A Survey on Demand Response Programs in Smart Grids: Pricing Methods and Optimization Algorithms

The smart grid concept continues to evolve and various methods have been developed to enhance the energy efficiency of the electricity infrastructure. Demand Response (DR) is considered as the most cost-effective and reliable solution for the smoothing of the demand curve, when the system is under stress. DR refers to a procedure that is applied to motivate changes in the customers' power consumption habits, in response to incentives regarding the electricity prices. In this paper, we provide a comprehensive review of various DR schemes and programs, based on the motivations offered to the consumers to participate in the program. We classify the proposed DR schemes according to their control mechanism, to the motivations offered to reduce the power consumption and to the DR decision variable. We also present various optimization models for the optimal control of the DR strategies that have been proposed so far. These models are also categorized, based on the target of the optimization procedure. The key aspects that should be considered in the optimization problem are the system's constraints and the computational complexity of the applied optimization algorithm.

[1]  Salman Mohagheghi,et al.  Intelligent demand response scheme for energy management of industrial systems , 2012, 2012 IEEE Industry Applications Society Annual Meeting.

[2]  Christoforos N. Hadjicostis,et al.  Distributed algorithms for control of demand response and distributed energy resources , 2011, IEEE Conference on Decision and Control and European Control Conference.

[3]  D. T. Nguyen,et al.  Pool-Based Demand Response Exchange—Concept and Modeling , 2011 .

[4]  Sachin S. Sapatnekar,et al.  Residential task scheduling under dynamic pricing using the multiple knapsack method , 2012, 2012 IEEE PES Innovative Smart Grid Technologies (ISGT).

[5]  Giuseppe Tommaso Costanzo,et al.  A System Architecture for Autonomous Demand Side Load Management in Smart Buildings , 2012, IEEE Transactions on Smart Grid.

[6]  Leandros Tassiulas,et al.  Optimal Control Policies for Power Demand Scheduling in the Smart Grid , 2012, IEEE Journal on Selected Areas in Communications.

[7]  S. Widergren,et al.  Real-time pricing demand response in operations , 2012, 2012 IEEE Power and Energy Society General Meeting.

[8]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[9]  Haiwang Zhong,et al.  Coupon incentive-based demand response (CIDR) in smart grid , 2012, 2012 IEEE Power and Energy Society General Meeting.

[10]  F. Wolak Residential Customer Response to Real-time Pricing: The Anaheim Critical Peak Pricing Experiment , 2007 .

[11]  Michael Devetsikiotis,et al.  Optimal Power Allocation Under Communication Network Externalities , 2012, IEEE Transactions on Smart Grid.

[12]  Na Li,et al.  Optimal demand response based on utility maximization in power networks , 2011, 2011 IEEE Power and Energy Society General Meeting.

[13]  H. Allcott,et al.  Real Time Pricing and Electricity Markets , 2009 .

[14]  Na Li,et al.  Two Market Models for Demand Response in Power Networks , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[15]  Sangtae Ha,et al.  Optimized Day-Ahead Pricing for Smart Grids with Device-Specific Scheduling Flexibility , 2012, IEEE Journal on Selected Areas in Communications.

[16]  Mohamed A. El-Sharkawi,et al.  Optimal Charging Strategies for Unidirectional Vehicle-to-Grid , 2011, IEEE Transactions on Smart Grid.

[17]  Amit Narayan,et al.  Simulating integrated volt/var control and distributed demand response using GridSpice , 2011, 2011 IEEE First International Workshop on Smart Grid Modeling and Simulation (SGMS).

[18]  Xiaoming Feng,et al.  Getting Smart , 2010, IEEE Power and Energy Magazine.

[19]  A. Yousefi,et al.  A probabilistic risk-based approach for spinning reserve provision using day-ahead demand response program , 2010 .

[20]  Salman Mohagheghi Communication services and data model for demand response , 2012, 2012 IEEE Online Conference on Green Communications (GreenCom).

[21]  J. Borwein,et al.  Convex Analysis And Nonlinear Optimization , 2000 .

[22]  Nirwan Ansari,et al.  The Progressive Smart Grid System from Both Power and Communications Aspects , 2012, IEEE Communications Surveys & Tutorials.

[23]  Xi Fang,et al.  Managing smart grid information in the cloud: opportunities, model, and applications , 2012, IEEE Network.

[24]  Iain MacGill,et al.  Coordinated Scheduling of Residential Distributed Energy Resources to Optimize Smart Home Energy Services , 2010, IEEE Transactions on Smart Grid.

