刘明涛¹, 谢俊¹(), 张秋艳¹, 包长玉¹, 常逸凡¹, 段佳南¹, 施雄华², 鲍永²

1.河海大学 能源与电气学院, 南京 211100
2.南京南瑞继保电气有限公司, 南京 211102

收稿日期:2021-08-07出版日期:2021-12-28发布日期:2021-12-30
通讯作者:谢俊E-mail:jxie@hhu.edu.cn
作者简介:刘明涛(1996-),男,河南省周口市人,硕士生,主要从事电力市场与电力系统安全经济运行研究.
基金资助:国家重点研发计划(2019YFE0105200);国家自然科学基金资助项目(U1965104)

Short-Term Production Simulation of Power System Containing Wind Power Under Carbon Trading Environment

LIU Mingtao¹, XIE Jun¹(), ZHANG Qiuyan¹, BAO Changyu¹, CHANG Yifan¹, DUAN Jianan¹, SHI Xionghua², BAO Yong²

1. College of Energy and Electrical Engineering, Hohai University, Nanjing 211100, China
2. NR Electric Co., Ltd., Nanjing 211102, China

Received:2021-08-07Online:2021-12-28Published:2021-12-30
Contact:XIE Jun E-mail:jxie@hhu.edu.cn

摘要/Abstract

摘要： 为提高风电参与市场的竞争力,促进电力系统低碳化运行,满足风电出力不确定性对电力系统生产模拟模型的完善性、灵活性提出的新要求,从低碳经济角度分析电能成本构成,应用随机规划理论,提出一种含风电电力系统短期生产模拟模型,该模型以短期电能成本期望值最小为目标,考虑碳交易市场的参与,协同优化日前发电出力、实时功率调整、发电备用容量、弃风和切负荷.以改进的IEEE-39节点系统为例,量化评估了碳交易机制、碳交易价格、风电装机规模对短期电能成本的影响及对碳减排的贡献.结果表明,所提模型能够有效分析碳交易环境下含风电电力系统短期电能成本、碳排放、运行风险等情况,具有较好的应用前景.
关键词: 风电, 生产模拟, 低碳经济, 随机规划, 碳交易市场
Abstract: In order to improve the competitiveness of wind power in participating in the power market, promote low-carbon operation of the power system, and meet the new requirements for the completeness and flexibility of the production simulation model due to the uncertainty of wind power output,this paper analyzes the electricity cost composition from the perspective of low-carbon economy, and applies the stochastic programming theory to propose a short-term production simulation model of power system containing wind power. Considering the participation of the carbon trading market, this model aims to minimize the expected cost of electricity production in a short-term time scale, and coordinately optimize the day-ahead power output, real-time power regulation, power reserve capacity, wind curtailment, and load shedding. Taking the modified IEEE 39-bus system as an example, this paper quantitatively evaluates the impact of carbon trading mechanism, carbon trading price, and wind power installed capacity on electricity costs and their contributions to carbon emission reduction. The simulation results show that the proposed model can effectively analyze the short-term electricity cost, carbon emissions, and operational risks of the power system containing wind power under the carbon trading environment, thus has a promise application prospect.
Key words: wind power, production simulation, low-carbon economy, stochastic programming, carbon trading market


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