电力系统保护与控制2025，Vol.53Issue(5)：1-10,10.DOI:10.19783/j.cnki.pspc.240712
电-碳-绿证市场耦合下的源-荷双层交互优化
Optimization of source-load bilayer interaction in the coupling of electricity-carbon-green certificate markets
摘要
Abstract
Under the"dual carbon"policy,it is crucial to address how market participants can integrate electricity trading,carbon trading,and green certificate trading to maximize their profits,reduce system carbon emissions,and increase renewable energy consumption.To tackle this issue,a multi-market coupled source-load bi-level optimization model is proposed.First,to strengthen the coupling between the carbon market and other markets,carbon allowances are allocated based on the proportion of thermal power generation.The incremental variation rate of carbon allowances with thermal power output is derived and incorporated into the marginal cost of carbon trading for thermal power producers.To stimulate activity in the green certificate market,a tiered penalty mechanism is introduced for insufficient green certificate purchases.Given the uncertainty of wind power output,a stochastic optimization method is used to construct wind power output scenarios.These are then transformed into deterministic scenarios by the K-medoids method.Subsequently,a bilayer interactive optimization model of electric-carbon-green certificate coupling is established.The upper-level objective minimizes market participants'operating cost,while the lower-level objective maximizes social welfare.Finally,based on an analysis of the PJM5 node system,the effectiveness of the proposed model is verified.The results demonstrate that the proposed method can optimize resource allocation,reduce system carbon emissions,and improve renewable energy consumption.关键词
电力市场/碳市场/绿证市场/市场耦合/双层优化Key words
electricity market/carbon market/green certificate market/market coupling/bilayer optimization引用本文复制引用
张国良,蔺红,田易之..电-碳-绿证市场耦合下的源-荷双层交互优化[J].电力系统保护与控制,2025,53(5):1-10,10.基金项目
This work is supported by the National Natural Science Foundation of China(No.52367012). 国家自然科学基金项目资助(52367012) （No.52367012）
新疆维吾尔自治区重点研发专项资助(2022B01020-3) （2022B01020-3）
