| 引用本文: | 郑凌蔚,刘士荣,周文君,李金龙,吴舜裕.并网型可再生能源发电系统容量配置与优化[J].电力系统保护与控制,2014,42(17):31-37.[点击复制] |
| ZHENG Ling-wei,LIU Shi-rong,ZHOU Wen-jun,LI Jin-long,WU Shun-yu.Capacity configuration and optimization of grid-connected renewable energy power generation system[J].Power System Protection and Control,2014,42(17):31-37[点击复制] |
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| 摘要: |
| 为了准确地配置并网型分布式发电系统容量，针对并网型风光混合发电系统，给出一种基于发电效率衰减、分时电价和负荷逐年增长等条件的并网型分布式发电系统容量优化配置方法。利用NASA气象网站的风速和日照辐射资料，生成单位容量风光电源的年度出力曲线，根据风光电源的年度衰减性，在单一电价、分段电价和本地消纳的不同应用场景下，对固定负荷和逐年增长负荷建立起分布式电源容量优化模型。在实例分析中，通过遗传算法求解，验证了该方法的有效性和正确性。该模型更加贴近实际工程应用，并能很好地扩展到包含多种分布式电源的并网型发电系统中 |
| 关键词: 分布式电源 风力发电 光伏发电 电源容量优化 |
| DOI： |
| 投稿时间：2014-01-22修订日期：2014-03-27 |
| 基金项目:浙江省科技计划重大专项(2009C11020)；浙江省自然科学基金（LQ12E07001） |
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| Capacity configuration and optimization of grid-connected renewable energy power generation system |
| ZHENG Ling-wei,LIU Shi-rong,ZHOU Wen-jun,LI Jin-long,WU Shun-yu |
| (Institute of Automation, East China University of Science and Technology, Shanghai 200237, China;Institute of Automation, East China University of Science and Technology, Shanghai 200237, China; Institute of Electrical Engineering & Automation, Hangzhou Dianzi University, Hangzhou 310018, China; Research Center of Detecting Instruments and Automati;Institute of Electrical Engineering & Automation, Hangzhou Dianzi University, Hangzhou 310018, China; Research Center of Detecting Instruments and Automation Systems Integration Technology, The Ministry of Education, Hangzhou 310018, China) |
| Abstract: |
| In order to configure accurately the capacity of grid-connected distributed generation system, a method of distributed generation system capacity optimization and configuration based on power generation efficiency attenuation, time-of-use electricity price and load increasing year by year which aims at the grid-connected wind-photovoltaic hybrid power generation system is given. Using the wind speed and sunshine radiation data of NASA's meteorological sites, annual output curve of unit capacity wind-photovoltaic power supply is obtained, the distributed generation planning model is established aiming at fixed load and increasing load in the scenario of single electricity price, time-of-use electricity price and elimination on the spot. In the case analysis, genetic algorithm is used to solve the equation, the method’s validity and correctness are verified. The model is more close to the actual engineering application, and it is easy to expand to grid-connected power generation system that includes a variety of distributed power, it is helpful for the application and promotion of grid-connected distributed generation system. |
| Key words: distributed generation wind power photovoltaic power power capacity optimization |
