Valuation of Power Purchase Agreements for Corporate Renewable Energy Procurement
Roozbeh Qorbanian, Nils L\"ohndorf, David Wozabal

TL;DR
This paper introduces a novel hybrid modeling approach combining fundamental and statistical methods to accurately forecast capture prices for corporate renewable PPAs, improving valuation accuracy over existing benchmarks.
Contribution
It develops a new regularized inverse optimization method within a fundamental market model to estimate technology costs and forecast capture prices more effectively.
Findings
Outperforms standard statistical benchmarks in European market data
Provides a practical framework for PPA valuation from the buyer's perspective
Demonstrates applicability to photovoltaic plant valuation in Spain
Abstract
Corporate renewable power purchase agreements (PPAs) are long-term contracts that enable companies to source renewable energy without having to develop and operate their own capacities. Typically, producers and consumers agree on a fixed per-unit price at which power is purchased. The value of the PPA to the buyer depends on the so called capture price defined as the difference between this fixed price and the market value of the produced volume during the duration of the contract. To model the capture price, practitioners often use either fundamental or statistical approaches to model future market prices, which both have their inherent limitations. We propose a new approach that blends the logic of fundamental electricity market models with statistical learning techniques. In particular, we use regularized inverse optimization in a quadratic fundamental bottom-up model of the power…
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Taxonomy
TopicsSustainable Supply Chain Management
