Optimal KW Generation/Demand Scheduling in a Factory Power System Considering Uncertain Renewables
碩士 === 中原大學 === 電機工程研究所 === 102 === Studies on unit commitment (UC) and renewable energy are now important topics as a result of shortage of energy. This thesis presents a novel method based on Genetic Algorithms for solving unit and elastic load commitments in a factory power system considering unc...
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| Format: | Others |
| Language: | zh-TW |
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2014
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| Online Access: | http://ndltd.ncl.edu.tw/handle/21272935669824240624 |
| Summary: | 碩士 === 中原大學 === 電機工程研究所 === 102 === Studies on unit commitment (UC) and renewable energy are now important topics as a result of shortage of energy. This thesis presents a novel method based on Genetic Algorithms for solving unit and elastic load commitments in a factory power system considering uncertain renewables. Two encodings are proposed for the unit and elastic load, incorporating with new crossover and mutation operations. Point Estimate Method (PEM) is used to sample the uncertain photovoltaic generation, modeled by a Gaussian distribution. The proposed method can attain the optimal cost of power generation subject to various operational constraints in the factory power system. This work obtains simulation results through four scenarios specified by different constraints. Simulation results show the applicability of the proposed method and validate the algorithm.
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