Energy Optimal Scheduling Strategy for Receiving End Grid Based on Improved Multi-objective Particle Swarm Optimization Algorithm

2023 IEEE International Conference on Power Science and Technology (ICPST) Pub Date : 2023-05-05 DOI:10.1109/ICPST56889.2023.10165437

Bingbin Chen, R. Chen, Wengeng Wu, Ji Wang, Dongxue Zhao

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Abstract

In order to improve the stability and economy of the coordinated operation of source-grid-load-storage at the end of the distribution network under the novel power system structure, this paper proposes a receiving end grid energy optimal scheduling strategy based on an improved multi-objective particle swarm optimization algorithm. First, the power characteristics of each power equipment of the receiving end grid are analyzed. A mathematical model of the receiving end grid is established, which is composed of distributed power supply, traditional power grid, and energy storage system. Then, the operating, environmental, and total costs of the receiving end grid are optimized. The mathematical model of multi-objective optimal dispatching of receiving end grid is established. Finally, the improved multi-objective particle swarm optimization algorithm is used to solve the model, and an energy optimal scheduling strategy is proposed. The simulation results show that the dispatching model and optimization algorithm can realize the economy, environmental protection, and reliability of receiving end grid dispatching.

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基于改进多目标粒子群算法的接收端电网能量优化调度策略

为了提高新型电力系统结构下配电网端源-网-蓄负荷协同运行的稳定性和经济性，提出了一种基于改进多目标粒子群优化算法的接收端电网能量优化调度策略。首先，分析了接收端电网各电力设备的功率特性。建立了由分布式电源、传统电网和储能系统组成的接收端电网的数学模型。然后对接收端电网的运行成本、环境成本和总成本进行了优化。建立了接收端电网多目标优化调度的数学模型。最后，采用改进的多目标粒子群优化算法对模型进行求解，提出了一种能量最优调度策略。仿真结果表明，该调度模型和优化算法能够实现接收端电网调度的经济性、环保性和可靠性。

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来源期刊

2023 IEEE International Conference on Power Science and Technology (ICPST)

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