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Optimal reactive power resources sizing for power system operations enhancement based on improved grey wolf optimiser

机译:基于改进的灰狼优化器的电力系统优化无功优化设计

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摘要

In recent years, optimal sizing and location of reactive power resources are drawing much attention to help the operators of the utilities to enhance the power system operations. Therefore, this work presents a new version of grey wolf optimiser (GWO) to solve the problem of optimal reactive power resources sizing for power system operation enhancement. The proposed method which called improved grey wolf optimiser (IGWO) can be derived by modifying the exploration-exploitation balance in the conventional GWO to enhance its rate of convergence. Also, the weighted distance strategy is employed in the proposed IGWO to overcome the drawback of the conventional GWO. Optimal reactive power resources sizing problem is non-linear and non-convex optimisation problem. To solve this problem, different objective functions are used. These objective functions are minimisation of generating cost, minimisation of transmission power loss and voltage profile improvement. The validity and superiority of the proposed IGWO method are tested using three standard IEEE systems for normal and contingency conditions. Then the results are compared with those obtained from other recently published algorithms. The simulation results show that the proposed IGWO method is more accurate and efficient than other recently published algorithms.
机译:近年来,无功功率的最佳尺寸和位置引起了人们的广泛关注,以帮助公用事业公司的运营商改善电力系统的运行。因此,这项工作提出了一种新版本的灰狼优化器(GWO),以解决优化无功功率资源规模以提高电力系统运行的问题。可以通过修改常规GWO中的勘探开发平衡来提高其收敛速度,从而得出所提出的改进灰狼优化器(IGWO)方法。而且,在提出的IGWO中采用了加权距离策略以克服常规GWO的缺点。最优无功资源规模确定问题是非线性和非凸优化问题。为了解决这个问题,使用了不同的目标函数。这些目标功能是最小化发电成本,最小化传输功率损耗和改善电压曲线。在正常和偶发情况下,使用三种标准IEEE系统测试了提出的IGWO方法的有效性和优越性。然后将结果与从其他最近发布的算法获得的结果进行比较。仿真结果表明,提出的IGWO方法比其他最近发表的算法更准确,更有效。

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