[25]  Steven Braithwait Behavior Modification , 2010, IEEE Power and Energy Magazine.

[26]  Sila Kiliccote,et al.  Utilizing Automated Demand Response in commercial buildings as non-spinning reserve product for ancillary services markets , 2011, IEEE Conference on Decision and Control and European Control Conference.

[27]  Walid Saad,et al.  Economics of Electric Vehicle Charging: A Game Theoretic Approach , 2012, IEEE Transactions on Smart Grid.

[28]  Hanno Hildmann,et al.  Influence of variable supply and load flexibility on Demand-Side Management , 2011, 2011 8th International Conference on the European Energy Market (EEM).

[29]  Hunt Allcott,et al.  Real-Time Pricing and Electricity Market Design , 2012 .

[30]  Jamshid Aghaei,et al.  Multi-objective self-scheduling of CHP (combined heat and power)-based microgrids considering demand response programs and ESSs (energy storage systems) , 2013 .

[31]  Long He,et al.  Stochastic Control for Smart Grid Users With Flexible Demand , 2013, IEEE Transactions on Smart Grid.

[32]  Pedro Faria,et al.  Intelligent energy resource management considering vehicle-to-grid: A Simulated Annealing approach , 2012, 2012 IEEE Power and Energy Society General Meeting.

[33]  T. Bräunl,et al.  The technical, economic and commercial viability of the vehicle-to-grid concept , 2012 .

[34]  Manfred Morari,et al.  Predictive power dispatch through negotiated locational pricing , 2010, 2010 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe).

[35]  Martha Martins Carvalho,et al.  Demand response models with correlated price data: A robust optimization approach , 2012 .

[36]  Zhong Fan,et al.  Distributed demand response and user adaptation in smart grids , 2010, 12th IFIP/IEEE International Symposium on Integrated Network Management (IM 2011) and Workshops.

[37]  Le Xie,et al.  Coupon Incentive-Based Demand Response: Theory and Case Study , 2013, IEEE Transactions on Power Systems.

[38]  N. Hatziargyriou,et al.  Microgrids: an overview of ongoing research, development, anddemonstration projects , 2007 .

[39]  Alec Brooks,et al.  Demand Dispatch , 2010, IEEE Power and Energy Magazine.

[40]  Thillainathan Logenthiran,et al.  Demand Side Management in Smart Grid Using Heuristic Optimization , 2012, IEEE Transactions on Smart Grid.

[41]  Arye Nehorai,et al.  An Optimal and Distributed Demand Response Strategy With Electric Vehicles in the Smart Grid , 2014, IEEE Transactions on Smart Grid.

[42]  Vincent W. S. Wong,et al.  Optimal Real-Time Pricing Algorithm Based on Utility Maximization for Smart Grid , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[43]  Joel Mickey Using load resources to meet ancillary service requirements in the ERCOT market: A case study , 2010, IEEE PES General Meeting.

[44]  Jose Medina,et al.  Demand Response and Distribution Grid Operations: Opportunities and Challenges , 2010, IEEE Transactions on Smart Grid.

[45]  Ning Lu,et al.  Appliance Commitment for Household Load Scheduling , 2011, IEEE Transactions on Smart Grid.

[46]  Yu Zhang,et al.  Design Considerations of a Centralized Load Controller Using Thermostatically Controlled Appliances for Continuous Regulation Reserves , 2013, IEEE Transactions on Smart Grid.

[47]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[48]  Long Zhou,et al.  Artificial neural network for load forecasting in smart grid , 2010, 2010 International Conference on Machine Learning and Cybernetics.

[49]  Tho Le-Ngoc,et al.  Challenges and research opportunities in wireless communication networks for smart grid , 2013, IEEE Wireless Communications.

[50]  Pramode K. Verma,et al.  Predicting user comfort level using machine learning for Smart Grid environments , 2011, ISGT 2011.

[51]  James Won-Ki Hong,et al.  Near optimal demand-side energy management under real-time demand-response pricing , 2010, 2010 International Conference on Network and Service Management.

[52]  Qun Zhou,et al.  Impact of demand response contracts on load forecasting in a smart grid environment , 2012, PES 2012.

[53]  Hamed Mohsenian Rad,et al.  Tackling co-existence and fairness challenges in autonomous Demand Side Management , 2012, 2012 IEEE Global Communications Conference (GLOBECOM).

[54]  Manuel Alcazar-Ortega Evaluation and Assessment of New Demand Response Products Based on the Use of Flexibility in Industrial Processes: Application to the Food Industry , 2011 .

