Pareto-Based Multi-objective Reactive Power Optimization for Power Grid with High-Penetration Wind and Solar Renewable Energies

doi:10.12204/j.issn.1000-7229.2020.07.013

Abstract

Abstract: To adapt the trend of high-penetration renewable energies paralleled in power grid， this paper constructs a multi-objective reactive power optimization for power grid with the controlled participation of high-penetration wind and solar renewable energies. Particularly， the reactive power regulation capacities of renewable energies are evaluated according to the wind speed， solar irradiation， and temperature in different time. To obtain the optimal dispatch scheme of transformer taps， shunt capacitor states， voltage outputs of generators， and reactive power outputs of renewable energies， a multi-objective salp swarm algorithm （MSSA） is employed for the multi-objective reactive power optimization. Then an improved ideal-point based decision method is designed to select a compromise solution among multiple non-dominated points， thus three objectives of power loss， voltage deviation， and static voltage stability margin can be properly balanced. Finally， an extended IEEE 9-bus system and an extended IEEE 39-bus system are used to evaluate the performance of the proposed algorithm compared with conventional multi-objective intelligent optimization algorithms. Simulation results demonstrate that the proposed algorithm can obtain a widely spread and well-distributed Pareto front compared with conventional multi-objective optimization algorithms. Moreover， the improved ideal-point based decision method not only can effectively reduce the power loss and voltage deviation， but also can improve the static voltage stability margin.

Key words: wind and solar renewable energies, Pareto, multi-objective optimization, reactive power optimization, multi-objective salp swarm algorithm （MSSA）

CLC Number:

TM 76

YANG Lei，WU Chen，HUANG Wei，GUO Cheng，XIANG Chuan，HE Xin，XING Chao，XI Xinze，ZHOU Xin，YANG Bo，ZHANG Xiaoshun. Pareto-Based Multi-objective Reactive Power Optimization for Power Grid with High-Penetration Wind and Solar Renewable Energies[J]. Electric Power Construction, doi: 10.12204/j.issn.1000-7229.2020.07.013.

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