电力科技与环保2026，Vol.42Issue(4)：574-581,8.DOI:10.19944/j.eptep.1674-8069.2026.04.006
基于数据驱动的厂级负荷分配优化策略研究
Data driven based strategy of plant-level load dispatch for the coal-fired power plant
摘要
Abstract
[Objective]Driven by the carbon peaking and carbon neutrality goals,coal-fired units are transitioning from baseload to flexible regulation power sources,resulting in prolonged low-load operation and a significant increase in net standard coal consumption.Scientifically allocating loads among multiple units to minimize plant-level energy consumption has become a critical issue for the thermal power industry.[Methods]This study takes six units of three types(1 000,600 and 300 MW)from a virtual power plant as the research objects,a data-driven plant-level load optimization strategy is proposed.Grey relational analysis is employed to screen key parameters affecting the net standard coal consumption rate,and an XGBoost-based coal consumption characteristic prediction model is constructed.With the objective of minimizing the plant-level net standard coal consumption rate,an adaptive parameter differential evolution algorithm based on historical success is introduced to dynamically solve the optimal load dispatch scheme satisfying grid load commands.[Results]The results indicate that the relative error of the proposed coal consumption rate prediction model fluctuates within 0.05%.The plant-level load allocation optimization strategy proposed in this paper achieves minimized overall energy consumption under varying total load demands.The coal-saving potential exhibits a trend of first increasing and then decreasing with the total load.When the plant-level load reaches 2 600 MW,the net standard coal consumption rate under the optimized load dispatch is only 312.29 g/(kW·h).Compared to conventional dispatch modes,it demonstrates a maximum coal-saving potential of 1.92 g/(kW·h),effectively reducing both plant-wide fuel consumption and carbon emissions.[Conclusion]The proposed data-driven plant-level load allocation strategy proposed herein offers a low-cost,high-efficiency technical pathway for thermal power plants to unlock energy-saving potential under flexible operating conditions.This provides support for establishing a new power system that is clean,low-carbon,safe,and efficient.关键词
厂级负荷分配/灰色关联/极端梯度提升算法/SHADE算法Key words
load dispatching/grey correlation analysis/extreme gradient boosting/SHADE algorithm分类
能源科技引用本文复制引用
刁冰,毕志颖,徐婧..基于数据驱动的厂级负荷分配优化策略研究[J].电力科技与环保,2026,42(4):574-581,8.基金项目
山西省重点研发计划项目(202502090302015) （202502090302015）