[55]  Peter Palensky,et al.  Demand Side Management: Demand Response, Intelligent Energy Systems, and Smart Loads , 2011, IEEE Transactions on Industrial Informatics.

[56]  Hak-Man Kim,et al.  A microgrid energy management system for inducing optimal demand response , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[57]  Chi Zhou,et al.  Knowing when to act: an optimal stopping method for smart grid demand response , 2011, IEEE Network.

[58]  Saifur Rahman,et al.  Demand response implementation in a home area network: A conceptual hardware architecture , 2012, 2012 IEEE PES Innovative Smart Grid Technologies (ISGT).

[59]  Malcolm McCulloch,et al.  Modeling the prospects of plug-in hybrid electric vehicles to reduce CO2 emissions , 2011 .

[60]  Quanyan Zhu,et al.  A differential game approach to distributed demand side management in smart grid , 2012, 2012 IEEE International Conference on Communications (ICC).

[61]  Henrik Madsen,et al.  A bilevel model for electricity retailers' participation in a demand response market environment , 2013 .

[62]  Jonathan Wang,et al.  Case studies of smart grid demand response programs in North America , 2011, ISGT 2011.

[63]  M.H. Nehrir,et al.  Demand response for smart microgrid: Initial results , 2011, ISGT 2011.

[64]  M. P. Moghaddam,et al.  Customer behavior based demand response model , 2012, 2012 IEEE Power and Energy Society General Meeting.

[65]  Alexandre Dolgui,et al.  A taxonomy of line balancing problems and their solutionapproaches , 2013 .

[66]  Sanem Sergici,et al.  The Impact of Informational Feedback on Energy Consumption -- A Survey of the Experimental Evidence , 2009 .

[67]  Vincent W. S. Wong,et al.  Real-time vehicle-to-grid control algorithm under price uncertainty , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[68]  Johanna L. Mathieu,et al.  Quantifying Changes in Building Electricity Use, With Application to Demand Response , 2011, IEEE Transactions on Smart Grid.

[69]  H. Abniki,et al.  The role of incentive based Demand Response programs in smart grid , 2011, 2011 10th International Conference on Environment and Electrical Engineering.

[70]  Zhenhua Jiang Agent-Based Control Framework for Distributed Energy Resources Microgrids , 2006, 2006 IEEE/WIC/ACM International Conference on Intelligent Agent Technology.

[71]  Shahin Nazarian,et al.  Concurrent optimization of consumer's electrical energy bill and producer's power generation cost under a dynamic pricing model , 2012, 2012 IEEE PES Innovative Smart Grid Technologies (ISGT).

[72]  Steven H. Low,et al.  Multi-period optimal energy procurement and demand response in smart grid with uncertain supply , 2011, IEEE Conference on Decision and Control and European Control Conference.

[73]  Peter Palensky,et al.  Demand response with functional buildings using simplified process models , 2011, IECON 2011 - 37th Annual Conference of the IEEE Industrial Electronics Society.

[74]  M. P. Moghaddam,et al.  Flexible demand response programs modeling in competitive electricity markets , 2011 .

[75]  Holger Hermanns,et al.  Demand-Response Management for Dependable Power Grids , 2013 .

[76]  Steffen Lamparter,et al.  An agent-based market platform for Smart Grids , 2010, AAMAS.

[77]  Taskin Koçak,et al.  A Survey on Smart Grid Potential Applications and Communication Requirements , 2013, IEEE Transactions on Industrial Informatics.

[78]  Zhong Fan,et al.  A Distributed Demand Response Algorithm and Its Application to PHEV Charging in Smart Grids , 2012, IEEE Transactions on Smart Grid.

[79]  Manfred Morari,et al.  Communication limitations in iterative real time pricing for power systems , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[80]  Quanyan Zhu,et al.  Dependable Demand Response Management in the Smart Grid: A Stackelberg Game Approach , 2013, IEEE Transactions on Smart Grid.

[81]  Xing Wang,et al.  Optimal Scheduling of Demand Response Events for Electric Utilities , 2013, IEEE Transactions on Smart Grid.

[82]  Z. Vale,et al.  Demand response in electrical energy supply: An optimal real time pricing approach , 2011 .

[83]  Salman Mohagheghi,et al.  Impact of demand response on distribution system reliability , 2011, 2011 IEEE Power and Energy Society General Meeting.

[84]  Ahmed Yousuf Saber,et al.  Efficient Utilization of Renewable Energy Sources by Gridable Vehicles in Cyber-Physical Energy Systems , 2010, IEEE Systems Journal.

