A team of researchers from Greece and Türkiye has analyzed a hybrid corporate power purchase agreement (PPA) model for co-located photovoltaic (PV) and battery energy storage system (BESS) projects. The proposed scheme blends contracted and merchant components to balance revenue stability and market exposure, aiming to improve project bankability while maximizing profits through wholesale market participation.
“The work introduces a new hybrid business and operational model for renewable assets that combines a modern corporate Pay-as-Delivered (PaD) PPA with active market participation,” researcher Georgios Gousis told pv magazine. “Unlike existing studies, where either the full generation is contracted or fully merchant, we explore a semi-contracted, semi-merchant PV-BESS framework. This dual approach enhances bankability under a PPA while maintaining flexibility to capture additional value in the electricity markets.”
The study models a renewable energy producer (REP) operating a utility-scale photovoltaic (PV) system with a co-located battery energy storage system (BESS) capable of optionally charging from the grid. In the first scenario, the REP stores surplus generation not contracted under the power purchase agreement (PPA), while in the second, it also charges the BESS with energy purchased from the off-peak day-ahead market (DAM). In both cases, the REP deploys stored energy in the DAM and balancing market (BM) in the upward direction, either through the integrated scheduling process up (ISPup) or the manual frequency restoration reserve up (mFRRup).
To test the scheme, the researchers produced year-ahead forecasts of solar output using a Bayesian long short-term memory (B-LSTM) neural network, offering results at different certainty levels (CLs) that represent the probability of meeting energy targets. They then applied mixed integer linear programming (MILP) to optimize battery capacity and dispatch strategy for both grid scenarios. Combining the B-LSTM and MILP outputs, the team used a Nash bargaining solution to determine a fair power purchase agreement (PPA) price.
“The coupling of Bayesian LSTM probabilistic forecast with a MILP optimization model has not been previously applied in this context,” said Gousis.
Image: University of Western Macedonia, Renewable Energy, CC BY 4.0
The method was demonstrated using PV data from Kozani, a town in northern Greece. It was tested under various specifications: battery energy storage system (BESS) capital expenditure (capex) ranging from €120 ($140)/kW to €180/kW and operational expenditure (opex) equal to 4% of capex. For the PV system, capex was €450/kW to €500/kW and opex was €7.50/kW. The discount rate was set at 4%, 8%, or 12%, with power purchase agreement (PPA) durations of 10, 12, or 14 years.
“We found that lowering the certainty level (i.e., contracting less firm energy) can substantially increase profitability due to greater market exposure, but at the expense of reduced bankability,” Gousis said. “Moreover, in case there is a lack of PV power production, the producer has to schedule market participation up to a week ahead if the PPA delivery is of top priority, which is examined in our work.”
“Lower-capex BESS enhances the financial viability of the project by allowing flexible storage sizing. Sensitivity analysis on PPA duration and discount rate demonstrates that longer contract lengths significantly increase net present value (NPV), justify larger BESS capacities, and reduce the required PPA price, thereby improving bankability,” the researchers said. “Allowing the BESS to import energy from the grid (Scenario 2) improves economic performance, particularly at higher cl values where the producer benefits from price arbitrage.”
The results were published in “Enhancing the viability and bankability of hybrid RES-BESS systems with corporate power purchase agreements and electricity market participation.” Researchers from Greece’s University of Western Macedonia and Turkey’s Sabanci University participated in the study.
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