摘要
This paper proposes an innovative genetic algorithm (GA) approach to solve the thermal unit commitment (UC) problem in power generation industry through a constraint satisfaction technique. Due to a large variety of constraints to be satisfied, the solution space of the UC problem is highly nonconvex, and therefore the UC problem can not be solved efficiently by the standard GA. To effectively deal with the constraints of the problem and greatly reduce the search space of the GA, the minimum up- and down-time constraints are embedded in the binary strings that are coded to represent the on-off states of the generating units. The violations of the other constraints are handled by integrating penalty factors into the cost function. Numerical results on the practical Taiwan Power (Taipower) system of 38 thermal units over a 24-hour period show that the features of easy implementation, fast convergence, and highly near-optimal solution in solving the UC problem can be achieved by the proposed GA approach.
原文 | English |
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頁面 | 267-274 |
頁數 | 8 |
出版狀態 | Published - 1995 1月 1 |
事件 | Proceedings of the 1995 IEEE International Conference on Fuzzy Systems. Part 1 (of 5) - Yokohama, Jpn 持續時間: 1995 3月 20 → 1995 3月 24 |
Other
Other | Proceedings of the 1995 IEEE International Conference on Fuzzy Systems. Part 1 (of 5) |
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城市 | Yokohama, Jpn |
期間 | 95-03-20 → 95-03-24 |
All Science Journal Classification (ASJC) codes
- 軟體
- 理論電腦科學
- 人工智慧
- 應用數學