| 摘 要: 本文以蓄电池损耗最低、购电费用最低和削峰填谷后负荷曲线的方差值最小为目标建立削峰填谷用储能 系统运行优化模型。利用多目标粒子群优化算法进行寻优，求解过程中针对粒子超出可行域的问题提出了一种改进的多 目标粒子群算法，使该算法能求解线性约束多目标优化问题，并采用TOPSIS法从最优Pareto解集中选取最优方案。最 后建立负荷与削峰填谷用储能系统模型进行仿真，结果表明该方法的有效性。 |
| 关键词: 削峰填谷；多目标粒子群算法；储能系统；TOPSIS法 |
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中图分类号: TP919
文献标识码: A
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| 基金项目: 国家自然科学基金(51407114);上海市自然科学基金(15ZR1418000);上海市科技创新行动计划项目(16DZ0503300). |
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| Economic Operation Strategy of the Energy Storage System for Peak Shaving and Valley Filling Based on Improved Particle Swarm Optimization Algorithm |
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LI Mengmeng,WANG Yufei,XUE Hua
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( Shanghai University of Electric Power, Shanghai 200090, China)
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| Abstract: The paper establishes the operation optimization model of the energy storage system for peaking shaving and valley filling,aiming to achieving the minimum battery loss,the lowest power purchase cost and the minimum variance value of load curves after peak shaving and valley filling.Based on Multiple Objective Particle Swarm Optimizer (MOPSO),the paper proposes an improved MOPSO to solve the problem of particle going beyond the feasible region.The algorithm is effective in the multi-objective optimization with linear constraints.The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is applied to select the optimal scheme from the optimal Pareto solution set.Finally,the energy storage system model with load peak shaving and valley filling is constructed,and the simulation results have verified the effectiveness of the proposed method. |
| Keywords: peak shaving and valley filling;Multiple Objective Particle Swarm Optimizer (MOPSO);energy storage system;the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) |