[85]  Ariel Rubinstein,et al.  A Course in Game Theory , 1995 .

[86]  Phani Chavali,et al.  Parallel autonomous optimization of demand response with renewable distributed generators , 2012, 2012 IEEE Third International Conference on Smart Grid Communications (SmartGridComm).

[87]  Multi-period Optimal Procurement and Demand Responses in the Presence of Uncertain Supply Libin Jiang , 2011 .

[88]  Saifur Rahman,et al.  Impact of TOU rates on distribution load shapes in a smart grid with PHEV penetration , 2010, IEEE PES T&D 2010.

[89]  M. Eissa Demand side management program evaluation based on industrial and commercial field data , 2011 .

[90]  Zita Vale,et al.  Distributed energy resource short-term scheduling using Signaled Particle Swarm Optimization , 2012 .

[91]  P. Siano,et al.  Combined Operations of Renewable Energy Systems and Responsive Demand in a Smart Grid , 2011, IEEE Transactions on Sustainable Energy.

[92]  Lazaros G. Papageorgiou,et al.  Optimal Scheduling of Smart Homes Energy Consumption with Microgrid , 2011 .

[93]  Gongguo Tang,et al.  A game-theoretic approach for optimal time-of-use electricity pricing , 2013, IEEE Transactions on Power Systems.

[94]  Katarina Kostkova,et al.  An introduction to load management , 2013 .

[95]  Masood Parvania,et al.  Demand Response Scheduling by Stochastic SCUC , 2010, IEEE Transactions on Smart Grid.

[96]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[97]  Vincent W. S. Wong,et al.  Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid , 2010, IEEE Transactions on Smart Grid.

[98]  C. McDiarmid SIMULATED ANNEALING AND BOLTZMANN MACHINES A Stochastic Approach to Combinatorial Optimization and Neural Computing , 1991 .

[99]  Jignesh Solanki,et al.  Residential Demand Response model and impact on voltage profile and losses of an electric distribution network , 2012 .

[100]  Margot Weijnen,et al.  Investing in smart grids within the market paradigm: The case of the Netherlands and its relevance for China , 2013 .

[101]  Walid Saad,et al.  Game Theoretic Methods for the Smart Grid , 2012, ArXiv.

[102]  Georgios B. Giannakis,et al.  Scalable and Robust Demand Response With Mixed-Integer Constraints , 2013, IEEE Transactions on Smart Grid.

[103]  Georgios B. Giannakis,et al.  Cooperative multi-residence demand response scheduling , 2011, 2011 45th Annual Conference on Information Sciences and Systems.

[104]  H. Chao Price-Responsive Demand Management for a Smart Grid World , 2010 .

[105]  Mo-Yuen Chow,et al.  A Survey on the Electrification of Transportation in a Smart Grid Environment , 2012, IEEE Transactions on Industrial Informatics.

[106]  Horst F. Wedde,et al.  Real-time multi-agent support for decentralized management of electric power , 2006, 18th Euromicro Conference on Real-Time Systems (ECRTS'06).

[107]  Shun-Hsien Huang,et al.  Demand response — An assessment of load participation in the ERCOT nodal market , 2012, 2012 IEEE Power and Energy Society General Meeting.

[108]  Matthias Wissner,et al.  The Smart Grid – A saucerful of secrets? , 2011 .

[109]  Ahmad Faruqui,et al.  The Power of Dynamic Pricing , 2009 .

[110]  Peter Luh,et al.  Load adaptive pricing: An emerging tool for electric utilities , 1981, 1981 20th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes.

[111]  J. Torriti,et al.  Demand response experience in Europe: Policies, programmes and implementation , 2010 .

[112]  A. Faruqui The Ethics of Dynamic Pricing , 2010 .

[113]  Georgios B. Giannakis,et al.  Residential demand response with interruptible tasks: Duality and algorithms , 2011, IEEE Conference on Decision and Control and European Control Conference.

[114]  P. T. Krein,et al.  Review of the Impact of Vehicle-to-Grid Technologies on Distribution Systems and Utility Interfaces , 2013, IEEE Transactions on Power Electronics.

[115]  Zhi Zhou,et al.  Agent-Based Electricity Market Simulation With Demand Response From Commercial Buildings , 2011, IEEE Transactions on Smart Grid.

[116]  Sunil K. Vuppala,et al.  Incorporating fairness within Demand response programs in smart grid , 2011, ISGT 2011.

[117]  Akihiko Yokoyama,et al.  Autonomous Distributed V2G (Vehicle-to-Grid) Satisfying Scheduled Charging , 2012, IEEE Transactions on Smart Grid.

