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|Title:||Efficient Nash bargain coordination of a cluster of cooperating energy buildings||Authors:||Chua, Wen Han||Keywords:||Engineering::Electrical and electronic engineering||Issue Date:||2022||Publisher:||Nanyang Technological University||Source:||Chua, W. H. (2022). Efficient Nash bargain coordination of a cluster of cooperating energy buildings. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157276||Project:||A1055-211||Abstract:||Economic expansion due to population growth across the world is one of the major factors as to why there has been an upward trend regarding energy demands around commercial and industrial buildings. Distributed energy resources such as photovoltaic panels and energy storage systems is increasing considerably around the globe. This study the need for the reduction of energy consumption within a cluster of buildings using game theory to improve energy efficiency while being environmentally sustainable. To demonstrate the game theory effectiveness, optimisation strategies for multi-player objectives and planning process for a clustered microgrid with three interconnected microgrids is investigated and to fulfil all participants in terms of efficiency and fairness, a cooperative strategy is used here. This also minimizes the intermittency of solar and wind-generated electricity. The game theory technique, notably the Nash Bargain Solution are performed for this project to attain optimum solutions. Simulations of the game models are constructed on MATLAB based on multi object optimization, criterions such as profit, stability, loss of power, and levelized cost of energy are considered to direct the objective functions. In short, for a cluster of microgrid proposed, which comprises of valid combination of wind turbines, photovoltaic panels and energy storage in a grid connected mode. A method of game theory is used for the optimization of power system model to find the correct proportions of generation resources, and to attain optimal payoff values.||URI:||https://hdl.handle.net/10356/157276||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Student Reports (FYP/IA/PA/PI)|
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