Open Access

ARTICLE

Optimization and Scheduling of Green Power System Consumption Based on Multi-Device Coordination and Multi-Objective Optimization

Liang Tang¹, Hongwei Wang¹, Xinyuan Zhu¹, Jiying Liu^2,*, Kaiyue Li^2,*
1 Division of New Energy Business, Shandong Electric Power Engineering Consulting Institute Co., Ltd., Jinan, 250013, China
2 School of Thermal Engineering, Shandong Jianzhu University, Jinan, 250101, China
* Corresponding Author: Jiying Liu. Email: ; Kaiyue Li. Email:

Energy Engineering https://doi.org/10.32604/ee.2025.063918

Received 28 January 2025; Accepted 14 April 2025; Published online 27 April 2025

Abstract

The intermittency and volatility of wind and photovoltaic power generation exacerbate issues such as wind and solar curtailment, hindering the efficient utilization of renewable energy and the low-carbon development of energy systems. To enhance the consumption capacity of green power, the green power system consumption optimization scheduling model (GPS-COSM) is proposed, which comprehensively integrates green power system, electric boiler, combined heat and power unit, thermal energy storage, and electrical energy storage. The optimization objectives are to minimize operating cost, minimize carbon emission, and maximize the consumption of wind and solar curtailment. The multi-objective particle swarm optimization algorithm is employed to solve the model, and a fuzzy membership function is introduced to evaluate the satisfaction level of the Pareto optimal solution set, thereby selecting the optimal compromise solution to achieve a dynamic balance among economic efficiency, environmental friendliness, and energy utilization efficiency. Three typical operating modes are designed for comparative analysis. The results demonstrate that the mode involving the coordinated operation of electric boiler, thermal energy storage, and electrical energy storage performs the best in terms of economic efficiency, environmental friendliness, and renewable energy utilization efficiency, achieving the wind and solar curtailment consumption rate of 99.58%. The application of electric boiler significantly enhances the direct accommodation capacity of the green power system. Thermal energy storage optimizes intertemporal regulation, while electrical energy storage strengthens the system’s dynamic regulation capability. The coordinated optimization of multiple devices significantly reduces reliance on fossil fuels.

---

Keywords

Multi-objective optimization scheduling model; multi-objective particle swarm optimization algorithm; consumption capacity of green power; wind and solar curtailment; coordinated optimization of multiple devices

---