短期电价不确定性下铜生产的需求响应调度

IF 3.9 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Sonja H.M. Germscheid , Fritz T.C. Röben , Han Sun , André Bardow , Alexander Mitsos , Manuel Dahmen
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引用次数: 0

摘要

在电力现货市场上营销工业过程的需求响应可以降低运营成本。我们应用我们的同步日前和日内电力市场参与方法(gerscheid等人,AIChE J. 2022;68:e17828),用我们先前推导的资源任务网络模型(Röben等人,J. CLEAN.)来分析电力密集型铜生产的需求响应潜力。刺激。2022;362:132221)。具体而言,我们通过考虑风险中性和风险厌恶市场参与的随机调度优化来解决日内价格的不确定性。与只参与前一天的市场相比,规避风险的参与每周可以节省1.9%。风险中性参与可以节省6.4%,但与周末较高的金融风险有关。此外,我们表明,负载转移能力在很大程度上取决于建模的开/关决策,无论是作为第一阶段还是第二阶段的整数决策,与随机调度相比,连续的日前和日内调度允许在平衡财务风险、预期成本和计算复杂性的同时参与两个市场。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Demand response scheduling of copper production under short-term electricity price uncertainty

Marketing demand response of industrial processes on electricity spot markets can reduce operational cost. We apply our simultaneous day-ahead and intraday electricity market participation approach (Germscheid et al., AIChE J. 2022;68:e17828) to analyze the demand response potential of power-intensive copper production with our previously derived resource–task network model (Röben et al., J. CLEAN. PROD. 2022;362:132221). Specifically, we tackle intraday price uncertainty by stochastic scheduling optimization considering both risk-neutral and risk-averse market participation. Risk-averse participation allows for 1.9% weekly savings compared to only participating on the day-ahead market. Risk-neutral participation allows for 6.4% savings, but is connected to higher financial risks on weekends. Moreover, we show that load-shifting capabilities significantly depend on modeling on/off decisions either as first or second-stage integer decisions and that sequential day-ahead and intraday scheduling allows to participate in both markets while balancing financial risk, expected cost, and computational complexity compared to stochastic scheduling.

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来源期刊
Computers & Chemical Engineering
Computers & Chemical Engineering 工程技术-工程:化工
CiteScore
8.70
自引率
14.00%
发文量
374
审稿时长
70 days
期刊介绍: Computers & Chemical Engineering is primarily a journal of record for new developments in the application of computing and systems technology to chemical engineering problems.
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