| 引用本文: | 齐 郑,徐希茜,熊 巍,陈艳波.基于变时段设计改进多目标差分进化算法的风/光/火/储日前优化调度[J].电力系统保护与控制,2024,52(16):62-71.[点击复制] |
| QI Zheng,XU Xixi,XIONG Wei,CHEN Yanbo.An improved multi objective differential evolution algorithm based on variable time period design for a wind/photovoltaic/thermal/storage system day ahead optimization scheduling[J].Power System Protection and Control,2024,52(16):62-71[点击复制] |
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| 摘要: |
| 在高比例新能源馈入的新型电力系统中，新能源出力的不确定性导致火电难以满足调度计划的精度需求，风/光/火/储系统的经济调度求解算法面临严峻挑战。为此，提出一种基于变时段设计的多目标差分进化算法。首先按各时段负荷特征构建风/光/火/储系统的变时段日前调度规则。进而以系统运行经济成本与污染排放量为目标，基于多目标差分进化算法求解变时段系统日前调度模型的Pareto解集。最后，用IEEE 39节点系统进行测试。结果表明在风、光、储与火电的约束条件均符合校验的情形下，相较于其他算法，该方法使计算结果更加优化，火电机组出力跟踪调度计划效果显著提高，验证了所提方法的有效性。 |
| 关键词: 风/光/火/储系统 变时段设计 日前调度计划 多目标差分进化算法 优化调度 |
| DOI：10.19783/j.cnki.pspc.240128 |
| 投稿时间：2024-01-26修订日期：2024-04-03 |
| 基金项目:国家自然科学基金项目资助(52077076) |
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| An improved multi objective differential evolution algorithm based on variable time period design for a wind/photovoltaic/thermal/storage system day ahead optimization scheduling |
| QI Zheng1,XU Xixi1,XIONG Wei2,CHEN Yanbo1 |
| (1. School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China;
2. Shaanxi Yellow River Group Co., Ltd., Xi’an 710005, China) |
| Abstract: |
| In the new power system, with a high proportion of new energy, the uncertainty of new energy output not only makes it difficult for thermal power to meet the accuracy requirements of scheduling plans, but also poses serious challenges to the economic scheduling algorithm for wind/photovoltaic/thermal/storage systems. For this reason, a multi-objective differential evolution algorithm based on variable time period design is proposed. First, the variable time period day ahead scheduling rules of a wind/photovoltaic/thermal/storage system are constructed according to the load characteristics of each time period. Then, taking the economic cost of system operation and the amount of pollution emission as the objectives, the Pareto solution set of the day ahead scheduling model of the system with variable time periods is solved based on the multi-objective differential evolution algorithm. Finally, the IEEE 39-bus system is tested. The results show that, under the constraint conditions of wind, photovoltaic power, storage, and thermal power all meet the verification criteria. Compared to other algorithms, the objective function obtained by the proposed method tends to be optimal, and the effectiveness of the thermal power unit output tracking scheduling plan is significantly improved, verifying the effectiveness of the proposed method. |
| Key words: wind/photovoltaic/thermal/storage system variable time period design day ahead scheduling plan multi-objective differential evolution algorithm optimized dispatching |
