandro; Stebel, Sergio Leandro; Neves Junior, Flavio [Universidade Tecnologica Federal do Parana (UTFPR), Curitiba, PR (Brazil); Ribas, Paulo Cesar [PETROBRAS S.A., Rio de Janeiro, RJ (Brazil). Centro de Pesquisas (CENPES)

2008-07-01

This work presents a computational tool to assist the operational scheduling of a pipeline network. In this network, transfer of products is carried out by batches, from a source to a destination. This tool implements a proposal to determine priorities of the outgoing batches as well as alternatives for sequencing them fulfilling the stated periods stipulated. This proposal uses an analysis of production and demand plans, stockage, products draining in terminals, as well as operational restrictions of the pipeline network, looking for optimizing the use of resources such as pipes, bombs and tanks. The scenario in study is composed by 14 areas (4 refineries, 2 harbours, 6 distribution centres and 2 costumers) and 29 pipes. Prioritizing the attendance to the areas of source or demand, the algorithm carries choices between routes and possible batches volumes, considering calculations of time windows, that determine the limited interval when transference operations must occur. Moreover, operations called 'lung' are also treated, which involve flow changes during the movement. (author)

Analysis of Facebook content demand patterns

OpenAIRE

Kihl, Maria; Larsson, Robin; Unnervik, Niclas; Haberkamm, Jolina; Arvidsson, Åke; Aurelius, Andreas

2014-01-01

Data volumes in communication networks increase rapidly. Further, usage of social network applications is very wide spread among users, and among these applications, Facebook is the most popular. In this paper, we analyse user demands patterns and content popularity of Facebook generated traffic. The data comes from residential users in two metropolitan access networks in Sweden, and we analyse more than 17 million images downloaded by almost 16,000 Facebook users. We show that the distributi...

Sensitivity analysis of energy demands on performance of CCHP system

International Nuclear Information System (INIS)

Li, C.Z.; Shi, Y.M.; Huang, X.H.

2008-01-01

Sensitivity analysis of energy demands is carried out in this paper to study their influence on performance of CCHP system. Energy demand is a very important and complex factor in the optimization model of CCHP system. Average, uncertainty and historical peaks are adopted to describe energy demands. The mix-integer nonlinear programming model (MINLP) which can reflect the three aspects of energy demands is established. Numerical studies are carried out based on energy demands of a hotel and a hospital. The influence of average, uncertainty and peaks of energy demands on optimal facility scheme and economic advantages of CCHP system are investigated. The optimization results show that the optimal GT's capacity and economy of CCHP system mainly lie on the average energy demands. Sum of capacities of GB and HE is equal to historical heating demand peaks, and sum of capacities of AR and ER are equal to historical cooling demand peaks. Maximum of PG is sensitive with historical peaks of energy demands and not influenced by uncertainty of energy demands, while the corresponding influence on DH is adverse

Money Demand Features in CEE Countries

Directory of Open Access Journals (Sweden)

Valentina-Ioana MERA

2016-01-01

Full Text Available The existence of a stable relationship between money demand and its determinants is important for the efficiency of monetary policy. In this paper we carried a preliminary analysis on the variables that can influence money demand in five Central and Eastern European countries (Bulgaria, Czech Republic, Hungary, Poland and Romania in order to determine which characteristics define the evolution of money demand and its determinants, and how volatile they are. The results indicate a number of similarities in terms of monetary development and also suggest that some additional variables that may influence money demand in this specific sample.

Demand side participation for frequency containment in the web of cells architecture

NARCIS (Netherlands)

Syed, M.H.; Burt, G.M.; Kok, J.K.; Hulst, R. d

2015-01-01

A large number of demand side management schemes have been proposed in literature for provision of frequency control ancillary services to the network. However, it is assumed that all the flexible devices within the network are managed and controlled under one demand side management (DSM) scheme. In

Window-Based Popularity Caching for IPTV On-Demand Services

OpenAIRE

Hsuan Chiu; Chi-He Chang; Chao-Wei Tseng; Chi-Shi Liu

2011-01-01

In recent years, many telecommunication companies have regarded IP network as a new delivery platform for providing TV services because IP network is equipped with two-way and high-speed communication abilities which are appropriate to provide on-demand services and linear TV programs. However, in this IPTV system, the requests of VOD (video on demand) are usually aggregated in a short period intensively and user preferences are fluctuated dynamically. Moreover, the VOD content is updated fre...

Economic assessment of smart grids solutions. Analysis carried out by the distribution network operators. Executive Summary 2017. The new paths of electricity

International Nuclear Information System (INIS)

2017-05-01

The economic viability of the Smart grids solutions is a key concern. This was highlighted in a letter from the ministries for the Environment, Sustainable Development and Energy and for the Economy, Industry and Digital Technology, which requested additional information regarding this question with regard to the distribution and transmission networks. Enedis and ADEeF (Association gathering electricity distributors in France), have realized a study on the economic assessment of smart grids solutions, in order to analyze associated costs and benefits. This study is part of a global approach conducted by the Ministries and in collaboration with ADEME and RTE. The functions featured in this study concern the transmission substation and MV network: Operational planning system, Extension of self-healing capabilities of the distribution network, Centralised dynamic voltage control, Self-adaptive reactive power control by MV producers, Active power curtailment of MV production, Use of flexibility for demand constraints. The results presented in this study are coherent with actual investment decisions and foreshadow future action plans

Ongoing activity in temporally coherent networks predicts intra-subject fluctuation of response time to sporadic executive control demands.

Science.gov (United States)

Nozawa, Takayuki; Sugiura, Motoaki; Yokoyama, Ryoichi; Ihara, Mizuki; Kotozaki, Yuka; Miyauchi, Carlos Makoto; Kanno, Akitake; Kawashima, Ryuta

2014-01-01

Can ongoing fMRI BOLD signals predict fluctuations in swiftness of a person's response to sporadic cognitive demands? This is an important issue because it clarifies whether intrinsic brain dynamics, for which spatio-temporal patterns are expressed as temporally coherent networks (TCNs), have effects not only on sensory or motor processes, but also on cognitive processes. Predictivity has been affirmed, although to a limited extent. Expecting a predictive effect on executive performance for a wider range of TCNs constituting the cingulo-opercular, fronto-parietal, and default mode networks, we conducted an fMRI study using a version of the color-word Stroop task that was specifically designed to put a higher load on executive control, with the aim of making its fluctuations more detectable. We explored the relationships between the fluctuations in ongoing pre-trial activity in TCNs and the task response time (RT). The results revealed the existence of TCNs in which fluctuations in activity several seconds before the onset of the trial predicted RT fluctuations for the subsequent trial. These TCNs were distributed in the cingulo-opercular and fronto-parietal networks, as well as in perceptual and motor networks. Our results suggest that intrinsic brain dynamics in these networks constitute "cognitive readiness," which plays an active role especially in situations where information for anticipatory attention control is unavailable. Fluctuations in these networks lead to fluctuations in executive control performance.

CRISP. Market-oriented online supply-demand matching

International Nuclear Information System (INIS)

Kamphuis, I.G.; Kester, J.C.P.; Carlsson, P; Akkermans, H.

2004-04-01

Current power distribution systems are operated in a top-down manner. Power production control and price formation take place on a central level on the basis of relatively static data from a data collection and dispatching network with a limited scope and granularity. When incorporating a more considerable fraction of small-scale producers on the basis of, for instance, renewable energy, operation of the distribution grid requires more data to be collected from a more extensive information and data communication network. Furthermore, increased local flows, in the form of two-way communication with distributed computation techniques, enable a more dynamic adaptation in power supply and demand patterns paving the way to a flexible way of embedding of ill-predictable supply of some types of renewable energy sources. DSM-programs have been in use in the utility sector for years now. In this document, first, current Demand Side Management (DSM) and Demand Response Resource (DRR) techniques are discussed; then, supply side management especially in a DG (Distributed Generation) context is treated. A framework of novel concepts and possible technology directions is presented subsequently and some preliminary scenarios are shown to illustrate these concepts. An overview of more flexible supply and demand matching schemes is given essentially based on four distinct types of SDM clusters. It appears, that it is possible to fulfil requirements for these distributed environments in terms of needed information and communication technology, ICT, if these are paralleled with the expected future penetration of ever-smaller scale data-exchange networks at power customer sites. Agent technology using algorithms from micro-economic market theory offers a promising possibility for managing the complexity of price formation and supply demand matching in these fine-grained bottom-up control distribution networks. Implication of these technical developments in terms of market and business

Impacts of climate change on electricity network business

International Nuclear Information System (INIS)

Martikainen, A.

2006-04-01

Climate has a significant impact on the electricity network business. The electricity network is under the weather pressure all the time and it is planned and constructed to withstand normal climatic stresses. The electricity network that has been planned and constructed now, is expected to be in operation next 40 years. If climatic stresses change in this period, it can cause significant impacts on electricity network business. If the impacts of climate change are figured out in advance, it is possible to mitigate negative points of climate change and exploit the positive points. In this paper the impact of climate change on electricity network business is presented. The results are based on RCAO climate model scenarios. The climate predictions were composed to the period 2016. 2045. The period 1960.1990 was used as a control period. The climate predictions were composed for precipitation, temperature, hoarfrost, thunder, ground frost and wind. The impacts of the change of the climate variables on electricity network business were estimated from technical and economical points of view. The estimation was based on the change predictions of the climate variables. It is expected that climate change will cause more damages than benefits on the electricity network business. The increase of the number of network faults will be the most significant and demanding disadvantage caused by climate change. If networks are not improved to be more resistant for faults, then thunder, heavy snow and wind cause more damages especially to overhead lines in medium voltage network. Increasing precipitation and decreasing amount of ground frost weaken the strength of soil. The construction work will be more difficult with the present vehicles because wet and unfrozen ground can not carry heavy vehicles. As a consequence of increasing temperature, the demand of heating energy will decrease and the demand of cooling energy will increase. This is significant for the electricity

A Complex Network Approach for the Estimation of the Energy Demand of Electric Mobility.

Science.gov (United States)

Mureddu, Mario; Facchini, Angelo; Scala, Antonio; Caldarelli, Guido; Damiano, Alfonso

2018-01-10

We study how renewable energy impacts regional infrastructures considering the full deployment of electric mobility at that scale. We use the Sardinia Island in Italy as a paradigmatic case study of a semi-closed system both by energy and mobility point of view. Human mobility patterns are estimated by means of census data listing the mobility dynamics of about 700,000 vehicles, the energy demand is estimated by modeling the charging behavior of electric vehicle owners. Here we show that current renewable energy production of Sardinia is able to sustain the commuter mobility even in the theoretical case of a full switch from internal combustion vehicles to electric ones. Centrality measures from network theory on the reconstructed network of commuter trips allows to identify the most important areas (hubs) involved in regional mobility. The analysis of the expected energy flows reveals long-range effects on infrastructures outside metropolitan areas and points out that the most relevant unbalances are caused by spatial segregation between production and consumption areas. Finally, results suggest the adoption of planning actions supporting the installation of renewable energy plants in areas mostly involved by the commuting mobility, avoiding spatial segregation between consumption and generation areas.

The energy demand in the Narino Department

International Nuclear Information System (INIS)

Unidad de Planeacion Minero Energetica, UPME

2000-01-01

In the object of making a first approach of regional energy requirements analysis and the good way of satisfying them, the UPME undertook a global energy study for the Narino Department. In this study (UPME 1999) was carried out an analysis of the energy demand and of the socioeconomic factors that determine it; they were also studied the consumptions and the current energy offer and the alternatives of future evolution, with the purpose of having the basic tools of a departmental energy plan. The present article refers specifically to the analysis of the demand and it seeks to show the readers the complexity and the volume of necessary information to carry out the demand studies. They are multiple factors that determine the energy demand in the Narino Department. The size, growth populations, geographical distribution and cultural characteristic, the border condition, the faulty infrastructure of communications, the agricultural economic structure and the low entrance per capita

Impact Analysis of Demand Response Intensity and Energy Storage Size on Operation of Networked Microgrids

Directory of Open Access Journals (Sweden)

Akhtar Hussain

2017-06-01

Full Text Available Integration of demand response (DR programs and battery energy storage system (BESS in microgrids are beneficial for both microgrid owners and consumers. The intensity of DR programs and BESS size can alter the operation of microgrids. Meanwhile, the optimal size for BESS units is linked with the uncertainties associated with renewable energy sources and load variations. Similarly, the participation of enrolled customers in DR programs is also uncertain and, among various other factors, uncertainty in market prices is a major cause. Therefore, in this paper, the impact of DR program intensity and BESS size on the operation of networked microgrids is analyzed while considering the prevailing uncertainties. The uncertainties associated with forecast load values, output of renewable generators, and market price are realized via the robust optimization method. Robust optimization has the capability to provide immunity against the worst-case scenario, provided the uncertainties lie within the specified bounds. The worst-case scenario of the prevailing uncertainties is considered for evaluating the feasibility of the proposed method. The two representative categories of DR programs, i.e., price-based and incentive-based DR programs are considered. The impact of change in DR intensity and BESS size on operation cost of the microgrid network, external power trading, internal power transfer, load profile of the network, and state-of-charge (SOC of battery energy storage system (BESS units is analyzed. Simulation results are analyzed to determine the integration of favorable DR program and/or BESS units for different microgrid networks with diverse objectives.

Novel algorithm for aggregated demand response strategy for smart distribution network

NARCIS (Netherlands)

Babar, M.; Ahamed, I.; Shah, A.; Al-Ammar, E.A.; Malik, N.H.

2013-01-01

Advancement in demand side management strategies enables smart grid to cope with the ever increasing energy demand and provide economic benefit to all of it's stakeholders. Moreover, emerging concept of smart pricing and advances in load control can provide new business opportunities for demand side

Network Intrusion Detection through Stacking Dilated Convolutional Autoencoders

Directory of Open Access Journals (Sweden)

Yang Yu

2017-01-01

Full Text Available Network intrusion detection is one of the most important parts for cyber security to protect computer systems against malicious attacks. With the emergence of numerous sophisticated and new attacks, however, network intrusion detection techniques are facing several significant challenges. The overall objective of this study is to learn useful feature representations automatically and efficiently from large amounts of unlabeled raw network traffic data by using deep learning approaches. We propose a novel network intrusion model by stacking dilated convolutional autoencoders and evaluate our method on two new intrusion detection datasets. Several experiments were carried out to check the effectiveness of our approach. The comparative experimental results demonstrate that the proposed model can achieve considerably high performance which meets the demand of high accuracy and adaptability of network intrusion detection systems (NIDSs. It is quite potential and promising to apply our model in the large-scale and real-world network environments.

Early Detection of Peak Demand Days of Chronic Respiratory Diseases Emergency Department Visits Using Artificial Neural Networks.

Science.gov (United States)

Khatri, Krishan L; Tamil, Lakshman S

2018-01-01

Chronic respiratory diseases, mainly asthma and chronic obstructive pulmonary disease (COPD), affect the lives of people by limiting their activities in various aspects. Overcrowding of hospital emergency departments (EDs) due to respiratory diseases in certain weather and environmental pollution conditions results in the degradation of quality of medical care, and even limits its availability. A useful tool for ED managers would be to forecast peak demand days so that they can take steps to improve the availability of medical care. In this paper, we developed an artificial neural network based classifier using multilayer perceptron with back propagation algorithm that predicts peak event (peak demand days) of patients with respiratory diseases, mainly asthma and COPD visiting EDs in Dallas County of Texas in the United States. The precision and recall for peak event class were 77.1% and 78.0%, respectively, and those for nonpeak events were 83.9% and 83.2%, respectively. The overall accuracy of the system is 81.0%.

Optimal Operations and Resilient Investments in Steam Networks

Energy Technology Data Exchange (ETDEWEB)

Bungener, Stéphane L., E-mail: stephane.bungener@a3.epfl.ch [Industrial Process and Energy Systems Engineering, École Polytechnique Fédérale de Lausanne, Lausanne (Switzerland); Van Eetvelde, Greet [Environmental and Spatial Management, Faculty of Engineering and Architecture, Ghent University, Ghent (Belgium); Maréchal, François [Industrial Process and Energy Systems Engineering, École Polytechnique Fédérale de Lausanne, Lausanne (Switzerland)

2016-01-20

Steam is a key energy vector for industrial sites, most commonly used for process heating and cooling, cogeneration of heat and mechanical power as a motive fluid or for stripping. Steam networks are used to carry steam from producers to consumers and between pressure levels through letdowns and steam turbines. The steam producers (boilers, heat and power cogeneration units, heat exchangers, chemical reactors) should be sized to supply the consumers at nominal operating conditions as well as peak demand. First, this paper proposes an Mixed Integer Linear Programing formulation to optimize the operations of steam networks in normal operating conditions and exceptional demand (when operating reserves fall to zero), through the introduction of load shedding. Optimization of investments based on operational and investment costs are included in the formulation. Though rare, boiler failures can have a heavy impact on steam network operations and costs, leading to undercapacity and unit shutdowns. A method is therefore proposed to simulate steam network operations when facing boiler failures. Key performance indicators are introduced to quantify the network’s resilience. The proposed methods are applied and demonstrated in an industrial case study using industrial data. The results indicate the importance of oversizing key steam producing equipments and the value of industrial symbiosis to increase industrial site resilience.

Optimal Operations and Resilient Investments in Steam Networks

International Nuclear Information System (INIS)

Bungener, Stéphane L.; Van Eetvelde, Greet; Maréchal, François

2016-01-01

Steam is a key energy vector for industrial sites, most commonly used for process heating and cooling, cogeneration of heat and mechanical power as a motive fluid or for stripping. Steam networks are used to carry steam from producers to consumers and between pressure levels through letdowns and steam turbines. The steam producers (boilers, heat and power cogeneration units, heat exchangers, chemical reactors) should be sized to supply the consumers at nominal operating conditions as well as peak demand. First, this paper proposes an Mixed Integer Linear Programing formulation to optimize the operations of steam networks in normal operating conditions and exceptional demand (when operating reserves fall to zero), through the introduction of load shedding. Optimization of investments based on operational and investment costs are included in the formulation. Though rare, boiler failures can have a heavy impact on steam network operations and costs, leading to undercapacity and unit shutdowns. A method is therefore proposed to simulate steam network operations when facing boiler failures. Key performance indicators are introduced to quantify the network’s resilience. The proposed methods are applied and demonstrated in an industrial case study using industrial data. The results indicate the importance of oversizing key steam producing equipments and the value of industrial symbiosis to increase industrial site resilience.

Key on demand (KoD) for software-defined optical networks secured by quantum key distribution (QKD).

Science.gov (United States)

Cao, Yuan; Zhao, Yongli; Colman-Meixner, Carlos; Yu, Xiaosong; Zhang, Jie

2017-10-30

Software-defined optical networking (SDON) will become the next generation optical network architecture. However, the optical layer and control layer of SDON are vulnerable to cyberattacks. While, data encryption is an effective method to minimize the negative effects of cyberattacks, secure key interchange is its major challenge which can be addressed by the quantum key distribution (QKD) technique. Hence, in this paper we discuss the integration of QKD with WDM optical networks to secure the SDON architecture by introducing a novel key on demand (KoD) scheme which is enabled by a novel routing, wavelength and key assignment (RWKA) algorithm. The QKD over SDON with KoD model follows two steps to provide security: i) quantum key pools (QKPs) construction for securing the control channels (CChs) and data channels (DChs); ii) the KoD scheme uses RWKA algorithm to allocate and update secret keys for different security requirements. To test our model, we define a security probability index which measures the security gain in CChs and DChs. Simulation results indicate that the security performance of CChs and DChs can be enhanced by provisioning sufficient secret keys in QKPs and performing key-updating considering potential cyberattacks. Also, KoD is beneficial to achieve a positive balance between security requirements and key resource usage.

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.

Optical Access Networks

Science.gov (United States)

Zheng, Jun; Ansari, Nirwan

2005-06-01

Call for Papers: Optical Access Networks With the wide deployment of fiber-optic technology over the past two decades, we have witnessed a tremendous growth of bandwidth capacity in the backbone networks of today's telecommunications infrastructure. However, access networks, which cover the "last-mile" areas and serve numerous residential and small business users, have not been scaled up commensurately. The local subscriber lines for telephone and cable television are still using twisted pairs and coaxial cables. Most residential connections to the Internet are still through dial-up modems operating at a low speed on twisted pairs. As the demand for access bandwidth increases with emerging high-bandwidth applications, such as distance learning, high-definition television (HDTV), and video on demand (VoD), the last-mile access networks have become a bandwidth bottleneck in today's telecommunications infrastructure. To ease this bottleneck, it is imperative to provide sufficient bandwidth capacity in the access networks to open the bottleneck and thus present more opportunities for the provisioning of multiservices. Optical access solutions promise huge bandwidth to service providers and low-cost high-bandwidth services to end users and are therefore widely considered the technology of choice for next-generation access networks. To realize the vision of optical access networks, however, many key issues still need to be addressed, such as network architectures, signaling protocols, and implementation standards. The major challenges lie in the fact that an optical solution must be not only robust, scalable, and flexible, but also implemented at a low cost comparable to that of existing access solutions in order to increase the economic viability of many potential high-bandwidth applications. In recent years, optical access networks have been receiving tremendous attention from both academia and industry. A large number of research activities have been carried out or

Vocational Education Teachers' Personal Network at School as a Resource for Innovative Work Behaviour

Science.gov (United States)

Messmann, Gerhard; Mulder, Regina H.; Palonen, Tuire

2018-01-01

Purpose: This paper aims to investigate the role of characteristics of vocational education teachers' personal network at the workplace for determining the resources that enable them to cope with innovation-related demands at work. Design/methodology/approach: A survey study with 48 vocational education teachers is carried out. Social network…

A Simplified Network Model for Travel Time Reliability Analysis in a Road Network

Directory of Open Access Journals (Sweden)

Kenetsu Uchida

2017-01-01

Full Text Available This paper proposes a simplified network model which analyzes travel time reliability in a road network. A risk-averse driver is assumed in the simplified model. The risk-averse driver chooses a path by taking into account both a path travel time variance and a mean path travel time. The uncertainty addressed in this model is that of traffic flows (i.e., stochastic demand flows. In the simplified network model, the path travel time variance is not calculated by considering all travel time covariance between two links in the network. The path travel time variance is calculated by considering all travel time covariance between two adjacent links in the network. Numerical experiments are carried out to illustrate the applicability and validity of the proposed model. The experiments introduce the path choice behavior of a risk-neutral driver and several types of risk-averse drivers. It is shown that the mean link flows calculated by introducing the risk-neutral driver differ as a whole from those calculated by introducing several types of risk-averse drivers. It is also shown that the mean link flows calculated by the simplified network model are almost the same as the flows calculated by using the exact path travel time variance.

Communication technologies for demand side management

Energy Technology Data Exchange (ETDEWEB)

Uuspaeae, P [VTT Energy, Espoo (Finland)

1998-08-01

The scope of this research is data communications for electric utilities, specifically for the purposes of Demand Side Management (DSM). Demand Side Management has the objective to change the customer`s end use of energy in a manner that benefits both the customer and the utility. For example, peak demand may be reduced, and the peak demand may be relocated to off peak periods. Thus additional investments in generation and network may be avoided. A number of Demand Side Management functions can be implemented if a communication system is available between the Electric Utility and the Customer. The total communication capacity that is needed, will depend on several factors, such as the functions that are chosen for DSM, and on the number and type of customers. Some functions may be handled with one-way communications, while some other functions need to have two-way communication

Forecasting annual gross electricity demand by artificial neural networks using predicted values of socio-economic indicators and climatic conditions: Case of Turkey

International Nuclear Information System (INIS)

Günay, M. Erdem

2016-01-01

In this work, the annual gross electricity demand of Turkey was modeled by multiple linear regression and artificial neural networks as a function population, gross domestic product per capita, inflation percentage, unemployment percentage, average summer temperature and average winter temperature. Among these, the unemployment percentage and the average winter temperature were found to be insignificant to determine the demand for the years between 1975 and 2013. Next, the future values of the statistically significant variables were predicted by time series ANN models, and these were simulated in a multilayer perceptron ANN model to forecast the future annual electricity demand. The results were validated with a very high accuracy for the years that the electricity demand was known (2007–2013), and they were also superior to the official predictions (done by Ministry of Energy and Natural Resources of Turkey). The model was then used to forecast the annual gross electricity demand for the future years, and it was found that, the demand will be doubled reaching about 460 TW h in the year 2028. Finally, it was concluded that the approach applied in this work can easily be implemented for other countries to make accurate predictions for the future. - Highlights: • Electricity demand of Turkey increased from 15.6 to 246.4 TW h in 1975–2013 period. • Population, GDP per capita, inflation and average summer temperature influence demand. • Future values of descriptor variables can be predicted by time series ANN models. • ANN model simulated by the predicted values of descriptors can forecast the demand. • Demand is forecasted to be doubled reaching about 460 TW h in the year 2028.

Minimum cost connection networks

DEFF Research Database (Denmark)

Hougaard, Jens Leth; Tvede, Mich

In the present paper we consider the allocation of cost in connection networks. Agents have connection demands in form of pairs of locations they want to be connected. Connections between locations are costly to build. The problem is to allocate costs of networks satisfying all connection demands...

Smart Demand Response Based on Smart Homes

Directory of Open Access Journals (Sweden)

Jingang Lai

2015-01-01

Full Text Available Smart homes (SHs are crucial parts for demand response management (DRM of smart grid (SG. The aim of SHs based demand response (DR is to provide a flexible two-way energy feedback whilst (or shortly after the consumption occurs. It can potentially persuade end-users to achieve energy saving and cooperate with the electricity producer or supplier to maintain balance between the electricity supply and demand through the method of peak shaving and valley filling. However, existing solutions are challenged by the lack of consideration between the wide application of fiber power cable to the home (FPCTTH and related users’ behaviors. Based on the new network infrastructure, the design and development of smart DR systems based on SHs are related with not only functionalities as security, convenience, and comfort, but also energy savings. A new multirouting protocol based on Kruskal’s algorithm is designed for the reliability and safety of the SHs distribution network. The benefits of FPCTTH-based SHs are summarized at the end of the paper.

Software defined wireless sensor networks application opportunities for efficient network management: a survey

CSIR Research Space (South Africa)

Modieginyane, KM

2017-03-01

Full Text Available Wireless Sensor Networks (WSNs) are commonly used information technologies of modern networking and computing platforms. Today's network computing applications are faced with a high demand of powerful network functionalities. Functional network...

Roadway network productivity assessment : system-wide analysis under variant travel demand

Science.gov (United States)

2008-11-01

The analysis documented in this report examines the hypothesis that the system-wide productivity of a metropolitan freeway system in peak periods is higher in moderate travel demand conditions than in excessive travel demand conditions. The approach ...

Y-Source Impedance Network

DEFF Research Database (Denmark)

Siwakoti, Yam Prasad; Loh, Poh Chiang; Blaabjerg, Frede

2014-01-01

This letter introduces a new versatile Y-shaped impedance network for realizing converters that demand a very high-voltage gain, while using a small duty ratio. To achieve that, the proposed network uses a tightly coupled transformer with three windings, whose obtained gain is presently not matched...... by existing networks operated at the same duty ratio. The proposed impedance network also has more degrees of freedom for varying its gain, and hence, more design freedom for meeting requirements demanded from it. This capability has been demonstrated by mathematical derivation, and proven in experiment...

High-resolution stochastic integrated thermal–electrical domestic demand model

International Nuclear Information System (INIS)

McKenna, Eoghan; Thomson, Murray

2016-01-01

Highlights: • A major new version of CREST’s demand model is presented. • Simulates electrical and thermal domestic demands at high-resolution. • Integrated structure captures appropriate time-coincidence of variables. • Suitable for low-voltage network and urban energy analyses. • Open-source development in Excel VBA freely available for download. - Abstract: This paper describes the extension of CREST’s existing electrical domestic demand model into an integrated thermal–electrical demand model. The principle novelty of the model is its integrated structure such that the timing of thermal and electrical output variables are appropriately correlated. The model has been developed primarily for low-voltage network analysis and the model’s ability to account for demand diversity is of critical importance for this application. The model, however, can also serve as a basis for modelling domestic energy demands within the broader field of urban energy systems analysis. The new model includes the previously published components associated with electrical demand and generation (appliances, lighting, and photovoltaics) and integrates these with an updated occupancy model, a solar thermal collector model, and new thermal models including a low-order building thermal model, domestic hot water consumption, thermostat and timer controls and gas boilers. The paper reviews the state-of-the-art in high-resolution domestic demand modelling, describes the model, and compares its output with three independent validation datasets. The integrated model remains an open-source development in Excel VBA and is freely available to download for users to configure and extend, or to incorporate into other models.

Calculation method of water injection forward modeling and inversion process in oilfield water injection network

Science.gov (United States)

Liu, Long; Liu, Wei

2018-04-01

A forward modeling and inversion algorithm is adopted in order to determine the water injection plan in the oilfield water injection network. The main idea of the algorithm is shown as follows: firstly, the oilfield water injection network is inversely calculated. The pumping station demand flow is calculated. Then, forward modeling calculation is carried out for judging whether all water injection wells meet the requirements of injection allocation or not. If all water injection wells meet the requirements of injection allocation, calculation is stopped, otherwise the demand injection allocation flow rate of certain step size is reduced aiming at water injection wells which do not meet requirements, and next iterative operation is started. It is not necessary to list the algorithm into water injection network system algorithm, which can be realized easily. Iterative method is used, which is suitable for computer programming. Experimental result shows that the algorithm is fast and accurate.

WiMAX network performance monitoring & optimization

DEFF Research Database (Denmark)

Zhang, Qi; Dam, H

2008-01-01

frequency reuse, capacity planning, proper network dimensioning, multi-class data services and so on. Furthermore, as a small operator we also want to reduce the demand for sophisticated technicians and man labour hours. To meet these critical demands, we design a generic integrated network performance......In this paper we present our WiMAX (worldwide interoperability for microwave access) network performance monitoring and optimization solution. As a new and small WiMAX network operator, there are many demanding issues that we have to deal with, such as limited available frequency resource, tight...... this integrated network performance monitoring and optimization system in our WiMAX networks. This integrated monitoring and optimization system has such good flexibility and scalability that individual function component can be used by other operators with special needs and more advanced function components can...

Distributed Optimisation Algorithm for Demand Side Management in a Grid-Connected Smart Microgrid

Directory of Open Access Journals (Sweden)

Omowunmi Mary Longe

2017-06-01

Full Text Available The contributions of Distributed Energy Generation (DEG and Distributed Energy Storage (DES for Demand Side Management (DSM purposes in a smart macrogrid or microgrid cannot be over-emphasised. However, standalone DEG and DES can lead to under-utilisation of energy generation by consumers and financial investments; in grid-connection mode, though, DEG and DES can offer arbitrage opportunities for consumers and utility provider(s. A grid-connected smart microgrid comprising heterogeneous (active and passive smart consumers, electric vehicles and a large-scale centralised energy storage is considered in this paper. Efficient energy management by each smart entity is carried out by the proposed Microgrid Energy Management Distributed Optimisation Algorithm (MEM-DOA installed distributively within the network according to consumer type. Each smart consumer optimises its energy consumption and trading for comfort (demand satisfaction and profit. The proposed model was observed to yield better consumer satisfaction, higher financial savings, and reduced Peak-to-Average-Ratio (PAR demand on the utility grid. Other associated benefits of the model include reduced investment on peaker plants, grid reliability and environmental benefits. The MEM-DOA also offered participating smart consumers energy and tariff incentives so that passive smart consumers do not benefit more than active smart consumers, as was the case with some previous energy management algorithms.

[Ecological carrying capacity and Chongming Island's ecological construction].

