Power purchase agreements (PPAs) have become an important corporate procurement vehicle for renewable power, especially among companies that have committed to targets requiring a certain fraction of their power demand be met by renewables. PPAs are long-term contracts that provide renewable energy certificates (RECs) to the corporate buyer and take two main forms: Physical vs Virtual. Physical PPAs deliver power in addition to RECs, while virtual PPAs are financial contracts that hedge (at least partially) power price uncertainty. We compare procurement portfolios that sign physical PPAs with ones that sign virtual PPAs, focusing on fixed-volume contracts and emphasizing uncertainties in power demand and the prices of power and RECs. In particular, we first analyze a two-stage stochastic model to understand the behavior of procurement quantities and costs when using physical and virtual PPAs as well as variants that limit risk. We subsequently formulate a Markov decision process (MDP) that optimizes the multi-stage procurement of power to reach and sustain a renewable procurement target. By leveraging state-of-the-art reoptimization techniques, we solve this MDP on realistic instances to near optimality, and highlight the relative benefits of using PPA types to meet a renewable target. We underscore a trade-off between expected cost and cash flow variance that buyers should consider when choosing between physical and virtual PPAs. Moreover, advanced reoptimization techniques significantly impact the ability to manage this trade-off.

中文翻译：

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实体与虚拟企业购电协议：在需求和价格不确定的情况下满足可再生能源目标


购电协议（PPA）已成为可再生能源的重要企业采购工具，特别是对于那些承诺通过可再生能源满足一定比例电力需求的公司而言。 PPA 是向企业买家提供可再生能源证书 (REC) 的长期合同，主要采取两种形式：物理形式和虚拟形式。除了 REC 之外，物理购电协议还提供电力，而虚拟购电协议是对冲（至少部分）电价不确定性的金融合同。我们将签署物理购电协议的采购组合与签署虚拟购电协议的采购组合进行比较，重点关注固定数量的合同，并强调电力需求以及电力和可再生能源证书价格的不确定性。特别是，我们首先分析两阶段随机模型，以了解使用物理和虚拟购电协议以及限制风险的变体时采购数量和成本的行为。随后，我们制定了马尔可夫决策过程（MDP），优化多阶段电力采购，以达到并维持可再生能源采购目标。通过利用最先进的重新优化技术，我们在现实实例上解决了该 MDP，使其接近最优，并强调了使用 PPA 类型来满足可再生能源目标的相对优势。我们强调买家在选择实体购电协议和虚拟购电协议时应考虑预期成本和现金流差异之间的权衡。此外，先进的重新优化技术极大地影响了管理这种权衡的能力。