[118]  J. K. Kok,et al.  PowerMatcher: multiagent control in the electricity infrastructure , 2005, AAMAS '05.

[119]  Xinping Guan,et al.  Optimal demand response using mechanism design in the smart grid , 2012, Proceedings of the 31st Chinese Control Conference.

[120]  K. J. Ray Liu,et al.  A cheat-proof game theoretic demand response scheme for smart grids , 2012, 2012 IEEE International Conference on Communications (ICC).

[121]  A.G. Martins,et al.  A Multiple Objective Approach to Direct Load Control Using an Interactive Evolutionary Algorithm , 2007, IEEE Transactions on Power Systems.

[122]  P. Centolella The integration of Price Responsive Demand into Regional Transmission Organization (RTO) wholesale power markets and system operations , 2010 .

[123]  François Bouffard,et al.  Decentralized Demand-Side Contribution to Primary Frequency Control , 2011, IEEE Transactions on Power Systems.

[124]  Manuel Alcázar-Ortega,et al.  Methodology for validating technical tools to assess customer Demand Response: Application to a commercial customer , 2011 .

[125]  Yunsi Fei,et al.  Dynamic Residential Demand Response and Distributed Generation Management in Smart Microgrid with Hierarchical Agents , 2011 .

[126]  Guy R. Newsham,et al.  The effect of utility time-varying pricing and load control strategies on residential summer peak electricity use: A review , 2010 .

[127]  Hamed Mohsenian Rad,et al.  Vehicle-to-Aggregator Interaction Game , 2012, IEEE Transactions on Smart Grid.

[128]  Yang Xiao,et al.  Cyber Security and Privacy Issues in Smart Grids , 2012, IEEE Communications Surveys & Tutorials.

[129]  Karen Herter,et al.  Residential response to critical-peak pricing of electricity: California evidence , 2010 .

[130]  Lorna A. Greening,et al.  Demand response resources: Who is responsible for implementation in a deregulated market? , 2010 .

[131]  Hamed Mohsenian Rad,et al.  Optimal Residential Load Control With Price Prediction in Real-Time Electricity Pricing Environments , 2010, IEEE Transactions on Smart Grid.

[132]  Miao Pan,et al.  Optimal Power Management of Residential Customers in the Smart Grid , 2012, IEEE Transactions on Parallel and Distributed Systems.

[133]  Kathleen L. Spees,et al.  Demand Response and Electricity Market Efficiency , 2007 .

[134]  David Faulkner,et al.  Opportunities, Barriers and Actions for Industrial Demand Response in California , 2009 .

[135]  Daniel Olsen,et al.  Opportunities for Energy Efficiency and Demand Response in the California Cement Industry , 2012 .

[136]  Pedro Faria,et al.  An optimal scheduling problem in distribution networks considering V2G , 2011, 2011 IEEE Symposium on Computational Intelligence Applications In Smart Grid (CIASG).

[137]  Karen Herter Residential implementation of critical-peak pricing of electricity , 2007 .

[138]  Anna Scaglione,et al.  From Packet to Power Switching: Digital Direct Load Scheduling , 2012, IEEE Journal on Selected Areas in Communications.

[139]  Manuel Alcázar Ortega,et al.  Technical and economical tools to assess customer demand response in the commercial sector , 2009 .

[140]  J. Aghaei,et al.  Demand response in smart electricity grids equipped with renewable energy sources: A review , 2013 .

[141]  Barbara R. Alexander Dynamic Pricing? Not So Fast! A Residential Consumer Perspective , 2010 .

[142]  Ahmad Faruqui,et al.  The Value of Dynamic Pricing in Mass Markets , 2002 .

[143]  V. Vittal,et al.  A Framework for Evaluation of Advanced Direct Load Control With Minimum Disruption , 2008, IEEE Transactions on Power Systems.

[144]  Liu Kai,et al.  Optimization of electric vehicle charging station location based on game theory , 2011, Proceedings 2011 International Conference on Transportation, Mechanical, and Electrical Engineering (TMEE).

[145]  Eirikur Ragnarsson,et al.  Price it Right: Household Response to a Time-of-Use Electricity Pricing Experiment in Auckland, New Zealand , 2012 .

[146]  Wolfgang Ketter,et al.  Demand side management—A simulation of household behavior under variable prices , 2011 .

[147]  Hamed Mohsenian Rad,et al.  Achieving Optimality and Fairness in Autonomous Demand Response: Benchmarks and Billing Mechanisms , 2013, IEEE Transactions on Smart Grid.

