Hierarchical Optimization Strategy Considering Regulation of Electric-Fused Magnesium High-Energy-Consuming Load and Deep Peak Regulation of Thermal Power

Kexin Ren, Yibo Wang (), Shunjiang Wang, Chuang Liu and Xudong Zhao
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Kexin Ren: School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China
Yibo Wang: School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China
Shunjiang Wang: State Grid Liaoning Electric Power Co., Ltd., Shenyang 110004, China
Chuang Liu: School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China
Xudong Zhao: School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China

Energies, 2025, vol. 18, issue 20, 1-19

Abstract: The randomness and volatility of wind power increase peak regulation pressure, leading to wind curtailment despite the deep peak regulation efforts of thermal power units. By integrating conventional power source dispatch and high-energy-consuming load configuration, a two-layer optimization model is developed to maximize wind curtailment absorption and minimize thermal power deep peak regulation costs. The model first analyzes the fused magnesium load’s operating characteristics and its dispatch-participation model, then combines with the thermal power deep peak regulation model for hierarchical joint peak regulation. Applying the method to an actual regional system via CPLEX shows that it reduces wind curtailment, optimizes thermal power deep peak regulation, and improves power generation economic efficiency.

Keywords: high energy-consuming load of electrically fused magnesium; wind power consumption; deep regulation of thermal power; hierarchical optimization; combined peak regulation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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