Science.gov (United States)

Wang, Kaiyun; Zou, Chunjing; Kong, Zhenghong; Wang, Tianhou; Chen, Xiaoyong

2005-12-01

This paper overviewed the goals of Chongming Island's ecological construction and its background, analyzed the current eco-economic status and constraints of the Island, and put forward some scientific issues on its ecological construction. It was suggested that for the resources-saving and sustainable development of the Island, the researches on its ecological construction should be based on its ecological carrying capacity, fully take the regional characteristics into consideration, and refer the successful development modes at home and abroad. The carrying capacity study should ground on systemic and dynamic views, give a thorough evaluation of the Island's present carrying capacity, simulate its possible changes, and forecast its demands and risks. Operable countermeasures to promote the Island's carrying capacity should be worked out, new industry structure, population scale, and optimized distribution projects conforming to regional carrying capacity should be formulated, and effective ecological security alarming and control system should be built, with the aim of providing suggestions and strategic evidences for the decision-making of economic development and sustainable environmental resources use of the region.

The Influence of Recognition and Social Support on European Health Professionals' Occupational Stress: A Demands-Control-Social Support-Recognition Bayesian Network Model.

Science.gov (United States)

García-Herrero, Susana; Lopez-Garcia, Jose R; Herrera, Sixto; Fontaneda, Ignacio; Báscones, Sonia Muñoz; Mariscal, Miguel A

2017-01-01

Healthcare professionals undergo high levels of occupational stress as a result of their working conditions. Thus, the aim of this study is to develop a model that focuses on healthcare professionals so as to analyze the influence that job demands, control, social support, and recognition have on the likelihood that a worker will experience stress. The data collected correspond to 2,211 healthcare workers from 35 countries, as reported in the sixth European Working Condition Survey (EWCS). The results obtained from this study allow us to infer stress under several working condition scenarios and to identify the more relevant variables in order to reduce this stress in healthcare professionals, which is of paramount importance to managing the stress of workers in this sector. The Bayesian network proposed indicates that emotional demands have a greater influence on raising the likelihood of stress due to workload than do family demands. The results show that the support of colleagues, in general, has less effect on reducing stress than social support from superiors. Furthermore, the sensitivity analysis shows that, in high-demand and low-control situations, recognition clearly impacts stress, drastically reducing it.

Intrinsic motivation and organizational identification among on-demand workers.

Science.gov (United States)

Rockmann, Kevin W; Ballinger, Gary A

2017-09-01

On-demand firms provide services for clients through a network of on-demand workers ready to complete specific tasks for a set contractual price. Given such on-demand work is defined by payment on short-term contracts with no obligation for continued employment, there is little reason to believe on-demand workers experience more than extrinsic motivation and a transactional relationship with the on-demand firm. However, using self-determination theory, we argue that to the degree that on-demand work fulfills innate psychological needs individual on-demand workers will develop intrinsic motivation, which further leads to organizational identification with the on-demand firm. Across 2 survey-based studies we find support for this path to organizational identification. This adds to the literature on motivation and identification by strengthening the link between individual needs and the individual-organizational relationship. Implications for theory and for the management of on-demand workers are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Demand chain management - The evolution

Directory of Open Access Journals (Sweden)

D Ericsson

2011-06-01

Full Text Available The concepts of Supply Chain Management (SCM and Demand Chain Management (DCM are among the new and debated topics concerning logistics in the literature. The question considered in this paper is: “Are these concepts needed or will they just add to the confusion?” Lasting business concepts have always evolved in close interaction between business and academia. Different approaches start out in business and they are then, more or less si- multaneously, aligned, integrated, systemised and structured in academia. In this way a terminology (or language is provided that helps in further diffusion of the concepts. There is a lack of consensus on the definition of the concept of SCM. This may be one of the major reasons for the difficulty in advancing the science and measuring the results of implementation in business. Relationships in SCM span from rather loose coalitions to highly structured virtual network integrations. DCM is a highly organised chain in which the key is mutual interdependence and partnership. The purpose is to create a distinctive competence for the chain as a whole that helps to identify and satisfy customer needs and wishes. The classical research concerning vertical marketing systems is very helpful in systemising the rather unstructured discussions in current SCM research. The trend lies in increasing competition between channels rather than between companies, which in turn leads to the creation of channels with a high degree of partnership and mutual interdependence between members. These types of channels are known as organised vertical marketing systems in the classic marketing channel research. The behaviour in these types of channels, as well as the formal and informal structures, roles in the network, power and dependence relations, etc. are well covered topics in the literature. The concept of vertical marketing systems lies behind the definition of demand chains and demand chain management proposed in this paper. A

The demand of guava in Colombia

Directory of Open Access Journals (Sweden)

Julio César Alonso-Cifuentes

2017-01-01

Full Text Available In Colombia, no systematic work have been carried out to determine the demand for fruits beyond descriptive analysis of per capita consumption according to different individual socioeconomic characteristics and much less for a specific product such as guava, Psidium guajava L. (Myrtaceae. This paper estimates the relationship between guava prices and the demand of guava in Colombia. We found that guava consumption is not affected by its price and its demand is highly correlated to income. While socio-economic characteristics such as income, education and household head labor affect the decision-making for consuming guava, other characteristics such as race and the number of household members determine the quantity of guava consumed in a Colombian household.

Big data analytics for the virtual network topology reconfiguration use case

OpenAIRE

Gifre Renom, Lluís; Morales Alcaide, Fernando; Velasco Esteban, Luis Domingo; Ruiz Ramírez, Marc

2016-01-01

ABNO's OAM Handler is extended with big data analytics capabilities to anticipate traffic changes in volume and direction. Predicted traffic is used to trigger virtual network topology re-optimization. When the virtual topology needs to be reconfigured, predicted and current traffic matrices are used to find the optimal topology. A heuristic algorithm to adapt current virtual topology to meet both actual demands and expected traffic matrix is proposed. Experimental assessment is carried ou...

Flexible Transmission Network Expansion Planning Considering Uncertain Renewable Generation and Load Demand Based on Hybrid Clustering Analysis

Directory of Open Access Journals (Sweden)

Yun-Hao Li

2015-12-01

Full Text Available This paper presents a flexible transmission network expansion planning (TNEP approach considering uncertainty. A novel hybrid clustering technique, which integrates the graph partitioning method and rough fuzzy clustering, is proposed to cope with uncertain renewable generation and load demand. The proposed clustering method is capable of recognizing the actual cluster distribution of complex datasets and providing high-quality clustering results. By clustering the hourly data for renewable generation and load demand, a multi-scenario model is proposed to consider the corresponding uncertainties in TNEP. Furthermore, due to the peak distribution characteristics of renewable generation and heavy investment in transmission, the traditional TNEP, which caters to rated renewable power output, is usually uneconomic. To improve the economic efficiency, the multi-objective optimization is incorporated into the multi-scenario TNEP model, while the curtailment of renewable generation is considered as one of the optimization objectives. The solution framework applies a modified NSGA-II algorithm to obtain a set of Pareto optimal planning schemes with different levels of investment costs and renewable generation curtailments. Numerical results on the IEEE RTS-24 system demonstrated the robustness and effectiveness of the proposed approach.

Grower demand for sensor-controlled irrigation

Science.gov (United States)

Lichtenberg, Erik; Majsztrik, John; Saavoss, Monica

2015-01-01

Water scarcity is likely to increase in the coming years, making improvements in irrigation efficiency increasingly important. An emerging technology that promises to increase irrigation efficiency substantially is a wireless irrigation sensor network that uploads sensor data into irrigation management software, creating an integrated system that allows real-time monitoring and control of moisture status that has been shown in experimental settings to reduce irrigation costs, lower plant loss rates, shorten production times, decrease pesticide application, and increase yield, quality, and profit. We use an original survey to investigate likely initial acceptance, ceiling adoption rates, and profitability of this new sensor network technology in the nursery and greenhouse industry. We find that adoption rates for a base system and demand for expansion components are decreasing in price, as expected. The price elasticity of the probability of adoption suggests that sensor networks are likely to diffuse at a rate somewhat greater than that of drip irrigation. Adoption rates for a base system and demand for expansion components are increasing in specialization in ornamental production: growers earning greater shares of revenue from greenhouse and nursery operations are willing to pay more for a base system and are willing to purchase larger numbers of expansion components at any given price. We estimate that growers who are willing to purchase a sensor network expect investment in this technology to generate significant profit, consistent with findings from experimental studies.

the determinants of demand for public transport services in kumasi

African Journals Online (AJOL)

dmosman.admin

The objective of the study was to establish the major factors influencing demand as well as de- velop a demand model for urban passenger transport services in Kumasi, Ghana. ... Cities in developing countries often spend be- ... the total urban road network was in “Good” ... several other functions of a national, regional.

Smart electric storage heating and potential for residential demand response

OpenAIRE

Darby, S

2017-01-01

Low-carbon transition plans for temperate and sub-polar regions typically involve some electrification of space heating. This poses challenges to electricity system operation and market design, as it increases overall demand and alters the temporal patterns of that demand. One response to the challenge is to ‘smarten’ electrical heating, enabling it to respond to network conditions by storing energy at times of plentiful supply, releasing it in response to customer demands and offering rapid-...

Distributed generation, storage, demand response and energy efficiency as alternatives to grid capacity enhancement

International Nuclear Information System (INIS)

Poudineh, Rahmatallah; Jamasb, Tooraj

2014-01-01

The need for investment in capital intensive electricity networks is on the rise in many countries. A major advantage of distributed resources is their potential for deferring investments in distribution network capacity. However, utilizing the full benefits of these resources requires addressing several technical, economic and regulatory challenges. A significant barrier pertains to the lack of an efficient market mechanism that enables this concept and also is consistent with business model of distribution companies under an unbundled power sector paradigm. This paper proposes a market-oriented approach termed as “contract for deferral scheme” (CDS). The scheme outlines how an economically efficient portfolio of distributed generation, storage, demand response and energy efficiency can be integrated as network resources to reduce the need for grid capacity and defer demand driven network investments. - Highlights: • The paper explores a practical framework for smart electricity distribution grids. • The aim is to defer large capital investments in the network by utilizing and incentivising distributed generation, demand response, energy efficiency and storage as network resources. • The paper discusses a possible new market model that enables integration of distributed resources as alternative to grid capacity enhancement

Location-Aided Reliable Routing for Opportunistic Networks

Institute of Scientific and Technical Information of China (English)

Yong Yang; Zhi Ren; Jibi Li

2012-01-01

In our study, we investigate the problem of location-based routing in opportunistic networks. Due to the uncertainty of end-to-end paths between sources and destinations, the classical location-based ad hoc routing protocols cannot adapt to the environment of opportunistic networks, which leads to the decrease of the delivery rate of data. To address it, we propose in this paper a novel location-aided routing protocol which is suitable for opportunistic networks. In our protocol, a node can send location information on demand by using prediction mechanism, and when sending a data packet, the node chooses multiple neighbors which are closer to the destination as next hops. If the candidate neighbors do not exist, the node carries the data till it meets a proper neighbor or the destination. Theoretical analysis and simulation results show that our proposed protocol outperforms DREAM (Distance Routing Effect Protocol Mobility) and one of its improved versions, BFDREAM (Boundary Forwarding DREAM), in terms of the delivery rate and overhead.

[Ecotourism carrying capacity of Hangzhou Xixi National Wetland Park in China].

Science.gov (United States)

Li, Rui; Rong, Liang

2007-10-01

In this paper, an integrated estimation on the ecotourism carrying capacity of Hangzhou Xixi National Wetland Park in China was made from the aspects of ecological carrying capacity, spatial carrying capacity, facility carrying capacity, management carrying capacity, and psychological carrying capacity. The results indicated that the tourism carrying capacity of the Park was 4 145 - 6 450 persons per day. The rational distance between man and bird was first adopted to determine the ecotourism carrying capacity of wetland, which provided an effective solution both to fully ensure bird safety and to appropriately develop wetland tourism. The estimation of psychological carrying capacity based on tourist satisfaction degree reflected more objectively the extent the tourist demands satisfied at the planning, construction and management of tour places. Such an integrated estimation method based on the distance between man and bird and the tourist satisfaction degree could be of practical and instructive significances in the planning and management of wetland parks.

Reciprocity on Demand : Sharing and Exchanging Food in Northwestern Namibia.

Science.gov (United States)

Schnegg, Michael

2015-09-01

Two competing models concerning food transfers prominent in the anthropological literature conceptualize such transfers either as sharing or as exchange. Sharing is understood as situational transactions formed through demands and unconditional giving, whereas reciprocal exchange is understood in terms of networking and keeping score. I propose that the picture is more complicated than these classifications suggests. Drawing on data collected in Northwestern Namibia, I show that sharing and reciprocal exchange are dynamically interrelated in actual food transfers. As a local norm, people can demand food from anyone, and they are typically given food in response to a demand. However, in practice, food transfer networks emerge (N = 62) that are highly reciprocal and fit the exchange model much better. Although the sharing norm makes no restrictions on whom to ask, in practice people often turn to their neighbors. Interpersonal dynamics account for why some of those ties become strongly reciprocal and others do not. Under these circumstances, unconditional sharing, a norm that has been viewed as an alternative to exchange, can lead to reciprocity via reciprocity on demand.

PERIODIC REVIEW SYSTEM FOR INVENTORY REPLENISHMENT CONTROL FOR A TWO-ECHELON LOGISTICS NETWORK UNDER DEMAND UNCERTAINTY: A TWO-STAGE STOCHASTIC PROGRAMING APPROACH

OpenAIRE

Cunha, P.S.A.; Oliveira, F.; Raupp, Fernanda M.P.

2017-01-01

ABSTRACT Here, we propose a novel methodology for replenishment and control systems for inventories of two-echelon logistics networks using a two-stage stochastic programming, considering periodic review and uncertain demands. In addition, to achieve better customer services, we introduce a variable rationing rule to address quantities of the item in short. The devised models are reformulated into their deterministic equivalent, resulting in nonlinear mixed-integer programming models, which a...

Carrying capacity of water resources in Bandung Basin

Science.gov (United States)

Marganingrum, D.

2018-02-01

The concept of carrying capacity is widely used in various sectors as a management tool for sustainable development processes. This idea has also been applied in watershed or basin scale. Bandung Basin is the upstream of Citarum watershed known as one of the national strategic areas. This area has developed into a metropolitan area loaded with various environmental problems. Therefore, research that is related to environmental carrying capacity in this area becomes a strategic issue. However, research on environmental carrying capacity that has been done in this area is still partial either in water balance terminology, land suitability, ecological footprint, or balance of supply and demand of resources. This paper describes the application of the concept of integrated environmental carrying capacity in order to overcome the increasing complexity and dynamic environmental problems. The sector that becomes the focus of attention is the issue of water resources. The approach method to be carried out is to combine the concept of maximum balance and system dynamics. The dynamics of the proposed system is the ecological dynamics and population that cannot be separated from one another as a unity of the Bandung Basin ecosystem.

Functional Cortical Network in Alpha Band Correlates with Social Bargaining

Science.gov (United States)

Billeke, Pablo; Zamorano, Francisco; Chavez, Mario; Cosmelli, Diego; Aboitiz, Francisco

2014-01-01

Solving demanding tasks requires fast and flexible coordination among different brain areas. Everyday examples of this are the social dilemmas in which goals tend to clash, requiring one to weigh alternative courses of action in limited time. In spite of this fact, there are few studies that directly address the dynamics of flexible brain network integration during social interaction. To study the preceding, we carried out EEG recordings while subjects played a repeated version of the Ultimatum Game in both human (social) and computer (non-social) conditions. We found phase synchrony (inter-site-phase-clustering) modulation in alpha band that was specific to the human condition and independent of power modulation. The strength and patterns of the inter-site-phase-clustering of the cortical networks were also modulated, and these modulations were mainly in frontal and parietal regions. Moreover, changes in the individuals’ alpha network structure correlated with the risk of the offers made only in social conditions. This correlation was independent of changes in power and inter-site-phase-clustering strength. Our results indicate that, when subjects believe they are participating in a social interaction, a specific modulation of functional cortical networks in alpha band takes place, suggesting that phase synchrony of alpha oscillations could serve as a mechanism by which different brain areas flexibly interact in order to adapt ongoing behavior in socially demanding contexts. PMID:25286240

Analysis of a Residential Building Energy Consumption Demand Model

Directory of Open Access Journals (Sweden)

Meng Liu

2011-03-01

Full Text Available In order to estimate the energy consumption demand of residential buildings, this paper first discusses the status and shortcomings of current domestic energy consumption models. Then it proposes and develops a residential building energy consumption demand model based on a back propagation (BP neural network model. After that, taking residential buildings in Chongqing (P.R. China as an example, 16 energy consumption indicators are introduced as characteristics of the residential buildings in Chongqing. The index system of the BP neutral network prediction model is established and the multi-factorial BP neural network prediction model of Chongqing residential building energy consumption is developed using the Cshap language, based on the SQL server 2005 platform. The results obtained by applying the model in Chongqing are in good agreement with actual ones. In addition, the model provides corresponding approximate data by taking into account the potential energy structure adjustments and relevant energy policy regulations.

GIS-TEHNOLOGIES IN GEOMARKET AND GEODEMOGRAPHIC RESEARCHES OF NETWORK RETAIL

Directory of Open Access Journals (Sweden)

L. I. Popkova

2013-01-01

Full Text Available In this work we see the analysis of territorial organization of a network retail in Kursk. One of the factors influencing success the retail business is the accounting of spatial distribution of buyers as well as suppliers. Two key concepts follow from this idea: "geo-demand" and "geo-competition". Main objective of research was the development of a technique of border definition for new supermarkets by means of GIS.This technique represents sequence of the following operations: first it is necessary to carry out the geo-demand analysis for finding of potential clients; secondly, the geo-competition is analyzed, the trade zones of competing shops are defined; thirdly, potential places of new supermarkets localization are defined by results combination of two previous steps.

A Novel Technique to Enhance Demand Responsiveness

DEFF Research Database (Denmark)

Farashbashi-Astaneh, Seyed-Mostafa; Bhattarai, Bishnu Prasad; Bak-Jensen, Birgitte

2015-01-01

In this study, a new pricing approach is proposed to increase demand responsiveness. The proposed approach considers two well-known demand side management techniques, namely peak shaving and valley filling. This is done by incentivising consumers by magnifying price difference between peak and off......-peak hours. The usefulness of the suggested method is then investigated by its combination with an electric vehicle optimal scheduling methodology which captures both economic valuation and grid technical constraints. This case is chosen in this study to address network congestion issues, namely under...

Airborne Network Optimization with Dynamic Network Update

Science.gov (United States)

2015-03-26

source si and a target ti . For each commodity (si, ki) the commodity specifies a non- negative demand di [5]. The objective of the multi-commodity...queue predictions, and network con- gestion [15]. The implementation of the DRQC uses the Kalman filter to predict the state of the network and optimize

Impact of Mobility-on-Demand on Traffic Congestion: Simulation-based Study

OpenAIRE

Fiedler, David; Čáp, Michal; Čertický, Michal

2017-01-01

The increasing use of private vehicles for transportation in cities results in a growing demand for parking space and road network capacity. In many densely populated urban areas, however, the capacity of existing infrastructure is insufficient and extremely difficult to expand. Mobility-on-demand systems have been proposed as a remedy to the problem of limited parking space because they are able to satisfy the existing transportation demand with fewer shared vehicles and consequently require...

A Probabilistic Short-Term Water Demand Forecasting Model Based on the Markov Chain

Directory of Open Access Journals (Sweden)

Francesca Gagliardi

2017-07-01

Full Text Available This paper proposes a short-term water demand forecasting method based on the use of the Markov chain. This method provides estimates of future demands by calculating probabilities that the future demand value will fall within pre-assigned intervals covering the expected total variability. More specifically, two models based on homogeneous and non-homogeneous Markov chains were developed and presented. These models, together with two benchmark models (based on artificial neural network and naïve methods, were applied to three real-life case studies for the purpose of forecasting the respective water demands from 1 to 24 h ahead. The results obtained show that the model based on a homogeneous Markov chain provides more accurate short-term forecasts than the one based on a non-homogeneous Markov chain, which is in line with the artificial neural network model. Both Markov chain models enable probabilistic information regarding the stochastic demand forecast to be easily obtained.

Must-carry regulation: a must or a burden?

NARCIS (Netherlands)

van Eijk, N.; van der Sloot, B.; Nikoltchev, S.

2012-01-01

The first must-carry rules date back to 1990, the time when space on analogue broadcasting networks was limited and when supply grew quickly due to the introduction of private broadcasters. To ensure that channels of general interest would still be transmitted, countries introduced rules to regulate

Wireless traffic steering for green cellular networks

CERN Document Server

Zhang, Shan; Zhou, Sheng; Niu, Zhisheng; Shen, Xuemin (Sherman)

2016-01-01

This book introduces wireless traffic steering as a paradigm to realize green communication in multi-tier heterogeneous cellular networks. By matching network resources and dynamic mobile traffic demand, traffic steering helps to reduce on-grid power consumption with on-demand services provided. This book reviews existing solutions from the perspectives of energy consumption reduction and renewable energy harvesting. Specifically, it explains how traffic steering can improve energy efficiency through intelligent traffic-resource matching. Several promising traffic steering approaches for dynamic network planning and renewable energy demand-supply balancing are discussed. This book presents an energy-aware traffic steering method for networks with energy harvesting, which optimizes the traffic allocated to each cell based on the renewable energy status. Renewable energy demand-supply balancing is a key factor in energy dynamics, aimed at enhancing renewable energy sustainability to reduce on-grid energy consum...

Survivable integrated grooming in multi-granularity optical networks

Science.gov (United States)

Wu, Jingjing; Guo, Lei; Wei, Xuetao; Liu, Yejun

2012-05-01

Survivability is an important issue to ensure the service continuity in optical network. At the same time, with the granularity of traffic demands ranging from sub-wavelength-level to wavelength-level, traffic demands need to be aggregated and carried over the network in order to utilize resources effectively. Therefore, multi-granularity grooming is proposed to save the cost and reduce the number of switching ports in Optical-Cross Connects (OXCs). However, current works mostly addressed the survivable wavelength or waveband grooming. Therefore, in this paper, we propose three heuristic algorithms called Multi-granularity Dedicated Protection Grooming (MDPG), Multi-granularity Shared Protection Grooming (MSPG) and Multi-granularity Mixed Protection Grooming (MMPG), respectively. All of them are performed based on the Survivable Multi-granularity Integrated Auxiliary Graph (SMIAG) that includes one Wavelength Integrated Auxiliary Graph (WIAG) for wavelength protection and one waveBand Integrated Auxiliary Graph (BIAG) for waveband protection. Numerical results show that MMPG has the lowest average port-cost, the best resource utilization ratio and the lowest blocking probability among these three algorithms. Compared with MDPG, MSPG has lower average port-cost, better resource utilization ratio and lower blocking probability.

Does Knowledge Contribute to the Acceptance of Demand Response?

Directory of Open Access Journals (Sweden)

Salla Annala

2014-03-01

Full Text Available More flexible demand side would benefit the electricity markets, networks and sustainable power generation in many ways. The success of demand response programs, however, relies on consumer acceptance. This paper reviews previous studies about acceptability of different kinds of residential demand response programs. Furthermore, it discusses whether consumers who are more aware of the principles and benefits of demand response have more positive attitudes towards demand response programs. The results of the literature review and two survey studies suggest that price and security of supply are currently bigger motives to change consumption behaviour than environmental issues and that the savings expected to trigger any action (and to lead to lasting change in behaviour may be relatively high. Therefore, the framing of demand response programs goals may affect the acceptance. Additionally, consumers seem to prefer simple price structures that remain constant for a long time to more dynamic options.

Optical Access Networks

Science.gov (United States)

Zheng, Jun; Ansari, Nirwan

2005-01-01

Call for Papers: Optical Access Networks Guest Editors Jun Zheng, University of Ottawa Nirwan Ansari, New Jersey Institute of Technology Submission Deadline: 1 June 2005 Background With the wide deployment of fiber-optic technology over the past two decades, we have witnessed a tremendous growth of bandwidth capacity in the backbone networks of today's telecommunications infrastructure. However, access networks, which cover the "last-mile" areas and serve numerous residential and small business users, have not been scaled up commensurately. The local subscriber lines for telephone and cable television are still using twisted pairs and coaxial cables. Most residential connections to the Internet are still through dial-up modems operating at a low speed on twisted pairs. As the demand for access bandwidth increases with emerging high-bandwidth applications, such as distance learning, high-definition television (HDTV), and video on demand (VoD), the last-mile access networks have become a bandwidth bottleneck in today's telecommunications infrastructure. To ease this bottleneck, it is imperative to provide sufficient bandwidth capacity in the access networks to open the bottleneck and thus present more opportunities for the provisioning of multiservices. Optical access solutions promise huge bandwidth to service providers and low-cost high-bandwidth services to end users and are therefore widely considered the technology of choice for next-generation access networks. To realize the vision of optical access networks, however, many key issues still need to be addressed, such as network architectures, signaling protocols, and implementation standards. The major challenges lie in the fact that an optical solution must be not only robust, scalable, and flexible, but also implemented at a low cost comparable to that of existing access solutions in order to increase the economic viability of many potential high-bandwidth applications. In recent years, optical access networks

Dual stack deployment in a carrier grade network to fulfill the demands of next generation of internet

International Nuclear Information System (INIS)

Khanzada, T.J.S.

2013-01-01

The Internet is migrating from IPv4 (Internet Protocol version 4) to IPv6 (Internet Protocol version 6). The high cost of migration services from IPv4-IPv6 and system complexity are main factors for slow adaption of IPv6 This paper presents the implementation of migration techniques from IPv4-IPv6. Furthermore, existing IPv4 addresses have already been depleted in IANA (Internet Assigned Numbers Authority) and will be soon exhausted in RIR (Regional Internet Registry) while more clients are joining the Internet. Slower rate of the progress of IPv6 confirms complete shifting from IPv4-IPv6 at once is still long away, although fewer parts of IPv6 have been employed in current market goods. Integration of IPv4 and IPv6 is carried in order to take care of online users. In this paper, it is suggested that hierarchical direction finding structural design in IPv4 and IPv6 will improve the efficiency of IPv4 network. This research work provides the way to design the network scenario for the carrier grade set of connections. The carrier grade network scenario routers are named to be Karachi, Sukkur, Islamabad, Multan and Peshawar for the managerial simulation purposes. The carrier grade network deployment is implemented along with dual stack to migrate to IPv6. This study holds the way to deploy IPv4-IPv6 carrier grade network by providing real time scenario which is yet not considered in the literature to the best of our knowledge. (author)

Dual Stack Deployment in a Carrier Grade Network to Fulfill the Demands of Next Generation of Internet

Directory of Open Access Journals (Sweden)

Tarique Jamil Saifullah Khanzada

2013-07-01

Full Text Available The Internet is migrating from IPv4 (Internet Protocol version 4 to IPv6 (Internet Protocol version 6. The high cost of migration services from IPv4-IPv6 and system complexity are main factors for slow adaption of IPv6 This paper presents the implementation of migration techniques from IPv4-IPv6. Furthermore, existing IPv4 addresses have already been depleted in IANA (Internet Assigned Numbers Authority and will be soon exhausted in RIR (Regional Internet Registry while more clients are joining the Internet. Slower rate of the progress of IPv6 confirms complete shifting from IPv4-IPv6 at once is still long away, although fewer parts of IPv6 have been employed in current market goods. Integration of IPv4 and IPv6 is carried in order to take care of online users. In this paper, it is suggested that hierarchical direction finding structural design in IPv4 and IPv6 will improve the efficiency of IPv4 network. This research work provides the way to design the network scenario for the carrier grade set of connections. The carrier grade network scenario routers are named to be Karachi, Sukkur, Islamabad, Multan and Peshawar for the managerial simulation purposes. The carrier grade network deployment is implemented along with dual stack to migrate to IPv6. This study holds the way to deploy IPv4-IPv6 carrier grade network by providing real time scenario which is yet not considered in the literature to the best of our knowledge

Performansi Video on Demand (VOD) Pada Virtual Private Network (VPN) Menggunakan OpenVPN

OpenAIRE

Priyambudi, Henry Okta

2013-01-01

Multimedia streaming menggunakanmedia video, sebagai cara penyampaian informasi yanglebih baik dibandingkan dengan teks atau suara. Salahsatu jenis multimedia streaming adalah Video OnDemand (VOD). Pada sistem video on demand, file videotelah disimpan terlebih dahulu di dalam server. Clientmerequest file video yang diinginkan dan prosesstreaming dapat dilakukan.. Salah satu kelemahan darivideo on demand adalah tidak ada sistem authentifikasipada client. Setiap client dapat melakukan streaming...

Cloud-Centric and Logically Isolated Virtual Network Environment Based on Software-Defined Wide Area Network

Directory of Open Access Journals (Sweden)

Dongkyun Kim

2017-12-01

Full Text Available Recent development of distributed cloud environments requires advanced network infrastructure in order to facilitate network automation, virtualization, high performance data transfer, and secured access of end-to-end resources across regional boundaries. In order to meet these innovative cloud networking requirements, software-defined wide area network (SD-WAN is primarily demanded to converge distributed cloud resources (e.g., virtual machines (VMs in a programmable and intelligent manner over distant networks. Therefore, this paper proposes a logically isolated networking scheme designed to integrate distributed cloud resources to dynamic and on-demand virtual networking over SD-WAN. The performance evaluation and experimental results of the proposed scheme indicate that virtual network convergence time is minimized in two different network models such as: (1 an operating OpenFlow-oriented SD-WAN infrastructure (KREONET-S which is deployed on the advanced national research network in Korea, and (2 Mininet-based experimental and emulated networks.

WATER NETWORK INTEGRATION IN RAW SUGAR PRODUCTION

Directory of Open Access Journals (Sweden)

Junior Lorenzo Llanes

2017-07-01

Full Text Available One of the main process industries in Cuba is that of the sugarcane. Among the characteristics of this industry is the high demand of water in its processes. In this work a study of water integration was carried out from the different operations of the production process of raw sugar, in order to reduce the fresh water consumption. The compound curves of sources and demands were built, which allowed the determination of the minimum water requirement of the network (1587,84 m3/d, as well as the amount of effluent generated (0,35 m3/tcane.The distribution scheme of fresh water and water reuse among different operations were obtained from the nearest neighbor algorithm. From considering new quality constrains was possible to eliminate the external water consumption, as well as to reduce the amount of effluent in a 37% in relation to the initial constrains.

Violence and weapon carrying in music videos. A content analysis.

Science.gov (United States)

DuRant, R H; Rich, M; Emans, S J; Rome, E S; Allred, E; Woods, E R

1997-05-01

The positive portrayal of violence and weapon carrying in televised music videos is thought to have a considerable influence on the normative expectations of adolescents about these behaviors. To perform a content analysis of the depictions of violence and weapon carrying in music videos, including 5 genres of music (rock, rap, adult contemporary, rhythm and blues, and country), from 4 television networks and to analyze the degree of sexuality or eroticism portrayed in each video and its association with violence and weapon carrying, as an indicator of the desirability of violent behaviors. Five hundred eighteen videos were recorded during randomly selected days and times of the day from the Music Television, Video Hits One, Black Entertainment Television, and Country Music Television networks. Four female and 4 male observers aged 17 to 24 years were trained to use a standardized content analysis instrument. Interobserver reliability testing resulted in a mean (+/- SD) percentage agreement of 89.25% +/- 7.10% and a mean (+/- SD) kappa of 0.73 +/- 0.20. All videos were observed by rotating 2-person, male-female teams that were required to reach agreement on each behavior that was scored. Music genre and network differences in behaviors were analyzed with chi 2 tests. A higher percentage (22.4%) of Music Television videos portrayed overt violence than Video Hits One (11.8%), Country Music Television (11.8%), and Black Entertainment Television (11.5%) videos (P = .02). Rap (20.4%) had the highest portrayal of violence, followed by rock (19.8%), country (10.8%), adult contemporary (9.7%), and rhythm and blues (5.9%) (P = .006). Weapon carrying was higher on Music Television (25.0%) than on Black Entertainment Television (11.5%), Video Hits One (8.4%), and Country Music Television (6.9%) (P violence (P violence and weapon carrying, which is glamorized by music artists, actors, and actresses.

