Meeting corporate renewable power targets

Abstract

Prominent companies have committed to procuring a percentage of their power demand from renewable sources by a future date in the face of uncertain power demand and stochastic power and renewable energy certificate (REC) prices. We study procurement portfolios based on two dominant strategies to achieve this target: long-term procurement of power and RECs at a fixed price using corporate power purchase agreements (CPPAs) and short-term purchases at volatile prices. We analyze a two-stage model to understand the behavior of procurement costs when using financial and physical CPPA variants employed in practice, which informs the structuring of these contracts. We subsequently formulate a Markov decision process (MDP) that optimizes the multi-stage procurement of power to reach and sustain a renewable procurement target. Our MDP is intractable because its action space is non-convex and its state space has high-dimensional endogenous and exogenous components. Although approximate methods to solve this MDP are limited, a procurement policy can be obtained using an easy-to-implement "primal" reoptimization strategy, which solves a deterministic model with stochastic quantities in the MDP replaced by forecasts. This approach does not, however, provide a lower bound on the optimal policy value. We propose a novel "dual" reoptimization heuristic which computes both procurement decisions and a lower bound while retaining the desirable implementation properties of primal reoptimization. On realistic instances, the dual reoptimization policy is near-optimal and outperforms policies from primal reoptimization and other heuristics. Our numerical results also highlight the benefits of using CPPA contracts to meet a renewable target.