[148]  Vincent W. S. Wong,et al.  Optimal energy consumption scheduling using mechanism design for the future smart grid , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[149]  Hanne Sæle,et al.  Demand Response From Household Customers: Experiences From a Pilot Study in Norway , 2011, IEEE Transactions on Smart Grid.

[150]  Jose M. Yusta,et al.  Optimal pricing of default customers in electrical distribution systems: Effect behavior performance of demand response models , 2007 .

[151]  Shuang Gao,et al.  Opportunities and Challenges of Vehicle-to-Home, Vehicle-to-Vehicle, and Vehicle-to-Grid Technologies , 2013, Proceedings of the IEEE.

[152]  Mohammed H. Albadi,et al.  A summary of demand response in electricity markets , 2008 .

[153]  Hideharu Sugihara,et al.  Analyzing the system effects of optimal demand response utilization for reserve procurement and peak clipping , 2010, IEEE PES General Meeting.

[154]  Mustafa A. Biviji,et al.  Lessons learned from smart grid enabled pricing programs , 2011, 2011 IEEE Power and Energy Conference at Illinois.

[155]  Mike Zimmerman The industry demands better demand response , 2012, 2012 IEEE PES Innovative Smart Grid Technologies (ISGT).

[156]  Jorge J. Gómez-Sanz,et al.  A multi-agent system architecture for smart grid management and forecasting of energy demand in virtual power plants , 2013, IEEE Communications Magazine.

[157]  Hamid Sharif,et al.  A Survey on Smart Grid Communication Infrastructures: Motivations, Requirements and Challenges , 2013, IEEE Communications Surveys & Tutorials.

[158]  Rafael Wisniewski,et al.  Control for large scale demand response of thermostatic loads* , 2013, 2013 American Control Conference.

[159]  Lieven Vandevelde,et al.  Active Load Control in Islanded Microgrids Based on the Grid Voltage , 2011, IEEE Transactions on Smart Grid.

[160]  Anna Scaglione,et al.  Demand-Side Management in the Smart Grid: Information Processing for the Power Switch , 2012, IEEE Signal Processing Magazine.

[161]  Hani Hagras,et al.  Creating an ambient-intelligence environment using embedded agents , 2004, IEEE Intelligent Systems.

[162]  Singiresu S. Rao Engineering Optimization : Theory and Practice , 2010 .

[163]  Lingfeng Wang,et al.  A demand side management based simulation platform incorporating heuristic optimization for management of household appliances , 2012 .

[164]  Yuan Wu,et al.  Demand Response Management via Real-Time Electricity Price Control in Smart Grids , 2013, IEEE Journal on Selected Areas in Communications.

[165]  Chen Chen,et al.  An innovative RTP-based residential power scheduling scheme for smart grids , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[166]  Ahmed Yousuf Saber,et al.  Intelligent unit commitment with vehicle-to-grid —A cost-emission optimization , 2010 .

[167]  H. Allcott,et al.  Rethinking Real Time Electricity Pricing , 2011 .

[168]  Nokhum Markushevich,et al.  Integrated Voltage, Var Control and demand response in distribution systems , 2009, 2009 IEEE/PES Power Systems Conference and Exposition.

[169]  Stephen B. Wicker,et al.  Inferring Personal Information from Demand-Response Systems , 2010, IEEE Security & Privacy.

[170]  Willett Kempton,et al.  Using fleets of electric-drive vehicles for grid support , 2007 .

[171]  Hamid Sharif,et al.  A Survey on Cyber Security for Smart Grid Communications , 2012, IEEE Communications Surveys & Tutorials.

[172]  D. Brandt,et al.  A linear programming model for reducing system peak through customer load control programs , 1996 .

[173]  Xi Fang,et al.  3. Full Four-channel 6.3-gb/s 60-ghz Cmos Transceiver with Low-power Analog and Digital Baseband Circuitry 7. Smart Grid — the New and Improved Power Grid: a Survey , 2022 .

[174]  Khosrow Moslehi,et al.  A Reliability Perspective of the Smart Grid , 2010, IEEE Transactions on Smart Grid.

[175]  Mohamed A. El-Sharkawi,et al.  Optimal Scheduling of Vehicle-to-Grid Energy and Ancillary Services , 2012, IEEE Transactions on Smart Grid.

[176]  Amr M. Youssef,et al.  A Water-Filling Based Scheduling Algorithm for the Smart Grid , 2012, IEEE Transactions on Smart Grid.

[177]  Qiuwei Wu,et al.  Direct Load Control (DLC) Considering Nodal Interrupted Energy Assessment Rate (NIEAR) in Restructured Power Systems , 2010, IEEE Transactions on Power Systems.

