Fuzzy Logic Based Prosumer Agent in a Modular Smart Grid Prosumer Architecture

The investment to DERs (Distributed Energy Resources) in the emerging smart energy grids are critical to achieving goals for environmental protection, reducing energy costs and coping with failures. An architecture and market mechanism is needed to support the participation of owners of DERs that aim to maximize the profit from this investment within a system that is also able to achieve grid level objectives. Due to privacy requirements, owners of DERs should not be requested to divulge information such as the state of charge of a local energy store, and yet such information is very relevant for operating the grid in such a way that meets the objectives of the owner of the grid, who may operate a large power plant that is ultimately responsible for satisfying the load that cannot be covered by DERs. This paper builds on previous work to propose a modular multi-agent architecture in which prosumer agents represent DER owners and an auctioneer agent represents the power plant operator. The architecture allows the different agents to use different algorithms aiming at satisfying local and grid level objectives while meeting the privacy requirement. In particular, a fuzzy logic based algorithm is developed for the distributed automation platform that supports the architecture. The capability of the architecture to flexibly evaluate the performance of various algorithms from the DER owner and plant operator perspective is demonstrated with a case study in the district heating domain.

[1]  G. P. Beretta,et al.  Optimal power production scheduling in a complex cogeneration system with heat storage , 2000, Collection of Technical Papers. 35th Intersociety Energy Conversion Engineering Conference and Exhibit (IECEC) (Cat. No.00CH37022).

[2]  J. Verstege,et al.  Committing and dispatching power units and storage devices in cogeneration systems with renewable energy sources , 1996 .

[3]  Mario Gerla,et al.  Energy Service Interface: Accessing to Customer Energy Resources for Smart Grid Interoperation , 2013, IEEE Journal on Selected Areas in Communications.

[4]  Chen-Wei Yang,et al.  Towards an IEC 61499 compliance profile for smart grids review and analysis of possibilities , 2012, IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society.

[5]  Valeriy Vyatkin,et al.  Distributed Power System Automation With IEC 61850, IEC 61499, and Intelligent Control , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[6]  Eleonora D'Andrea,et al.  Computational intelligence techniques for solar photovoltaic system applications , 2012, 2012 Sustainable Internet and ICT for Sustainability (SustainIT).

[7]  Giovanni Acampora,et al.  Exploiting Timed Automata based Fuzzy Controllers for voltage regulation in Smart Grids , 2011, 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011).

[8]  Tomonobu Senjyu,et al.  Intelligent Economic Operation of Smart-Grid Facilitating Fuzzy Advanced Quantum Evolutionary Method , 2013, IEEE Transactions on Sustainable Energy.

[9]  H. T. Mouftah,et al.  Peak Load Curtailment in a Smart Grid Via Fuzzy System Approach , 2014, IEEE Transactions on Smart Grid.

[10]  Hong Cui,et al.  Multi-objective optimal allocation of distributed generation in smart grid , 2011, 2011 International Conference on Electrical and Control Engineering.

[11]  Pernille M. Overbye.  CHP & district heating with thermal storage , 2007 .

[12]  Matthias Stifter,et al.  Applying open standards and open source software for smart grid applications: Simulation of distributed intelligent control of power systems , 2011, 2011 IEEE Power and Energy Society General Meeting.

[13]  R. Ramirez-Iniguez,et al.  Renewable heat incentive for solar thermal systems in the United Kingdom: The next big thing? , 2012, 2012 IEEE International Conference on Power and Energy (PECon).

[14]  Seppo Sierla,et al.  Co-simulation of a dynamic process simulator and an event-based control system: Case district heating system , 2014, Proceedings of the 2014 IEEE Emerging Technology and Factory Automation (ETFA).

[15]  Nikolaos Papakonstantinou,et al.  An auction-based smart district heating grid , 2015, 2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA).

[16]  Guo Han-Ding,et al.  Probe into City District Heating Price Management Under Franchising System , 2008, 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing.

[17]  A. Snijders,et al.  Recent Inter-seasonal Underground Thermal Energy Storage Applications in Canada , 2006, 2006 IEEE EIC Climate Change Conference.

[18]  P. Mancarella.  Distributed multi-generation options to increase environmental efficiency in smart cities , 2012, 2012 IEEE Power and Energy Society General Meeting.

[19]  Mohammad A. S. Masoum,et al.  A fuzzy TOPSIS approach for home energy management in smart grid with considering householders' preferences , 2013, 2013 IEEE PES Innovative Smart Grid Technologies Conference (ISGT).

[20]  Osama A. Mohammed,et al.  Optimal charging of plug-in electric vehicles for a car park infrastructure , 2012, 2012 IEEE Industry Applications Society Annual Meeting.

[21]  Valeriy Vyatkin,et al.  Cosimulation Environment for Event-Driven Distributed Controls of Smart Grid , 2013, IEEE Transactions on Industrial Informatics.

