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1.新能源电力系统全国重点实验室(华北电力大学),北京市 102206
2.国网电力科学研究院有限公司(南瑞集团有限公司),江苏省南京市 211106
Received:17 October 2023,
Revised:2024-06-23,
Published Online:08 August 2024,
Published:10 November 2024
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欧阳诗琪,蒋凯,薛禹胜等.考虑多市场价格与碳核查不确定性的发电企业交易策略[J].电力系统自动化,2024,48(21):71-81.
OUYANG Shiqi,JIANG Kai,XUE Yusheng,et al.Trading Strategy for Power Generation Companies Considering Multi-market Price and Carbon Verification Uncertainties[J].Automation of Electric Power Systems,2024,48(21):71-81.
欧阳诗琪,蒋凯,薛禹胜等.考虑多市场价格与碳核查不确定性的发电企业交易策略[J].电力系统自动化,2024,48(21):71-81. DOI: 10.7500/AEPS20231017003.
OUYANG Shiqi,JIANG Kai,XUE Yusheng,et al.Trading Strategy for Power Generation Companies Considering Multi-market Price and Carbon Verification Uncertainties[J].Automation of Electric Power Systems,2024,48(21):71-81. DOI: 10.7500/AEPS20231017003.
随着中国“碳达峰·碳中和”战略的提出,发电企业不仅需要参与电能量和煤炭市场交易,还需根据实际碳排放水平参与碳市场交易。然而,由于电-碳-煤多市场间存在交易规则不同、交易时序异步、交易随机要素多元等特点,发电企业面向单一市场的传统交易策略难以适用,亟需一种考虑多元随机性的多市场协同交易策略。文中考虑多市场价格风险和碳市场核查的不确定性,提出了发电企业电-碳-煤中长期滚动交易决策模型。该模型首先基于年前预测价格决策年度合约电量和年度购煤量;然后,根据每月最新价格预测,滚动优化年度剩余月份的月度合约电量、月度购煤量以及碳配额交易量;最后,以燃煤发电企业为研究对象进行算例分析,分为碳买方和碳卖方两个基础场景进行比较研究。结果表明,所提模型能够为发电企业在电-碳-煤多市场中的交易提供策略指导,在发电企业作为碳买方和碳卖方的场景下,分别提高了约7.6%和6.4%的企业总利润。
With the proposal of China’s “carbon emission peak and carbon neutrality” strategy
power generation companies not only need to participate in the electricity energy and coal market trading
but also need to participate in the carbon market trading according to the actual carbon emission level. However
due to the characteristics of different trading rules
asynchronous trading timing and multiple trading random elements among electricity-carbon-coal multi-markets
the traditional trading strategies of power generation companies facing a single market are difficult to apply
and a multi-market collaborative trading strategy that takes into account multiple randomness is urgently needed. Considering the uncertainties of multi-market price risks and carbon market verification
the paper proposes a medium- and long-term rolling trading decision model of electricity-carbon-coal for power generation companies. First
the model determines the annual contract electricity volume and coal purchase volume based on pre-forecasted prices for the upcoming year. Then
according to the latest monthly price forecast
the monthly contract electricity volume
monthly coal purchase volume
and carbon quota trading volume in the remaining months of the year are optimized on a rolling basis. Finally
the coal fired power generation companies as the research object for case analysis
are divided into two basic scenarios of carbon buyer and carbon seller for comparative study. The results show that the proposed model can provide strategic guidance for power generation companies to trade in the electricity-carbon-coal multi-market. In the scenario of power generation companies as carbon buyers and carbon sellers
the total profits of enterprises can be increased by about 7.6% and 6.4%
respectively.
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