[178]  R.J. Thomas,et al.  Demand-Side Bidding Agents: Modeling and Simulation , 2008, IEEE Transactions on Power Systems.

[179]  Hye-Jin Kim,et al.  Genetic Algorithm-Based Charging Task Scheduler for Electric Vehicles in Smart Transportation , 2012, ACIIDS.

[180]  Robert Lasseter,et al.  Smart Distribution: Coupled Microgrids , 2011, Proceedings of the IEEE.

[181]  Sila Kiliccote,et al.  Findings from Seven Years of Field Performance Data for Automated Demand Response in Commercial Buildings , 2010 .

[182]  Sagar Naik,et al.  A Survey of Communication Protocols for Automatic Meter Reading Applications , 2011, IEEE Communications Surveys & Tutorials.

[183]  M. Parsa Moghaddam,et al.  Modeling and prioritizing demand response programs in power markets , 2010 .

[184]  Nico Keyaerts,et al.  How to Engage Consumers in Demand Response: A Contract Perspective , 2013 .

[185]  Sekyung Han,et al.  Development of an Optimal Vehicle-to-Grid Aggregator for Frequency Regulation , 2010, IEEE Transactions on Smart Grid.

[186]  Stephen P. Boyd,et al.  Dynamic Network Energy Management via Proximal Message Passing , 2013, Found. Trends Optim..

[187]  Jidong Wang,et al.  Optimal dispatching model of Smart Home Energy Management System , 2012, IEEE PES Innovative Smart Grid Technologies.

[188]  Manuel Alcázar-Ortega,et al.  Evaluation and assessment of demand response potential applied to the meat industry , 2012 .

[189]  Peng Xu,et al.  Introduction to Commercial Building Control Strategies and Techniques for Demand Response , 2007 .

[190]  Sanem Sergici,et al.  Piloting the Smart Grid , 2009 .

[191]  Anna Scaglione,et al.  Coordinated home energy management for real-time power balancing , 2012, 2012 IEEE Power and Energy Society General Meeting.

[192]  Peter Palensky,et al.  Load recognition for automated demand response in microgrids , 2010, IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society.

[193]  Anno Accademico,et al.  Smart Grid Communications: Overview of research challenges, solutions and standardization activities , 2013 .

[194]  Tariq Samad,et al.  Smart grid technologies and applications for the industrial sector , 2012, Comput. Chem. Eng..

[195]  Martin Pehnt,et al.  Load management for refrigeration systems: Potentials and barriers , 2011 .

[196]  Jignesh Solanki,et al.  Demand response model and its effects on voltage profile of a distribution system , 2011, 2011 IEEE Power and Energy Society General Meeting.

[197]  Thomas J. Overbye,et al.  Smart Grids and Beyond: Achieving the Full Potential of Electricity Systems , 2012, Proceedings of the IEEE.

[198]  Alma Y. Alanis,et al.  Forecasting for smart grid applications with Higher Order Neural Networks , 2012, World Automation Congress 2012.

[199]  Albert Molderink,et al.  Domestic energy management methodology for optimizing efficiency in Smart Grids , 2009, 2009 IEEE Bucharest PowerTech.

[200]  Shaojie Tang,et al.  Distributed Demand and Response Algorithm for Optimizing Social-Welfare in Smart Grid , 2012, 2012 IEEE 26th International Parallel and Distributed Processing Symposium.

[201]  Hitoshi Yano,et al.  A novel charging-time control method for numerous EVs based on a period weighted prescheduling for power supply and demand balancing , 2012, 2012 IEEE PES Innovative Smart Grid Technologies (ISGT).

[202]  Reza Iravani,et al.  Potential-Function Based Control of a Microgrid in Islanded and Grid-Connected Modes , 2010, IEEE Transactions on Power Systems.

[203]  Salman Mohagheghi,et al.  Demand Response Architecture: Integration into the Distribution Management System , 2010, 2010 First IEEE International Conference on Smart Grid Communications.

[204]  George W. Arnold,et al.  Challenges and Opportunities in Smart Grid: A Position Article , 2011, Proceedings of the IEEE.

[205]  Ding Li,et al.  Auctioning game based Demand Response scheduling in smart grid , 2011, 2011 IEEE Online Conference on Green Communications.

[206]  Roger King,et al.  Control method for multi-microgrid systems in smart grid environment—Stability, optimization and smart demand participation , 2012, 2012 IEEE PES Innovative Smart Grid Technologies (ISGT).

