考虑碳排放配额和碳交易的新能源电力系统日前优化调度
Day-Ahead Optimal Scheduling of New Energy Power System Considering Carbon Emission Quota and Carbon Trading
魏伟 1叶利 1方毅 1汪应春 1刘奕舟2
作者信息
- 1. 国网湖北省电力有限公司营销服务中心(计量中心),湖北武汉 443080
- 2. 三峡大学电气与新能源学院,湖北宜昌 443002
- 折叠
摘要
在电力系统碳交易市场化的背景下,研究一种科学、有效的碳排放额度分配策略,具有重要的理论和实际意义.该文在新能源大规模接入的现状下,考虑限制排放主体的碳排放量,并在排放主体间建立碳交易模型,提出一种考虑碳排放配额和碳交易的日前优化调度方法.分别构建火电和风电碳交易费用的模型,提出一种基于熵值法的碳排放额度分配策略,对区域电网基准线排放因子的权重进行重新分配;考虑到因风电接入而造成常规火电机组产生的额外碳排放量,在碳交易价格预测的基础上,计算不同类型机组的碳交易费用;以调度时段内系统总费用最小为优化目标,构建考虑碳排放交易的日前优化调度模型,并求解该模型.仿真结果验证了所提方法的正确性和有效性.
Abstract
In the context of the marketization of carbon trading in the power system,it is of great theoretical and practical significance to study a scientific and effective carbon emission quota allocation strategy.To this end,under the current situation of large-scale access of new energy,in the purpose to limit the emission of various carbon emitters and construct a carbon trading model among them,this paper proposes a day-ahead optimal scheduling method taking into account carbon emission quotas and carbon trading.Firstly,the carbon transaction cost models of thermal power and wind power are constructed respectively,and a carbon emission quota allocation strategy based on entropy method is proposed to redistribute the weights of baseline emission factors for the regional power grid.Second,considering the additional carbon emissions of conventional thermal generating units caused by wind power access,the carbon trading costs of different types for generation units are calculated on the basis of carbon trading price prediction.Thereafter,a day-ahead optimal scheduling model considering carbon emissions trading is constructed with the objective of minimizing the total cost of the system in the scheduling period.The simulation results have verified the correctness and effectiveness of the proposed method.
关键词
碳交易/日前优化调度/碳排放配额分配/熵值法Key words
carbon trading/day-ahead optimal scheduling/allocation of carbon emission credits/entropy method引用本文复制引用
基金项目
国家自然科学基金(U20A20306)
国家电网湖北省电力公司科技项目(U20A20306)
出版年
2024
NETL
NSTL
维普
万方数据