The significance and current situation of reactive power optimization

Bi, Hanwen

doi:10.1063/1.5116464

Cited by 1 publication

(2 citation statements)

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“…With the proposal of the smart grid, it has become a developing trend that distributed generation (DG) gradually joins and becomes an essential part of the power distribution system [1,2]. Experts in the power industry generally agree that the adoption of DG technology is the main way to save money, reduce primary energy consumption, and improve the flexibility and stability of power systems [3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

“…Since the multi-objective reactive power optimization problem of distribution network with DG is a very complex non-linear problem, domestic and foreign scholars have proposed various simplified mathematical models and optimization algorithms to solve it. Many heuristics have been applied to reactive power optimization problems, such as genetic algorithms (GA) [5,10], particle swarm algorithms (PSO) [6,11,12], and deep learning algorithms [13]. Meanwhile, many scholars have improved these algorithms, which have improved the speed and accuracy of the algorithms to solve reactive power optimization problems to different degrees [14,15].…”

Section: Introductionmentioning

confidence: 99%

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Distributed Integrated Synthetic Adaptive Multi-Objective Reactive Power Optimization

Song

et al. 2022

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Reactive power is the core problem of voltage stability and economical operation in power systems. Aiming at the problem that multi-objective normalization reactive power optimization function is dependent on weight, an integrated synthesis of adaptive multi-objective particle swarm optimization (ISAMOPSO) is proposed to achieve weight adaptive. Through seven test functions and three algorithm comparison experiments, it is proved that the ISAMOPSO algorithm has stronger global search capability and better convergence. Considering the optimal access position and capacity of distributed generation (DG), the ISAMOPSO algorithm is used for three-objective reactive power optimization. Finally, the results indicate that the ISAMOPSO algorithm can not only provide a variety of optimization schemes to meet different needs, but also realize dynamic reactive power optimization, which further proves that the algorithm can provide effective technical support for solving reactive power optimization problems in practical engineering.

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