实现企业可再生能源目标

Alessio Trivella, Danial Mohseni-Taheri, Selvaprabu Nadarajah
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引用次数: 6

摘要

几家公司已经承诺在未来的某一天从可再生能源中获取一定比例的电力需求。为了实现这一目标,与可再生能源发电企业签订了基于固定执行价格的长期金融合同,即虚拟购电协议(VPPAs)。我们使用vppa组合作为马尔可夫决策过程来制定滚动电力购买,考虑发电机可用性和电价、可再生能源证书和vppa的不确定性。获得最优采购策略是棘手的。我们认为基于预测的再优化启发式与实践一致,限制了不同VPPA类型的采购和新协议的时间。我们扩展了这些启发式方法,并引入了基于信息松弛的再优化启发式方法,这两种方法都允许完全的采购和时间灵活性。后一种启发式在做决定时也考虑到了未来的不确定性。我们通过数值比较上述政策及其在涉及新的执行价格随机过程校准数据的现实实例中的变化,来评估滚动电力购买以满足可再生目标的决策灵活性的价值。与没有灵活性的政策相比,具有完全时间灵活性和没有采购灵活性的政策可以显著降低采购成本。在前一种策略中引入采购灵活性可以进一步显著降低成本,从而为使用动态和异构的VPPA投资组合提供支持。计算这种性质的近最优投资组合需要使用我们基于信息松弛的再优化启发式方法,因为通过基于预测的再优化构建的投资组合具有更高的次最优性。这篇论文被Ilia Tsetlin,行为经济学和决策分析所接受。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Meeting Corporate Renewable Power Targets
Several corporations have committed to procuring a percentage of their electricity demand from renewable sources by a future date. Long-term financial contracts with renewable generators based on a fixed strike price, known as virtual power purchase agreements (VPPAs), are popular to meet such a target. We formulate rolling power purchases using a portfolio of VPPAs as a Markov decision process, accounting for uncertainty in generator availability and in the prices of electricity, renewable energy certificates, and VPPAs. Obtaining an optimal procurement policy is intractable. We consider forecast-based reoptimization heuristics consistent with practice that limit the sourcing of different VPPA types and the timing of new agreements. We extend these heuristics and introduce an information-relaxation based reoptimization heuristic, both of which allow for full sourcing and timing flexibilities. The latter heuristic also accounts for future uncertainties when making a decision. We assess the value of decision flexibility in rolling power purchases to meet a renewable target by numerically comparing the aforementioned policies and variants thereof on realistic instances involving a novel strike price stochastic process calibrated to data. Policies with full timing flexibility and no sourcing flexibility reduce procurement costs significantly compared with one with neither type of flexibility. Introducing sourcing flexibility in the former policies results in further significant cost reduction, thus providing support for using VPPA portfolios that are both dynamic and heterogeneous. Computing near-optimal portfolios of this nature entails using our information-relaxation based reoptimization heuristic because portfolios constructed via forecast-based reoptimization exhibit higher suboptimality. This paper was accepted by Ilia Tsetlin, behavioral economics and decision analysis.
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