摘要
能源短缺和低碳减排背景下,国内碳排放权交易制度的实施和欧盟碳边境调节机制(carbonborderadjustment mechanism,CBAM)政策(碳关税)的确立,大大增加了发电企业和电力用户的发用电成本压力。如何在新的市场环境中作出最优决策,是电力市场各主体亟须考虑的实际问题。针对这一问题,该文提出了考虑碳交易和碳关税的电力市场主体最优决策模型。该模型在发用两侧分别考虑了碳市场中的碳配额制度、预测碳价水平和碳关税中的间接电力碳排放对市场主体购售电碳成本的影响,并采用金豺优化算法求解不同碳价水平、碳关税价格及征税比例等多种情景下市场各主体的决策行为。通过仿真结果表明了在碳交易和碳关税的双重影响下,用户更趋向于与可再生能源(renewableenergy sources,RES)发电商交易,促进了RES的发展。
In the context of energy shortage and low carbon emission reduction,the implementation of the domestic carbon emission trading system and the establishment of the EU CBAM have greatly increased the pressure on the power generation cost of the power producing enterprises and the power users.How to make the optimal decisions in the new market environment is a practical problem for the main players of the power market to consider urgently.To solve this problem,this paper proposes an optimal decision-making model of the electricity market subjects considering carbon trading and the CBAM(Carbon Border Adjustment Mechanism).The model takes into account the impacts of the carbon quota system in the carbon market,the predicted carbon prices,the indirect power carbon emissions on the carbon costs of the electricity purchase and sales of the market entities on both sides of the power generation and consumption.The Golden Jackal optimization algorithm is used to solve the decision-making behavior of various market entities under various scenarios such as different carbon price levels,carbon tariff prices and tax rates.The simulation results show that under the dual influence of carbon trading and carbon tariffs,the users tend to trade with the renewable energy source producers,which promotes the development of the RES(renewable energy sources).
作者
刘阳
刘继春
杨语嫣
LIU Yang;LIU Jichun;YANG Yuyan(College of Electrical Engineering,Sichuan University,Chengdu 610065,Sichuan Province,China)
出处
《电网技术》
EI
CSCD
北大核心
2023年第8期3111-3120,共10页
Power System Technology
基金
国家自然科学基金项目“竞争性售电服务市场基础理论与关键技术”(U2066209)。
关键词
碳市场
电力市场
碳价预测
碳关税
金豺优化算法
carbon market
electricity market
carbon price prediction
carbon tariff
golden jackal optimization algorithm