Water demand forecasting: review of soft computing methods.

Science.gov (United States)

Ghalehkhondabi, Iman; Ardjmand, Ehsan; Young, William A; Weckman, Gary R

2017-07-01

Demand forecasting plays a vital role in resource management for governments and private companies. Considering the scarcity of water and its inherent constraints, demand management and forecasting in this domain are critically important. Several soft computing techniques have been developed over the last few decades for water demand forecasting. This study focuses on soft computing methods of water consumption forecasting published between 2005 and 2015. These methods include artificial neural networks (ANNs), fuzzy and neuro-fuzzy models, support vector machines, metaheuristics, and system dynamics. Furthermore, it was discussed that while in short-term forecasting, ANNs have been superior in many cases, but it is still very difficult to pick a single method as the overall best. According to the literature, various methods and their hybrids are applied to water demand forecasting. However, it seems soft computing has a lot more to contribute to water demand forecasting. These contribution areas include, but are not limited, to various ANN architectures, unsupervised methods, deep learning, various metaheuristics, and ensemble methods. Moreover, it is found that soft computing methods are mainly used for short-term demand forecasting.

Controlling market power and price spikes in electricity networks: Demand-side bidding.

Science.gov (United States)

Rassenti, Stephen J; Smith, Vernon L; Wilson, Bart J

2003-03-04

In this article we report an experiment that examines how demand-side bidding can discipline generators in a market for electric power. First we develop a treatment without demand-side bidding; two large firms are allocated baseload and intermediate cost generators such that either firm might unilaterally withhold the capacity of its intermediate cost generators from the market to benefit from the supracompetitive prices that would result from only selling its baseload units. In a converse treatment, ownership of some of the intermediate cost generators is transferred from each of these firms to two other firms such that no one firm could unilaterally restrict output to spawn supracompetitive prices. Having established a well controlled data set with price spikes paralleling those observed in the naturally occurring economy, we also extend the design to include demand-side bidding. We find that demand-side bidding completely neutralizes the exercise of market power and eliminates price spikes even in the presence of structural market power.

A Multicast Protocol Utilizing On-demand Routing Strategy for MPRN

Institute of Scientific and Technical Information of China (English)

无

2002-01-01

This paper proposes a multicast protocol utilizing ondemand routing strategy for mobile packet radio network. It does not maintain permanent route tables with full topological views. Instead, multicast senders apply on-demand procedures to dynamically discover routes and build forwarding group in this protocol. The data packets are propagated by each forwarding group member via scoped flooding, so the protocol can reduce network bandwidth overhead and avoid the propagation of potentially large routing updates throughout the network.

Delay model and performance testing for FPGA carry chain TDC

International Nuclear Information System (INIS)

Kang Xiaowen; Liu Yaqiang; Cui Junjian Yang Zhangcan; Jin Yongjie

2011-01-01

Time-of-flight (TOF) information would improve the performance of PET (position emission tomography). TDC design is a key technique. It proposed Carry Chain TDC Delay model. Through changing the significant delay parameter of model, paper compared the difference of TDC performance, and finally realized Time-to-Digital Convertor (TDC) based on Carry Chain Method using FPGA EP2C20Q240C8N with 69 ps LSB, max error below 2 LSB. Such result could meet the TOF demand. It also proposed a Coaxial Cable Measuring method for TDC testing, without High-precision test equipment. (authors)

An EPQ Model with Increasing Demand and Demand Dependent Production Rate under Trade Credit Financing

Directory of Open Access Journals (Sweden)

Juanjuan QIN

2015-05-01

Full Text Available This paper investigates an EPQ model with the increasing demand and demand dependent production rate involving the trade credit financing policy, which is seldom reported in the literatures. The model considers the manufacturer was offered by the supplier a delayed payment time. It is assumed that the demand is a linear increasing function of the time and the production rate is proportional to the demand. That is, the production rate is also a linear function of time. This study attempts to offer a best policy for the replenishment cycle and the order quantity for the manufacturer to maximum its profit per cycle. First, the inventory model is developed under the above situation. Second, some useful theoretical results have been derived to characterize the optimal solutions for the inventory system. The Algorithm is proposed to obtain the optimal solutions of the manufacturer. Finally, the numerical examples are carried out to illustrate the theorems, and the sensitivity analysis of the optimal solutions with respect to the parameters of the inventory system is performed. Some important management insights are obtained based on the analysis.

Feature Extraction Method for High Impedance Ground Fault Localization in Radial Power Distribution Networks

DEFF Research Database (Denmark)

Jensen, Kåre Jean; Munk, Steen M.; Sørensen, John Aasted

1998-01-01

A new approach to the localization of high impedance ground faults in compensated radial power distribution networks is presented. The total size of such networks is often very large and a major part of the monitoring of these is carried out manually. The increasing complexity of industrial...... of three phase voltages and currents. The method consists of a feature extractor, based on a grid description of the feeder by impulse responses, and a neural network for ground fault localization. The emphasis of this paper is the feature extractor, and the detection of the time instance of a ground fault...... processes and communication systems lead to demands for improved monitoring of power distribution networks so that the quality of power delivery can be kept at a controlled level. The ground fault localization method for each feeder in a network is based on the centralized frequency broadband measurement...

ANALISIS PERMINTAAN (DEMAND ANALYSIS PELAYANAN KESEHATAN PUSKESMAS DI KABUPATEN MOJOKERTO

Directory of Open Access Journals (Sweden)

Wasis Budiarto

2012-09-01

Full Text Available A study on demand for health centre was carried out at Mojokerto Regency, East Java. The study convered 300 respondents (15 years old and over which were collected from two areas, urban (Kecamatan Bangsal and rural (Kecamatan Puri. The objectives of this study were to measure the demand for health centre services and to determine the influencing factors. A household survey was conducted in this study, using household and individual as unit of analysis and a multiple linier regression technique was used as analysis. In general, the result showed that needs were the most important factor affecting demand. In the urban health centres positive factor affecting individual demand were distance, family size and need, however in the rural health centre were cost, time and need were factors affecting demand. Factors affecting family demand for health services is different from individual demand. In urban and rural areas, family demand for health center was substitute alternative of the demand for the phycisian services.

Mapping Urban Heat Demand with the Use of GIS-Based Tools

Directory of Open Access Journals (Sweden)

Artur Wyrwa

2017-05-01

Full Text Available This article presents a bottom-up approach for calculation of the useful heat demand for space heating and hot water preparation using geo-referenced datasets for buildings at the city level. This geographic information system (GIS based approach was applied in the case study for the city of Krakow, where on the one hand the district heat network is well developed, while on the other hand there are still substantial number of buildings burning solid fuels in individual boilers and stoves, causing air pollution. The calculated heat demand was aggregated in the grid with 100 m × 100 m spatial resolution to deliver the heat map depicting the current situation for 21 buildings types. The results show that the residential buildings, in particular one- and multi-family buildings, have the highest share in overall demand for heat. By combining the results with location of the district heat (DH network, the potential areas in its close vicinity that have sufficient heat demand density for developing the net were pointed out. Future evolution in heat demand for space heating in one-family houses was evaluated with the use of deterministic method employing building stock model. The study lays a foundation for planning the development of the heating system at the city level.

Radon levels in a water distribution network

International Nuclear Information System (INIS)

Alabdula'aly, A.I.

1997-01-01

The capital city of Saudi Arabia, Riyadh, relies on both desalinated sea water as well as treated groundwater to meet all its water requirements. About 66% of the water demand is met by desalinated sea water, and the remaining is supplied by six groundwater treatment plants located in the vicinity of the city and supplied with water from 161 wells. The desalinated sea water is blended with only one plant product water and pumped to the distribution network, whereas the other five plants product water is pumped directly to the network. A study of 222 Rn levels in the city distribution network was carried out in which 89 samples were collected from different locations representing the city districts. All samples have shown low radon levels with an average concentration of 0.2 Bq l -1 and a range values of 0.1-1.0 Bq l -1 . The level of radon in different parts of the network was found to be influenced by the water sources to which they are supplied. The lowest radon levels were observed in districts supplied mostly by desalinated sea water. (Author)

New grid based test bed environment for carrying out ad-hoc networking experiments

CSIR Research Space (South Africa)

Johnson, D

2006-09-01

Full Text Available and the third is to do analysis on a real test bed network which has implemented the ad-hoc networking protocol. This paper concerns the third option. Most researchers who have done work on test bed environments have used either indoor Wifi inter-office links...

A-Source Impedance Network

DEFF Research Database (Denmark)

Siwakoti, Yam Prasad; Blaabjerg, Frede; Galigekere, Veda Prakash

2016-01-01

A novel A-source impedance network is proposed in this letter. The A-source impedance network uses an autotransformer for realizing converters for any application that demand a very high dc voltage gain. The network utilizes a minimal turns ratio compared to other Magnetically Coupled Impedance S...

Hierarchical Network Design Using Simulated Annealing

DEFF Research Database (Denmark)

Thomadsen, Tommy; Clausen, Jens

2002-01-01

networks are described and a mathematical model is proposed for a two level version of the hierarchical network problem. The problem is to determine which edges should connect nodes, and how demand is routed in the network. The problem is solved heuristically using simulated annealing which as a sub......-algorithm uses a construction algorithm to determine edges and route the demand. Performance for different versions of the algorithm are reported in terms of runtime and quality of the solutions. The algorithm is able to find solutions of reasonable quality in approximately 1 hour for networks with 100 nodes....

Development and application of computer network for working out of researches on high energy physics

International Nuclear Information System (INIS)

Boos, Eh.G.; Tashimov, M.A.

2001-01-01

Computer network of the Physical and Technological Institute of the Ministry and Science and Education of the Republic of Kazakhstan (FTI of MSE RK) jointing a number of the research institutions, leading universities and other enterprises of Almaty city. At the present time more than 350 computers are connected to this network, the velocity of satellite channel is increased up to 192 k bit/s per one reception. The university segments of the network are separated in individual domen. A new software for analysis and proceeding of experimental data are implemented and other measures are carried out as well. However an increasing volume of information exchange between nuclear-physical center demanding the further information network development. So for providing consumers demands in information exchange in the nearest years in the paper the possibility for following measures maintenance are considered: (1) Increase of satellite channel velocity up to 1-2 M bit/s by replace of the existing SDM-100 modem on a rapid one. Now using the Kedr-M station and the CISCO-2501 tracer allowing to provide such velocity; (2) Convert of the Institute local calculation network on the new Fast Ethernet technology permitting to increase the information transmission velocity up to 100 M bit/s at the complete succession of existing Ethernet; (3) The Proxy-server (Firewaal) install at the network support assay, that giving the possibility for discharging of satellite channel and localization of segment of the network, connected with learning on the Internet not in damage to educational process. In the framework of cooperation with DESY German accelerating center with help of the indicated network the data about 2 hundred thousand deep inelastic interactions of electrons with protons measured at ZEUS detector are obtained. Data about 10 thousand of events simulated at the OPAL installation are received as well. Besides the computer network is using for operative information exchange and

The Optimal Replenishment Policy under Trade Credit Financing with Ramp Type Demand and Demand Dependent Production Rate

Directory of Open Access Journals (Sweden)

Juanjuan Qin

2014-01-01

Full Text Available This paper investigates the optimal replenishment policy for the retailer with the ramp type demand and demand dependent production rate involving the trade credit financing, which is not reported in the literatures. First, the two inventory models are developed under the above situation. Second, the algorithms are given to optimize the replenishment cycle time and the order quantity for the retailer. Finally, the numerical examples are carried out to illustrate the optimal solutions and the sensitivity analysis is performed. The results show that if the value of production rate is small, the retailer will lower the frequency of putting the orders to cut down the order cost; if the production rate is high, the demand dependent production rate has no effect on the optimal decisions. When the trade credit is less than the growth stage time, the retailer will shorten the replenishment cycle; when it is larger than the breakpoint of the demand, within the maturity stage of the products, the trade credit has no effect on the optimal order cycle and the optimal order quantity.

The impact of small scale cogeneration on the gas demand at distribution level

International Nuclear Information System (INIS)

Vandewalle, J.; D’haeseleer, W.

2014-01-01

Highlights: • Impact on the gas network of a massive implementation of cogeneration. • Distributed energy resources in a smart grid environment. • Optimisation of cogeneration scheduling. - Abstract: Smart grids are often regarded as an important step towards the future energy system. Combined heat and power (CHP) or cogeneration has several advantages in the context of the smart grid, which include the efficient use of primary energy and the reduction of electrical losses through transmission. However, the role of the gas network is often overlooked in this context. Therefore, this work presents an analysis of the impact of a massive implementation of small scale (micro) cogeneration units on the gas demand at distribution level. This work shows that using generic information in the simulations overestimates the impact of CHP. Furthermore, the importance of the thermal storage tank capacity on the impact on the gas demand is shown. Larger storage tanks lead to lower gas demand peaks and hence a lower impact on the gas distribution network. It is also shown that the use of an economically led controller leads to similar results compared to classical heat led control. Finally, it results that a low sell back tariff for electricity increases the impact of cogeneration on the gas demand peak

Access control for on-demand provisioned cloud infrastructure services

NARCIS (Netherlands)

Ngo, C.T.

2016-01-01

The evolution of Cloud Computing brings advantages to both customers and service providers to utilize and manage computing and network resources more efficiently with virtualization, service-oriented architecture technologies, and automated on-demand resource provisioning. However, these advantages

PERIODIC REVIEW SYSTEM FOR INVENTORY REPLENISHMENT CONTROL FOR A TWO-ECHELON LOGISTICS NETWORK UNDER DEMAND UNCERTAINTY: A TWO-STAGE STOCHASTIC PROGRAMING APPROACH

Directory of Open Access Journals (Sweden)

P.S.A. Cunha

Full Text Available ABSTRACT Here, we propose a novel methodology for replenishment and control systems for inventories of two-echelon logistics networks using a two-stage stochastic programming, considering periodic review and uncertain demands. In addition, to achieve better customer services, we introduce a variable rationing rule to address quantities of the item in short. The devised models are reformulated into their deterministic equivalent, resulting in nonlinear mixed-integer programming models, which are then approximately linearized. To deal with the uncertain nature of the item demand levels, we apply a Monte Carlo simulation-based method to generate finite and discrete sets of scenarios. Moreover, the proposed approach does not require restricted assumptions to the behavior of the probabilistic phenomena, as does several existing methods in the literature. Numerical experiments with the proposed approach for randomly generated instances of the problem show results with errors around 1%.

High Electricity Demand in the Northeast U.S.: PJM Reliability Network and Peaking Unit Impacts on Air Quality.

Science.gov (United States)

Farkas, Caroline M; Moeller, Michael D; Felder, Frank A; Henderson, Barron H; Carlton, Annmarie G

2016-08-02

On high electricity demand days, when air quality is often poor, regional transmission organizations (RTOs), such as PJM Interconnection, ensure reliability of the grid by employing peak-use electric generating units (EGUs). These "peaking units" are exempt from some federal and state air quality rules. We identify RTO assignment and peaking unit classification for EGUs in the Eastern U.S. and estimate air quality for four emission scenarios with the Community Multiscale Air Quality (CMAQ) model during the July 2006 heat wave. Further, we population-weight ambient values as a surrogate for potential population exposure. Emissions from electricity reliability networks negatively impact air quality in their own region and in neighboring geographic areas. Monitored and controlled PJM peaking units are generally located in economically depressed areas and can contribute up to 87% of hourly maximum PM2.5 mass locally. Potential population exposure to peaking unit PM2.5 mass is highest in the model domain's most populated cities. Average daily temperature and national gross domestic product steer peaking unit heat input. Air quality planning that capitalizes on a priori knowledge of local electricity demand and economics may provide a more holistic approach to protect human health within the context of growing energy needs in a changing world.

Data-driven Demand Response Characterization and Quantification

DEFF Research Database (Denmark)

Le Ray, Guillaume; Pinson, Pierre; Larsen, Emil Mahler

2017-01-01

Analysis of load behavior in demand response (DR) schemes is important to evaluate the performance of participants. Very few real-world experiments have been carried out and quantification and characterization of the response is a difficult task. Nevertheless it will be a necessary tool for portf...

Demand side integration aspects in active distribution planning

DEFF Research Database (Denmark)

Silvestro, Federico; Baitch, Alex; Pilo, Fabrizio

2013-01-01

will be implemented in practice? How will regulatory frameworks and connection agreements evolve to support ADSs? The present work provides some information about the closer and closer integration between network planning and Demand Side Integration that is foreseen in the future and shows the necessity to develop...

Impaired action potential initiation in GABAergic interneurons causes hyperexcitable networks in an epileptic mouse model carrying a human Na(V)1.1 mutation.

Science.gov (United States)

Hedrich, Ulrike B S; Liautard, Camille; Kirschenbaum, Daniel; Pofahl, Martin; Lavigne, Jennifer; Liu, Yuanyuan; Theiss, Stephan; Slotta, Johannes; Escayg, Andrew; Dihné, Marcel; Beck, Heinz; Mantegazza, Massimo; Lerche, Holger

2014-11-05

Mutations in SCN1A and other ion channel genes can cause different epileptic phenotypes, but the precise mechanisms underlying the development of hyperexcitable networks are largely unknown. Here, we present a multisystem analysis of an SCN1A mouse model carrying the NaV1.1-R1648H mutation, which causes febrile seizures and epilepsy in humans. We found a ubiquitous hypoexcitability of interneurons in thalamus, cortex, and hippocampus, without detectable changes in excitatory neurons. Interestingly, somatic Na(+) channels in interneurons and persistent Na(+) currents were not significantly changed. Instead, the key mechanism of interneuron dysfunction was a deficit of action potential initiation at the axon initial segment that was identified by analyzing action potential firing. This deficit increased with the duration of firing periods, suggesting that increased slow inactivation, as recorded for recombinant mutated channels, could play an important role. The deficit in interneuron firing caused reduced action potential-driven inhibition of excitatory neurons as revealed by less frequent spontaneous but not miniature IPSCs. Multiple approaches indicated increased spontaneous thalamocortical and hippocampal network activity in mutant mice, as follows: (1) more synchronous and higher-frequency firing was recorded in primary neuronal cultures plated on multielectrode arrays; (2) thalamocortical slices examined by field potential recordings revealed spontaneous activities and pathological high-frequency oscillations; and (3) multineuron Ca(2+) imaging in hippocampal slices showed increased spontaneous neuronal activity. Thus, an interneuron-specific generalized defect in action potential initiation causes multisystem disinhibition and network hyperexcitability, which can well explain the occurrence of seizures in the studied mouse model and in patients carrying this mutation. Copyright © 2014 the authors 0270-6474/14/3414874-16$15.00/0.

User Requirements & Demand for Services and Applications in PNs

DEFF Research Database (Denmark)

Jiang, Bo

This paper focuses on the methodology for analyses of user requirements and demand for specific services and applications in relation to personal networks (PNs). The paper has a strong user-centric approach to service and application development based on the widely accepted fact that future servi...... demand for services and applications in a PN setting. This further includes discussion of service categorization, service description and human-value issues as personalization, security and privacy, billing and price and human-computer interaction paradigms....

Energy and electricity demand forecasting for nuclear power planning in developing countries

International Nuclear Information System (INIS)

1988-07-01

This Guidebook is designed to be a reference document to forecast energy and electricity demand. It presents concepts and methodologies that have been developed to make an analytical approach to energy/electricity demand forecasting as part of the planning process. The Guidebook is divided into 6 main chapters: (Energy demand and development, energy demand analysis, electric load curve analysis, energy and electricity demand forecasting, energy and electricity demand forecasting tools used in various organizations, IAEA methodologies for energy and electricity demand forecasting) and 3 appendices (experience with case studies carried out by the IAEA, reference technical data, reference economic data). A bibliography and a glossary complete the Guidebook. Refs, figs and tabs

Carrying capacities for nature parks as engines for sustainable regional development

DEFF Research Database (Denmark)

Brandt, Jesper; Holmes, Esbern

as a departure for the comparison of the protectional conditions for the parks. Many other aspects of the nature and social carrying capacities however also constitute important conditions for the park management. Increasing emphasis on visitor experience is not only a challenge for the nature protection......Growth in the number of visitors is an upcoming problem in nature parks. Nature parks are at the same time facing increasing demand, falling public appropriations and receding focus on their conservation functions. To ensure a balancing of nature protection and economic utilization the concept...... of carrying capacity has received increasing attention among park-authorities all over the world. A comparative analysis of conditions and initiatives related to visitor/nature carrying capacities in 8 nature parks in the Baltic region has been carried out. All the parks are candidates for recognition...

Water quality modeling in the dead end sections of drinking water distribution networks.

Science.gov (United States)

Abokifa, Ahmed A; Yang, Y Jeffrey; Lo, Cynthia S; Biswas, Pratim

2016-02-01

Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to water stagnation leads to rapid reduction of disinfectant residuals allowing the regrowth of microbial pathogens. Water quality models developed so far apply spatial aggregation and temporal averaging techniques for hydraulic parameters by assigning hourly averaged water demands to the main nodes of the network. Although this practice has generally resulted in minimal loss of accuracy for the predicted disinfectant concentrations in main water transmission lines, this is not the case for the peripheries of the distribution network. This study proposes a new approach for simulating disinfectant residuals in dead end pipes while accounting for both spatial and temporal variability in hydraulic and transport parameters. A stochastic demand generator was developed to represent residential water pulses based on a non-homogenous Poisson process. Dispersive solute transport was considered using highly dynamic dispersion rates. A genetic algorithm was used to calibrate the axial hydraulic profile of the dead-end pipe based on the different demand shares of the withdrawal nodes. A parametric sensitivity analysis was done to assess the model performance under variation of different simulation parameters. A group of Monte-Carlo ensembles was carried out to investigate the influence of spatial and temporal variations in flow demands on the simulation accuracy. A set of three correction factors were analytically derived to adjust residence time, dispersion rate and wall demand to overcome simulation error caused by spatial aggregation approximation. The current model results show better agreement with field-measured concentrations of conservative fluoride tracer and free chlorine disinfectant than the simulations of recent advection dispersion reaction models published in the literature. Accuracy of the simulated

Security Services Lifecycle Management in on-demand infrastructure services

NARCIS (Netherlands)

Demchenko, Y.; de Laat, C.; Lopez, D.R.; García-Espín, J.A.; Qiu, J.; Zhao, G.; Rong, C.

2010-01-01

Modern e-Science and high technology industry require high-performance and complicated network and computer infrastructure to support distributed collaborating groups of researchers and applications that should be provisioned on-demand. The effective use and management of the dynamically provisioned

Quantitative Efficiency Evaluation Method for Transportation Networks

Directory of Open Access Journals (Sweden)

Jin Qin

2014-11-01

Full Text Available An effective evaluation of transportation network efficiency/performance is essential to the establishment of sustainable development in any transportation system. Based on a redefinition of transportation network efficiency, a quantitative efficiency evaluation method for transportation network is proposed, which could reflect the effects of network structure, traffic demands, travel choice, and travel costs on network efficiency. Furthermore, the efficiency-oriented importance measure for network components is presented, which can be used to help engineers identify the critical nodes and links in the network. The numerical examples show that, compared with existing efficiency evaluation methods, the network efficiency value calculated by the method proposed in this paper can portray the real operation situation of the transportation network as well as the effects of main factors on network efficiency. We also find that the network efficiency and the importance values of the network components both are functions of demands and network structure in the transportation network.

Adaptation possibilities of the nuclear electricity production to the demand; Possibilites d'adaptation de la production d'electricite nucleaires a la demande

Energy Technology Data Exchange (ETDEWEB)

Acket, C

2009-02-15

Meeting about the CO{sub 2} emissions from electric heating showed that the leak of adaptation from nuclear reactors led the use of thermal power plants (coal, petroleum, gas) to control the demand variations. This argument is analyzed in the document: is it possible to replace those thermal power plants by nuclear reactors? In this framework the author analyzes the network needs, the electricity sources and the demand answer and the specificities of the nuclear. (A.L.B.)

Price elasticity estimation of electricity demand in France

International Nuclear Information System (INIS)

Bourbonnais, Regis; Keppler, Jan Horst

2013-10-01

On request of the French Union of Electricity (UFE), the authors have carried out a series of econometric statistical tests in order to determine the price elasticity of electricity demand in France. The results obtained are all solid and realistic

On achieving network throughput demand in cognitive radio-based home area networks

NARCIS (Netherlands)

Sarijari, M.A.B.; Abdullah, M.S.; Janssen, G.J.M.; Van der Veen, A.J.

2015-01-01

The growing number of wireless devices for in-house use is causing a more intense use of the spectrum to satisfy the required quality-of-service such as throughput. This has contributed to spectrum scarcity and interference problems particularly in home area networks (HAN). Cognitive radio (CR) has

Using turbidity for designing water networks.

Science.gov (United States)

Castaño, J A; Higuita, J C

2016-05-01

Some methods to design water networks with minimum fresh water consumption are based on the selection of a key contaminant. In most of these "single contaminant methods", a maximum allowable concentration of contaminants must be established in water demands and water sources. Turbidity is not a contaminant concentration but is a property that represents the "sum" of other contaminants, with the advantage that it can be cheaper and easily measured than biological oxygen demand, chemical oxygen demand, suspended solids, dissolved solids, among others. The objective of this paper is to demonstrate that turbidity can be used directly in the design of water networks just like any other contaminant concentration. A mathematical demonstration is presented and in order to validate the mathematical results, the design of a water network for a guava fudge production process is performed. The material recovery pinch diagram and nearest neighbors algorithm were used for the design of the water network. Nevertheless, this water network could be designed using other single contaminant methodologies. The maximum error between the expected and the real turbidity values in the water network was 3.3%. These results corroborate the usefulness of turbidity in the design of water networks. Copyright © 2016 Elsevier Ltd. All rights reserved.

Traffic engineering and regenerator placement in GMPLS networks with restoration

Science.gov (United States)

Yetginer, Emre; Karasan, Ezhan

2002-07-01

In this paper we study regenerator placement and traffic engineering of restorable paths in Generalized Multipro-tocol Label Switching (GMPLS) networks. Regenerators are necessary in optical networks due to transmission impairments. We study a network architecture where there are regenerators at selected nodes and we propose two heuristic algorithms for the regenerator placement problem. Performances of these algorithms in terms of required number of regenerators and computational complexity are evaluated. In this network architecture with sparse regeneration, offline computation of working and restoration paths is studied with bandwidth reservation and path rerouting as the restoration scheme. We study two approaches for selecting working and restoration paths from a set of candidate paths and formulate each method as an Integer Linear Programming (ILP) prob-lem. Traffic uncertainty model is developed in order to compare these methods based on their robustness with respect to changing traffic patterns. Traffic engineering methods are compared based on number of additional demands due to traffic uncertainty that can be carried. Regenerator placement algorithms are also evaluated from a traffic engineering point of view.

Ecological balance between supply and demand based on cultivated land ecological footprint method in Guizhou Province

Science.gov (United States)

Qian, Qinghuan; Zhou, Dequan; Bai, Xiaoyong; Xiao, Jianyong; Chen, Fei; Zeng, Cheng

2018-01-01

In order to construct the indicators of the balance between supply and demand of the cultivated land ecological carrying capacity, basing on the relation of the cultivated land ecological carrying capacity supply and demand, applying the model of Cultivated Land Ecological Footprints and the method of CIS and considering the factors of cultivated land production, taking the statistical data of 2015 as an example, and then made a systematic evaluation of the balance between supply and demand of the cultivated land ecological carrying capacity in Guizhou Province. The results show that (1) the spatial distribution of supply and demand of cultivated land ecological carrying capacity in Guizhou is unbalanced, and the northern and eastern parts are the overloading area, the middle, the south and the west parts are the balance area. (2) From the perspective of cultivated land structure, the crops with ecological carrying capacity surplus were rice, vegetables and peanuts, among which rice was the highest and the ecological balance index was 0.7354. The crops with ecological carrying capacity overload were potato, wheat, maize, rapeseeds, soybeans and cured tobacco, of which the index of potato up to 7.11, other types of indices are less than 1.5. The research can provide the ecological security early warning, the overall plan of land use and sustainable development of the area cultivated land with scientific evidence and decision support.

Joint Planning Of Energy Storage and Transmission Considering Wind-Storage Combined System and Demand Side Response

Science.gov (United States)

Huang, Y.; Liu, B. Z.; Wang, K. Y.; Ai, X.

2017-12-01

In response to the new requirements of the operation mode of wind-storage combined system and demand side response for transmission network planning, this paper presents a joint planning of energy storage and transmission considering wind-storage combined system and demand side response. Firstly, the charge-discharge strategy of energy storage system equipped at the outlet of wind farm and demand side response strategy are analysed to achieve the best comprehensive benefits through the coordination of the two. Secondly, in the general transmission network planning model with wind power, both energy storage cost and demand side response cost are added to the objective function. Not only energy storage operation constraints and but also demand side response constraints are introduced into the constraint condition. Based on the classical formulation of TEP, a new formulation is developed considering the simultaneous addition of the charge-discharge strategy of energy storage system equipped at the outlet of the wind farm and demand side response strategy, which belongs to a typical mixed integer linear programming model that can be solved by mature optimization software. The case study based on the Garver-6 bus system shows that the validity of the proposed model is verified by comparison with general transmission network planning model. Furthermore, the results demonstrate that the joint planning model can gain more economic benefits through setting up different cases.

Security framework for virtualised infrastructure services provisioned on-demand

NARCIS (Netherlands)

Ngo, C.; Membrey, P.; Demchenko, Y.; de Laat, C.

2011-01-01

Cloud computing is developing as a new wave of ICT technologies, offering a common approach to on-demand provisioning computation, storage and network resources which are generally referred to as infrastructure services. Most of currently available commercial Cloud services are built and organized

Carry

DEFF Research Database (Denmark)

Koijen, Ralph S.J.; Moskowitz, Tobias J.; Heje Pedersen, Lasse

that include global equities, global bonds, currencies, commodities, US Treasuries, credit, and equity index options. This predictability underlies the strong returns to "carry trades" that go long high-carry and short low-carry securities, applied almost exclusively to currencies, but shown here...

A local area network for medical research; planning, realization and experience.

Science.gov (United States)

Schosser, R; Weiss, C; Messmer, K

1991-01-01

This report focuses on the planning and realization of an interdisciplinary local area network (LAN) for medical research at the University of Heidelberg. After a detailed requirements analysis, several networks were evaluated by means of a test installation, and a cost-performance analysis was carried out. At present, the LAN connects 45 (IBM-compatible) PCs, several heterogeneous mainframes (IBM, DEC and Siemens) and provides access to the public X.25 network and to wide-area networks for research (EARN, BITNET). The network supports application software that is frequently needed in medical research (word processing, statistics, graphics, literature databases and services, etc.). Compliance with existing "official" (e.g., IEEE 802.3) and "de facto" standards (e.g., PostScript) was considered to be extremely important for the selection of both hardware and software. Customized programs were developed to improve access control, user interface and on-line help. Wide acceptance of the LAN was achieved through extensive education and maintenance facilities, e.g., teaching courses, customized manuals and a hotline service. Since requirements of clinical routine differ substantially from medical research needs, two separate networks (with a gateway in between) are proposed as a solution to optimally satisfy the users' demands.

The determining factors of natural gas demand in domestic sector

International Nuclear Information System (INIS)

Cadoret, I.

1992-01-01

Natural gas plays an important role in domestic sector. For example, in France, Italy, Germany and United-Kingdom the natural gas share in energy demand of domestic sector is respectively 26%, 44%, 34% and 63%. A study of energy policies, natural gas industry structure and tarification system of this four countries indicates that gas development is linked to the government and petroleum companies policy. Econometric models estimation show by another way that when natural gas is introduced in domestic sector, the demand follows the distribution network. When the market is saturated, the demand changes with energy price and household income. 8 refs., 2 tabs., 5 figs

Efficient Bandwidth Management for Ethernet Passive Optical Networks

KAUST Repository

Elrasad, Amr

2016-01-01

The increasing bandwidth demands in access networks motivates network operators, networking devices manufacturers, and standardization institutions to search for new approaches for access networks. These approaches should support higher bandwidth

Electricity demand in France: what's at stake for the energy transition?

