Unit commitment by genetic algorithm with specialized search operators

Grzegorz Dudek

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Unit commitment by genetic algorithm with specialized search operators

机译：通过遗传算法与专门的搜索运算符进行单位承诺

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摘要

An approach for solving the unit commitment problem based on genetic algorithm with new search operators is presented. These operators, specific to the problem, are mutation with a probability of bit change depending on load demand, production and start-up costs of the generating units and transposition. The method incorporates time-dependent start-up costs, demand and reserve constraints, minimum up and down time constraints and units power generation limits. Repair algorithms or penalty factors in the objective function are applied to the infeasible solutions. Numerical results showed an improvement in the solution cost compared to the results obtained from genetic algorithm with standard operators and other techniques.

机译：提出了一种基于遗传算法的带有新搜索算子的机组承诺问题解决方法。这些操作员（具体针对该问题）会根据负载需求，发电机组的生产和启动成本以及换位而发生比特变化概率的突变。该方法结合了与时间有关的启动成本，需求和储备约束，最小的上下时间约束以及单位发电限制。目标函数中的修复算法或惩罚因子被应用于不可行的解决方案。数值结果表明，与使用标准算子和其他技术从遗传算法获得的结果相比，解决方案的成本有所提高。

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来源
《Electric power systems research》 |2004年第3期|p.299-308|共10页
作者
Grzegorz Dudek;
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作者单位

Institute of Electrical Power Engineering, Technical University of Czestochowa, Al. Armii Krajowej 17, Czestochowa 42-200, Poland;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类理论与分析;发电、发电厂;
关键词
unit commitment; power generation dispatch; genetic algorithms; evolutionary computation; combinatorial optimization;

机译：机组承诺;发电调度;遗传算法;进化计算;组合优化;

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专利

1. Unit commitment by genetic algorithm with penalty methods and a comparison of Lagrangian search and genetic algorithm—economic dispatch example [J] . G B Sheble, T T Maifeld, K Brittig, International Journal of Electrical Power & Energy Systems . 1996,第6期

机译：遗传算法与罚分法的单位承诺以及拉格朗日搜索和遗传算法的比较-经济调度示例
2. Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem [J] . Mantawy A.H., Abdel-Magid Y.L., Selim S.Z. IEEE Transactions on Power Systems . 1999,第3期

机译：集成遗传算法，禁忌搜索和模拟退火以解决单位承诺问题
3. Integrating genetic algorithms, tabu search, and simulated annealing for the unit commitment problem [J] . Mantawy A.H., Abdel-Magid Y.L. IEEE Transactions on Power Systems . 1999,第3期

机译：集成遗传算法，禁忌搜索和模拟退火来解决机组承诺问题
4. GENETIC ALGORITHMS SOLUTION TO OPTIMAL MAINTENANCE SCHEDULING (OMS) OF GENERATING UNITS WITH MODIFIED GENETIC OPERATORS [C] . S. BASKAR, P. SUBBARAJ, S. TAMILSELVI, 37th International Universities Power Engineering Conference (UPEC 2002) . 2002

机译：具有修正遗传算子的发电机组最优维护调度（OMS）的遗传算法解
5. Modified crossover operators for protein folding simulation with genetic algorithms. [D] . Jackson, David. 2004

机译：改进的交叉算子，用于使用遗传算法进行蛋白质折叠模拟。
6. A Modified Genetic Algorithm with Local Search Strategies and Multi-Crossover Operator for Job Shop Scheduling Problem [O] . Monique Simplicio Viana, Orides Morandin Junior, Rodrigo Colnago Contreras 2020

机译：具有本地搜索策略和作业商店调度问题的多交叉运算符的修改遗传算法
7. Integrating genetic algorithms, tabu search, and simulatedannealing for the unit commitment problem [O] . Mantawy A.H., Abdel-Magid Y.L., Selim S.Z. 1999

机译：集成遗传算法，禁忌搜索和模拟退火为单位承诺问题

Unit commitment by genetic algorithm with specialized search operators

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