Robust Procurement Planning for Community Choice Aggregators: Managing Market Price Uncertainty

Abstract

Community Choice Aggregators (CCAs) play an important role in the energy transition by procuring renewable electricity for local communities while balancing affordability, resource adequacy, and clean-energy requirements. In California, these long-term procurement decisions are coordinated through integrated resource planning (IRP). However, conventional IRP frameworks typically represent wholesale electricity prices deterministically, even though price uncertainty can expose CCAs to substantial financial risk by affecting the cost of market imports and, particularly, the value of export opportunities. This paper develops a robust optimization framework for CCA resource procurement that hedges against uncertainty in wholesale import and export prices. We extend the open-source GenX capacity expansion model with a budgeted robust optimization formulation that protects procurement decisions against adverse price realizations while remaining computationally tractable for large-scale, multistage planning studies. Using data from a California CCA, we show that market price uncertainty can materially change optimal procurement strategies. Rather than aggressively expanding renewable capacity based on expected export revenues, robust portfolios reduce dependence on uncertain market revenues, leading to more conservative renewable investments and less reliance on market exports. We demonstrate that moderate uncertainty budgets provide most of the risk-reduction benefits of robust planning at limited additional cost, whereas higher robustness levels yield diminishing benefits as portfolio conservatism increases. These findings provide guidance for selecting uncertainty budgets in IRP studies and demonstrate how robust optimization can support affordable and resilient procurement decisions as CCAs contribute to the transition toward low-carbon electricity systems.