International Nuclear Information System (INIS)

Berghmans, Nicolas

2017-02-01

This study identifies five key issues linked to electricity consumption to be taken into consideration in the management of the French power system transition: articulating the building stock renovation strategy and electricity consumption; integrating demand for electricity stemming from the development of electric vehicles; addressing winter 'peak' demand with specific demand-side policies; establishing energy demand management economic models as a flexible solution for the power system; identifying the impact of the emergence of a power system that is decentralised, balanced locally and connected with other energy carriers on the nature of demand for power from the grid. In the context of weak economic and demographic growth, the recent stabilization of electricity demand in France can be attributed to 'structural' factors, i.e. the continued expansion of the tertiary sector in the economy and the acceleration in energy efficiency gains. This evolution was poorly anticipated by stakeholders in the sector, which contributed to an imbalance between electricity demand and supply in Europe. In the absence of a major disruption, planning for transition in the electrical system should be made assuming relatively stable demand. However, major transformations will change the nature of the requirements placed on the electricity system: the times at which energy is consumed, the ability to manage the demand side of the system, and the geographical location of electricity demand within the network. Five key challenges are identified to anticipate the development of electricity consumption patterns: the role of electricity in satisfying building sector heating requirements, the integration of electric vehicle charging, the evolution of the winter demand peak, the development of demand-side management, and the emergence of an electric system based on local-level balancing. Too often considered an exogenous factor, the development in electricity consumption is in fact central

Price, environment and security: Exploring multi-modal motivation in voluntary residential peak demand response

International Nuclear Information System (INIS)

Gyamfi, Samuel; Krumdieck, Susan

2011-01-01

Peak demand on electricity grids is a growing problem that increases costs and risks to supply security. Residential sector loads often contribute significantly to seasonal and daily peak demand. Demand response projects aim to manage peak demand by applying price signals and automated load shedding technologies. This research investigates voluntary load shedding in response to information about the security of supply, the emission profile and the cost of meeting critical peak demand in the customers' network. Customer willingness to change behaviour in response to this information was explored through mail-back survey. The diversified demand modelling method was used along with energy audit data to estimate the potential peak load reduction resulting from the voluntary demand response. A case study was conducted in a suburb of Christchurch, New Zealand, where electricity is the main source for water and space heating. On this network, all water heating cylinders have ripple-control technology and about 50% of the households subscribe to differential day/night pricing plan. The survey results show that the sensitivity to supply security is on par with price, with the emission sensitivity being slightly weaker. The modelling results show potential 10% reduction in critical peak load for aggregate voluntary demand response. - Highlights: → Multiple-factor behaviour intervention is necessarily for effective residential demand response. → Security signals can achieve result comparable to price. → The modelling results show potential 10% reduction in critical peak load for aggregate voluntary demand response. → New Zealand's energy policy should include innovation and development of VDR programmes and technologies.

A Hybrid Approach on Tourism Demand Forecasting

Science.gov (United States)

Nor, M. E.; Nurul, A. I. M.; Rusiman, M. S.

2018-04-01

Tourism has become one of the important industries that contributes to the country’s economy. Tourism demand forecasting gives valuable information to policy makers, decision makers and organizations related to tourism industry in order to make crucial decision and planning. However, it is challenging to produce an accurate forecast since economic data such as the tourism data is affected by social, economic and environmental factors. In this study, an equally-weighted hybrid method, which is a combination of Box-Jenkins and Artificial Neural Networks, was applied to forecast Malaysia’s tourism demand. The forecasting performance was assessed by taking the each individual method as a benchmark. The results showed that this hybrid approach outperformed the other two models

Inventory redistribution for fashion products under demand parameter update

NARCIS (Netherlands)

Kiesmuller, G.P.; Minner, S.

2009-01-01

Demand for fashion products is usually highly uncertain. Often, there is only one possibility for procurement before the selling season. In order to improve the traditional newsvendor-type overage-underage trade-off we study a network of two expected profit maximizing retailers selling a fashion

Cisco Networking Essentials

CERN Document Server

McMillan, Troy

2011-01-01

An engaging approach for anyone beginning a career in networking As the world leader of networking products and services, Cisco products are constantly growing in demand. Yet, few books are aimed at those who are beginning a career in IT--until now. Cisco Networking Essentials provides a solid foundation on the Cisco networking products and services with thorough coverage of fundamental networking concepts. Author Troy McMillan applies his years of classroom instruction to effectively present high-level topics in easy-to-understand terms for beginners. With this indispensable full-color resour

Distributed MPC applied to power demand side control

NARCIS (Netherlands)

Larsen, G.K.H.; Pons, J.; Achterop, S.; Scherpen, J.M.A.

2013-01-01

In the future, global energy balance of a smart grid system can be achieved by its agents deciding on their own power demand locally and the exchange of these decisions. In this paper, we model a network of households with washing machine programs that can be shifted in time so that the overall

Social working memory: neurocognitive networks and directions for future research.

Science.gov (United States)

Meyer, Meghan L; Lieberman, Matthew D

2012-01-01

Navigating the social world requires the ability to maintain and manipulate information about people's beliefs, traits, and mental states. We characterize this capacity as social working memory (SWM). To date, very little research has explored this phenomenon, in part because of the assumption that general working memory systems would support working memory for social information. Various lines of research, however, suggest that social cognitive processing relies on a neurocognitive network (i.e., the "mentalizing network") that is functionally distinct from, and considered antagonistic with, the canonical working memory network. Here, we review evidence suggesting that demanding social cognition requires SWM and that both the mentalizing and canonical working memory neurocognitive networks support SWM. The neural data run counter to the common finding of parametric decreases in mentalizing regions as a function of working memory demand and suggest that the mentalizing network can support demanding cognition, when it is demanding social cognition. Implications for individual differences in social cognition and pathologies of social cognition are discussed.

On the choice of the demand and hydraulic modeling approach to WDN real-time simulation

Science.gov (United States)

Creaco, Enrico; Pezzinga, Giuseppe; Savic, Dragan

2017-07-01

This paper aims to analyze two demand modeling approaches, i.e., top-down deterministic (TDA) and bottom-up stochastic (BUA), with particular reference to their impact on the hydraulic modeling of water distribution networks (WDNs). In the applications, the hydraulic modeling is carried out through the extended period simulation (EPS) and unsteady flow modeling (UFM). Taking as benchmark the modeling conditions that are closest to the WDN's real operation (UFM + BUA), the analysis showed that the traditional use of EPS + TDA produces large pressure head and water discharge errors, which can be attenuated only when large temporal steps (up to 1 h in the case study) are used inside EPS. The use of EPS + BUA always yields better results. Indeed, EPS + BUA already gives a good approximation of the WDN's real operation when intermediate temporal steps (larger than 2 min in the case study) are used for the simulation. The trade-off between consistency of results and computational burden makes EPS + BUA the most suitable tool for real-time WDN simulation, while benefitting from data acquired through smart meters for the parameterization of demand generation models.

Software Defined Networking to support IP address mobility in future LTE network

NARCIS (Netherlands)

Karimzadeh Motallebi Azar, Morteza; Valtulina, Luca; van den Berg, Hans Leo; Pras, Aiko; Liebsch, Marco; Taleb, Tarik

2017-01-01

The existing LTE network architecture dose not scale well to increasing demands due to its highly centralized and hierarchical composition. In this paper we discuss the major modifications required in the current LTE network to realize a decentralized LTE architecture. Next, we develop two IP

Addressing the minimum fleet problem in on-demand urban mobility.

Science.gov (United States)

Vazifeh, M M; Santi, P; Resta, G; Strogatz, S H; Ratti, C

2018-05-01

Information and communication technologies have opened the way to new solutions for urban mobility that provide better ways to match individuals with on-demand vehicles. However, a fundamental unsolved problem is how best to size and operate a fleet of vehicles, given a certain demand for personal mobility. Previous studies 1-5 either do not provide a scalable solution or require changes in human attitudes towards mobility. Here we provide a network-based solution to the following 'minimum fleet problem', given a collection of trips (specified by origin, destination and start time), of how to determine the minimum number of vehicles needed to serve all the trips without incurring any delay to the passengers. By introducing the notion of a 'vehicle-sharing network', we present an optimal computationally efficient solution to the problem, as well as a nearly optimal solution amenable to real-time implementation. We test both solutions on a dataset of 150 million taxi trips taken in the city of New York over one year 6 . The real-time implementation of the method with near-optimal service levels allows a 30 per cent reduction in fleet size compared to current taxi operation. Although constraints on driver availability and the existence of abnormal trip demands may lead to a relatively larger optimal value for the fleet size than that predicted here, the fleet size remains robust for a wide range of variations in historical trip demand. These predicted reductions in fleet size follow directly from a reorganization of taxi dispatching that could be implemented with a simple urban app; they do not assume ride sharing 7-9 , nor require changes to regulations, business models, or human attitudes towards mobility to become effective. Our results could become even more relevant in the years ahead as fleets of networked, self-driving cars become commonplace 10-14 .

Economic Analysis of Urban Fuelwood Demand - The case of Harare in Zimbabwe

NARCIS (Netherlands)

Chambwera, M.

2004-01-01

This study carries out an economic analysis of the demand for fuelwood in urban areas using Harare, the capital city of Zimbabwe, as a case study. The demand for fuelwood in urban areas is one of the causes of several environmental and health problems in Africa, where the up to 90% of energy

Presenting automatic demand control (ADC) as a new frequency control method in smart grids

Energy Technology Data Exchange (ETDEWEB)

Ameli, Mohammad Taghi; Ameli, Ali; Maleki, Hamed [Power and Water Univ. of Technology, Tehran (Iran, Islamic Republic of); Mobarhani, Alireza [Amir Kabir Univ. of Technology, Tehran (Iran, Islamic Republic of)

2011-07-01

Electric power is the most important part of human energy consumption, and since it has a low storage coefficient it is of particular importance to establish a balance in demand and generation in order to modify and optimize consumption patterns. The expression ''Smart Grid'' can be used to describe technologies which are applied for the automation and optimization of the generation, transmission and distribution network management. This technology requires the integration of information and communication technology in electrical network operation. This paper will study how the Smart Grid capabilites can be used to manage and optimize power network consumption, as well as how the consumers collaboration process using an AGC (Automatic Generation Control) system acts to provide secondary frequency control through consumed load shedding. Reestablishing the balance between demand and generation in critical network operation is also investigated. In other words, utilizing the above method, a new system, ADC (Automatic Demand Control), is offered for use alongside the AGC system in Smart Grids to restore the frequency value to its nominal value. This can lead to a more competitive electricity market and reduce the system storage while maintaining adequate security and network reliability. One of the benefits of the proposed methods described in this paper, in addition to restoring the frequency value to its nominal value, is lower costs and a more economic network operation through reducing fuel and CO2 emission by managing and controlling the amount of the consumed load in the Smart Grid. Also consumers are given the capability to have a specific timetable to economize on their energy requirements which will also reduce the load peak and the network losses. (orig.)

The Integron: Adaptation On Demand.

Science.gov (United States)

Escudero, José Antonio; Loot, Céline; Nivina, Aleksandra; Mazel, Didier

2015-04-01

The integron is a powerful system which, by capturing, stockpiling, and rearranging new functions carried by gene encoding cassettes, confers upon bacteria a rapid adaptation capability in changing environments. Chromosomally located integrons (CI) have been identified in a large number of environmental Gram-negative bacteria. Integron evolutionary history suggests that these sedentary CIs acquired mobility among bacterial species through their association with transposable elements and conjugative plasmids. As a result of massive antibiotic use, these so-called mobile integrons are now widespread in clinically relevant bacteria and are considered to be the principal agent in the emergence and rise of antibiotic multiresistance in Gram-negative bacteria. Cassette rearrangements are catalyzed by the integron integrase, a site-specific tyrosine recombinase. Central to these reactions is the single-stranded DNA nature of one of the recombination partners, the attC site. This makes the integron a unique recombination system. This review describes the current knowledge on this atypical recombination mechanism, its implications in the reactions involving the different types of sites, attC and attI, and focuses on the tight regulation exerted by the host on integron activity through the control of attC site folding. Furthermore, cassette and integrase expression are also highly controlled by host regulatory networks and the bacterial stress (SOS) response. These intimate connections to the host make the integron a genetically stable and efficient system, granting the bacteria a low cost, highly adaptive evolution potential "on demand".

Towards green high capacity optical networks

Science.gov (United States)

Glesk, I.; Mohd Warip, M. N.; Idris, S. K.; Osadola, T. B.; Andonovic, I.

2011-09-01

The demand for fast, secure, energy efficient high capacity networks is growing. It is fuelled by transmission bandwidth needs which will support among other things the rapid penetration of multimedia applications empowering smart consumer electronics and E-businesses. All the above trigger unparallel needs for networking solutions which must offer not only high-speed low-cost "on demand" mobile connectivity but should be ecologically friendly and have low carbon footprint. The first answer to address the bandwidth needs was deployment of fibre optic technologies into transport networks. After this it became quickly obvious that the inferior electronic bandwidth (if compared to optical fiber) will further keep its upper hand on maximum implementable serial data rates. A new solution was found by introducing parallelism into data transport in the form of Wavelength Division Multiplexing (WDM) which has helped dramatically to improve aggregate throughput of optical networks. However with these advancements a new bottleneck has emerged at fibre endpoints where data routers must process the incoming and outgoing traffic. Here, even with the massive and power hungry electronic parallelism routers today (still relying upon bandwidth limiting electronics) do not offer needed processing speeds networks demands. In this paper we will discuss some novel unconventional approaches to address network scalability leading to energy savings via advance optical signal processing. We will also investigate energy savings based on advanced network management through nodes hibernation proposed for Optical IP networks. The hibernation reduces the network overall power consumption by forming virtual network reconfigurations through selective nodes groupings and by links segmentations and partitionings.

The Dynamic Enterprise Network Composition Algorithm for Efficient Operation in Cloud Manufacturing

Directory of Open Access Journals (Sweden)

Gilseung Ahn

2016-11-01

Full Text Available As a service oriented and networked model, cloud manufacturing (CM has been proposed recently for solving a variety of manufacturing problems, including diverse requirements from customers. In CM, on-demand manufacturing services are provided by a temporary production network composed of several enterprises participating within an enterprise network. In other words, the production network is the main agent of production and a subset of an enterprise network. Therefore, it is essential to compose the enterprise network in a way that can respond to demands properly. A properly-composed enterprise network means the network can handle demands that arrive at the CM, with minimal costs, such as network composition and operation costs, such as participation contract costs, system maintenance costs, and so forth. Due to trade-offs among costs (e.g., contract cost and opportunity cost of production, it is a non-trivial problem to find the optimal network enterprise composition. In addition, this includes probabilistic constraints, such as forecasted demand. In this paper, we propose an algorithm, named the dynamic enterprise network composition algorithm (DENCA, based on a genetic algorithm to solve the enterprise network composition problem. A numerical simulation result is provided to demonstrate the performance of the proposed algorithm.

Open Automated Demand Response Communications Specification (Version 1.0)

Energy Technology Data Exchange (ETDEWEB)

Piette, Mary Ann; Ghatikar, Girish; Kiliccote, Sila; Koch, Ed; Hennage, Dan; Palensky, Peter; McParland, Charles

2009-02-28

The development of the Open Automated Demand Response Communications Specification, also known as OpenADR or Open Auto-DR, began in 2002 following the California electricity crisis. The work has been carried out by the Demand Response Research Center (DRRC), which is managed by Lawrence Berkeley National Laboratory. This specification describes an open standards-based communications data model designed to facilitate sending and receiving demand response price and reliability signals from a utility or Independent System Operator to electric customers. OpenADR is one element of the Smart Grid information and communications technologies that are being developed to improve optimization between electric supply and demand. The intention of the open automated demand response communications data model is to provide interoperable signals to building and industrial control systems that are preprogrammed to take action based on a demand response signal, enabling a demand response event to be fully automated, with no manual intervention. The OpenADR specification is a flexible infrastructure to facilitate common information exchange between the utility or Independent System Operator and end-use participants. The concept of an open specification is intended to allow anyone to implement the signaling systems, the automation server or the automation clients.

Smart Demand for Improving Short-term Voltage Control on Distribution Networks

DEFF Research Database (Denmark)

Garcia-Valle, Rodrigo; P. Da Silva, Luiz C.; Xu, Zhao

2009-01-01

customer integration to aid power system performance is almost inevitable. This study introduces a new type of smart demand side technology, denoted demand as voltage controlled reserve (DVR), to improve short-term voltage control, where customers are expected to play a more dynamic role to improve voltage...... control. The technology can be provided by thermostatically controlled loads as well as other types of load. This technology is proven to be effective in case of distribution systems with a large composition of induction motors, where the voltage presents a slow recovery characteristic due to deceleration...... of the motors during faults. This study presents detailed models, discussion and simulation tests to demonstrate the technical viability and effectiveness of the DVR technology for short-term voltage control....

Market integration of flexible demand and DG-RES supply. A new approach for demand response

International Nuclear Information System (INIS)

Warmer, C.J.; Hommelberg, M.P.F.; Kamphuis, I.G.; Kok, J.K.

2007-06-01

In this paper we discuss the shortcomings of traditional Demand Response programs in an environment in which a large amount of distributed generation is available. An innovative approach is given in which true Customer Site Integration is obtained in the spirit of the liberalized electricity market, by making use of the load flexibility of underlying processes of production and consumption devices. The approach is based on distributed control mechanisms and incorporates new market models for distribution and aggregation costs, load losses, and network constraints

Optimal residential smart appliances scheduling considering distribution network constraints

Directory of Open Access Journals (Sweden)

Yu-Ree Kim

2016-01-01

Full Text Available As smart appliances (SAs are more widely adopted within distribution networks, residential consumers can contribute to electricity market operations with demand response resources and reduce their electricity bill. However, if the schedules of demand response resources are determined only by the economic electricity rate signal, the schedule can be unfeasible due to the distribution network constraints. Furthermore, it is impossible for consumers to understand the complex physical characteristics and reflect them in their everyday behaviors. This paper introduces the concept of load coordinating retailer (LCR that deals with demand responsive appliances to reduce electrical consumption for the given distribution network constraints. The LCR can play the role of both conventional retailer and aggregated demand response provider for residential customers. It determines the optimal schedules for the aggregated neighboring SAs according to their types within each distribution feeder. The optimization algorithms are developed using Mixed Integer Linear Programming, and the distribution network is solved by the Newton–Raphson AC power flow.

Hub network design for sparse travel demand within the African aviation industry

CSIR Research Space (South Africa)

Ssamula, B

2007-07-01

Full Text Available and analysed to reveal that the best option for a hub network is the so-called geo-political network. A geo-political network is where hubs are created in the North, South, East and West of Africa, at airports with strong political influence, high passenger...

A methodology for extracting knowledge rules from artificial neural networks applied to forecast demand for electric power; Uma metodologia para extracao de regras de conhecimento a partir de redes neurais artificiais aplicadas para previsao de demanda por energia eletrica

Energy Technology Data Exchange (ETDEWEB)

Steinmetz, Tarcisio; Souza, Glauber; Ferreira, Sandro; Santos, Jose V. Canto dos; Valiati, Joao [Universidade do Vale do Rio dos Sinos (PIPCA/UNISINOS), Sao Leopoldo, RS (Brazil). Programa de Pos-Graduacao em Computacao Aplicada], Emails: trsteinmetz@unisinos.br, gsouza@unisinos.br, sferreira, jvcanto@unisinos.br, jfvaliati@unisinos.br

2009-07-01

We present a methodology for the extraction of rules from Artificial Neural Networks (ANN) trained to forecast the electric load demand. The rules have the ability to express the knowledge regarding the behavior of load demand acquired by the ANN during the training process. The rules are presented to the user in an easy to read format, such as IF premise THEN consequence. Where premise relates to the input data submitted to the ANN (mapped as fuzzy sets), and consequence appears as a linear equation describing the output to be presented by the ANN, should the premise part holds true. Experimentation demonstrates the method's capacity for acquiring and presenting high quality rules from neural networks trained to forecast electric load demand for several amounts of time in the future. (author)

Electrical network capacity support from demand side response: Techno-economic assessment of potential business cases for small commercial and residential end-users

International Nuclear Information System (INIS)

Martínez Ceseña, Eduardo A.; Good, Nicholas; Mancarella, Pierluigi

2015-01-01

Demand Side Response (DSR) is recognised for its potential to bring economic benefits to various electricity sector actors, such as energy retailers, Transmission System Operators (TSOs) and Distribution Network Operators (DNOs). However, most DSR is provided by large industrial and commercial consumers, and little research has been directed to the quantification of the value that small (below 100 kW) commercial and residential end-users could accrue by providing DSR services. In particular, suitable models and studies are needed to quantify potential business cases for DSR from small commercial and residential end-users. Such models and studies should consider the technical and physical characteristics of the power system and demand resources, together with the economic conditions of the power market. In addition, the majority of research focuses on provision of energy arbitrage or ancillary services, with very little attention to DSR services for network capacity support. Accordingly, this paper presents comprehensive techno-economic methodologies for the quantification of three capacity-based business cases for DSR from small commercial and residential end-users. Case study results applied to a UK context indicate that, if the appropriate regulatory framework is put in place, services for capacity support to both DNOs and TSOs can result into potentially attractive business cases for DSR from small end-users with minimum impact on their comfort level. -- Highlights: •We present three business cases for DSR from domestic and commercial end-users. •A comprehensive techno-economic methodology is proposed for the quantification of each DSR business cases. •The regulatory implications associated with each business case are discussed

Robust optimal control of material flows in demand-driven supply networks

NARCIS (Netherlands)

Laumanns, M.; Lefeber, A.A.J.

2006-01-01

We develop a model based on stochastic discrete-time controlleddynamical systems in order to derive optimal policies for controllingthe material flow in supply networks. Each node in the network isdescribed as a transducer such that the dynamics of the material andinformation flows within the entire

The Training Demand in Organizational Changes Processes in the Spanish Wine Sector

Science.gov (United States)

Gil, Alfonso J.; Garcia-Alcaraz, Jorge L.; Mataveli, Mara

2015-01-01

Purpose: The purpose of this paper is to describe the role of training demand in the organisational changes. Design/methodology/approach: The paper describes the demand of training courses in the Rioja wine sector in Spain and its relation with the changes in the sector carried out in recent years. Through a questionnaire, wineries' managers asked…

Reducing electricity demand peaks by scheduling home appliances usage

Energy Technology Data Exchange (ETDEWEB)

Rossello-Busquet, A.; Kardaras, G.; Baek Iversen, V.; Soler, J.; Dittmann, L.

2011-05-15

Nowadays there is a tendency to consume electricity during the same period of the day leading to demand peaks. Regular energy consumption habits lead to demand peaks at specific temporal intervals, because users consume power at the same time. In order to avoid demand peaks, users' appliances should consume electricity in a more temporarily distributed way. A new methodology to schedule the usage of home appliances is proposed and analyzed in this paper. The main concept behind this approach is the aggregation of home appliances into priority classes and the definition of a maximum power consumption limit, which is not allowed to be exceeded during peak hours. The scenario simulated describes a modern household, where the electrical devices are classified in low and high priority groups. The high priority devices are always granted power in order to operate without temporal restrictions. On the contrary, the low priority devices have to pause their operation, when the algorithm dictates it, and resume it in the future. This can become beneficial for both energy companies and users. The electricity suppliers companies will be capable of regulating power generation during demand peaks periods. Moreover, users can be granted lower electricity bill rates for accepting delaying the operation of some of their appliances. In order to analyze this scenario, teletraffic engineering theory, which is used in evaluating the performance of telecommunication networks, is used. A reversible fair scheduling (RFS) algorithm, which was originally developed for telecommunication networks, is applied. The purpose is to analyze how a power consumption limit and priorities for home appliances will affect the demand peak and the users' everyday life. Verification of the effectiveness of the RFS algorithm is done by means of simulation and by using real data for power consumption and operation hours. The defined maximum power limit of 750 and 1000 Watt was not exceeded during

MPLS for metropolitan area networks

CERN Document Server

Tan, Nam-Kee

2004-01-01

METROPOLITAN AREA NETWORKS AND MPLSRequirements of Metropolitan Area Network ServicesMetropolitan Area Network OverviewThe Bandwidth DemandThe Metro Service Provider's Business ApproachesThe Emerging Metro Customer Expectations and NeedsSome Prevailing Metro Service OpportunitiesService Aspects and RequirementsRoles of MPLS in Metropolitan Area NetworksMPLS PrimerMPLS ApplicationsTRAFFIC ENGINEERING ASPECTS OF METROPOLITAN AREA NETWORKSTraffic Engineering ConceptsNetwork CongestionHyper Aggregation ProblemEasing CongestionNetwork ControlTactical versus Strategic Traffic EngineeringIP/ATM Overl

Hierarchical Network Design

DEFF Research Database (Denmark)

Thomadsen, Tommy

2005-01-01

Communication networks are immensely important today, since both companies and individuals use numerous services that rely on them. This thesis considers the design of hierarchical (communication) networks. Hierarchical networks consist of layers of networks and are well-suited for coping...... with changing and increasing demands. Two-layer networks consist of one backbone network, which interconnects cluster networks. The clusters consist of nodes and links, which connect the nodes. One node in each cluster is a hub node, and the backbone interconnects the hub nodes of each cluster and thus...... the clusters. The design of hierarchical networks involves clustering of nodes, hub selection, and network design, i.e. selection of links and routing of ows. Hierarchical networks have been in use for decades, but integrated design of these networks has only been considered for very special types of networks...

Demand response offered by households with direct electric heating

International Nuclear Information System (INIS)

Kofod, C.; Togeby, M.

2004-01-01

The peak power balance in the Nordic power system is gradually turning to be very tight, especially in the electric area of southern Sweden and eastern Denmark. Power stations are closed and hardly any investments in new production are carried out. Demand response is considered essential when the formation of spot prices shall send the signal of needed investments in new capacity. Demand response which are based on individual preferences, and carried out automatically, can be one way to increase the volume of price elastic demand. Demand response need hourly metering for calculation and documentation of the decrease in demand, and controllability in order to meet the timing requirements. Within the EU SAVE project EFFLOCOM (2002 - 2004), a Danish demand response pilot project was established in 2003 including 25 single family homes with direct electrical heating. The system has been tested during the winter 2003/2004. The tested technologies include hourly metering, communication by GRPS as well as the Internet. GPRS is used for daily remote meter reading and automatic control of the electric heating including individual control of up to five zones. The system is designed for automatic activation when the Nord Pool hourly Elspot prices exceed preset levels. The system can also be used as regulating power. The EFFLOCOM Web Bite includes an interactive demonstrator of the system. The developed customer Web Bite is including the services: 1) Access to setting the limits for the maximum duration of interruption for up to five different control zones for two periods of the day and for three price levels. 2) Access to stop an actual interruption. 3) A report on the hourly, daily, weekly and monthly use of electricity and the saved bonus by demand response control. The report is updated daily. The goals of up to 5 kW controlled per house were fulfilled. Besides the demand response bonus the customers have also saved electricity. A customer survey did show that the

National networks of Healthy Cities in Europe.

Science.gov (United States)

Janss Lafond, Leah; Heritage, Zoë

2009-11-01

National networks of Healthy Cities emerged in the late 1980s as a spontaneous reaction to a great demand by cities to participate in the Healthy Cities movement. Today, they engage at least 1300 cities in the European region and form the backbone of the Healthy Cities movement. This article provides an analysis of the results of the regular surveys of national networks that have been carried out principally since 1997. The main functions and achievements of national networks are presented alongside some of their most pressing challenges. Although networks have differing priorities and organizational characteristics, they do share common goals and strategic directions based on the Healthy Cities model (see other articles in this special edition of HPI). Therefore, it has been possible to identify a set of organizational and strategic factors that contribute to the success of networks. These factors form the basis of a set of accreditation criteria for national networks and provide guidance for the establishment of new national networks. Although national networks have made substantial achievements, they continue to face a number of dilemmas that are discussed in the article. Problems a national network must deal with include how to obtain sustainable funding, how to raise the standard of work in cities without creating exclusive participation criteria and how to balance the need to provide direct support to cities with its role as a national player. These dilemmas are similar to other public sector networks. During the last 15 years, the pooling of practical expertise in urban health has made Healthy Cities networks an important resource for national as well as local governments. Not only do they provide valuable support to their members but they often advise ministries and other national institutions on effective models to promote sustainable urban health development.

A rational approach to estimating the surgical demand elasticity needed to guide manpower reallocation during contagious outbreaks.

Science.gov (United States)

Tsao, Hsiao-Mei; Sun, Ying-Chou; Liou, Der-Ming

2015-01-01

Emerging infectious diseases continue to pose serious threats to global public health. So far, however, few published study has addressed the need for manpower reallocation needed in hospitals when such a serious contagious outbreak occurs. To quantify the demand elasticity of the major surgery types in order to guide future manpower reallocation during contagious outbreaks. Based on a nationwide research database in Taiwan, we extracted the monthly volumes of major surgery types for the period 1998-2003, which covered the SARS period, in order to carry out a time series analysis. The demand elasticity of each surgery type was then estimated by autoregressive integrated moving average (ARIMA) analysis. During the study period, the surgical volumes of most selected surgery types either increased or remained steady. We categorized these surgery types into low-, moderate- and high-elastic groups according to their demand elasticity. Appendectomy, 'open reduction of fracture with internal fixation' and 'free skin graft' were in the low demand elasticity group. Transurethral prostatectomy and extracorporeal shockwave lithotripsy (ESWL) were in the high demand elasticity group. The manpower of the departments carrying out the surgeries with low demand elasticity should be maintained during outbreaks. In contrast, departments in charge of surgeries mainly with high demand elasticity, like urology departments, may be in a position to have part of their staff reallocated. Taking advantage of the demand variation during the SARS period in 2003, we adopted the concept of demand elasticity and used a time series approach to figure out an effective index of demand elasticity for various types of surgery that could be used as a rational reference to carry out manpower reallocation during contagious outbreak situations.

Future demand in electrical power and meeting this demand, in particular with the aid of nuclear energy

International Nuclear Information System (INIS)

1976-07-01

As a part of the research program in question, the study deals with meeting the electrical power demand in the FRG until the year 2000 in the best possible way with regard to costs, and evaluating the long-term technical, ecological, and economical effects resulting thereof. With the aid of a model, the construction of additional plants and the use of the FRG's power plant network, always applying economical criteria, are investigated while allowing for adequate assurance of supply. It becomes obvious that the power plants and fuels available influence a 25-year planning period. In the year 2000, nuclear energy will play a dominating role in meeting the demand, the conventional thermal power plants will be used more for coping with the above-average medium laods, while peak loads will be met, above all, by pump storage stations. (UA) [de

A comparative study of 1D and 3D hemodynamics in patient-specific hepatic portal vein networks

Directory of Open Access Journals (Sweden)

Jonášová A.

2014-12-01

Full Text Available The development of software for use in clinical practice is often associated with many requirements and restrictions set not only by the medical doctors, but also by the hospital’s budget. To meet the requirement of reliable software, which is able to provide results within a short time period and with minimal computational demand, a certain measure of modelling simplification is usually inevitable. In case of blood flow simulations carried out in large vascular networks such as the one created by the hepatic portal vein, simplifications are made by necessity. The most often employed simplification includes the approach in the form of dimensional reduction, when the 3D model of a large vascular network is substituted with its 1D counterpart. In this context, a question naturally arises, how this reduction can affect the simulation accuracy and its outcome. In this paper, we try to answer this question by performing a quantitative comparison of 3D and 1D flow models in two patient-specific hepatic portal vein networks. The numerical simulations are carried out under average flow conditions and with the application of the three-element Windkessel model, which is able to approximate the downstream flow resistance of real hepatic tissue. The obtained results show that, although the 1D model can never truly substitute the 3D model, its easy implementation, time-saving model preparation and almost no demands on computer technology dominate as advantages over obvious but moderate modelling errors arising from the performed dimensional reduction.

