Non-cooperative game theory based energy management systems for energy district in the retail market considering DER uncertainties

In this study, a general framework for implementing a retail energy market based on the Nikaido-Isoda/relaxation algorithm is proposed as an electricity market structure with large distributed energy resources (DERs) penetration and demand side management of consumers. Moreover, the consumers are able to participate in the market as prosumers (i.e. producer and consumer at the same time). By considering the related uncertainties, the DERs can maximise their expected payoff or profit by undertaking strategies through the price bidding strategy, based on the proposed structure, considering Nash equilibrium. The results show the effectiveness and accuracy of the proposed framework in determining the optimal power set-points of players participating in the market to achieve the objectives.

[1]  Mehrdad Abedi,et al.  Optimal daily scheduling of reconfiguration based on minimisation of the cost of energy losses and switching operations in microgrids , 2015 .

[2]  Andreas Sumper,et al.  Experimental validation of a real time energy management system for microgrids in islanded mode using a local day-ahead electricity market and MINLP , 2013 .

[3]  J. D. Guy.  Security Constrained Unit Commitment , 1971 .

[4]  R. Rubinstein,et al.  On relaxation algorithms in computation of noncooperative equilibria , 1994, IEEE Trans. Autom. Control..

[5]  Matthias Klusch,et al.  Dynamic Coalition Formation among Rational Agents , 2002, IEEE Intell. Syst..

[6]  Leigh Tesfatsion,et al.  Agent-Based Computational Economics: Growing Economies From the Bottom Up , 2002, Artificial Life.

[7]  Mousa Marzband,et al.  Implementation of an Optimal Energy Management within Islanded Microgrid , 2014 .

[8]  Mehdi Savaghebi,et al.  Distributed Smart Decision-Making for a Multimicrogrid System Based on a Hierarchical Interactive Architecture , 2016, IEEE Transactions on Energy Conversion.

[9]  Andreas Sumper,et al.  Energy management system of hybrid microgrid with energy storage , 2012 .

[10]  Andreas Sumper,et al.  Real time experimental implementation of optimum energy management system in standalone Microgrid by using multi-layer ant colony optimization , 2016 .

[11]  Ziyad M. Salameh,et al.  Optimum photovoltaic array size for a hybrid wind/PV system , 1994 .

[12]  Jacek B. Krawczyk,et al.  Numerical solutions to coupled-constraint (or generalised Nash) equilibrium problems , 2007, Comput. Manag. Sci..

[13]  J. Krawczyk,et al.  Numerical solutions to Nash-Cournot equilibria in coupled constraint electricity markets , 2004, IEEE Transactions on Power Systems.

[14]  Andreas Sumper,et al.  Experimental Validation of a Real-Time Energy Management System Using Multi-Period Gravitational Search Algorithm for Microgrids in Islanded Mode , 2014 .

[15]  Andreas Sumper,et al.  Experimental evaluation of a real time energy management system for stand-alone microgrids in day-ahead markets , 2013 .

[16]  Rongrit Chatthaworn,et al.  Transmission network expansion planning considering renewable energy target with Taguchi's orthogonal array testing , 2014 .

[17]  João Pedro Pedroso,et al.  Electricity day-ahead markets: Computation of Nash equilibria , 2014 .

[18]  Salvina Gagliano,et al.  Hybrid solar/wind power system probabilistic modelling for long-term performance assessment , 2006 .

[19]  J. Contreras,et al.  Nash-Cournot Equilibria in Hydrothermal Electricity Markets , 2011, IEEE Transactions on Power Systems.

[20]  Mousa Marzband,et al.  Experimental validation of optimal real-time energy management system for microgrids , 2014 .

[21]  Mehdi Savaghebi,et al.  An Optimal Energy Management System for Islanded Microgrids Based on Multiperiod Artificial Bee Colony Combined With Markov Chain , 2017, IEEE Systems Journal.

[22]  Mousa Marzband,et al.  Optimal energy management for stand‐alone microgrids based on multi‐period imperialist competition algorithm considering uncertainties: experimental validation , 2016 .

[23]  Farrokh Aminifar,et al.  Probabilistic Home Load Controlling Considering Plug-in Hybrid Electric Vehicle Uncertainties , 2014 .

[24]  Gevork B. Gharehpetian,et al.  Game-theoretic approach to cooperative control of distributed energy resources in islanded microgrid considering voltage and frequency stability , 2013, Neural Computing and Applications.

[25]  A. A. Chen,et al.  Stochastic simulation and forecasting of hourly average wind speed sequences in Jamaica , 1991 .

[26]  Ashkan Rahimi-Kian,et al.  NetPMS: an internet-based power market simulator for educational purposes , 2012 .

[27]  A. Huang,et al.  A game theoretic framework for a next-generation retail electricity market with high penetration of distributed residential electricity suppliers , 2014 .

[28]  Serge Lefebvre,et al.  Improving the quality of an optimal power flow solution by Taguchi method , 1995 .

[29]  Rongrit Chatthaworn Student Member and,et al.  Transmission network expansion planning considering renewable energy target with Taguchi's orthogonal array testing , 2014 .

[30]  Han Yu,et al.  Robust Transmission Network Expansion Planning Method With Taguchi's Orthogonal Array Testing , 2011, IEEE Transactions on Power Systems.

[31]  Fushuan Wen,et al.  Optimal bidding strategies for competitive generators and large consumers , 2001 .

[32]  Jianhui Wang,et al.  Outer-approximation method for security constrained unit commitment , 2013 .

[33]  N. Nabona,et al.  An Oligopoly Model for Medium-Term Power Planning in a Liberalized Electricity Market , 2009, IEEE Transactions on Power Systems.

[34]  Kwang-Ho Lee,et al.  Strategy Equilibrium in Stackelberg Model with Transmission Congestion in Electricity Market , 2014 .