考虑小时负荷变化的平衡配电网分布式发电优化配置的元启发式算法

S. Saha, V. Mukherjee
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引用次数: 1

摘要

针对径向配电系统中分布式发电机组的优化配置问题,提出了一种新的优化技术——多目标修正共生生物搜索(MOMSOS)。考虑将太阳能光伏、风力涡轮机和生物质能系统等三种可再生DG机组纳入RDS。DG集成过程以年能量损失、年投资和运行成本、年购电成本和系统总电压偏差四个运行目标的最小化为指导。在本研究中,可再生能源发电和系统负荷的小时变化被考虑为现实的规划。在69节点RDS上的仿真结果表明了该方法的有效性,在保证系统性能的同时,成功地确定了DG单元的最佳位置和大小。
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A Novel Meta-heuristic for Optimal Allocation of Distributed Generation in Balanced Distribution Network Considering Hourly Load Variation
In this paper, a novel optimization technique, namely, multi-objective modified symbiotic organisms search (MOMSOS) is proposed for optimal allocation of distributed generation (DG) units in radial distribution system (RDS). Three renewable DG units, such as, solar photovoltaic, wind turbine and biomass system are considered for integration into the RDS. The process of DG integration is guided by minimization of four operational objectives, such as, annual energy loss, annual investment and operating cost, annual electricity purchase cost and total voltage deviation of the system. In this study the hourly variation in generation of renewable sources and system load are considered for realistic planning. The simulation results on 69-node RDS show the effectiveness of the proposed approach as it successfully determines the optimal locations and sizes of the DG units while im proving the system performance.
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