Analysis of Cool Roof Coatings for Residential Demand Side Management in Tropical Australia

Directory of Open Access Journals (Sweden)

Wendy Miller

2015-06-01

Full Text Available Cool roof coatings have a beneficial impact on reducing the heat load of a range of building types, resulting in reduced cooling energy loads. This study seeks to understand the extent to which cool roof coatings could be used as a residential demand side management (DSM strategy for retrofitting existing housing in a constrained network area in tropical Australia where peak electrical demand is heavily influenced by residential cooling loads. In particular this study seeks to determine whether simulation software used for building regulation purposes can provide networks with the ‘impact certainty’ required by their DSM principles. The building simulation method is supported by a field experiment. Both numerical and experimental data confirm reductions in total consumption (kWh and energy demand (kW. The nature of the regulated simulation software, combined with the diverse nature of residential buildings and their patterns of occupancy, however, mean that simulated results cannot be extrapolated to quantify benefits to a broader distribution network. The study suggests that building data gained from regulatory simulations could be a useful guide for potential impacts of widespread application of cool roof coatings in this region. The practical realization of these positive impacts, however, would require changes to the current business model for the evaluation of DSM strategies. The study provides seven key recommendations that encourage distribution networks to think beyond their infrastructure boundaries, recognising that the broader energy system also includes buildings, appliances and people.

Behaviour of steam turbine power control of large power plant units in case of network short-circuits

International Nuclear Information System (INIS)

Kindermann, W.; Fork, K.

1978-01-01

In order to investigate the behaviour of the turbine control system during strong pendulum motions, an analysis is carried out using a digital computer program by which the reactor, the turbine, the generator and, in a simplified way, the network can be simulated to the necessary degree. Plotter pictures can show the main physical quantities. In all cases, the turbine control system should be able to distinguish between strong pendulum amplitude with acceleration of the rotational angles and sudden release criteria. This demand can be satisfied by a simple adjustment in the Kraftwerk Union turbine control system. Only a few seconds after shut-off of a severe network failure, the turbines are back to their rated power, thus contributing to reliability of supply in this critical network situation. (orig.) [de

Power System Integration of Flexible Demand in the Low Voltage Network

DEFF Research Database (Denmark)

Thavlov, Anders

, it is natural to consider electricity consumption from households as an integrated part of a potential flexible demand side in the future power system. However, as an individual unit a single household is not able to generate a large impact in the power system. Therefore, a mechanism is needed which can...... is even greater as almost 50% of the electricity consumption in households is utilised for space heating and cooling and for heating of domestic hot water. Consequently, there exists a significant potential in the integration of power consumption for heating purposes in households for demand response...... of electricity on the Nordic energy exchange, Nord Pool, or alternatively the flexibility can be sold as an ancillary service to the transmission system operator. In this way, the electricity consumption in households are indirectly integrated into the power market, through the virtual power plant...

Mobile cloud networking: mobile network, compute, and storage as one service on-demand

NARCIS (Netherlands)

Jamakovic, Almerima; Bohnert, Thomas Michael; Karagiannis, Georgios; Galis, A.; Gavras, A.

2013-01-01

The Future Communication Architecture for Mobile Cloud Services: Mobile Cloud Networking (MCN)1 is a EU FP7 Large scale Integrating Project (IP) funded by the European Commission. MCN project was launched in November 2012 for the period of 36 month. In total top-tier 19 partners from industry and

Demand and capacity planning in the emergency department: how to do it.

Science.gov (United States)

Higginson, I; Whyatt, J; Silvester, K

2011-02-01

Unless emergency departments have adequate capacity to meet demand, they will fail to meet clinical and performance standards and will be operating in the 'coping zone'. This carries risks both for staff and patients. As part of a quality improvement programme, the authors undertook an in-depth analysis of demand and capacity for an emergency department in the UK. The paper describes this rigorous approach to capacity planning, which draws on techniques from other industries. Proper capacity planning is vital, but is often poorly done. Planning using aggregated data will lead to inadequate capacity. Understanding demand, and particularly the variation in that demand, is critical to success. Analysis of emergency department demand and capacity is the first step towards effective workforce planning and process redesign.

[Method for optimal sensor placement in water distribution systems with nodal demand uncertainties].

Science.gov (United States)

Liu, Shu-Ming; Wu, Xue; Ouyang, Le-Yan

2013-08-01

The notion of identification fitness was proposed for optimizing sensor placement in water distribution systems. Nondominated Sorting Genetic Algorithm II was used to find the Pareto front between minimum overlap of possible detection times of two events and the best probability of detection, taking nodal demand uncertainties into account. This methodology was applied to an example network. The solutions show that the probability of detection and the number of possible locations are not remarkably affected by nodal demand uncertainties, but the sources identification accuracy declines with nodal demand uncertainties.

Mobile Ad Hoc Networks in Bandwidth-Demanding Mission-Critical Applications: Practical Implementation Insights

KAUST Repository

Bader, Ahmed

2016-09-28

There has been recently a growing trend of using live video feeds in mission-critical applications. Real-time video streaming from front-end personnel or mobile agents is believed to substantially improve situational awareness in mission-critical operations such as disaster relief, law enforcement, and emergency response. Mobile Ad Hoc Networks (MANET) is a natural contender in such contexts. However, classical MANET routing schemes fall short in terms of scalability, bandwidth and latency; all three metrics being quite essential for mission-critical applications. As such, autonomous cooperative routing (ACR) has gained traction as the most viable MANET proposition. Nonetheless, ACR is also associated with a few implementation challenges. If they go unaddressed, will deem ACR practically useless. In this paper, efficient and low-complexity remedies to those issues are presented, analyzed, and validated. The validation is based on field experiments carried out using software-defined radio (SDR) platforms. Compared to classical MANET routing schemes, ACR was shown to offer up to 2X better throughput, more than 4X reduction in end-to-end latency, while observing a given target of transport rate normalized to energy consumption.

Timing of product introduction in network economies under heterogeneous demand

DEFF Research Database (Denmark)

Winther, Christian Dahl

This paper studies the introduction of a new and incompatible technology in a spatial market with network externalities. In competition with an established network, the entrant chooses how long to do research and a level of product differentiation, which determine the adoption patterns of consumers...... level of product differentiation that should be chosen by the sponsor of the new technology in equilibrium. Third, the formal relationship between these variables are derived under compatibility.  Fourth, the entering firm's problem is solved by numerical methods to gain insight into the optimal linkage...... between research time and product design....

Self-deployable mobile sensor networks for on-demand surveillance

Science.gov (United States)

Miao, Lidan; Qi, Hairong; Wang, Feiyi

2005-05-01

This paper studies two interconnected problems in mobile sensor network deployment, the optimal placement of heterogeneous mobile sensor platforms for cost-efficient and reliable coverage purposes, and the self-organizable deployment. We first develop an optimal placement algorithm based on a "mosaicked technology" such that different types of mobile sensors form a mosaicked pattern uniquely determined by the popularity of different types of sensor nodes. The initial state is assumed to be random. In order to converge to the optimal state, we investigate the swarm intelligence (SI)-based sensor movement strategy, through which the randomly deployed sensors can self-organize themselves to reach the optimal placement state. The proposed algorithm is compared with the random movement and the centralized method using performance metrics such as network coverage, convergence time, and energy consumption. Simulation results are presented to demonstrate the effectiveness of the mosaic placement and the SI-based movement.

Spatial price dynamics: From complex network perspective

Science.gov (United States)

Li, Y. L.; Bi, J. T.; Sun, H. J.

2008-10-01

The spatial price problem means that if the supply price plus the transportation cost is less than the demand price, there exists a trade. Thus, after an amount of exchange, the demand price will decrease. This process is continuous until an equilibrium state is obtained. However, how the trade network structure affects this process has received little attention. In this paper, we give a evolving model to describe the levels of spatial price on different complex network structures. The simulation results show that the network with shorter path length is sensitive to the variation of prices.

Analisis Permintaan (Demand Analysis) Pelayanan Kesehatan Puskesmas di Kabupaten Mojokerto

OpenAIRE

Budiarto, Wasis

1996-01-01

A study on demand for health centre was carried out at Mojokerto Regency, East Java. The study convered 300 respondents (15 years old and over) which were collected from two areas, urban (Kecamatan Bangsal) and rural (Kecamatan Puri). The objectives of this study were to measure the demand for health centre services and to determine the influencing factors. A household survey was conducted in this study, using household and individual as unit of analysis and a multiple linier regression techn...

Acquisition of ICU data: concepts and demands.

Science.gov (United States)

Imhoff, M

1992-12-01

As the issue of data overload is a problem in critical care today, it is of utmost importance to improve acquisition, storage, integration, and presentation of medical data, which appears only feasible with the help of bedside computers. The data originates from four major sources: (1) the bedside medical devices, (2) the local area network (LAN) of the ICU, (3) the hospital information system (HIS) and (4) manual input. All sources differ markedly in quality and quantity of data and in the demands of the interfaces between source of data and patient database. The demands for data acquisition from bedside medical devices, ICU-LAN and HIS concentrate on technical problems, such as computational power, storage capacity, real-time processing, interfacing with different devices and networks and the unmistakable assignment of data to the individual patient. The main problem of manual data acquisition is the definition and configuration of the user interface that must allow the inexperienced user to interact with the computer intuitively. Emphasis must be put on the construction of a pleasant, logical and easy-to-handle graphical user interface (GUI). Short response times will require high graphical processing capacity. Moreover, high computational resources are necessary in the future for additional interfacing devices such as speech recognition and 3D-GUI. Therefore, in an ICU environment the demands for computational power are enormous. These problems are complicated by the urgent need for friendly and easy-to-handle user interfaces. Both facts place ICU bedside computing at the vanguard of present and future workstation development leaving no room for solutions based on traditional concepts of personal computers.(ABSTRACT TRUNCATED AT 250 WORDS)

Modeling complexity in engineered infrastructure system: Water distribution network as an example

Science.gov (United States)

Zeng, Fang; Li, Xiang; Li, Ke

2017-02-01

The complex topology and adaptive behavior of infrastructure systems are driven by both self-organization of the demand and rigid engineering solutions. Therefore, engineering complex systems requires a method balancing holism and reductionism. To model the growth of water distribution networks, a complex network model was developed following the combination of local optimization rules and engineering considerations. The demand node generation is dynamic and follows the scaling law of urban growth. The proposed model can generate a water distribution network (WDN) similar to reported real-world WDNs on some structural properties. Comparison with different modeling approaches indicates that a realistic demand node distribution and co-evolvement of demand node and network are important for the simulation of real complex networks. The simulation results indicate that the efficiency of water distribution networks is exponentially affected by the urban growth pattern. On the contrary, the improvement of efficiency by engineering optimization is limited and relatively insignificant. The redundancy and robustness, on another aspect, can be significantly improved through engineering methods.

Dynamic optical resource allocation for mobile core networks with software defined elastic optical networking.

Science.gov (United States)

Zhao, Yongli; Chen, Zhendong; Zhang, Jie; Wang, Xinbo

2016-07-25

Driven by the forthcoming of 5G mobile communications, the all-IP architecture of mobile core networks, i.e. evolved packet core (EPC) proposed by 3GPP, has been greatly challenged by the users' demands for higher data rate and more reliable end-to-end connection, as well as operators' demands for low operational cost. These challenges can be potentially met by software defined optical networking (SDON), which enables dynamic resource allocation according to the users' requirement. In this article, a novel network architecture for mobile core network is proposed based on SDON. A software defined network (SDN) controller is designed to realize the coordinated control over different entities in EPC networks. We analyze the requirement of EPC-lightpath (EPCL) in data plane and propose an optical switch load balancing (OSLB) algorithm for resource allocation in optical layer. The procedure of establishment and adjustment of EPCLs is demonstrated on a SDON-based EPC testbed with extended OpenFlow protocol. We also evaluate the OSLB algorithm through simulation in terms of bandwidth blocking ratio, traffic load distribution, and resource utilization ratio compared with link-based load balancing (LLB) and MinHops algorithms.

Cross-layer restoration with software defined networking based on IP over optical transport networks

Science.gov (United States)

Yang, Hui; Cheng, Lei; Deng, Junni; Zhao, Yongli; Zhang, Jie; Lee, Young

2015-10-01

The IP over optical transport network is a very promising networking architecture applied to the interconnection of geographically distributed data centers due to the performance guarantee of low delay, huge bandwidth and high reliability at a low cost. It can enable efficient resource utilization and support heterogeneous bandwidth demands in highly-available, cost-effective and energy-effective manner. In case of cross-layer link failure, to ensure a high-level quality of service (QoS) for user request after the failure becomes a research focus. In this paper, we propose a novel cross-layer restoration scheme for data center services with software defined networking based on IP over optical network. The cross-layer restoration scheme can enable joint optimization of IP network and optical network resources, and enhance the data center service restoration responsiveness to the dynamic end-to-end service demands. We quantitatively evaluate the feasibility and performances through the simulation under heavy traffic load scenario in terms of path blocking probability and path restoration latency. Numeric results show that the cross-layer restoration scheme improves the recovery success rate and minimizes the overall recovery time.

Modelling of demand response and market power

International Nuclear Information System (INIS)

Kristoffersen, B.B.; Donslund, B.; Boerre Eriksen, P.

2004-01-01

Demand-side flexibility and demand response to high prices are prerequisites for the proper functioning of the Nordic power market. If the consumers are unwilling to respond to high prices, the market may fail the clearing, and this may result in unwanted forced demand disconnections. Being the TSO of Western Denmark, Eltra is responsible of both security of supply and the design of the power market within its area. On this basis, Eltra has developed a new mathematical model tool for analysing the Nordic wholesale market. The model is named MARS (MARket Simulation). The model is able to handle hydropower and thermal production, nuclear power and wind power. Production, demand and exchanges modelled on an hourly basis are new important features of the model. The model uses the same principles as Nord Pool (The Nordic Power Exchange), including the division of the Nordic countries into price areas. On the demand side, price elasticity is taken into account and described by a Cobb-Douglas function. Apart from simulating perfect competition markets, particular attention has been given to modelling imperfect market conditions, i.e. exercise of market power on the supply side. Market power is simulated by using game theory, including the Nash equilibrium concept. The paper gives a short description of the MARS model. Besides, focus is on the application of the model in order to illustrate the importance of demand response in the Nordic market. Simulations with different values of demand elasticity are compared. Calculations are carried out for perfect competition and for the situation in which market power is exercised by the large power producers in the Nordic countries (oligopoly). (au)

Electronic Equipment of Self-Actuated Mobile Device for Load Carrying

Directory of Open Access Journals (Sweden)

T. Janecka

1994-12-01

Full Text Available The device dealt in this work is determined namely for carrying invalid persons on various types of stairs or other not flat surfaces. But it can serve also to other purposes.To enable fulfilling all given demands, the design was consulted with other research workers solving the tasks of similar features.Resulting mechanical device, enabling aspects of movement required, is controlled by electronic and microprocessor circuits that obtain the input information from sensitive units investigating the terrain.

Fuzzy multi-objective sustainable and green closed-loop supply chain network design

DEFF Research Database (Denmark)

Soleimani, Hamed; Govindan, Kannan; Saghafi, Hamid

2017-01-01

recycling raw material recycling. Modeling this chain is carried out by accounting for environmental considerations, total profit optimization, and reduction of lost working days due to occupational accidents, we well as maximizing responsiveness to customer demand. In order to solve the model, genetic...... algorithm has been used and multiple scenarios with different aspects have been studied. Solving this model provides decisions regarding opening or closing of each of the components of the network and the optimal product flow among them. The results prove the feasibility of the presented model...... and the applicability of the developed solution methodology....

Growing Brazilian demand to spur gas network in South America

International Nuclear Information System (INIS)

Deffarges, E.H.; Maurer, L.I.A.

1993-01-01

A recent combination in South America of economic and geopolitical factors is prompting development of a new integrated gas-pipeline network in the continent's Southern Cone. The crucial factors include privatization, regional integration, economic growth, and environmental concerns. The area, Latin America's largest regional entity, includes Brazil (population 150 million and a 1990 GNP of about $375 billion, 9th largest in the world), Argentina (population 32 million and the third largest Latin American economy after Brazil and Mexico), Bolivia, Chile, Paraguay, and Uruguay. Argentina, Brazil, Paraguay, and Uruguay are members of the MercoSur economic bloc whose objective is to develop free trade in the region. There are very few integrated pipeline networks in the world. Besides the giant North American system, with hundreds of producers and pipelines, there is only one other large integrated network. It connects continental European countries to their outside suppliers such as Norway, the C.I.S., and Algeria. The emergence of a new pipeline system is therefore important for the natural-gas industry worldwide and even more so if it occurs in a region now growing rapidly after a decade of economic difficulties

PV-Powered CoMP-Based Green Cellular Networks with a Standby Grid Supply

Directory of Open Access Journals (Sweden)

Abu Jahid

2017-01-01

Full Text Available This paper proposes a novel framework for PV-powered cellular networks with a standby grid supply and an essential energy management technique for achieving envisaged green networks. The proposal considers an emerging cellular network architecture employing two types of coordinated multipoint (CoMP transmission techniques for serving the subscribers. Under the proposed framework, each base station (BS is powered by an individual PV solar energy module having an independent storage device. BSs are also connected to the conventional grid supply for meeting additional energy demand. We also propose a dynamic inter-BS solar energy sharing policy through a transmission line for further greening the proposed network by minimizing the consumption from the grid supply. An extensive simulation-based study in the downlink of a Long-Term Evolution (LTE cellular system is carried out for evaluating the energy efficiency performance of the proposed framework. System performance is also investigated for identifying the impact of various system parameters including storage factor, storage capacity, solar generation capacity, transmission line loss, and different CoMP techniques.

New Class of Hybrid Materials for Detection, Capture, and "On-Demand" Release of Carbon Monoxide.

Science.gov (United States)

Pitto-Barry, Anaïs; Lupan, Alexandru; Ellingford, Christopher; Attia, Amr A A; Barry, Nicolas P E

2018-04-25

Carbon monoxide (CO) is both a substance hazardous to health and a side product of a number of industrial processes, such as methanol steam reforming and large-scale oxidation reactions. The separation of CO from nitrogen (N 2 ) in industrial processes is considered to be difficult because of the similarities of their electronic structures, sizes, and physicochemical properties (e.g., boiling points). Carbon monoxide is also a major poison in fuel cells because of its adsorption onto the active sites of the catalysts. It is therefore of the utmost economic importance to discover new materials that enable effective CO capture and release under mild conditions. However, methods to specifically absorb and easily release CO in the presence of contaminants, such as water, nitrogen, carbon dioxide, and oxygen, at ambient temperature are not available. Here, we report the simple and versatile fabrication of a new class of hybrid materials that allows capture and release of carbon monoxide under mild conditions. We found that carborane-containing metal complexes encapsulated in networks made of poly(dimethylsiloxane) react with CO, even when immersed in water, leading to dramatic color and infrared signature changes. Furthermore, we found that the CO can be easily released from the materials by simply dipping the networks into an organic solvent for less than 1 min, at ambient temperature and pressure, which not only offers a straightforward recycling method, but also a new method for the "on-demand" release of carbon monoxide. We illustrated the utilization of the on-demand release of CO from the networks by carrying out a carbonylation reaction on an electron-deficient metal complex that led to the formation of the CO-adduct, with concomitant recycling of the gel. We anticipate that our sponge-like materials and scalable methodology will open up new avenues for the storage, transport, and controlled release of CO, the silent killer and a major industrial poison.

Optimal Energy Management of Combined Cooling, Heat and Power in Different Demand Type Buildings Considering Seasonal Demand Variations

Directory of Open Access Journals (Sweden)

Akhtar Hussain

2017-06-01

Full Text Available In this paper, an optimal energy management strategy for a cooperative multi-microgrid system with combined cooling, heat and power (CCHP is proposed and has been verified for a test case of building microgrids (BMGs. Three different demand types of buildings are considered and the BMGs are assumed to be equipped with their own combined heat and power (CHP generators. In addition, the BMGs are also connected to an external energy network (EEN, which contains a large CHP, an adsorption chiller (ADC, a thermal storage tank, and an electric heat pump (EHP. By trading the excess electricity and heat energy with the utility grid and EEN, each BMG can fulfill its energy demands. Seasonal energy demand variations have been evaluated by selecting a representative day for the two extreme seasons (summer and winter of the year, among the real profiles of year-round data on electricity, heating, and cooling usage of all the three selected buildings. Especially, the thermal energy management aspect is emphasized where, bi-lateral heat trading between the energy supplier and the consumers, so-called energy prosumer concept, has been realized. An optimization model based on mixed integer linear programming has been developed for minimizing the daily operation cost of the EEN while fulfilling the energy demands of the BMGs. Simulation results have demonstrated the effectiveness of the proposed strategy.

Network architecture in a converged optical + IP network

Science.gov (United States)

Wakim, Walid; Zottmann, Harald

2012-01-01

As demands on Provider Networks continue to grow at exponential rates, providers are forced to evaluate how to continue to grow the network while increasing service velocity, enhancing resiliency while decreasing the total cost of ownership (TCO). The bandwidth growth that networks are experiencing is in the form packet based multimedia services such as video, video conferencing, gaming, etc... mixed with Over the Top (OTT) content providers such as Netflix, and the customer's expectations that best effort is not enough you end up with a situation that forces the provider to analyze how to gain more out of the network with less cost. In this paper we will discuss changes in the network that are driving us to a tighter integration between packet and optical layers and how to improve on today's multi - layer inefficiencies to drive down network TCO and provide for a fully integrated and dynamic network that will decrease time to revenue.

Energy savings through self-backhauling for future heterogeneous networks

International Nuclear Information System (INIS)

Faruk, Nasir; Ruttik, Kalle; Mutafungwa, Edward; Jäntti, Riku

2016-01-01

Mobile operators face continuous challenge of enhancing network capacity and coverage so as to meet demand for ubiquitous high-speed mobile data connectivity. Unfortunately, these enhancements are typically accompanied by increased burden of network energy consumption. Heterogeneous network (HetNet) deployments of a large number of low power small base stations (SBS) to complement existing macro base stations is an approach that increases network capacity but potentially reduces overall network energy consumption. The SBS backhaul links in HetNets present a significant powering burden. In this paper, we show how self backhauling of SBS can reduce overall network power demand. A backhaul-energy consumption model is developed and used to investigate the energy efficiency of different backhauling options. We note that significant energy savings could be achieved through the use of self-backhauling when compared with the conventional microwave backhauling. The results presented would provide guidelines for energy- and cost-efficient backhaul implementation for future HetNets. - Highlights: • A backhaul-energy consumption model is developed. • Self backhauling of small base stations can reduce overall network power demand. • Energy saving strategy presented would relieved the burden on the power networks. • Results provide guidelines for energy and cost effective backhaul implementation.

The power to choose. Demand response in liberalized electricity markets

International Nuclear Information System (INIS)

2003-01-01

Highly volatile electricity prices are becoming a more frequent and unwanted characteristic of modern electricity wholesale markets. But low demand elasticity, mainly the result of a lack of incentives and consumers' inability to control demand, means that consumer behaviour is not reflected in the cost of energy. This study analyses the impact of price-responsive demand and shows how pricing, policy and technology can be used to inform consumer behaviour and choice. Informed choice and market-based valuation of electricity supply will ensure liberalized markets are competitive, efficient, less volatile and able to provide long term security of supply. Significant benefits will occur even if only 5% of customers become responsive to price-incentives and information. And customers will respond to well designed programs, thereby developing a role in ensuring efficient price formulation for electricity. This study analyses the economic, efficiency and security benefits and identifies the changes in electricity tariffs and the network infrastructure needed to achieve greater demand response

On Maximizing the Lifetime of Wireless Sensor Networks by Optimally Assigning Energy Supplies

Science.gov (United States)

Asorey-Cacheda, Rafael; García-Sánchez, Antonio Javier; García-Sánchez, Felipe; García-Haro, Joan; Gonzalez-Castaño, Francisco Javier

2013-01-01

The extension of the network lifetime of Wireless Sensor Networks (WSN) is an important issue that has not been appropriately solved yet. This paper addresses this concern and proposes some techniques to plan an arbitrary WSN. To this end, we suggest a hierarchical network architecture, similar to realistic scenarios, where nodes with renewable energy sources (denoted as primary nodes) carry out most message delivery tasks, and nodes equipped with conventional chemical batteries (denoted as secondary nodes) are those with less communication demands. The key design issue of this network architecture is the development of a new optimization framework to calculate the optimal assignment of renewable energy supplies (primary node assignment) to maximize network lifetime, obtaining the minimum number of energy supplies and their node assignment. We also conduct a second optimization step to additionally minimize the number of packet hops between the source and the sink. In this work, we present an algorithm that approaches the results of the optimization framework, but with much faster execution speed, which is a good alternative for large-scale WSN networks. Finally, the network model, the optimization process and the designed algorithm are further evaluated and validated by means of computer simulation under realistic conditions. The results obtained are discussed comparatively. PMID:23939582

On Maximizing the Lifetime of Wireless Sensor Networks by Optimally Assigning Energy Supplies

Directory of Open Access Journals (Sweden)

Francisco Javier González-Castano

2013-08-01

Full Text Available The extension of the network lifetime of Wireless Sensor Networks (WSN is an important issue that has not been appropriately solved yet. This paper addresses this concern and proposes some techniques to plan an arbitrary WSN. To this end, we suggest a hierarchical network architecture, similar to realistic scenarios, where nodes with renewable energy sources (denoted as primary nodes carry out most message delivery tasks, and nodes equipped with conventional chemical batteries (denoted as secondary nodes are those with less communication demands. The key design issue of this network architecture is the development of a new optimization framework to calculate the optimal assignment of renewable energy supplies (primary node assignment to maximize network lifetime, obtaining the minimum number of energy supplies and their node assignment. We also conduct a second optimization step to additionally minimize the number of packet hops between the source and the sink. In this work, we present an algorithm that approaches the results of the optimization framework, but with much faster execution speed, which is a good alternative for large-scale WSN networks. Finally, the network model, the optimization process and the designed algorithm are further evaluated and validated by means of computer simulation under realistic conditions. The results obtained are discussed comparatively.

Regulating electricity demand peaks for home appliances using reversible fair scheduling

DEFF Research Database (Denmark)

Kardaras, Georgios; Rossello Busquet, Ana; Iversen, Villy Bæk

2010-01-01

This paper describes a novel methodology for regulating electricity demand peaks for home appliances. To achieve this objective, we will make use of the reversible fair scheduling algorithm originally developed for telecommunication networks. The main concept behind this approach is the aggregati...

Directed graph based carbon flow tracing for demand side carbon obligation allocation

DEFF Research Database (Denmark)

Sun, Tao; Feng, Donghan; Ding, Teng

2016-01-01

In order to achieve carbon emission abatement, some researchers and policy makers have cast their focus on demand side carbon abatement potentials. This paper addresses the problem of carbon flow calculation in power systems and carbon obligation allocation at demand side. A directed graph based...... method for tracing carbon flow is proposed. In a lossy network, matrices such as carbon losses, net carbon intensity (NCI) and footprint carbon intensity (FCI) are obtained with the proposed method and used to allocate carbon obligation at demand side. Case studies based on realistic distribution...... and transmission systems are provided to demonstrate the effectiveness of the proposed method....

Sonification of network traffic flow for monitoring and situational awareness

Science.gov (United States)

2018-01-01

Maintaining situational awareness of what is happening within a computer network is challenging, not only because the behaviour happens within machines, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation techniques are widely used to present information about network traffic dynamics. Although they provide operators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way. Also, because they require visual attention they are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system for monitoring computer networks to support network administrators’ situational awareness. SoNSTAR provides an auditory representation of all the TCP/IP traffic within a network based on the different traffic flows between between network hosts. A user study showed that SoNSTAR raises situational awareness levels by enabling operators to understand network behaviour and with the benefit of lower workload demands (as measured by the NASA TLX method) than visual techniques. SoNSTAR identifies network traffic features by inspecting the status flags of TCP/IP packet headers. Combinations of these features define particular traffic events which are mapped to recorded sounds to generate a soundscape that represents the real-time status of the network traffic environment. The sequence, timing, and loudness of the different sounds allow the network to be monitored and anomalous behaviour to be detected without the need to continuously watch a monitor screen. PMID:29672543

Sonification of network traffic flow for monitoring and situational awareness.

Science.gov (United States)

Debashi, Mohamed; Vickers, Paul

2018-01-01

Maintaining situational awareness of what is happening within a computer network is challenging, not only because the behaviour happens within machines, but also because data traffic speeds and volumes are beyond human ability to process. Visualisation techniques are widely used to present information about network traffic dynamics. Although they provide operators with an overall view and specific information about particular traffic or attacks on the network, they often still fail to represent the events in an understandable way. Also, because they require visual attention they are not well suited to continuous monitoring scenarios in which network administrators must carry out other tasks. Here we present SoNSTAR (Sonification of Networks for SiTuational AwaReness), a real-time sonification system for monitoring computer networks to support network administrators' situational awareness. SoNSTAR provides an auditory representation of all the TCP/IP traffic within a network based on the different traffic flows between between network hosts. A user study showed that SoNSTAR raises situational awareness levels by enabling operators to understand network behaviour and with the benefit of lower workload demands (as measured by the NASA TLX method) than visual techniques. SoNSTAR identifies network traffic features by inspecting the status flags of TCP/IP packet headers. Combinations of these features define particular traffic events which are mapped to recorded sounds to generate a soundscape that represents the real-time status of the network traffic environment. The sequence, timing, and loudness of the different sounds allow the network to be monitored and anomalous behaviour to be detected without the need to continuously watch a monitor screen.

Digital Natives, Social Networks and the Future of Libraries

Directory of Open Access Journals (Sweden)

Yaşar Tonta

2013-11-01

Full Text Available Facebook, MySpace, Flickr and YouTube are currently among the most frequently visited websites with Web 2.0 features. They are used not only for social networking and entertainment but also for access to information, for learning and for carrying out professional work. Social networks commonly have Web 2.0 features, offer personalized services and allow users to incorporate their own content easily and describe, organize and share it with others, thereby enriching users’ experience. Some users tend to “live” on those social networks and expect information providing organizations to offer similar services. They want libraries to be as accessible, flexible, open to collaboration and sharing as that of social networks and heighten the expectations from such institutions. The future of libraries is closely associated with how successfully they meet the demands of digital users. Otherwise, the “net generation” or the “digital natives” grown up with the Web, Google and Facebook would see libraries as outdated institutions and “take their business elsewhere” to satisfy their information needs. In this paper, the impact of the technological convergence on information providing organizations is reviewed and the challenges and opportunities facing libraries in the digital environment are discussed.

Demand Response Load Following of Source and Load Systems

DEFF Research Database (Denmark)

Hu, Jianqiang; Cao, Jinde; Yong, Taiyou

2017-01-01

This paper presents a demand response load following strategy for an interconnected source and load system, in which we utilize traditional units and population of cooling thermostatically controlled loads (TCLs) to follow the mismatched power caused by the load activities and the renewable power...... injection in real time. In the demand side of power systems, these TCLs are often affiliated to a bus load agent and can be aggregated to multiple TCL aggregators. Firstly, aggregate evaluation of the TCL aggregator is carried out based on a bilinear aggregate model so as to derive the available regulation...

