Decarbonation of urban districts would be critical for reducing carbon footprints. In this sense, Renewable Energy Communities (RECs) support this transition through collective self-consumption, yet their local generation rarely meets the local demand, still requiring grid-supplied residual energy. Power Purchase Agreements (PPAs) could bridge this gap by providing off-site renewable energy to RECs, but their associated risks often limit access for non-corporate buyers. Therefore, this paper proposes a PPA portfolio optimization tool to enable RECs to participate in PPAs as buyers and partially cover their residual demand. The methodology is based on a bi-objective optimization using the Pareto front to maximise both Net Present Value (NPV) and Conditional Value-at-Risk (CVaR) such that both economic returns and risk mitigation are balanced. The optimization tool is tested on a 15-years PPA (2026-2040). Uncertainty over the long-term is addressed by considering input data across 10 scenarios, ranging from high to low penetration of renewable energy scenarios. The results indicate that the contractual configuration varies according to whether the economic return or risk mitigation is prioritised, leaving the portfolio choice to the buyer.
Power Purchase Agreements Portfolio Optimisation to address Residual Demand in Energy Communities
Taromboli, Giulia;Iuculano, Giacomo;Del Pero, Claudio;Bovera, Filippo
2025-01-01
Abstract
Decarbonation of urban districts would be critical for reducing carbon footprints. In this sense, Renewable Energy Communities (RECs) support this transition through collective self-consumption, yet their local generation rarely meets the local demand, still requiring grid-supplied residual energy. Power Purchase Agreements (PPAs) could bridge this gap by providing off-site renewable energy to RECs, but their associated risks often limit access for non-corporate buyers. Therefore, this paper proposes a PPA portfolio optimization tool to enable RECs to participate in PPAs as buyers and partially cover their residual demand. The methodology is based on a bi-objective optimization using the Pareto front to maximise both Net Present Value (NPV) and Conditional Value-at-Risk (CVaR) such that both economic returns and risk mitigation are balanced. The optimization tool is tested on a 15-years PPA (2026-2040). Uncertainty over the long-term is addressed by considering input data across 10 scenarios, ranging from high to low penetration of renewable energy scenarios. The results indicate that the contractual configuration varies according to whether the economic return or risk mitigation is prioritised, leaving the portfolio choice to the buyer.| File | Dimensione | Formato | |
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Power_Purchase_Agreements_Portfolio_Optimisation_to_address_Residual_Demand_in_Energy_Communities.pdf
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