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启发式多目标优化算法在能源和电力系统中的典型应用综述

A Survey of Featured Applications of Heuristic Multi-objective Optimization Algorithms in Power and Energy Systems

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【作者】 朱晓东王颖杨之乐郭媛君

【Author】 ZHU Xiaodong;WANG Ying;YANG Zhile;GUO Yuanjun;School of Electrical Engineering,Zhengzhou University;Shenzhen Institutes of Advanced Technology,Chinese Academy of Sciences;

【通讯作者】 杨之乐;

【机构】 郑州大学电气工程学院中国科学院深圳先进技术研究院

【摘要】 能源与电力系统是现代社会人类生存和发展的基础,在发电、热转换等能源传输和转化过程中存在着极大的低效和浪费,造成日益严重的环境污染与资源消耗.针对能源电力系统中的经济性、环保性及社会友好性等多个目标进行全面、综合的优化设计和运行调度,是创造低碳智慧能源的必要途径.基于启发式多目标优化算法具有灵活性高、适用范围广、求解效率高等特点,经过数十年的发展,现已成为工程优化领域的重要求解工具.本文旨在系统地整理启发式多目标优化算法在求解电力和能源系统中典型问题的应用,重点对6个典型问题的求解应用进行探讨、分析,结合现阶段存在的问题,指出该领域未来亟待研究和探索的方向.

【Abstract】 Power and energy systems are the foundation of human survival and development in modern society.They played an indispensable role in daily production and life. However,significant inefficiencies and wastes found in the process of energy transmission and transformation,such as power generation and energy conversion,could result in increasingly environmental pollution and resource consumption. In order to create a low-carbon energy future,it was a necessary way to optimize the design and operation of energy and power systems aiming at maximization to the economic,environmental and social friendly benefit. After decades of development,Multiobjective heuristics optimization algorithms with characteristics of high flexibility,wide application range and high efficiency. have become crucial tools in the solving various engineering optimization. This paper aimed to systematically reviewing state-of-the-art heuristic based multi-objective optimization algorithms for solving six typical problems in power and energy systems. Comprehensive discussions on the methodologies and a brief insight on future research direction have also been proposed.

【基金】 国家自然科学基金资助项目(51607177、61876169、61433012、U1435215);国家博士后科学基金面上项目(2018M631005);广东省自然科学基金博士启动项目(2018A030310671)
  • 【文献出处】 郑州大学学报(工学版) ,Journal of Zhengzhou University(Engineering Science) , 编辑部邮箱 ,2019年05期
  • 【分类号】TM73;TP18;TK01
  • 【被引频次】14
  • 【下载频次】845
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