Demand side management. Benefits and challenges

International Nuclear Information System (INIS)

Strbac, Goran

2008-01-01

In this paper, the major benefits and challenges of electricity demand side management (DSM) are discussed in the context of the UK electricity system. The relatively low utilisation of generation and networks (of about 50%) means that there is significant scope for DSM to contribute to increasing the efficiency of the system investment. The importance of the diversity of electricity load is discussed and the negative effects of DSM on load diversity illustrated. Ageing assets, the growth in renewable and other low-carbon generation technologies and advances in information and communication technologies are identified as major additional drivers that could lead to wider applications of DSM in the medium term. Potential benefits of DSM are discussed in the context of generation and of transmission and distribution networks. The provision of back-up capacity by generation may not be efficient as it will be needed relatively infrequently, and DSM may be better placed to support security. We also present an analysis of the value of DSM in balancing generation and demand in a future UK electricity system with significant variable renewable generation. We give a number of reasons for the relatively slow uptake of DSM, particularly in the residential, commercial and small business sectors. They include a lack of metering, information and communication infrastructure, lack of understanding of the benefits of DSM, problems with the competitiveness of DSM when compared with traditional approaches, an increase in the complexity of system operation and inappropriate market incentives. (author)

Conceptual Framework and Computational Research of Hierarchical Residential Household Water Demand

Directory of Open Access Journals (Sweden)

Baodeng Hou

2018-05-01

Full Text Available Although the quantity of household water consumption does not account for a huge proportion of the total water consumption amidst socioeconomic development, there has been a steadily increasing trend due to population growth and improved urbanization standards. As such, mastering the mechanisms of household water demand, scientifically predicting trends of household water demand, and implementing reasonable control measures are key focuses of current urban water management. Based on the categorization and characteristic analysis of household water, this paper used Maslow’s Hierarchy of Needs to establish a level and grade theory of household water demand, whereby household water is classified into three levels (rigid water demand, flexible water demand, and luxury water demand and three grades (basic water demand, reasonable water demand, and representational water demand. An in-depth analysis was then carried out on the factors that influence the computation of household water demand, whereby equations for different household water categories were established, and computations for different levels of household water were proposed. Finally, observational experiments on household water consumption were designed, and observation and simulation computations were performed on three typical households in order to verify the scientific outcome and rationality of the computation of household water demand. The research findings contribute to the enhancement and development of prediction theories on water demand, and they are of high theoretical and realistic significance in terms of scientifically predicting future household water demand and fine-tuning the management of urban water resources.

Investigating risk and robustness measures for supply chain network design under demand uncertainty

DEFF Research Database (Denmark)

Govindan, Kannan; Fattahi, Mohammad

2017-01-01

to obtain risk-averse and robust solutions, respectively. Computational results are presented on a real-life case study to illustrate the applicability of the proposed approaches. To compare these different decision-making situations, a simulation approach is used. Furthermore, by several test problems......-variable demands. To deal with the stochastic demands, a Latin Hypercube Sampling method is applied to generate a fan of scenarios and then, a backward scenario reduction technique reduces the number of scenarios. Weighted mean-risk objectives by using different risk measures and minimax objective are examined...

Competition Between Networks: A Study of the Market for Yellow Pages

OpenAIRE

Marc Rysman

2004-01-01

This paper estimates the importance of network effects in the market for Yellow Pages. I estimate three simultaneous equations: consumer demand for usage of a directory, advertiser demand for advertising and a publisher's first-order condition (derived from profit-maximizing behaviour). Estimation shows that advertisers value consumer usage and that consumers value advertising, implying a network effect. I find that internalizing network effects would significantly increase surplus. As an app...

Consumerism and the Sister Carrie's American Dream%Consumerism and the Sister Carrie''s American Dream

Institute of Scientific and Technical Information of China (English)

卢亚丽

2017-01-01

From the aspect of consumerism to this text analyze Sister Carrie's"American dream"destruction. The author wholly and deeply analyzes the embodiment of consumerism in Dreiser's Sister Carrie and Dreiser's outlook and values under the effect of consumerism. To prove that the reason for destruction of Carrie's American dream is consumerism.

Demand access communications for TDRSS users

Science.gov (United States)

Zillig, David; Weinberg, Aaron; Mcomber, Robert

1994-01-01

The Tracking and Data Relay Satellite System (TDRSS) has long been used to provide reliable low and high-data rate relay services between user spacecraft in Earth orbit and the ground. To date, these TDRSS services have been implemented via prior scheduling based upon estimates of user needs and mission event timelines. While this approach may be necessary for large users that require greater amounts of TDRSS resources, TDRSS can potentially offer the planned community of smaller science missions (e.g., the small explorer missions), and other emerging users, the unique opportunity for services on demand. In particular, innovative application of the existing TDRSS Multiple Access (MA) subsystem, with its phased array antenna, could be used to implement true demand access services without modification to either the TDRSS satellites or the user transponder, thereby introducing operational and performance benefits to both the user community and the Space Network. In this paper, candidate implementations of demand access service via the TDRSS MA subsystem are examined in detail. Both forward and return link services are addressed and a combination of qualitative and quantitative assessments are provided. The paper also identifies further areas for investigation in this ongoing activity that is being conducted by GSFC/Code 531 under the NASA Code O Advanced Systems Program.

Look-Ahead Strategies Based on Store-Carry and Forward Relaying for Energy Efficient Cellular Communications

Directory of Open Access Journals (Sweden)

Panayiotis Kolios

2010-11-01

Full Text Available With the increasing availability of Internet type services on mobile devices and the attractive flat rate all-you-can-eat billing system, cellular telecommunication networks are experiencing a tremendous growth in data usage demand. However, there are increasing concerns that current network deployment trends (including more efficient radio access techniques and increased spectrum allocation strategies, will be unable to support the increased Internet traffic in a sustainable way. The delay tolerant nature of mobile Internet traffic allows for a large degree of flexibility in optimizing network performance to meet different design objectives and it’s a feature that has mostly gone unexplored by the research community. In this paper, we introduce a novel message forwarding mechanism in cellular networks that benefits from the inherent delay tolerance of Internet type services to provide flexible and adjustable forwarding strategies for efficient network operation while guaranteeing timely deliveries. By capitalizing on the elasticity of message delivery deadlines and the actual mobility of nodes inside the cell, considerable performance gains can be achieved by physically propagating information messages within the network.

Social working memory: Neurocognitive networks and directions for future research

Directory of Open Access Journals (Sweden)

Meghan L Meyer

2012-12-01

Full Text Available Navigating the social world requires the ability to maintain and manipulate information about people’s beliefs, traits, and mental states. We characterize this capacity as social working memory. To date, very little research has explored this phenomenon, in part because of the assumption that general working memory systems would support working memory for social information. Various lines of research, however, suggest that social cognitive processing relies on a neurocognitive network (i.e., the ‘mentalizing network’ that is functionally distinct from, and considered antagonistic with, the canonical working memory network. Here, we review evidence suggesting that demanding social cognition requires social working memory and that both the mentalizing and canonical working memory neurocognitive networks support social working memory. The neural data run counter to the common finding of parametric decreases in mentalizing regions as a function of working memory demand and suggest that the mentalizing network can support demanding cognition, when it is demanding social cognition. Implications for individual differences in social cognition and pathologies of social cognition are discussed.

Robustness of airline route networks

Science.gov (United States)

Lordan, Oriol; Sallan, Jose M.; Escorihuela, Nuria; Gonzalez-Prieto, David

2016-03-01

Airlines shape their route network by defining their routes through supply and demand considerations, paying little attention to network performance indicators, such as network robustness. However, the collapse of an airline network can produce high financial costs for the airline and all its geographical area of influence. The aim of this study is to analyze the topology and robustness of the network route of airlines following Low Cost Carriers (LCCs) and Full Service Carriers (FSCs) business models. Results show that FSC hubs are more central than LCC bases in their route network. As a result, LCC route networks are more robust than FSC networks.

Mobile Virtual Private Networking

Science.gov (United States)

Pulkkis, Göran; Grahn, Kaj; Mårtens, Mathias; Mattsson, Jonny

Mobile Virtual Private Networking (VPN) solutions based on the Internet Security Protocol (IPSec), Transport Layer Security/Secure Socket Layer (SSL/TLS), Secure Shell (SSH), 3G/GPRS cellular networks, Mobile IP, and the presently experimental Host Identity Protocol (HIP) are described, compared and evaluated. Mobile VPN solutions based on HIP are recommended for future networking because of superior processing efficiency and network capacity demand features. Mobile VPN implementation issues associated with the IP protocol versions IPv4 and IPv6 are also evaluated. Mobile VPN implementation experiences are presented and discussed.

The need for standardization in laboratory networks.

Science.gov (United States)

Peter, Trevor F; Shimada, Yoko; Freeman, Richard R; Ncube, Bekezela N; Khine, Aye-Aye; Murtagh, Maurine M

2009-06-01

Expanding health care services for HIV, tuberculosis, and malaria has increased the demand for affordable and reliable laboratory diagnostics in resource-limited countries. Many countries are responding by upgrading their public laboratories and introducing new technology to provide expanded testing services into more regions. This expansion carries the risk of increasing the diversity of an already highly diverse technology and testing platform landscape, making it more difficult to manage laboratory networks across different levels of the health care system. To prevent this trend, countries are recommended to implement policies and guidelines that standardize test menus, technology, platforms, and commodities across multiple laboratories. The benefits of standardization include rational prioritization of resources for capacity development and more efficient supply chain management through volume-based price discounts for reagents and instrument service. Procurement procedures, including specification, prequalification, and contract negotiation, need to align with the standardization policies for maximum benefit. Standardization should be adhered to irrespective of whether procurement is centralized or decentralized or whether carried out by national bodies or development partners.

A probabilistic approach to combining smart meter and electric vehicle charging data to investigate distribution network impacts

International Nuclear Information System (INIS)

Neaimeh, Myriam; Wardle, Robin; Jenkins, Andrew M.; Yi, Jialiang; Hill, Graeme; Lyons, Padraig F.; Hübner, Yvonne; Blythe, Phil T.; Taylor, Phil C.

2015-01-01

Highlights: • Working with unique datasets of EV charging and smart meter load demand. • Distribution networks are not a homogenous group with more capabilities to accommodate EVs than previously suggested. • Spatial and temporal diversity of EV charging demand alleviate the impacts on networks. • An extensive recharging infrastructure could enable connection of additional EVs on constrained distribution networks. • Electric utilities could increase the network capability to accommodate EVs by investing in recharging infrastructure. - Abstract: This work uses a probabilistic method to combine two unique datasets of real world electric vehicle charging profiles and residential smart meter load demand. The data was used to study the impact of the uptake of Electric Vehicles (EVs) on electricity distribution networks. Two real networks representing an urban and rural area, and a generic network representative of a heavily loaded UK distribution network were used. The findings show that distribution networks are not a homogeneous group with a variation of capabilities to accommodate EVs and there is a greater capability than previous studies have suggested. Consideration of the spatial and temporal diversity of EV charging demand has been demonstrated to reduce the estimated impacts on the distribution networks. It is suggested that distribution network operators could collaborate with new market players, such as charging infrastructure operators, to support the roll out of an extensive charging infrastructure in a way that makes the network more robust; create more opportunities for demand side management; and reduce planning uncertainties associated with the stochastic nature of EV charging demand.

System markets: Indirect network effects in action, or inaction?

NARCIS (Netherlands)

J.L.G. Binken (Jeroen)

2010-01-01

textabstractIn this dissertation, I empirically examine system markets up close. More specifically I examine indirect network effects, both demand-side and supply-side indirect network effects. Indirect network effects are the source of positive feedback in system markets, or so network effect

Review of the Main Activities Carried out by the CSN in the Last Five Years

International Nuclear Information System (INIS)

2006-01-01

Nearing the time to finalise a new phase for the Consejo de Seguridad Nuclear, it is time to make a brief account of the main activities carried out over the past five years. During this period, one in which the CSN celebrated its 25th Anniversary, the organisation has served a social demand in a modernisation and adjustment process, followed by the continuous improvement process which throughout its history the former management, teams have carried out with great stamina and dedication. (Author)

Evaluating auditory perception and communication demands required to carry out work tasks and complimentary hearing resources and skills for older workers with hearing loss.

Science.gov (United States)

Jennings, M B; Shaw, L; Hodgins, H; Kuchar, D A; Bataghva, L Poost-Foroosh

2010-01-01

For older workers with acquired hearing loss, this loss as well as the changing nature of work and the workforce, may lead to difficulties and disadvantages in obtaining and maintaining employment. Currently there are very few instruments that can assist workplaces, employers and workers to prepare for older workers with hearing loss or with the evaluation of auditory perception demands of work, especially those relevant to communication, and safety sensitive workplaces that require high levels of communication. This paper introduces key theoretical considerations that informed the development of a new framework, The Audiologic Ergonomic (AE) Framework to guide audiologists, work rehabilitation professionals and workers in developing tools to support the identification and evaluation of auditory perception demands in the workplace, the challenges to communication and the subsequent productivity and safety in the performance of work duties by older workers with hearing loss. The theoretical concepts underpinning this framework are discussed along with next steps in developing tools such as the Canadian Hearing Demands Tool (C-HearD Tool) in advancing approaches to evaluate auditory perception and communication demands in the workplace.

The Employment of spatial autoregressive models in predicting demand for natural gas

International Nuclear Information System (INIS)

Castro, Jorge Henrique de; Silva, Alexandre Pinto Alves da

2010-01-01

Develop the natural gas network is critical success factor for the distribution company. It is a decision that employs the demand given location 'x' and a future time 't' so that the net allows the best conditions for the return of the capital. In this segment, typical network industry, the spatial infra-structure vision associated to the market allows better evaluation of the business because to mitigate costs and risks. In fact, economic models little developed in order to assess the question of the location, due to its little employment by economists. The objective of this article is to analyze the application of spatial perspective in natural gas demand forecasting and to identify the models that can be employed observing issues of dependency and spatial heterogeneity; as well as the capacity of mapping of variables associated with the problem. (author)

Impact of realistic communications for fast-acting demand side management

DEFF Research Database (Denmark)

Dambrauskas, Paulius; Syed, Mazheruddin H.; Blair, Steven M.

2017-01-01

The rising penetration of intermittent energy resources is increasing the need for more diverse electrical energy resources that are able to support ancillary services. Demand side management (DSM) has a significant potential to fulfil this role, but several challenges are still impeding the wide......-scale integration of DSM. One of the major challenges is ensuring the performance of the networks that enable communications between control centres and the end DSM resources. This study presents an analysis of all communications networks that typically participate in the activation of DSM, and provides an estimate...... for the overall latency that these networks incur. The most significant sources of delay from each of the components of the communications network are identified which allows the most critical aspects to be determined. This analysis, therefore, offers a detailed evaluation of the performance of DSM resources...

Future Parking Demand at Rail Stations in Klang Valley

Directory of Open Access Journals (Sweden)

Ho Phooi Wai

2017-01-01

Full Text Available Klang Valley, Malaysia is currently undergoing a massive development of rail transportation system expansion where the current integrated rail transit system will see new extensions of two MRT lines and an LRT line by year 2020. By year 2017, the first MRT line will be ready to run with 31 new rail stations connected to the current passenger rail network. The existing Park and Ride facilities in Klang Valley are commonly known as being unable to sufficiently cater for the current parking space demand. Therefore, with the expansion of many additional rail stations which are rapidly under construction, there are doubts that the future parking space at rail stations will be able to accommodate the sudden rise of rail passengers. Although the authorities are increasing parking bays at various locations, will the future parking demand at rail stations be sufficient? This paper studies the factors influencing parking demand in terms of population, car ownership, new car registrations and passenger rail ridership and estimating the future parking demand using Linear Regression method. Result shows that the forecasted parking demand at rail stations after the implementation of the first new MRT system in 2017 is 2.7 times more than in 2014.

The electric energy demand-side planning: necessity and possibilities of execution

International Nuclear Information System (INIS)

Sposito, E.S.

1991-05-01

Aiming at reducing the level of investments, is presented a demand-side planning approach, divided into two parts. The first part is an analysis on the actual need of our demand-side approaching. In view of this, is showed a set of data and comments both on economic and technological aspects concerning the electric network and sector, as well as evaluation of the social, ecological and financial aspects which could act against the full expansion of the electric system. In the second part, a demand-side planning methodology is introduced, as well as its main concepts, its variables and its instruments of affecting the demand: energy conservation, replacement of sources, reduction of losses and electric power decentralized generation. Each of them is fully detailed in a set of planning policies and actions. Concluding is presented the basic elements of a National Electric Energy Substitution and Conservation Plan - PLANSCON. (author)

Approximability of Robust Network Design

NARCIS (Netherlands)

Olver, N.K.; Shepherd, F.B.

2014-01-01

We consider robust (undirected) network design (RND) problems where the set of feasible demands may be given by an arbitrary convex body. This model, introduced by Ben-Ameur and Kerivin [Ben-Ameur W, Kerivin H (2003) New economical virtual private networks. Comm. ACM 46(6):69-73], generalizes the

Energy flow models for the estimation of technical losses in distribution network

International Nuclear Information System (INIS)

Au, Mau Teng; Tan, Chin Hooi

2013-01-01

This paper presents energy flow models developed to estimate technical losses in distribution network. Energy flow models applied in this paper is based on input energy and peak demand of distribution network, feeder length and peak demand, transformer loading capacity, and load factor. Two case studies, an urban distribution network and a rural distribution network are used to illustrate application of the energy flow models. Results on technical losses obtained for the two distribution networks are consistent and comparable to network of similar types and characteristics. Hence, the energy flow models are suitable for practical application.

China’s primary energy demands in 2020: Predictions from an MPSO–RBF estimation model

International Nuclear Information System (INIS)

Yu Shiwei; Wei Yiming; Wang Ke

2012-01-01

Highlights: ► A Mix-encoding PSO and RBF network-based energy demand forecasting model is proposed. ► The proposed model has simpler structure and smaller estimated errors than other ANN models. ► China’s energy demand could reach 6.25 billion, 4.16 billion, and 5.29 billion tons tce. ► China’s energy efficiency in 2020 will increase by more than 30% compared with 2009. - Abstract: In the present study, a Mix-encoding Particle Swarm Optimization and Radial Basis Function (MPSO–RBF) network-based energy demand forecasting model is proposed and applied to forecast China’s energy consumption until 2020. The energy demand is analyzed for the period from 1980 to 2009 based on GDP, population, proportion of industry in GDP, urbanization rate, and share of coal energy. The results reveal that the proposed MPSO–RBF based model has fewer hidden nodes and smaller estimated errors compared with other ANN-based estimation models. The average annual growth of China’s energy demand will be 6.70%, 2.81%, and 5.08% for the period between 2010 and 2020 in three scenarios and could reach 6.25 billion, 4.16 billion, and 5.29 billion tons coal equivalent in 2020. Regardless of future scenarios, China’s energy efficiency in 2020 will increase by more than 30% compared with 2009.

Demand response from the non-domestic sector: Early UK experiences and future opportunities

International Nuclear Information System (INIS)

Grünewald, Philipp; Torriti, Jacopo

2013-01-01

Demand response is believed by some to become a major contributor towards system balancing in future electricity networks. Shifting or reducing demand at critical moments can reduce the need for generation capacity, help with the integration of renewables, support more efficient system operation and thereby potentially lead to cost and carbon reductions for the entire energy system. In this paper we review the nature of the response resource of consumers from different non-domestic sectors in the UK, based on extensive half hourly demand profiles and observed demand responses. We further explore the potential to increase the demand response capacity through changes in the regulatory and market environment. The analysis suggests that present demand response measures tend to stimulate stand-by generation capacity in preference to load shifting and we propose that extended response times may favour load based demand response, especially in sectors with significant thermal loads. - Highlights: • Empirical demand response data from non-domestic sector evaluated. • Load profiles suggest strong sector dependence on availability response at system peak. • Majority of aggregated demand response still stems from stand-by generation, not from demand turn down. • Scope for substantial increase in demand response capacity if response times were extended

Evaluation of the Electric Vehicle Impact in the Power Demand Curve in a Smart Grid Environment

DEFF Research Database (Denmark)

Morais, Hugo; Sousa, Tiago; Vale, Zita

2014-01-01

be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve...... for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs...... and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32...

[Measuring water ecological carrying capacity with the ecosystem-service-based ecological footprint (ESEF) method: Theory, models and application].

Science.gov (United States)

Jiao, Wen-jun; Min, Qing-wen; Li, Wen-hua; Fuller, Anthony M

2015-04-01

Integrated watershed management based on aquatic ecosystems has been increasingly acknowledged. Such a change in the philosophy of water environment management requires recognizing the carrying capacity of aquatic ecosystems for human society from a more general perspective. The concept of the water ecological carrying capacity is therefore put forward, which considers both water resources and water environment, connects socio-economic development to aquatic ecosystems and provides strong support for integrated watershed management. In this paper, the authors proposed an ESEF-based measure of water ecological carrying capacity and constructed ESEF-based models of water ecological footprint and capacity, aiming to evaluate water ecological carrying capacity with footprint methods. A regional model of Taihu Lake Basin was constructed and applied to evaluate the water ecological carrying capacity in Changzhou City which located in the upper reaches of the basin. Results showed that human demand for water ecosystem services in this city had exceeded the supply capacity of local aquatic ecosystems and the significant gap between demand and supply had jeopardized the sustainability of local aquatic ecosystems. Considering aqua-product provision, water supply and pollutant absorption in an integrated way, the scale of population and economy aquatic ecosystems in Changzhou could bear only 54% of the current status.

Predictive routing for autonomous mobility-on-demand systems with ride-sharing

NARCIS (Netherlands)

Alonso Mora, J.; Wallar, Alex; Rus, Daniela; Bicchi, A.; Maciejewski, T.

2017-01-01

Ride-sharing, or carpooling, systems with autonomous vehicles will provide efficient and reliable urban mobility on demand. In this work we present a method for dynamic vehicle routing that leverages historical data to improve the performance of a network of self-driving taxis. In particular, we

Physical-layer Network Coding in Two-Way Heterogeneous Cellular Networks with Power Imbalance

OpenAIRE

Thampi, Ajay K; Liew, Soung Chang; Armour, Simon M D; Fan, Zhong; You, Lizhao; Kaleshi, Dritan

2016-01-01

The growing demand for high-speed data, quality of service (QoS) assurance and energy efficiency has triggered the evolution of 4G LTE-A networks to 5G and beyond. Interference is still a major performance bottleneck. This paper studies the application of physical-layer network coding (PNC), a technique that exploits interference, in heterogeneous cellular networks. In particular, we propose a rate-maximising relay selection algorithm for a single cell with multiple relays assuming the decode...

Spatial dimensions of the demand for homeownership

DEFF Research Database (Denmark)

Sørensen, Jens Fyhn Lykke

2010-01-01

This paper introduces the concept of "spatial location satisfaction" and examines its relation to the individual demand for homeownership. Based on a Danish questionnaire survey carried out in a rural study area (N=1000) and in an urban study area (N=1015), a tenure choice model was estimated...... relating spatial location satisfaction to homeownership, while adjusting for control variables. The spatial location satisfaction variable was constructed from two questionnaire items asking respondents to state their actual and preferred place of settlement given five location type options: large city......, medium-sized city, small town, village, and "in the countryside". As hypothesised, the study shows a strong association between spatial location satisfaction and the individual demand for homeownership. This association is robust across study areas. Spatial location satisfaction is highest in the rural...

Reliability constrained decision model for energy service provider incorporating demand response programs

International Nuclear Information System (INIS)

Mahboubi-Moghaddam, Esmaeil; Nayeripour, Majid; Aghaei, Jamshid

2016-01-01

Highlights: • The operation of Energy Service Providers (ESPs) in electricity markets is modeled. • Demand response as the cost-effective solution is used for energy service provider. • The market price uncertainty is modeled using the robust optimization technique. • The reliability of the distribution network is embedded into the framework. • The simulation results demonstrate the benefits of robust framework for ESPs. - Abstract: Demand response (DR) programs are becoming a critical concept for the efficiency of current electric power industries. Therefore, its various capabilities and barriers have to be investigated. In this paper, an effective decision model is presented for the strategic behavior of energy service providers (ESPs) to demonstrate how to participate in the day-ahead electricity market and how to allocate demand in the smart distribution network. Since market price affects DR and vice versa, a new two-step sequential framework is proposed, in which unit commitment problem (UC) is solved to forecast the expected locational marginal prices (LMPs), and successively DR program is applied to optimize the total cost of providing energy for the distribution network customers. This total cost includes the cost of purchased power from the market and distributed generation (DG) units, incentive cost paid to the customers, and compensation cost of power interruptions. To obtain compensation cost, the reliability evaluation of the distribution network is embedded into the framework using some innovative constraints. Furthermore, to consider the unexpected behaviors of the other market participants, the LMP prices are modeled as the uncertainty parameters using the robust optimization technique, which is more practical compared to the conventional stochastic approach. The simulation results demonstrate the significant benefits of the presented framework for the strategic performance of ESPs.

Spatial analysis of bus transport networks using network theory

Science.gov (United States)

Shanmukhappa, Tanuja; Ho, Ivan Wang-Hei; Tse, Chi Kong

2018-07-01

In this paper, we analyze the bus transport network (BTN) structure considering the spatial embedding of the network for three cities, namely, Hong Kong (HK), London (LD), and Bengaluru (BL). We propose a novel approach called supernode graph structuring for modeling the bus transport network. A static demand estimation procedure is proposed to assign the node weights by considering the points of interests (POIs) and the population distribution in the city over various localized zones. In addition, the end-to-end delay is proposed as a parameter to measure the topological efficiency of the bus networks instead of the shortest distance measure used in previous works. With the aid of supernode graph representation, important network parameters are analyzed for the directed, weighted and geo-referenced bus transport networks. It is observed that the supernode concept has significant advantage in analyzing the inherent topological behavior. For instance, the scale-free and small-world behavior becomes evident with supernode representation as compared to conventional or regular graph representation for the Hong Kong network. Significant improvement in clustering, reduction in path length, and increase in centrality values are observed in all the three networks with supernode representation. The correlation between topologically central nodes and the geographically central nodes reveals the interesting fact that the proposed static demand estimation method for assigning node weights aids in better identifying the geographically significant nodes in the network. The impact of these geographically significant nodes on the local traffic behavior is demonstrated by simulation using the SUMO (Simulation of Urban Mobility) tool which is also supported by real-world empirical data, and our results indicate that the traffic speed around a particular bus stop can reach a jammed state from a free flow state due to the presence of these geographically important nodes. A comparison

Coal demand prediction based on a support vector machine model

Energy Technology Data Exchange (ETDEWEB)

Jia, Cun-liang; Wu, Hai-shan; Gong, Dun-wei [China University of Mining & Technology, Xuzhou (China). School of Information and Electronic Engineering

2007-01-15

A forecasting model for coal demand of China using a support vector regression was constructed. With the selected embedding dimension, the output vectors and input vectors were constructed based on the coal demand of China from 1980 to 2002. After compared with lineal kernel and Sigmoid kernel, a radial basis function(RBF) was adopted as the kernel function. By analyzing the relationship between the error margin of prediction and the model parameters, the proper parameters were chosen. The support vector machines (SVM) model with multi-input and single output was proposed. Compared the predictor based on RBF neural networks with test datasets, the results show that the SVM predictor has higher precision and greater generalization ability. In the end, the coal demand from 2003 to 2006 is accurately forecasted. l0 refs., 2 figs., 4 tabs.

Orchestrating utility supply and demand in real-time via the Internet, home networks, and smart appliances

Energy Technology Data Exchange (ETDEWEB)

Cruickshank, R.F. III [Power Networks, Big Indian, NY (United States)

2008-07-01

This paper presented a model to illustrate the efficient coordination between the supply-side and demand-side of household electricity use and the magnitude of demand that can be managed using real-time pricing. In real-time supply and demand side management, a variable price for service is sent via Internet from the supply-side to the demand-side. The 3 benefits to this type of demand-side management are that traditional fossil-fuelled electrical capacity can operate less of the time and more efficiently; renewable electrical capacity such as wind and solar power can be put to use more efficiently when it becomes available; and additional means are available to protect the transmission and distribution infrastructure of the utility. A critical requirement is that pricing should change frequently throughout the day so that budget conscious consumers do not have to wait too long for favourable pricing to use their appliances. 12 refs., 9 figs.

Inventor networks in renewable energies

DEFF Research Database (Denmark)

Cantner, Uwe; Graf, Holger; Herrmann, Johannes

2016-01-01

on patent data. Our results indicate notable differences between the technologies: the network size for wind power is driven by technology push and systemic instruments, while in photovoltaics, demand pull is decisive for network growth. By and large, the instruments complement each other and form...... energies. Our goal is to gain insights into the influence of this policy mix on the intensity and organization of inventive activities for wind power and photovoltaics in Germany since the 1980s. We examine the effect of different instruments on the size and structure of co-inventor networks based......Technological change and gains in efficiency of renewable power generation technologies are to a large extent driven by governmental support. Various policy instruments that can broadly be categorized as technology push, demand pull or systemic constitute part of the policy mix for renewable...

Demand management through centralized control system using power line communication for existing buildings

International Nuclear Information System (INIS)

Al-Mulla, A.; ElSherbini, A.

2014-01-01

Highlights: • A pilot system was developed for demand management of equipment in buildings. • The networking was based on LonWorks platform and power line communication. • Demand strategies led to load reductions up to 74% and energy savings up to 25%. • The peak load reduction is expected to reach 3.44 GW by the year 2030. - Abstract: Managing peak demand efficiently is vital for maintaining uninterrupted supply of electrical power by utility providers. In this work, a pilot system was developed for managing and controlling the demand of major power consuming equipment in buildings from a central server, while relying mostly on existing infrastructure and maintaining consumer comfort. The system was successfully demonstrated on a selected group of buildings using the LonWorks networking platform. At the building level, the system utilized power line and twisted pair communication to control the thermostats of air-conditioning (A/C) units. The higher level communication was executed through extensible markup language (XML) and simple object access protocol (SOAP). The system provided control capabilities based on A/C unit priority, thermostat temperature, building type and geographic location. The development and execution of demand management strategies for selected buildings led to peak load reductions up to 74%, in addition to energy savings up to 25%. Implementing such a system at a national level in Kuwait is estimated to reduce peak demand by 3.44 GW, amounting to capital savings of $4.13 billion. The use of existing infrastructure reduced the cost and installation time of the system. Based on the successful testing of this pilot system, a larger-scale system is being developed

Demand Uncertainty

DEFF Research Database (Denmark)

Nguyen, Daniel Xuyen

This paper presents a model of trade that explains why firms wait to export and why many exporters fail. Firms face uncertain demands that are only realized after the firm enters the destination. The model retools the timing of uncertainty resolution found in productivity heterogeneity models....... This retooling addresses several shortcomings. First, the imperfect correlation of demands reconciles the sales variation observed in and across destinations. Second, since demands for the firm's output are correlated across destinations, a firm can use previously realized demands to forecast unknown demands...... in untested destinations. The option to forecast demands causes firms to delay exporting in order to gather more information about foreign demand. Third, since uncertainty is resolved after entry, many firms enter a destination and then exit after learning that they cannot profit. This prediction reconciles...

Decision support program for congestion management using demand side flexibility

DEFF Research Database (Denmark)

Esmat, Ayman; Pinson, Pierre; Usaola, Julio

2017-01-01

In the past decades, Distribution System Operators (DSOs) have been mitigating distribution networks (DNs) contingencies by opting to grid reinforcements. However, this approach is not always cost and time efficient. Demand Side Flexibility (DSF) is one of the recent alternatives used in DNs cong...... effect is taken into consideration as well as the uncertain behavior of customers. Finally, the distribution grid of the Danish Bornholm Island is used to illustrate the merits of the DSP. The total cost incurred by the DSO is calculated and presented.......In the past decades, Distribution System Operators (DSOs) have been mitigating distribution networks (DNs) contingencies by opting to grid reinforcements. However, this approach is not always cost and time efficient. Demand Side Flexibility (DSF) is one of the recent alternatives used in DNs...... congestion management. Consequently, new market players such as aggregators are needed to handle DSF transaction between customers and DSOs. This paper proposes and models a decision support program (DSP) to optimize the total cost charged by the DSO for using DSF services. Moreover, the energy rebound...