[22]  R.S. Adhikari,et al.  Solar photovoltaic and thermal systems for electricity generation, space heating and domestic hot water in a residential building , 2011, 2011 International Conference on Clean Electrical Power (ICCEP).

[23]  H. E. Farag,et al.  Voltage regulation based on fuzzy multi-agent control scheme in smart grids , 2012, 2012 IEEE Energytech.

[24]  A. Jain,et al.  Fuzzy modeling and similarity based short term load forecasting using evolutionary particle swarm optimization , 2012, 2012 IEEE Power and Energy Society General Meeting.

[25]  A. Abu-Siada,et al.  Fuzzy Approach for Online Coordination of Plug-In Electric Vehicle Charging in Smart Grid , 2015, IEEE Transactions on Sustainable Energy.

[26]  Qiuye Sun,et al.  Observation of Chaos in Smart Grid and Stabilization Condition via Generalized Fuzzy Hyperbolic Model , 2011, 2011 Asia-Pacific Power and Energy Engineering Conference.

[27]  P. H. Nguyen,et al.  Agent-based control for building energy management in the smart grid framework , 2014, IEEE PES Innovative Smart Grid Technologies, Europe.

[28]  Chun-I Fan,et al.  Privacy-Enhanced Data Aggregation Scheme Against Internal Attackers in Smart Grid , 2014, IEEE Transactions on Industrial Informatics.

[29]  Xiaolei Dong,et al.  Human-Factor-Aware Privacy-Preserving Aggregation in Smart Grid , 2014, IEEE Systems Journal.

[30]  Pierluigi Mancarella,et al.  Energy and economic evaluation of power systems with heat networks , 2009 .

[31]  Peter Palensky,et al.  Co-simulation of components, controls and power systems based on open source software , 2013, 2013 IEEE Power & Energy Society General Meeting.

[32]  Rita Streblow,et al.  New energy concepts and related information technologies: Dual Demand Side Management , 2012, 2012 IEEE PES Innovative Smart Grid Technologies (ISGT).

[33]  Alfredo Vaccaro,et al.  A Self-Organizing Architecture Based on Cooperative Fuzzy Agents for Smart Grid Voltage Control , 2013, IEEE Transactions on Industrial Informatics.

[34]  Lakhmi C. Jain,et al.  Fuzzy logic decision-making in multi-agent systems for smart grids , 2013, 2013 IEEE Computational Intelligence Applications in Smart Grid (CIASG).

[35]  Preben Maegaard.  Balancing fluctuating power sources , 2010, 2010 World Non-Grid-Connected Wind Power and Energy Conference.

[36]  V. M. F. Mendes,et al.  Fuzzy clustering applied to a demand response model in a smart grid contingency scenario , 2014, 2014 International Symposium on Power Electronics, Electrical Drives, Automation and Motion.

[37]  Daniele Pala,et al.  An adaptive, agent-based protection scheme for radial distribution networks based on IEC 61850 and IEC 61499 , 2012 .

[38]  Christopher J. C. Williams,et al.  Demand side management through heat pumps, thermal storage and battery storage to increase local self-consumption and grid compatibility of PV systems , 2012, 2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe).

[39]  George Gross,et al.  Measurement Techniques for Online Battery State of Health Estimation in Vehicle-to-Grid Applications , 2014, IEEE Transactions on Instrumentation and Measurement.

[40]  Xiaoping Feng,et al.  Optimal design of pipe network of district cooling system based on genetic algorithm , 2010, 2010 Sixth International Conference on Natural Computation.

[41]  Ganesh K. Venayagamoorthy,et al.  Optimal fuzzy logic based coordination controller for improved transient stability of a smart grid , 2014, 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

[42]  G. Andersson,et al.  Optimal Coupling of Energy Infrastructures , 2007, 2007 IEEE Lausanne Power Tech.

[43]  Christoph Sorge,et al.  Do not snoop my habits: preserving privacy in the smart grid , 2012, IEEE Communications Magazine.

[44]  Valeriy Vyatkin,et al.  Virtual smart metering in automation and simulation of energy-efficient lighting system , 2013, 2013 IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA).

[45]  V. Vyatkin,et al.  Multiagent Smart Grid Automation Architecture Based on IEC 61850/61499 Intelligent Logical Nodes , 2012, IEEE Transactions on Industrial Electronics.

[46]  Eun-Kyu Lee,et al.  Fine-Grained Access to Smart Building Energy Resources , 2013, IEEE Internet Computing.

[47]  Seppo Sierla,et al.  Hybrid modeling and co-simulation of district heating systems with distributed energy resources , 2014, 2014 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES).

[48]  Chen-Wei Yang,et al.  Intelligent IEC 61850/61499 logical nodes for smart metering , 2012, 2012 IEEE Energy Conversion Congress and Exposition (ECCE).