An Improved Marine Predators Algorithm for Optimal Reactive Power Dispatch with Load and Wind-Solar Power Uncertainties

• Published in: IEEE access 2022, Vol.10, p.1-1
• Main Authors: Zhao, Jian, Li, Liying, Yu, Jiaxin, Li, Zhiwu
• Format: Article
• Language: English
• Subjects: Algorithms; Alternative energy sources; Computer simulation; Electrical loads; Energy sources; Epsilon constraint handling; Heuristic methods; marine predators algorithm; Monte Carlo simulation; optimal reactive power dispatch; Optimization; Power dispatch; Predators; Probability density functions; Reactive power; renewable energy; Solar energy; The ε-constraint handling; Uncertainty; Wind power
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2022.3224744

With the growing usage of renewable energy resources, the fluctuation and randomness of solar and wind power output have a significant influence on the safe and stable operation of a power system. Deciding how to deal with these uncertainties has become a hot topic for researchers and practitioners. In this paper, a hybrid improved marine predators algorithm is proposed to solve the optimal reactive power dispatch problem with load demand, and wind-solar power uncertainties. The ε constrained technique is adopted to deal with the constraints in the optimization problem. The uncertainty factors in the system are modeled using appropriate probability density functions. The backward reduction method is used to determine a representative set of scenarios from a large number of scenarios produced by a Monte Carlo simulation method. IEEE 30-bus test system is utilized to verify the proposed algorithm. The simulation results demonstrate that the algorithm can produce better results than other advanced metaheuristic algorithms.