Computer network for experimental research using ISDN

International Nuclear Information System (INIS)

Ida, Katsumi; Nakanishi, Hideya

1997-01-01

This report describes the development of a computer network that uses the Integrated Service Digital Network (ISDN) for real-time analysis of experimental plasma physics and nuclear fusion research. Communication speed, 64/128kbps (INS64) or 1.5Mbps (INS1500) per connection, is independent of how busy the network is. When INS-1500 is used, the communication speed, which is proportional to the public telephone connection fee, can be dynamically varied from 64kbps to 1472kbps (depending on how much data are being transferred using the Bandwidth-on-Demand (BOD) function in the ISDN Router. On-demand dial-up and time-out disconnection reduce the public telephone connection fee by 10%-97%. (author)

Demand pattern analysis of taxi trip data for anomalies detection and explanation

DEFF Research Database (Denmark)

Markou, Ioulia; Rodrigues, Filipe; Pereira, Francisco Camara

2017-01-01

Due to environmental and economic stress, strong investment exists now towards adaptive transport systems that can efficiently utilize capacity, minimizing costs and environmental impacts. The common vision is a system that dynamically changes itself (the supply) to anticipate traveler needs (the...... demand). In some occasions, unexpected and unwanted demand patterns are noticed in the traffic network that lead to system failures and cost implications. Significantly low speeds or excessively low flows at an unforeseeable time are only some of the phenomena that are often noticed and need...

Automated Demand Response Approaches to Household Energy Management in a Smart Grid Environment

Science.gov (United States)

Adika, Christopher Otieno

The advancement of renewable energy technologies and the deregulation of the electricity market have seen the emergence of Demand response (DR) programs. Demand response is a cost-effective load management strategy which enables the electricity suppliers to maintain the integrity of the power grid during high peak periods, when the customers' electrical load is high. DR programs are designed to influence electricity users to alter their normal consumption patterns by offering them financial incentives. A well designed incentive-based DR scheme that offer competitive electricity pricing structure can result in numerous benefits to all the players in the electricity market. Lower power consumption during peak periods will significantly enhance the robustness of constrained networks by reducing the level of power of generation and transmission infrastructure needed to provide electric service. Therefore, this will ease the pressure of building new power networks as we avoiding costly energy procurements thereby translating into huge financial savings for the power suppliers. Peak load reduction will also reduce the inconveniences suffered by end users as a result of brownouts or blackouts. Demand response will also drastically lower the price peaks associated with wholesale markets. This will in turn reduce the electricity costs and risks for all the players in the energy market. Additionally, DR is environmentally friendly since it enhances the flexibility of the power grid through accommodation of renewable energy resources. Despite its many benefits, DR has not been embraced by most electricity networks. This can be attributed to the fact that the existing programs do not provide enough incentives to the end users and, therefore, most electricity users are not willing to participate in them. To overcome these challenges, most utilities are coming up with innovative strategies that will be more attractive to their customers. Thus, this dissertation presents various

Network software of FD-NET local network for the RT-11 operational system

International Nuclear Information System (INIS)

Bobyshev, A.N.; Kutsenko, V.A.; Kravtsov, A.I.; Korzhavin, A.I.; Rozhkov, A.B.; Semenov, Yu.A.; Fedotov, O.P.

1987-01-01

Description of software of FD-Net ring local network based on the ''Elektronika-60'' and ''MERA-60'' microcomputers as well as on SM-3, SM-4 and ''MERA-125'' minicomputers is given. FD-Net local network is aimed at automatization of complex and labour-consuming physical experiments carried out at the THEP. It permits to carry out simultaneous application of external devices, files and programs as well as data exchange between problems solved by different computers. The architecture of FD-Net network hardware is considered as well as a general structure of software. Certain modules of network software and their interaction with each other are described

Networking for the Environment

DEFF Research Database (Denmark)

Dickel, Petra; Hörisch, Jacob; Ritter, Thomas

2018-01-01

Although the public debate on the environmental orientation of firms has intensified, there is a lack of understanding about the consequences of that orientation, especially in terms of its impact on firms' networking behavior. In order to fill this gap, this paper analyzes the impact of external...... and internal environmental orientation on start-ups’ network characteristics, because networks are both vital for the success of start-ups and resource demanding. More specifically, the effects of environmental orientation on networking frequency and network size among start-ups are analyzed. Empirical data...... from 248 technology-based start-ups shows that those firms with a strong external environmental orientation have significantly higher networking frequencies and build larger networks. Conversely, a strong internal environmental orientation is linked to smaller networks. Thus, the results highlight...

AC transmission network expansion planning considering circuits repowering and location of capacitors

Directory of Open Access Journals (Sweden)

Jaime A. López-López

2016-07-01

Full Text Available This paper deals with the Transmission Network Expansion Planning (TNEP problem. The TNEP consists of finding a set of new circuits on a power system, which is needed to attend a future demand. In its classical version, the TNEP only considers as solution candidates the addition of new lines and transformers. The main contribution of this paper consists in the inclusion of nonconventional solution candidates, namely the repowering of existing circuits and the location of capacitor banks. To take into account these last ones an AC model of the transmission network is considered. The solution of the proposed model is carried out using a Hybrid Genetic Algorithm. Results are compared and validated with previous works in the technical literature. The test systems used are the Garver system and IEEE 24 bus system. The results obtained in both systems showed that the inclusion of the non-conventional candidates, proposed in this paper, allows to reduce the cost of network expansion. This fact may be useful as an indicator for the system planner to consider new possibilities in the expansion studies.

R and D options for demand side management in Japanese electric utilities

International Nuclear Information System (INIS)

Yamamoto, Takahiko

1996-01-01

Japanese electric demand has been steadily increasing in accordance with the economic growth. However, Japanese electric utilities are facing several problems; increasing construction cost of power facilities, siting constraints and the environmental issue of greenhouse gas emissions. To overcome these problems, electric utilities have been promoting demand-side-management (DSM) activities as well as supplier-side measures, with some presently being carried out through promoting energy conservation technologies and introducing electric tariff options of specific contracts for residential/commercial and industrial consumers. Japanese electric utilities have been carrying out R and D for the future, in particular, energy storage and heat storage which contribute to the improvement of load factor. In this paper, I would like to outline the R and D options for DSM in Japan. (author)

Preparing for a Career as a Network Engineer

Science.gov (United States)

Morris, Gerard; Fustos, Janos; Haga, Wayne

2012-01-01

A network engineer is an Information Technology (IT) professional who designs, implements, maintains, and troubleshoots computer networks. While the United States is still experiencing relatively high unemployment, demand for network engineers remains strong. To determine what skills employers are looking for, data was collected and analyzed from…

Proliferation Networks and Financing

International Nuclear Information System (INIS)

Gruselle, Bruno

2007-01-01

The objective of this study is to propose practical solutions aimed at completing and strengthening the existing arrangement for the control of nuclear proliferation through a control of financial as well as material or immaterial flows. In a first part, the author proposes a systemic analysis of networks of suppliers and demanders. He notably evokes the Khan's network and the Iraqi acquisition network during the 1993-2001 period. He also proposes a modelling of proliferation networks (supplier networks and acquisition networks) and of their interactions. In a second part, the author examines possible means and policies aimed at neutralising proliferation networks: organisation, adaptation and improvement of intelligence tools in front of proliferation networks, and means, limitations and perspectives of network neutralisation. He also briefly addresses the possibility of military action to contain proliferation flows

基于5A景区最大承载量和游客接待量的旅游供需关系模型研究%Study of Mathematical Model Between Tourism Supply and Demand Based on Relationship of the 5A Level Scenic Spots' Maximum Carrying Capacity and the Amount of the Tourists

Institute of Scientific and Technical Information of China (English)

刘静; 刘耀龙; 段锦

2017-01-01

旅游承载量是反映旅游供给能力的重要指标,游客接待量是衡量旅游需求状况的常用指标.在分析我国5A级景区最大承载量空间分异特征的基础上,对2014年各省市5A级景区日最大承载量和年游客接待量进行相关性和回归分析,构建基于景区承载量和游客接待量的旅游供需关系模型.结果表明:(1)5A级景区最大承载量和游客接待量之间存在显著的正相关关系;(2)旅游供需关系模型可由复合函数定量表征;(3)模型能够预测旅游供需变化,对旅游业发展具有一定的指示意义.%Tourism carrying capacity is an important index to reflect the tourism supply capacity, and the amount of the tourists is a common index to measure tourism demand. On the basis of the analysis of the spatial distribution characteristics of 5A level scenic spots' maximum carrying capacity, the paper carries out correlation and regression analysis about the 5A level scenic' maximum carrying capacity and the amount of the tourists. Sample data is calculated or statistical results of 31 provinces in 2014. Tourism supply and demand model is constructed based on the relationship between the 5A level scenic spots' maximum carrying capacity and the amount of the tourists. Results indicate: (1)There is a significant positive correlation between the 5A level scenic spot'maximum carrying capacity and the amount of tourists; (2)The model of tourism supply and demand relations can be quantitatively characterized by complex functions;(3)The model can predict the change of tourism supply and demand, which have referential meaning to the development of tourism.

A User-Customized Virtual Network Platform for NaaS Cloud

Directory of Open Access Journals (Sweden)

Lei Xiao

2016-01-01

Full Text Available Now all kinds of public cloud providers take computing and storage resources as the user’s main demand, making it difficult for users to deploy complex network in the public cloud. This paper proposes a virtual cloud platform with network as the core demand of the user, which can provide the user with the capacity of free network architecture as well as all kinds of virtual resources. The network is isolated by port groups of the virtual distributed switch and the data forwarding and access control between different network segments are implemented by virtual machines loading a soft-routing system. This paper also studies the management interface of network architecture and the uniform way to connect the remote desktop of virtual resources on the web, hoping to provide some new ideas for the Network as a Service model.

Road Network Vulnerability Analysis Based on Improved Ant Colony Algorithm

Directory of Open Access Journals (Sweden)

Yunpeng Wang

2014-01-01

Full Text Available We present an improved ant colony algorithm-based approach to assess the vulnerability of a road network and identify the critical infrastructures. This approach improves computational efficiency and allows for its applications in large-scale road networks. This research involves defining the vulnerability conception, modeling the traffic utility index and the vulnerability of the road network, and identifying the critical infrastructures of the road network. We apply the approach to a simple test road network and a real road network to verify the methodology. The results show that vulnerability is directly related to traffic demand and increases significantly when the demand approaches capacity. The proposed approach reduces the computational burden and may be applied in large-scale road network analysis. It can be used as a decision-supporting tool for identifying critical infrastructures in transportation planning and management.

Regulatory Holidays and Optimal Network Expansion

NARCIS (Netherlands)

Willems, Bert; Zwart, Gijsbert

2016-01-01

We model the optimal regulation of continuous, irreversible, capacity expansion, in a model in which the regulated network firm has private information about its capacity costs, investments need to be financed out of the firm’s cash flows from selling network access and demand is stochastic. If

Quadratic Boost A-Source Impedance Network

DEFF Research Database (Denmark)

Siwakoti, Yam Prasad; Blaabjerg, Frede; Chub, Andrii

2016-01-01

A novel quadratic boost A-source impedance network is proposed to realize converters that demand very high voltage gain. To satisfy the requirement, the network uses an autotransformer where the obtained gain is quadratically dependent on the duty ratio and is unmatched by any existing impedance...

Applying the flow-capturing location-allocation model to an authentic network: Edmonton, Canada

NARCIS (Netherlands)

M.J. Hodgson (John); K.E. Rosing (Kenneth); A.L.G. Storrier (Leontien)

1996-01-01

textabstractTraditional location-allocation models aim to locate network facilities to optimally serve demand expressed as weights at nodes. For some types of facilities demand is not expressed at nodes, but as passing network traffic. The flow-capturing location-allocation model responds to this

Real-Time Communication Networks Onboard Ships

DEFF Research Database (Denmark)

Nielsen, Jens Frederik Dalsgaard; Nielsen, Kirsten Mølgaard; Jørgensen, N.

1995-01-01

This paper describes the ATOMOS communication network project carried out within the EU project ATOMOS, to be used for ISC purposes.......This paper describes the ATOMOS communication network project carried out within the EU project ATOMOS, to be used for ISC purposes....

A multifunctional multimaterial system for on-demand protein release.

Science.gov (United States)

Tuncaboylu, Deniz Ceylan; Friess, Fabian; Wischke, Christian; Lendlein, Andreas

2018-06-15

In order to provide best control of the regeneration process for each individual patient, the release of protein drugs administered during surgery may need to be timely adapted and/or delayed according to the progress of healing/regeneration. This study aims to establish a multifunctional implant system for a local on-demand release, which is applicable for various types of proteins. It was hypothesized that a tubular multimaterial container kit, which hosts the protein of interest as a solution or gel formulation, would enable on-demand release if equipped with the capacity of diameter reduction upon external stimulation. Using devices from poly(ɛ-caprolactone) networks, it could be demonstrated that a shape-memory effect activated by heat or NIR light enabled on-demand tube shrinkage. The decrease of diameter of these shape-memory tubes (SMT) allowed expelling the payload as demonstrated for several proteins including SDF-1α, a therapeutically relevant chemotactic protein, to achieve e.g. continuous release with a triggered add-on dosing (open tube) or an on-demand onset of bolus or sustained release (sealed tube). Considering the clinical relevance of protein factors in (stem) cell attraction to lesions and the progress in monitoring biomarkers in body fluids, such on-demand release systems may be further explored e.g. in heart, nerve, or bone regeneration in the future. Copyright © 2018. Published by Elsevier B.V.

Optimal dimensioning of low-energy district heating networks with operational planning

DEFF Research Database (Denmark)

Tol, Hakan; Svendsen, Svend

2012-01-01

in design stage resulted in satisfaction of heat demand of the house in low temperature operation. In this paper the operational planning of the low-energy DH systems was investigated to reduce the dimensions of the distribution network with consideration given both to current high-heat and future low......-heat demand situations. The operational planning was based on boosting (increasing) the supply temperature at peak-demand situations which occur rarely over a year period. Hence optimal pipe dimensions of low-energy DH systems were investigated based on the dynamic response of in-house heating systems...... of operational planning in comparison to DH network dimensioned according to high heat demand situation....

System analysis and planning of a gas distribution network

Energy Technology Data Exchange (ETDEWEB)

Salas, Edwin F.M.; Farias, Helio Monteiro [AUTOMIND, Rio de Janeiro, RJ (Brazil); Costa, Carla V.R. [Universidade Salvador (UNIFACS), BA (Brazil)

2009-07-01

The increase in demand by gas consumers require that projects or improvements in gas distribution networks be made carefully and safely to ensure a continuous, efficient and economical supply. Gas distribution companies must ensure that the networks and equipment involved are defined and designed at the appropriate time to attend to the demands of the market. To do that a gas distribution network analysis and planning tool should use distribution networks and transmission models for the current situation and the future changes to be implemented. These models are used to evaluate project options and help in making appropriate decisions in order to minimize the capital investment in new components or simple changes in operational procedures. Gas demands are increasing and it is important that gas distribute design new distribution systems to ensure this growth, considering financial constraints of the company, as well as local legislation and regulation. In this study some steps of developing a flexible system that attends to those needs will be described. The analysis of distribution requires geographically referenced data for the models as well as an accurate connectivity and the attributes of the equipment. GIS systems are often used as a deposit center that holds the majority of this information. GIS systems are constantly updated as distribution network equipment is modified. The distribution network modeling gathered from this system ensures that the model represents the current network condition. The benefits of this architecture drastically reduce the creation and maintenance cost of the network models, because network components data are conveniently made available to populate the distribution network. This architecture ensures that the models are continually reflecting the reality of the distribution network. (author)

Bribery games on inter-dependent regular networks.

Science.gov (United States)

Verma, Prateek; Nandi, Anjan K; Sengupta, Supratim

2017-02-16

We examine a scenario of social conflict that is manifest during an interaction between government servants providing a service and citizens who are legally entitled to the service, using evolutionary game-theory in structured populations characterized by an inter-dependent network. Bribe-demands by government servants during such transactions, called harassment bribes, constitute a widespread form of corruption in many countries. We investigate the effect of varying bribe demand made by corrupt officials and the cost of complaining incurred by harassed citizens, on the proliferation of corrupt strategies in the population. We also examine how the connectivity of the various constituent networks affects the spread of corrupt officials in the population. We find that incidents of bribery can be considerably reduced in a network-structured populations compared to mixed populations. Interestingly, we also find that an optimal range for the connectivity of nodes in the citizen's network (signifying the degree of influence a citizen has in affecting the strategy of other citizens in the network) as well as the interaction network aids in the fixation of honest officers. Our results reveal the important role of network structure and connectivity in asymmetric games.

Bribery games on inter-dependent regular networks

Science.gov (United States)

Verma, Prateek; Nandi, Anjan K.; Sengupta, Supratim

2017-02-01

We examine a scenario of social conflict that is manifest during an interaction between government servants providing a service and citizens who are legally entitled to the service, using evolutionary game-theory in structured populations characterized by an inter-dependent network. Bribe-demands by government servants during such transactions, called harassment bribes, constitute a widespread form of corruption in many countries. We investigate the effect of varying bribe demand made by corrupt officials and the cost of complaining incurred by harassed citizens, on the proliferation of corrupt strategies in the population. We also examine how the connectivity of the various constituent networks affects the spread of corrupt officials in the population. We find that incidents of bribery can be considerably reduced in a network-structured populations compared to mixed populations. Interestingly, we also find that an optimal range for the connectivity of nodes in the citizen’s network (signifying the degree of influence a citizen has in affecting the strategy of other citizens in the network) as well as the interaction network aids in the fixation of honest officers. Our results reveal the important role of network structure and connectivity in asymmetric games.

A precise time synchronization method for 5G based on radio-over-fiber network with SDN controller

Science.gov (United States)

He, Linkuan; Wei, Baoguo; Yang, Hui; Yu, Ao; Wang, Zhengyong; Zhang, Jie

2018-02-01

There is an increasing demand on accurate time synchronization with the growing bandwidth of network service for 5G. In 5G network, it's necessary for base station to achieve accurate time synchronization to guarantee the quality of communication. In order to keep accuracy time for 5G network, we propose a time synchronization system for satellite ground station based on radio-over-fiber network (RoFN) with software defined optical network (SDON) controller. The advantage of this method is to improve the accuracy of time synchronization of ground station. The IEEE 1588 time synchronization protocol can solve the problems of high cost and lack of precision. However, in the process of time synchronization, distortion exists during the transmission of digital time signal. RoF uses analog optical transmission links and therefore analog transmission can be implemented among ground stations instead of digital transmission, which means distortion and bandwidth waste in the process of digital synchronization can be avoided. Additionally, the thought of SDN, software defined network, can optimize RoFN with centralized control and simplifying base station. Related simulation had been carried out to prove its superiority.

End-System Network Interface Controller for 100 Gb/s Wide Area Networks: Final Report

Energy Technology Data Exchange (ETDEWEB)

Wen, Jesse [Acadia Optronics LLC, Rockville, MD (United States)

2013-08-30

In recent years, network bandwidth requirements have scaled multiple folds, pushing the need for the development of data exchange mechanisms at 100 Gb/s and beyond. High performance computing, climate modeling, large-scale storage, and collaborative scientific research are examples of applications that can greatly benefit by leveraging high bandwidth capabilities of the order of 100 Gb/s. Such requirements and advances in IEEE Ethernet standards, Optical Transport Unit4 (OTU4), and host-system interconnects demand a network infrastructure supporting throughput rates of the order of 100 Gb/s with a single wavelength. To address such a demand Acadia Optronics in collaboration with the University of New Mexico, proposed and developed a end-system Network Interface Controller (NIC) for the 100Gbps WANs. Acadia’s 100G NIC employs an FPGA based system with a high-performance processor interconnect (PCIe 3.0) and a high capacity optical transmission link (CXP) to provide data transmission at the rate of 100 Gbps.

Base Stock Policy in a Join-Type Production Line with Advanced Demand Information

Science.gov (United States)

Hiraiwa, Mikihiko; Tsubouchi, Satoshi; Nakade, Koichi

Production control such as the base stock policy, the kanban policy and the constant work-in-process policy in a serial production line has been studied by many researchers. Production lines, however, usually have fork-type, join-type or network-type figures. In addition, in most previous studies on production control, a finished product is required at the same time as arrival of demand at the system. Demand information is, however, informed before due date in practice. In this paper a join-type (assembly) production line under base stock control with advanced demand information in discrete time is analyzed. The recursive equations for the work-in-process are derived. The heuristic algorithm for finding appropriate base stock levels of all machines at short time is proposed and the effect of advanced demand information is examined by simulation with the proposed algorithm. It is shown that the inventory cost can decreases with little backlogs by using the appropriate amount of demand information and setting appropriate base stock levels.

An infrastructure with a unified control plane to integrate IP into optical metro networks to provide flexible and intelligent bandwidth on demand for cloud computing

Science.gov (United States)

Yang, Wei; Hall, Trevor

2012-12-01

The Internet is entering an era of cloud computing to provide more cost effective, eco-friendly and reliable services to consumer and business users and the nature of the Internet traffic will undertake a fundamental transformation. Consequently, the current Internet will no longer suffice for serving cloud traffic in metro areas. This work proposes an infrastructure with a unified control plane that integrates simple packet aggregation technology with optical express through the interoperation between IP routers and electrical traffic controllers in optical metro networks. The proposed infrastructure provides flexible, intelligent, and eco-friendly bandwidth on demand for cloud computing in metro areas.

PL/SQL and Bind Variable: the two ways to increase the efficiency of Network Databases

Directory of Open Access Journals (Sweden)

Hitesh KUMAR SHARMA

2011-12-01

Full Text Available Modern data analysis applications are driven by the Network databases. They are pushing traditional database and data warehousing technologies beyond their limits due to their massively increasing data volumes and demands for low latency. There are three major challenges in working with network databases: interoperability due to heterogeneous data repositories, proactively due to autonomy of data sources and high efficiency to meet the application demand. This paper provides the two ways to meet the third challenge of network databases. This goal can be achieved by network database administrator with the usage of PL/SQL blocks and bind variable. The paper will explain the effect of PL/SQL block and bind variable on Network database efficiency to meet the modern data analysis application demand.

Stochastic water demand modelling for a better understanding of hydraulics in water distribution networks

NARCIS (Netherlands)

Blokker, E.J.M.

2010-01-01

In the water distribution network water quality process take place influenced by de flow velocity and residence time of the water in the network. In order to understand how the water quality changes in the water distribution network, a good understanding of hydraulics is required. Specifically in

On robustness in food supply chain networks

NARCIS (Netherlands)

Vlajic, J.V.; Vorst, van der J.G.A.J.; Hendrix, E.M.T.

2010-01-01

Purpose: Today's business environment is characterized by challenges of strong global competition where companies tend to achieve leanness and maximum responsiveness to customer demand. Lean supply chain networks are vulnerable to all kind of disruptions. For food supply chain networks (FSCNs), due

Analysis and decrease of the energy demand of bioethanol-production by process integration

Energy Technology Data Exchange (ETDEWEB)

Pfeffer, Martin; Wukovits, Walter; Beckmann, Georg; Friedl, Anton [Vienna University of Technology, Getreidemarkt 9, A-1060 Vienna (Austria)

2007-11-15

Process simulation was used to decrease the external heat demand during the production of bioethanol by integration in a network of facilities for heat and power generation. Models for bioethanol fermentation and purification process, the production of DDGS as well as production and utilization of biogas were developed to calculate the heat demand of bioethanol-production and the amount of heat and power generated from residues of the bioethanol process. Depending on the form of biogas utilization (CHP-plant, biogas fired boiler) and the capacity of the bioethanol plant, the conversion of stillage from the bioethanol process to biogas covers a considerable amount of the heat demand necessary for bioethanol-production and purification. (author)

Network evolution model for supply chain with manufactures as the core

Science.gov (United States)

Jiang, Dali; Fang, Ling; Yang, Jian; Li, Wu; Zhao, Jing

2018-01-01

Building evolution model of supply chain networks could be helpful to understand its development law. However, specific characteristics and attributes of real supply chains are often neglected in existing evolution models. This work proposes a new evolution model of supply chain with manufactures as the core, based on external market demand and internal competition-cooperation. The evolution model assumes the external market environment is relatively stable, considers several factors, including specific topology of supply chain, external market demand, ecological growth and flow conservation. The simulation results suggest that the networks evolved by our model have similar structures as real supply chains. Meanwhile, the influences of external market demand and internal competition-cooperation to network evolution are analyzed. Additionally, 38 benchmark data sets are applied to validate the rationality of our evolution model, in which, nine manufacturing supply chains match the features of the networks constructed by our model. PMID:29370201

Network evolution model for supply chain with manufactures as the core.

Science.gov (United States)

Fang, Haiyang; Jiang, Dali; Yang, Tinghong; Fang, Ling; Yang, Jian; Li, Wu; Zhao, Jing

2018-01-01

Building evolution model of supply chain networks could be helpful to understand its development law. However, specific characteristics and attributes of real supply chains are often neglected in existing evolution models. This work proposes a new evolution model of supply chain with manufactures as the core, based on external market demand and internal competition-cooperation. The evolution model assumes the external market environment is relatively stable, considers several factors, including specific topology of supply chain, external market demand, ecological growth and flow conservation. The simulation results suggest that the networks evolved by our model have similar structures as real supply chains. Meanwhile, the influences of external market demand and internal competition-cooperation to network evolution are analyzed. Additionally, 38 benchmark data sets are applied to validate the rationality of our evolution model, in which, nine manufacturing supply chains match the features of the networks constructed by our model.

Network evolution model for supply chain with manufactures as the core.

Directory of Open Access Journals (Sweden)

Haiyang Fang

Full Text Available Building evolution model of supply chain networks could be helpful to understand its development law. However, specific characteristics and attributes of real supply chains are often neglected in existing evolution models. This work proposes a new evolution model of supply chain with manufactures as the core, based on external market demand and internal competition-cooperation. The evolution model assumes the external market environment is relatively stable, considers several factors, including specific topology of supply chain, external market demand, ecological growth and flow conservation. The simulation results suggest that the networks evolved by our model have similar structures as real supply chains. Meanwhile, the influences of external market demand and internal competition-cooperation to network evolution are analyzed. Additionally, 38 benchmark data sets are applied to validate the rationality of our evolution model, in which, nine manufacturing supply chains match the features of the networks constructed by our model.

Cyber Physical System Modelling of Distribution Power Systems for Dynamic Demand Response

Science.gov (United States)

Chu, Xiaodong; Zhang, Rongxiang; Tang, Maosen; Huang, Haoyi; Zhang, Lei

2018-01-01

Dynamic demand response (DDR) is a package of control methods to enhance power system security. A CPS modelling and simulation platform for DDR in distribution power systems is presented in this paper. CPS modelling requirements of distribution power systems are analyzed. A coupled CPS modelling platform is built for assessing DDR in the distribution power system, which combines seamlessly modelling tools of physical power networks and cyber communication networks. Simulations results of IEEE 13-node test system demonstrate the effectiveness of the modelling and simulation platform.

Study of forecasting maximum demand of electric power

Energy Technology Data Exchange (ETDEWEB)

Yoo, B.C.; Hwang, Y.J. [Korea Energy Economics Institute, Euiwang (Korea, Republic of)

1997-08-01

As far as the past performances of power supply and demand in Korea is concerned, one of the striking phenomena is that there have been repeated periodic surpluses and shortages of power generation facilities. Precise assumption and prediction of power demands is the basic work in establishing a supply plan and carrying out the right policy since facilities investment of the power generation industry requires a tremendous amount of capital and a long construction period. The purpose of this study is to study a model for the inference and prediction of a more precise maximum demand under these backgrounds. The non-parametric model considered in this study, paying attention to meteorological factors such as temperature and humidity, does not have a simple proportionate relationship with the maximum power demand, but affects it through mutual complicated nonlinear interaction. I used the non-parametric inference technique by introducing meteorological effects without importing any literal assumption on the interaction of temperature and humidity preliminarily. According to the analysis result, it is found that the non-parametric model that introduces the number of tropical nights which shows the continuity of the meteorological effect has better prediction power than the linear model. The non- parametric model that considers both the number of tropical nights and the number of cooling days at the same time is a model for predicting maximum demand. 7 refs., 6 figs., 9 tabs.

Ad Hoc on-Demand Distance Vector (AODV Routing Protocol Performance Evaluation on Hybrid Ad Hoc Network: Comparison of Result of Ns-2 Simulation and Implementation on Testbed using PDA

Directory of Open Access Journals (Sweden)

Riri Sari

2010-10-01

Full Text Available In Mobile Ad hoc NETwork (MANET, node supplemented with wireless equipment has the capacity to manage and organise autonomously, without the presence of network infrastructures. Hybrid ad hoc network, enable several nodes to move freely (mobile to create instant communication. Independent from infrastructure. They could access the Local Area Network (LAN or the Internet. Functionalities of ad hoc network very much dependent on the routing protocol that determines the routing around node. Ad hoc On-demand Distance Vector (AODV is one of routing protocols in ad hoc network which has a reactive characteristic. This protocol is the most common protocol being researched and used. In this Research, AODV protocol investigation was conducted by developing a testbed using Personal Computer, several Laptops (the Linux Red Hat operation system 9.0 and Fedora Core 2, and Personal Digital Assistant (PDA. This research also made a complete package by mean of cross compilation for PDA iPAQ. In general, results obtained from the simulation of AODV protocol using Network Simulator NS-2 are packet delivery ratio 99.89%, end-to-end delay of 0.14 seconds and routing overhead of 1,756.61 byte per second. Afterwards results from simulation were compared to results from testbed. Results obtained from testbed are as follows: the packet delivery ratio is 99.57%, the end-to-end delay is 1.004 seconds and the routing overhead is 1,360.36 byte per second.

OpenFlow Switching Performance using Network Simulator - 3

OpenAIRE

Sriram Prashanth, Naguru

2016-01-01

Context. In the present network inventive world, there is a quick expansion of switches and protocols, which are used to cope up with the increase in customer requirement in the networking. With increasing demand for higher bandwidths and lower latency and to meet these requirements new network paths are introduced. To reduce network load in present switching network, development of new innovative switching is required. These required results can be achieved by Software Define Network or Trad...

Reliability-Based Marginal Cost Pricing Problem Case with Both Demand Uncertainty and Travelers’ Perception Errors

Directory of Open Access Journals (Sweden)

Shaopeng Zhong

2013-01-01

Full Text Available Focusing on the first-best marginal cost pricing (MCP in a stochastic network with both travel demand uncertainty and stochastic perception errors within the travelers’ route choice decision processes, this paper develops a perceived risk-based stochastic network marginal cost pricing (PRSN-MCP model. Numerical examples based on an integrated method combining the moment analysis approach, the fitting distribution method, and the reliability measures are also provided to demonstrate the importance and properties of the proposed model. The main finding is that ignoring the effect of travel time reliability and travelers’ perception errors may significantly reduce the performance of the first-best MCP tolls, especially under high travelers’ confidence and network congestion levels. The analysis result could also enhance our understanding of (1 the effect of stochastic perception error (SPE on the perceived travel time distribution and the components of road toll; (2 the effect of road toll on the actual travel time distribution and its reliability measures; (3 the effect of road toll on the total network travel time distribution and its statistics; and (4 the effect of travel demand level and the value of reliability (VoR level on the components of road toll.

Cyber Insurance for Heterogeneous Wireless Networks

OpenAIRE

Lu, Xiao; Niyato, Dusit; Jiang, Hai; Wang, Ping; Poor, H. Vincent

2017-01-01

Heterogeneous wireless networks (HWNs) composed of densely deployed base stations of different types with various radio access technologies have become a prevailing trend to accommodate ever-increasing traffic demand in enormous volume. Nowadays, users rely heavily on HWNs for ubiquitous network access that contains valuable and critical information such as financial transactions, e-health, and public safety. Cyber risks, representing one of the most significant threats to network security an...

Satellite provided customer premise services: A forecast of potential domestic demand through the year 2000. Volume 2: Technical report

Science.gov (United States)

Kratochvil, D.; Bowyer, J.; Bhushan, C.; Steinnagel, K.; Al-Kinani, G.

