Improved Krill Herd Algorithm with Novel Constraint Handling Method for Solving Optimal Power Flow Problems
AbstractAs one of the most important tools used in operation and planning of power systems, the optimal power flow (OPF) problem considering the economy and security is large-scale, complex and hard to solve. In this paper, an improved krill herd algorithm (IKHA) has been proposed. In IKHA, the onlooker search mechanism is introduced to reduce the probability of falling into local optimum; and the parameter values of the proposed algorithm including inertia weight and step-length scale factor are varied according to the iteration of evolutionary process, which improves the exploration and exploitation capabilities. Moreover, a novel constraint handling method is proposed to guide the individual to the feasible space and ensure that the optimal solution satisfies the security constraints. Then, IKHA is combined with the novel constraint handling method to solve the multi-constrained OPF problem, and its performance is tested on the IEEE 30 bus, IEEE 57 bus and IEEE 118 bus systems for 10 different simulation cases containing linear and non-linear objective functions. The simulation results demonstrate that the proposed method can solve the OPF problem successfully and obtain better solutions compared with other methods reported in the recent literatures, which prove the feasibility and effectiveness of the improvements in this work. View Full-Text
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Chen, G.; Lu, Z.; Zhang, Z. Improved Krill Herd Algorithm with Novel Constraint Handling Method for Solving Optimal Power Flow Problems. Energies 2018, 11, 76.
Chen G, Lu Z, Zhang Z. Improved Krill Herd Algorithm with Novel Constraint Handling Method for Solving Optimal Power Flow Problems. Energies. 2018; 11(1):76.Chicago/Turabian Style
Chen, Gonggui; Lu, Zhengmei; Zhang, Zhizhong. 2018. "Improved Krill Herd Algorithm with Novel Constraint Handling Method for Solving Optimal Power Flow Problems." Energies 11, no. 1: 76.
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