Power flow control in grid-connected microgrid operation using Particle Swarm Optimization under variable load conditions
Power flow control in grid-connected microgrid operation using Particle Swarm Optimization under variable load conditions
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DOI：
10.1016/j.ijepes.2012.12.017
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发表时间：
2013-07
影响因子：
5.2
通讯作者：
W. Al-Saedi;S. Lachowicz;D. Habibi;O. Bass
中科院分区：
文献类型：
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作者：
W. Al-Saedi;S. Lachowicz;D. Habibi;O. Bass
提出了一种基于实时自校正方法的微电网最优潮流控制器。其目的是控制主电网和由分布式发电（DG）单元组成的微电网之间的有功功率和无功功率的流动。分布式发电机组以期望的比例共享功率是负荷变化过程中考虑的主要性能参数。本文还示出了控制器的响应的情况下，负载是高于或大大低于DG单元的额定功率。在这项工作中，控制器方案是由一个内部的电流控制环和一个外部的功率控制环的基础上的同步参考框架和传统的PI调节器。功率控制器是针对有功-无功功率（PQ）控制策略而设计的。粒子群优化算法（PSO）是一种智能搜索算法，用于功率控制参数的实时自整定。在本文中，所提出的策略是所需的负载功率平均分配微电网和公用事业公司之间的基础上，在负载变化的粒子群算法。当负载大于由微电网产生的功率时，公用事业公司供应差功率，而当负载小于由微电网产生的功率时，公用事业公司将额外的功率注入电网。结果表明，所提出的控制器提供了良好的响应，并证明了所提出的策略的有效性。
This paper presents an optimal power flow controller for a utility connected microgrid based on a real-time self-tuning method. The purpose is to control the flow of the active and reactive power between the main grid and the microgrid composed of Distributed Generation (DG) units. Sharing power at the desired ratio by the DG units is the main performance parameter which is considered during the load change. This paper also shows the response of the controller in situations, where the load is either higher or greatly lower than the rated power of the DG unit. In this work, the controller scheme is composed of an inner current control loop and an outer power control loop based on a synchronous reference frame and the conventional PI regulators. The power controller is designed for active–reactive power (PQ) control strategy. Particle Swarm Optimization (PSO) is an intelligent searching algorithm that is applied for real-time self-tuning of the power control parameters. In this paper, the proposed strategy is that the required load power is shared equally between the microgrid and the utility based on the PSO algorithm during the load change. The utility supplies the difference power when the load is more than the power generated by the microgrid, while it injects the extra power to the grid when the load is less than the power generated by the microgrid. The results show that the proposed controller offers an excellent response and proves the validity of the proposed strategy.