Optimal power flow incorporating wind energy and load reduction by BH algorithm and KOA algorithm

Z. Hasan, M. El-Hawary
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Abstract

Optimal power flow (OPF) is a nonlinear, nonconvex and large-scale optimization problem and one of the most important optimization problems in power system operation and control. In smart grid the OPF objectives are modified to minimizing the total fuel cost and the greenhouse gases emissions. One way of achieving this objective is by the integration of significant amount renewable energy and the integration of load reduction as demand side management measure. In this paper, OPF will be modeled and solved for smart grid network assuming significant integration of wind energy to the network and the load reduction programs are active using Khums optimization algorithm (KOA) and black hole optimization algorithm (BH). The IEEE 30-Bus system is used to illustrate performance of the proposed algorithms and results are compared with those in literature.
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利用BH算法和KOA算法优化风电减载潮流
最优潮流问题是一个非线性、非凸、大规模的优化问题,是电力系统运行与控制中最重要的优化问题之一。在智能电网中,OPF目标被修改为最小化总燃料成本和温室气体排放。实现这一目标的一种方法是将大量可再生能源和减少负荷作为需求侧管理措施相结合。本文将采用Khums优化算法(KOA)和黑洞优化算法(BH)对智能电网的OPF进行建模和求解,假设风电大量集成到电网中,并且负荷削减方案是主动的。用IEEE 30总线系统来说明所提算法的性能,并与文献中的结果进行了比较。
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