[207]  Meysam Doostizadeh,et al.  A day-ahead electricity pricing model based on smart metering and demand-side management , 2012 .

[208]  Oliver Kramer,et al.  Power Prediction in Smart Grids with Evolutionary Local Kernel Regression , 2010, HAIS.

[209]  Robert Schober,et al.  Optimal and autonomous incentive-based energy consumption scheduling algorithm for smart grid , 2010, 2010 Innovative Smart Grid Technologies (ISGT).

[210]  Xu Rong,et al.  A review on distributed energy resources and MicroGrid , 2008 .

[211]  Massoud Pedram,et al.  Demand-side load scheduling incentivized by dynamic energy prices , 2011, 2011 IEEE International Conference on Smart Grid Communications (SmartGridComm).

[212]  Pierluigi Siano,et al.  Demand response and smart grids—A survey , 2014 .

[213]  Shahin Nazarian,et al.  A nested game-based optimization framework for electricity retailers in the smart grid with residential users and PEVs , 2013, 2013 IEEE Online Conference on Green Communications (OnlineGreenComm).

[214]  M. P. Moghaddam,et al.  Demand response modeling considering Interruptible/Curtailable loads and capacity market programs , 2010 .

[215]  Vincent W. S. Wong,et al.  Advanced Demand Side Management for the Future Smart Grid Using Mechanism Design , 2012, IEEE Transactions on Smart Grid.

[216]  Abdulkerim Karabiber,et al.  A user-mode distributed energy management architecture for smart grid applications , 2012 .

[217]  P. Kriett,et al.  Optimal control of a residential microgrid , 2012 .

[218]  João Abel Peças Lopes,et al.  Coordinating Storage and Demand Response for Microgrid Emergency Operation , 2013, IEEE Transactions on Smart Grid.

[219]  Fouad Kamel,et al.  A Demand-Side Response Smart Grid Scheme to Mitigate Electrical Peak Demands and Access Renewable Energy Sources , 2010 .

[220]  Tao Hong,et al.  Modeling and forecasting hourly electric load by multiple linear regression with interactions , 2010, IEEE PES General Meeting.

[221]  Audrey Zibelman,et al.  Deployment of Demand Response as a Real-Time Resource in Organized Markets , 2008 .

[222]  Liang Zhou,et al.  QoE-driven power scheduling in smart grid: architecture, strategy, and methodology , 2012, IEEE Communications Magazine.

[223]  Pravin Varaiya,et al.  Smart Operation of Smart Grid: Risk-Limiting Dispatch , 2011, Proceedings of the IEEE.

[224]  Min Dong,et al.  Real-time welfare-maximizing regulation allocation in aggregator-EVs systems , 2013, 2013 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[225]  Yang Xiao,et al.  A survey of communication/networking in Smart Grids , 2012, Future Gener. Comput. Syst..

[226]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[227]  Zita Vale,et al.  An integrated approach for distributed energy resource short-term scheduling in smart grids considering realistic power system simulation , 2012 .

[228]  Hye-Jin Kim,et al.  Power consumption scheduling for peak load reduction in smart grid homes , 2011, SAC '11.

[229]  Wilsun Xu,et al.  An Event-Driven Demand Response Scheme for Power System Security Enhancement , 2011, IEEE Transactions on Smart Grid.

[230]  Shing-Chow Chan,et al.  Demand Response Optimization for Smart Home Scheduling Under Real-Time Pricing , 2012, IEEE Transactions on Smart Grid.

[231]  Hamid Khayyam,et al.  Intelligent control of vehicle to grid power , 2012 .

[232]  Jay Zarnikau,et al.  Demand participation in the restructured Electric Reliability Council of Texas market , 2010 .

[233]  P. Cappers,et al.  Demand Response in U.S. Electricity Markets: Empirical Evidence , 2010 .

[234]  Gang Xiong,et al.  Smart (in-home) power scheduling for demand response on the smart grid , 2011, ISGT 2011.

[235]  J. Oyarzabal,et al.  A Direct Load Control Model for Virtual Power Plant Management , 2009, IEEE Transactions on Power Systems.

[236]  Payam Teimourzadeh Baboli,et al.  Present status and future trends in enabling demand response programs , 2011, 2011 IEEE Power and Energy Society General Meeting.

[237]  Farrokh Aminifar,et al.  Load commitment in a smart home , 2012 .

[238]  Zhong Fan,et al.  An integer linear programming based optimization for home demand-side management in smart grid , 2012, 2012 IEEE PES Innovative Smart Grid Technologies (ISGT).