Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/157276
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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