Interdependent design and operation of solar photovoltaics and battery energy storage for economically viable decarbonisation of local energy systems

Abstract

Local energy systems are undergoing significant transformation by integrating more solar photovoltaics (PVs) and battery energy storage systems (BESS) to achieve net-zero targets in the energy sector. To ensure an affordable and sustainable decarbonisation process, optimising both system design and operation together is crucial for maximising system profitability and encouraging broader stakeholder participation in the energy transition. However, the complex interdependent influence on the system economic flows, along with the nonlinear characteristics of the system, make the economic optimisation extremely challenging. To address this, we developed a new framework based on advanced artificial intelligence to exploit a wider arbitrage margin under various trading mechanisms, including net metering, day-ahead, and dynamic frequency. We conducted optimisation study on a local energy system operating at University of Warwick using real data from demonstrated BESS and solar PVs, and the effectiveness of the proposed intelligent approach was validated, and the necessity of interdependent optimisation was highlighted. Results showed that, compared to the original campus system (20 MW-level), a carbon reduction rate of up to 61.4 % was achieved through net metering trading, while a maximum annual profit increase of 251 % was realised with dynamic frequency trading. The proposed intelligent framework can be applied to any energy systems with integrated solar PVs and BESS, where the adopted trading mechanism are associated with the system design and operation. The findings offer a practical tool for academics, investors, and policy makers to collaborate in the deployment of renewable energy and energy storage to accelerate the decarbonisation of energy supply.