1983-08-01

The potential United States domestic telecommunications demand for satellite provided customer premises voice, data and video services through the year 2000 were forecast, so that this information on service demand would be available to aid in NASA program planning. To accomplish this overall purpose the following objectives were achieved: development of a forecast of the total domestic telecommunications demand, identification of that portion of the telecommunications demand suitable for transmission by satellite systems, identification of that portion of the satellite market addressable by Computer premises services systems, identification of that portion of the satellite market addressabble by Ka-band CPS system, and postulation of a Ka-band CPS network on a nationwide and local level. The approach employed included the use of a variety of forecasting models, a market distribution model and a network optimization model. Forecasts were developed for; 1980, 1990, and 2000; voice, data and video services; terrestrial and satellite delivery modes; and C, Ku and Ka-bands.

Hybrid Multicast-Unicast Video Streaming over Heterogeneous Cellular Networks

OpenAIRE

Almowuena, Saleh Abdullah

2016-01-01

The demand for multimedia streaming over mobile networks has been steadily increasing in the past several years. For instance, it has become common for mobile users to stream full TV episodes, sports events, and movies while on the go. Unfortunately, this growth in demand has strained the wireless networks despite the significant increase in their capacities with recent generations. It has also caused a significant increase in the energy consumption at mobile terminals. To overcome these chal...

Inclusion of tank configurations as a variable in the cost optimization of branched piped-water networks

Science.gov (United States)

Hooda, Nikhil; Damani, Om

2017-06-01

The classic problem of the capital cost optimization of branched piped networks consists of choosing pipe diameters for each pipe in the network from a discrete set of commercially available pipe diameters. Each pipe in the network can consist of multiple segments of differing diameters. Water networks also consist of intermediate tanks that act as buffers between incoming flow from the primary source and the outgoing flow to the demand nodes. The network from the primary source to the tanks is called the primary network, and the network from the tanks to the demand nodes is called the secondary network. During the design stage, the primary and secondary networks are optimized separately, with the tanks acting as demand nodes for the primary network. Typically the choice of tank locations, their elevations, and the set of demand nodes to be served by different tanks is manually made in an ad hoc fashion before any optimization is done. It is desirable therefore to include this tank configuration choice in the cost optimization process itself. In this work, we explain why the choice of tank configuration is important to the design of a network and describe an integer linear program model that integrates the tank configuration to the standard pipe diameter selection problem. In order to aid the designers of piped-water networks, the improved cost optimization formulation is incorporated into our existing network design system called JalTantra.

Carry

DEFF Research Database (Denmark)

Koijen, Ralph S.J.; Moskowitz, Tobias; Pedersen, Lasse Heje

2018-01-01

-sectionally and in time series for a host of different asset classes, including global equities, global bonds, commodities, US Treasuries, credit, and options. Carry is not explained by known predictors of returns from these asset classes, and it captures many of these predictors, providing a unifying framework...... for return predictability. We reject a generalized version of Uncovered Interest Parity and the Expectations Hypothesis in favor of models with varying risk premia, in which carry strategies are commonly exposed to global recession, liquidity, and volatility risks, though none fully explains carry’s premium....

Networking - concepts and dimensions of the cross-cultural comparative study

DEFF Research Database (Denmark)

Rasmussen, Lauge Baungaard

2000-01-01

The litarature about networking is weak regarding precise definitions of networking and methodologies to analyse how networking is carried out in practice. Besides, the croos cultural dimension is often underestimated.......The litarature about networking is weak regarding precise definitions of networking and methodologies to analyse how networking is carried out in practice. Besides, the croos cultural dimension is often underestimated....

A novel machine learning approach for estimation of electricity demand: An empirical evidence from Thailand

International Nuclear Information System (INIS)

Mostafavi, Elham Sadat; Mostafavi, Seyyed Iman; Jaafari, Arefeh; Hosseinpour, Fariba

2013-01-01

Highlights: • A hybrid approach is presented for the estimation of the electricity demand. • The proposed method integrates the capabilities of GP and SA. • The GSA model makes accurate predictions of the electricity demand. - Abstract: This study proposes an innovative hybrid approach for the estimation of the long-term electricity demand. A new prediction equation was developed for the electricity demand using an integrated search method of genetic programming and simulated annealing, called GSA. The annual electricity demand was formulated in terms of population, gross domestic product (GDP), stock index, and total revenue from exporting industrial products of the same year. A comprehensive database containing total electricity demand in Thailand from 1986 to 2009 was used to develop the model. The generalization of the model was verified using a separate testing data. A sensitivity analysis was conducted to investigate the contribution of the parameters affecting the electricity demand. The GSA model provides accurate predictions of the electricity demand. Furthermore, the proposed model outperforms a regression and artificial neural network-based models

Efficient Networks Communication Routing Using Swarm Intelligence

OpenAIRE

Koushal Kumar

2012-01-01

As demonstrated by natural biological swarm’s collective intelligence has an abundance of desirable properties for problem-solving like in network routing. The focus of this paper is in the applications of swarm based intelligence in information routing for communication networks. As we know networks are growing and adopting new platforms as new technologies comes. Also according to new demands and requirements networks topologies and its complexity is increasing with time. Thus it is becomin...

Machine Perfusion of Porcine Livers with Oxygen-Carrying Solution Results in Reprogramming of Dynamic Inflammation Networks

Directory of Open Access Journals (Sweden)

David Sadowsky

2016-11-01

Full Text Available Background: Ex vivo machine perfusion (MP can better preserve organs for transplantation. We have recently reported on the first application of a MP protocol in which liver allografts were fully oxygenated, under dual pressures and subnormothermic conditions, with a new hemoglobin-based oxygen carrier solution specifically developed for ex vivo utilization. In those studies, MP improved organ function post-operatively and reduced inflammation in porcine livers. Herein, we sought to refine our knowledge regarding the impact of MP by defining dynamic networks of inflammation in both tissue and perfusate. Methods: Porcine liver allografts were preserved either with MP (n = 6 or with cold static preservation (CSP; n = 6, then transplanted orthotopically after 9 h of preservation. Fourteen inflammatory mediators were measured in both tissue and perfusate during liver preservation at multiple time points, and analyzed using Dynamic Bayesian Network (DyBN inference to define feedback interactions, as well as Dynamic Network Analysis (DyNA to define the time-dependent development of inflammation networks.Results: Network analyses of tissue and perfusate suggested an NLRP3 inflammasome-regulated response in both treatment groups, driven by the pro-inflammatory cytokine interleukin (IL-18 and the anti-inflammatory mediator IL-1 receptor antagonist (IL-1RA. Both DyBN and DyNA suggested a reduced role of IL-18 and increased role of IL-1RA with MP, along with increased liver damage with CSP. DyNA also suggested divergent progression of responses over the 9 h preservation time, with CSP leading to a stable pattern of IL-18-induced liver damage and MP leading to a resolution of the pro-inflammatory response. These results were consistent with prior clinical, biochemical, and histological findings after liver transplantation. Conclusion: Our results suggest that analysis of dynamic inflammation networks in the setting of liver preservation may identify novel

Optimal supply and demand investments in municipal energy systems

International Nuclear Information System (INIS)

Rolfsman, Bjoern

2004-01-01

In many municipalities, there are district heating networks, which are quite commonly supplied by combined heat and power plants (CHP). A district heating network contains buildings of different types. In this paper, one such municipal energy system is analysed. In order to provide space heating and domestic hot water, investments could be made on the supply side in power plants, or on the demand side in the buildings, for example in the form of extra wall insulation. The electricity from the CHP plants is supplied to the municipality but can also be sold to the electricity market, and electricity can, of course, also be bought from the market. The variation in price on the spot market over any given day is significant. The need for district heat in the building stock also varies, for example due to climatic conditions. The energy system in the case study is analysed with a mixed integer linear programming model. The model has 3 h time steps in order to reflect diurnal variations, and an entire year is analysed. A case study is presented for the city of Linkoeping in Sweden. On the demand side, the options are: extra wall insulation, extra attic insulation and better types of windows. The building stock is divided into nine categories

Resilience of Networked Infrastructure with Evolving Component Conditions: Pavement Network Application

DEFF Research Database (Denmark)

Levenberg, Eyal; Miller-Hooks, Elise; Asadabadi, Ali

2017-01-01

This paper deals with quantifying the resilience of a network of pavements. Calculations were carried out by modeling network performance under a set of possible damage-meteorological scenarios with known probability of occurrence. Resilience evaluation was performed a priori while accounting...

Aggregated Demand Modelling Including Distributed Generation, Storage and Demand Response

OpenAIRE

Marzooghi, Hesamoddin; Hill, David J.; Verbic, Gregor

2014-01-01

It is anticipated that penetration of renewable energy sources (RESs) in power systems will increase further in the next decades mainly due to environmental issues. In the long term of several decades, which we refer to in terms of the future grid (FG), balancing between supply and demand will become dependent on demand actions including demand response (DR) and energy storage. So far, FG feasibility studies have not considered these new demand-side developments for modelling future demand. I...

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...

Improving Network Performance with Affinity based Mobility Model in Opportunistic Network

OpenAIRE

Suvadip Batabyal; Parama Bhaumik

2012-01-01

Opportunistic network is a type of Delay Tolerant Network which is characterized by intermittent connectivity amongst the nodes and communication largely depends upon the mobility of the participating nodes. The network being highly dynamic, traditional MANET protocols cannot be applied and the nodes must adhere to store-carry-forward mechanism. Nodes do not have the information about the network topology, number of participating nodes and the location of the destination node. Hence, message ...

Technical-tactical and physiological demands of wrestling combats

OpenAIRE

Bianka Miarka

2016-01-01

Technical-tactical and physiological demand analyses of wrestling combats are important because they reveal essential information for the development of contextual training and specific physical preparation of wrestlers. Therefore, the aim of this review is to describe the characteristics of wrestling combats in freestyle, female and Greco-roman styles. The time-motion analysis presented in this article is the main component to carry out inferences on intensity and effort: pause ratio of comb...

An Auto Tuning Substation Peak Shaving Controller for Congestion Management Using Flexible Demand

DEFF Research Database (Denmark)

Sossan, Fabrizio; Marinelli, Mattia

2013-01-01

A closed loop substation peak shaving/congestion management controller for radial distribution networks is presented. The controller it uses an individual control signal in order to shift the consumption of a population of demand side resources, DSRs. The controller auto tunes its parameters on...

On-Demand Routing in Multi-hop Wireless Mobile Ad Hoc Networks

National Research Council Canada - National Science Library

Maltz, David A

2001-01-01

.... Routing protocols used in ad hoc networks must automatically adjust to environments that can vary between the extremes of high mobility with low bandwidth, and low mobility with high bandwidth...

A hybrid optical switch architecture to integrate IP into optical networks to provide flexible and intelligent bandwidth on demand for cloud computing

Science.gov (United States)

Yang, Wei; Hall, Trevor J.

2013-12-01

The Internet is entering an era of cloud computing to provide more cost effective, eco-friendly and reliable services to consumer and business users. As a consequence, the nature of the Internet traffic has been fundamentally transformed from a pure packet-based pattern to today's predominantly flow-based pattern. Cloud computing has also brought about an unprecedented growth in the Internet traffic. In this paper, a hybrid optical switch architecture is presented to deal with the flow-based Internet traffic, aiming to offer flexible and intelligent bandwidth on demand to improve fiber capacity utilization. The hybrid optical switch is capable of integrating IP into optical networks for cloud-based traffic with predictable performance, for which the delay performance of the electronic module in the hybrid optical switch architecture is evaluated through simulation.

Demand modelling for central heating systems

Energy Technology Data Exchange (ETDEWEB)

Heller, A.

2000-07-01

Most researchers in the field of heat demand estimation have focussed on explaning the load for a given plant based on rather few measurements. This approach is simply the only one adaptable with the very limited data material and limited computer power. This way of dealing with the subject is here called the top-down approach, due to the fact that one tries to explain the load from the overall data. The results of such efforts are discussed in the report, leading to inspiration for own work. Also the significance of the findings to the causes for given heat loads are discussed and summarised. Contrary to the top-down approach applied in literature, a here-called bottom-up approach is applied in this work, describing the causes of a given partial load in detail and combining them to explain the total load for the system. Three partial load 'components' are discussed: 1) Space heating. 2) Hot-Water Consumption. 3) Heat losses in pipe networks. The report is aimed at giving an introduction to these subjects, but at the same time at collecting the previous work done by the author. Space heating is shortly discussed and loads are generated by an advanced simulation model. A hot water consumption model is presented and heat loads, generated by this model, utilised in the overall work. Heat loads due to heat losses in district heating a given a high priority in the current work. Hence a detailed presentation and overview of the subject is given to solar heating experts normally not dealing with district heating. Based on the 'partial' loads generated by the above-mentioned method, an overall load model is built in the computer simulation environment TRNSYS. The final tool is then employed for the generation of time series for heat demand, representing a district heating area. The results are compared to alternative methods for the generation of heat demand profiles. Results form this comparison will be presented. Computerised modelling of systems

the structure of labour market and demand for hired labour for oil

African Journals Online (AJOL)

DEPT OF AGRICULTURAL ENGINEERING

Keywords: structure of labour, hired labour, oil palm production, demand ... age and sex of labour or employment status (i.e. ..... Work which by its nature or circumstances in which it is carried out is likely to harm the health, safety or morals of.

Cross-layer design in optical networks

CERN Document Server

Brandt-Pearce, Maïté; Demeester, Piet; Saradhi, Chava

2013-01-01

Optical networks have become an integral part of the communications infrastructure needed to support society’s demand for high-speed connectivity.  Cross-Layer Design in Optical Networks addresses topics in optical network design and analysis with a focus on physical-layer impairment awareness and network layer service requirements, essential for the implementation and management of robust scalable networks.  The cross-layer treatment includes bottom-up impacts of the physical and lambda layers, such as dispersion, noise, nonlinearity, crosstalk, dense wavelength packing, and wavelength line rates, as well as top-down approaches to handle physical-layer impairments and service requirements.

Emotional adjustment and distressed interpersonal relations among low-income African American mothers: moderating effects of demanding kin relations.

Science.gov (United States)

Taylor, Ronald D; Budescu, Mia

2013-01-01

Association of mothers' emotional adjustment and negative kin relations with distressed interpersonal relations was examined. Among 115 low-income African American mothers, relationship of depressive symptoms, self-esteem, and demanding kin relations with psychological control and stressful interpersonal relations was assessed. Depressive symptoms and demanding kin relations were positively associated with mothers' use of psychological control in parenting. Interaction of self-esteem with demanding kin relations revealed that self-esteem was negatively associated with psychological control for mothers with high-demanding kin relations but not for mothers with low-demanding kin relations. Mothers' depressive symptoms and demanding kin relations were positively associated with their stressful interpersonal relations. Findings were discussed in terms of the need for research on the beneficial and detrimental aspects of families' social network.

Bribery games on interdependent complex networks.

Science.gov (United States)

Verma, Prateek; Nandi, Anjan K; Sengupta, Supratim

2018-08-07

Bribe demands present a social conflict scenario where decisions have wide-ranging economic and ethical consequences. Nevertheless, such incidents occur daily in many countries across the globe. Harassment bribery constitute a significant sub-set of such bribery incidents where a government official demands a bribe for providing a service to a citizen legally entitled to it. We employ an evolutionary game-theoretic framework to analyse the evolution of corrupt and honest strategies in structured populations characterized by an interdependent complex network. The effects of changing network topology, average number of links and asymmetry in size of the citizen and officer population on the proliferation of incidents of bribery are explored. A complex network topology is found to be beneficial for the dominance of corrupt strategies over a larger region of phase space when compared with the outcome for a regular network, for equal citizen and officer population sizes. However, the extent of the advantage depends critically on the network degree and topology. A different trend is observed when there is a difference between the citizen and officer population sizes. Under those circumstances, increasing randomness of the underlying citizen network can be beneficial to the fixation of honest officers up to a certain value of the network degree. Our analysis reveals how the interplay between network topology, connectivity and strategy update rules can affect population level outcomes in such asymmetric games. Copyright © 2018 Elsevier Ltd. All rights reserved.

Default network modulation and large-scale network interactivity in healthy young and old adults.

Science.gov (United States)

Spreng, R Nathan; Schacter, Daniel L

2012-11-01

We investigated age-related changes in default, attention, and control network activity and their interactions in young and old adults. Brain activity during autobiographical and visuospatial planning was assessed using multivariate analysis and with intrinsic connectivity networks as regions of interest. In both groups, autobiographical planning engaged the default network while visuospatial planning engaged the attention network, consistent with a competition between the domains of internalized and externalized cognition. The control network was engaged for both planning tasks. In young subjects, the control network coupled with the default network during autobiographical planning and with the attention network during visuospatial planning. In old subjects, default-to-control network coupling was observed during both planning tasks, and old adults failed to deactivate the default network during visuospatial planning. This failure is not indicative of default network dysfunction per se, evidenced by default network engagement during autobiographical planning. Rather, a failure to modulate the default network in old adults is indicative of a lower degree of flexible network interactivity and reduced dynamic range of network modulation to changing task demands.

Assessing the benefits of residential demand response in a real time distribution energy market

International Nuclear Information System (INIS)

Siano, Pierluigi; Sarno, Debora

2016-01-01

Highlights: • A new probabilistic methodology, integrating DR in a distribution energy market is proposed. • The method can alleviate distribution network congestions. • This method based on D-LMPs allows cost savings for end-user customers. • Innovative thermal and shiftable loads Real Time control algorithms are also presented. - Abstract: In the field of electricity distribution networks and with the advent of smart grids and microgrids, the use of Distribution Locational Marginal Price (D-LMPs) in a Real Time (RT) distribution market managed by a Distribution System Operator (DSO) is discussed in presence of empowered residential end-users that are able to bid for energy by a demand aggregator while following Demand Response (DR) initiatives. Each customer is provided by a transactive controller, which reads the locational market signals and answers with a bid taking into account the user preferences about some appliances involved in DR activities and controlled by smart plugs-in. In particular, Heating Ventilation and Air Conditioning (HVAC) appliances and shiftable loads are controlled so that their consumption profile can be modified according to the price of energy. In order to assess the effectiveness of the proposed method in terms of energy and cost saving, an innovative probabilistic methodology for evaluating the impact of residential DR choices considering uncertainties related to load demand, user preferences, environmental conditions, house thermal behavior and wholesale market trends has been proposed. The uncertainties related to the stochastic variations of the variables involved are modeled by using the Monte Carlo Simulation (MCS) method. The combination of MCS and RT distribution market simulation based on D-LMPs are used to assess the operation and impact of the DR method over one month. Simulations results on an 84-buses distribution network confirmed that the proposed method allows saving costs for residential end-users and making

A multivariate time series approach to modeling and forecasting demand in the emergency department.

Science.gov (United States)

Jones, Spencer S; Evans, R Scott; Allen, Todd L; Thomas, Alun; Haug, Peter J; Welch, Shari J; Snow, Gregory L

2009-02-01

The goals of this investigation were to study the temporal relationships between the demands for key resources in the emergency department (ED) and the inpatient hospital, and to develop multivariate forecasting models. Hourly data were collected from three diverse hospitals for the year 2006. Descriptive analysis and model fitting were carried out using graphical and multivariate time series methods. Multivariate models were compared to a univariate benchmark model in terms of their ability to provide out-of-sample forecasts of ED census and the demands for diagnostic resources. Descriptive analyses revealed little temporal interaction between the demand for inpatient resources and the demand for ED resources at the facilities considered. Multivariate models provided more accurate forecasts of ED census and of the demands for diagnostic resources. Our results suggest that multivariate time series models can be used to reliably forecast ED patient census; however, forecasts of the demands for diagnostic resources were not sufficiently reliable to be useful in the clinical setting.

Tissue oxygen demand in regulation of the behavior of the cells in the vasculature.

Science.gov (United States)

Barvitenko, Nadezhda N; Aslam, Muhammad; Filosa, Jessica; Matteucci, Elena; Nikinmaa, Mikko; Pantaleo, Antonella; Saldanha, Carlota; Baskurt, Oguz K

2013-08-01

The control of arteriolar diameters in microvasculature has been in the focus of studies on mechanisms matching oxygen demand and supply at the tissue level. Functionally, important vascular elements include EC, VSMC, and RBC. Integration of these different cell types into functional units aimed at matching tissue oxygen supply with tissue oxygen demand is only achieved when all these cells can respond to the signals of tissue oxygen demand. Many vasoactive agents that serve as signals of tissue oxygen demand have their receptors on all these types of cells (VSMC, EC, and RBC) implying that there can be a coordinated regulation of their behavior by the tissue oxygen demand. Such functions of RBC as oxygen carrying by Hb, rheology, and release of vasoactive agents are considered. Several common extra- and intracellular signaling pathways that link tissue oxygen demand with control of VSMC contractility, EC permeability, and RBC functioning are discussed. © 2013 John Wiley & Sons Ltd.

Cross Layer Optimization and Simulation of Smart Grid Home Area Network

Directory of Open Access Journals (Sweden)

Lipi K. Chhaya

2018-01-01

Full Text Available An electrical “Grid” is a network that carries electricity from power plants to customer premises. Smart Grid is an assimilation of electrical and communication infrastructure. Smart Grid is characterized by bidirectional flow of electricity and information. Smart Grid is a complex network with hierarchical architecture. Realization of complete Smart Grid architecture necessitates diverse set of communication standards and protocols. Communication network protocols are engineered and established on the basis of layered approach. Each layer is designed to produce an explicit functionality in association with other layers. Layered approach can be modified with cross layer approach for performance enhancement. Complex and heterogeneous architecture of Smart Grid demands a deviation from primitive approach and reworking of an innovative approach. This paper describes a joint or cross layer optimization of Smart Grid home/building area network based on IEEE 802.11 standard using RIVERBED OPNET network design and simulation tool. The network performance can be improved by selecting various parameters pertaining to different layers. Simulation results are obtained for various parameters such as WLAN throughput, delay, media access delay, and retransmission attempts. The graphical results show that various parameters have divergent effects on network performance. For example, frame aggregation decreases overall delay but the network throughput is also reduced. To prevail over this effect, frame aggregation is used in combination with RTS and fragmentation mechanisms. The results show that this combination notably improves network performance. Higher value of buffer size considerably increases throughput but the delay is also greater and thus the choice of optimum value of buffer size is inevitable for network performance optimization. Parameter optimization significantly enhances the performance of a designed network. This paper is expected to serve

DEMAND FOR POT PLANTS FOR INTERIOR DECORATION IN VIEW OF THE SURVEY CARRIED OUT IN POZNAŃ

Directory of Open Access Journals (Sweden)

Monika Henschke

2013-12-01

Full Text Available The aim of the study was to determine the demand for pot plants for interior decoration at various points of sale in Poznan. The results were based on questionnaires filled by clients of three retail sale points with pot plants: flower shop, horticultural centre and building material market in Poznan and its surroundings. Collected information was analysed for a frequency of purchases, amount of money spent on pot plants, place of purchases, occasions for which plant was bought, preferences of buyers and pattern of purchases. Customers purchase plants in various points of sale from 7 to 9 pot plants per year, mostly in horticultural centres and in spring. Plants are used for interior decoration and are cultivated for many years, however cut flowers are more often chosen for a gift than pot plants. Whereas a significant part of building material market customers cultivate flowers pot plants for a short time, and they buy pot plants for a gift as often as cut flowers. Among plants with flowers Phalaenopsis and Anthurium are selected most frequently, and Zamioculcas and Yucca among plants with decorative foliage. While choosing plants, buyers are guided by the overall appearance and price.

Application of Thermal Network Model to Transient Thermal Analysis of Power Electronic Package Substrate

Directory of Open Access Journals (Sweden)

Masaru Ishizuka

2011-01-01

Full Text Available In recent years, there is a growing demand to have smaller and lighter electronic circuits which have greater complexity, multifunctionality, and reliability. High-density multichip packaging technology has been used in order to meet these requirements. The higher the density scale is, the larger the power dissipation per unit area becomes. Therefore, in the designing process, it has become very important to carry out the thermal analysis. However, the heat transport model in multichip modules is very complex, and its treatment is tedious and time consuming. This paper describes an application of the thermal network method to the transient thermal analysis of multichip modules and proposes a simple model for the thermal analysis of multichip modules as a preliminary thermal design tool. On the basis of the result of transient thermal analysis, the validity of the thermal network method and the simple thermal analysis model is confirmed.

Considering supply and demand of electric energy in life cycle assessments - a review of current methodologies

International Nuclear Information System (INIS)

Rehberger, M.; Hiete, M.

2015-01-01

A stable power grid requires a balance between electricity supply and demand. To compensate for changes in the demand the network operator puts on or takes off power plants from the net. Peak load plants operate only at times of high electricity demand. As levels for air pollutants emissions are typically lower for peak load plants for reasons of cost-effectiveness, one could argue that a unit of electric energy consumed during peak load has always been associated with a higher environmental impact than at other times. Furthermore, renewable energy technologies, smart approaches for improving the matching between electricity consumption and supply and new products such as electric vehicles or net zero emission buildings gain in importance. In life cycle assessment (LCA) environmental impacts associated with the production and possibly transmission of electricity are most often assessed based on temporally averaged national electricity mixes as electricity flows cannot be traced back to their origin. Neither fluctuations in the supply structure nor the composition of energy supply at a certain moment or regional differences are accounted for. A literature review of approaches for handling electricity in LCA is carried out to compare strengths and weaknesses of the approaches. A better understanding and knowledge about the source of electricity at a given time and place might be valuable information for further reducing environmental impacts, e.g. by shifting electricity consumption to times with ample supply of renewables. Integrating such information into LCA will allow a fairer assessment of a variety of new products which accept a lower energy efficiency to achieve a better integration of renewables into the grid. (authors)

Robust Power Supply Restoration for Self-Healing Active Distribution Networks Considering the Availability of Distributed Generation

Directory of Open Access Journals (Sweden)

Qiang Yang

2018-01-01

Full Text Available The increasing penetration of distributed generations (DGs with intermittent and stochastic characteristics into current power distribution networks can lead to increased fault levels and degradation in network protection. As one of the key requirements of active network management (ANM, efficient power supply restoration solution to guarantee network self-healing capability with full consideration of DG uncertainties is demanded. This paper presents a joint power supply restoration through combining the DG local restoration and switcher operation-based restoration to enhance the self-healing capability in active distribution networks considering the availability of distributed generation. The restoration algorithmic solution is designed to be able to carry out power restoration in parallel upon multiple simultaneous faults to maximize the load restoration while additionally minimizing power loss, topology variation and power flow changes due to switcher operations. The performance of the proposed solution is validated based on a 53-bus distribution network with wind power generators through extensive simulation experiments for a range of fault cases and DG scenarios generated based on Heuristic Moment Matching (HMM method to fully consider the DG randomness. The numerical result in comparison with the existing solutions demonstrates the effectiveness of the proposed power supply restoration solution.

Modelling Commodity Demands and Labour Supply with m-Demands

OpenAIRE

Browning, Martin

1999-01-01

In the empirical modelling of demands and labour supply we often lack data on a full set of goods. The usual response is to invoke separability assumptions. Here we present an alternative based on modelling demands as a function of prices and the quantity of a reference good rather than total expenditure. We term such demands m-demands. The advantage of this approach is that we make maximum use of the data to hand without invoking implausible separability assumptions. In the theory section qu...

Transmission design in a multimode HFC network

Science.gov (United States)

Cambron, G. Keith

1996-11-01

Contemporary hybrid fiber coaxial (HFC) networks are capable of supporting a wide range of services including traditional analog video, telephony, digital video, and data services. Each service has unique performance or service requirements. This contribution examines transmission design for one such network. Pacific Bell's advanced communications network (ACN). The design methodology begins with a set of end to end service quality objectives. Network impairments, such as noise, distortion and delay, are allocated across the network elements using a set of standard network models. These models are a representative set of the actual field designs and bound the network operating parameters. Network components, headend equipment, and customer premises equipment are specified analytically or characterized empirically in relationship to the chosen impairment set. The component parameters are then included in analytical models to estimate overall network performance. In addition to the forward path transmission considerations examined by traditional coaxial network designers, other dimensions including power consumption, traffic demand, and message latency are taken into account. Analytical models are used to estimate the effects of multiple modulation schemes within the unified network. The variability introduced by on demand services such as telephony and interactive digital services changes the base computational domain from deterministic models to stochastic ones. These models are then used to set operating parameters at measurable points throughout the network for proof of performance prior to turn up, and for ongoing performance monitoring. For closure, empirical results are compared with model projections as a way of verifying and improving the predictive models.

A Framework for Understanding and Generating Integrated Solutions for Residential Peak Energy Demand

Science.gov (United States)

Buys, Laurie; Vine, Desley; Ledwich, Gerard; Bell, John; Mengersen, Kerrie; Morris, Peter; Lewis, Jim

2015-01-01

Supplying peak energy demand in a cost effective, reliable manner is a critical focus for utilities internationally. Successfully addressing peak energy concerns requires understanding of all the factors that affect electricity demand especially at peak times. This paper is based on past attempts of proposing models designed to aid our understanding of the influences on residential peak energy demand in a systematic and comprehensive way. Our model has been developed through a group model building process as a systems framework of the problem situation to model the complexity within and between systems and indicate how changes in one element might flow on to others. It is comprised of themes (social, technical and change management options) networked together in a way that captures their influence and association with each other and also their influence, association and impact on appliance usage and residential peak energy demand. The real value of the model is in creating awareness, understanding and insight into the complexity of residential peak energy demand and in working with this complexity to identify and integrate the social, technical and change management option themes and their impact on appliance usage and residential energy demand at peak times. PMID:25807384

Unidirectional variable stiffness hydraulic actuator for load-carrying knee exoskeleton

Directory of Open Access Journals (Sweden)

Jun Zhu

2017-01-01

Full Text Available This article presents the design and experimental testing of a unidirectional variable stiffness hydraulic actuator for load-carrying knee exoskeleton. The proposed actuator is designed for mimicking the high-efficiency passive behavior of biological knee and providing actively assistance in locomotion. The adjustable passive compliance of exoskeletal knee is achieved through a variable ratio lever mechanism with linear elastic element. A compact customized electrohydraulic system is also designed to accommodate application demands. Preliminary experimental results show the prototype has good performances in terms of stiffness regulation and joint torque control. The actuator is also implemented in an exoskeleton knee joint, resulting in anticipant human-like passive compliance behavior.

Evaluation of the electric vehicle impact in the power demand curve in a smart grid environment

International Nuclear Information System (INIS)

Morais, Hugo; Sousa, Tiago; Vale, Zita; Faria, Pedro

2014-01-01

Highlights: • Multi-objective optimization of operation costs and load factor. • Contribution of electric vehicles to load diagram leveling. • Use of epigraph variables to transform non-convex functions in convex ones. • Evaluation of the obtained results considering different EVs penetration. - Abstract: Smart grids with an intensive penetration of distributed energy resources will play an important role in future power system scenarios. The intermittent nature of renewable energy sources brings new challenges, requiring an efficient management of those sources. Additional storage resources can be beneficially used to address this problem; the massive use of electric vehicles, particularly of vehicle-to-grid (usually referred as gridable vehicles or V2G), becomes a very relevant issue. This paper addresses the impact of Electric Vehicles (EVs) in system operation costs and in power demand curve for a distribution network with large penetration of Distributed Generation (DG) units. An efficient management methodology for EVs charging and discharging is proposed, considering a multi-objective optimization problem. The main goals of the proposed methodology are: to minimize the system operation costs and to minimize the difference between the minimum and maximum system demand (leveling the power demand curve). The proposed methodology perform the day-ahead scheduling of distributed energy resources in a distribution network with high penetration of DG and a large number of electric vehicles. It is used a 32-bus distribution network in the case study section considering different scenarios of EVs penetration to analyze their impact in the network and in the other energy resources management

Modelling the structure of complex networks

DEFF Research Database (Denmark)

Herlau, Tue