基于月约束的直接负荷控制契约的能耗曲线平坦化

IF 0.7 4区 管理学 Q3 Engineering
A. Fattahi, S. Ghodsi, S. Dasu, R. Ahmadi
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引用次数: 0

摘要

加州一家公用事业公司成功实施了一项开创性的模式,以平衡电力需求和供应,同时最大限度地降低成本。通过使用直接负荷控制合同(dlc),公司可以减少高峰时段的能源消耗。研究人员开发了一个考虑月和年约束的整数随机动态优化问题,允许有效执行dlcc。该模型采用了“降低阈值”策略,在高需求期间使能耗曲线变平,并使用加州独立系统运营商的实际数据进行了验证。实施后,公用事业公司实现了令人印象深刻的成本降低约4%。通过敏感性分析,提升客户体验,完善DLCC合同特征。这种创新模式的成功凸显了dlcc和先进优化技术在能源领域的潜力,为其他寻求优化电网稳定性和降低成本的公用事业公司提供了蓝图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Flattening Energy-Consumption Curves by Monthly Constrained Direct Load Control Contracts
California Utility Firm Implements Innovative Model, Reducing Costs by 4% A California utility firm has successfully implemented a pioneering model to balance electricity demand and supply while minimizing costs. By utilizing direct load control contracts (DLCCs), the firm can reduce energy consumption during peak hours. Researchers developed an integer stochastic dynamic optimization problem that considers monthly and annual constraints, allowing for effective execution of DLCCs. Incorporating a “reduce-to-threshold” policy to flatten energy-consumption curves during high demand, the model was verified using real data from the California Independent System Operator. When implemented, the utility firm achieved an impressive cost reduction of approximately 4%. Sensitivity analysis was conducted to enhance customer experience and improve DLCC contract features. The success of this innovative model highlights the potential of DLCCs and advanced optimization techniques in the energy sector, offering a blueprint for other utility companies seeking to optimize grid stability and reduce costs.
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来源期刊
Military Operations Research
Military Operations Research 管理科学-运筹学与管理科学
CiteScore
1.00
自引率
0.00%
发文量
0
审稿时长
>12 weeks
期刊介绍: Military Operations Research is a peer-reviewed journal of high academic quality. The Journal publishes articles that describe operations research (OR) methodologies and theories used in key military and national security applications. Of particular interest are papers that present: Case studies showing innovative OR applications Apply OR to major policy issues Introduce interesting new problems areas Highlight education issues Document the history of military and national security OR.
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