综合智慧能源2026，Vol.48Issue(3)：37-46,10.DOI:10.3969/j.issn.2097-0706.2026.03.004
基于APO-PSO的风光火储联合发电系统低碳优化调度
Low-carbon optimal scheduling of wind-solar-thermal-storage combined power generation systems based on APO-PSO
摘要
Abstract
Integrated power generation systems effectively manage distributed energy resources and reduce greenhouse gas emissions.However,current research predominantly prioritizes economic viability,with limited consideration given to energy conservation,emission reduction,and related market-oriented mechanisms,and lacks adaptive modeling of existing mechanisms in response to recent policy changes.Additionally,the stochasticity and volatility of renewable energy sources remain critical challenges to be addressed.Consequently,an optimal dispatch strategy for a wind-solar-thermal-storage combined power generation system considering a combined renewable energy certificate and stepped carbon trading mechanism was proposed,where mechanism design and model construction were deeply coupled.From the perspective of market-oriented mechanisms,renewable energy certificates were categorized into tradable and non-tradable types,followed by their deep integration into the trading framework.By leveraging stochastic chance-constrained programming to characterize renewable energy output uncertainty,a joint dispatch model comprising gas turbines,photovoltaics,wind power,and energy storage systems(ESS)was established.Furthermore,a hybrid artificial protozoa optimizer(APO)-particle swarm optimization(PSO)algorithm merging the APO and PSO was developed to enhance solution accuracy and convergence speed.The results demonstrated that the proposed method significantly enhanced renewable energy utilization and reduced carbon emissions.Moreover,the strategy fully mobilized the ESS to smooth power fluctuations,achieved peak shaving and valley filling,and exhibited improved stability and economic efficiency in power system operations.关键词
绿色证书交易/阶梯型碳交易/碳排放/优化调度/随机机会约束规划方法/人工原生动物优化器/风-光-火-储联合发电Key words
renewable energy certificate trading/stepped carbon trading/carbon emissions/optimal scheduling/stochastic chance-constrained programming/artificial protozoa optimizer/wind-solar-thermal-storage combined power generation分类
能源科技引用本文复制引用
穆雨彤,王巍..基于APO-PSO的风光火储联合发电系统低碳优化调度[J].综合智慧能源,2026,48(3):37-46,10.基金项目
黑龙江省自然科学基金项目(LC201407) Natural Science Foundation of Heilongjiang Province(LC201407) （LC201407）
