Game-theoretic optimization strategy for maximizing profits to both end-users and suppliers in building rooftop PV-based microgrids

Rooftop photovoltaic (PV) with battery storage offers a promising avenue for enhancing renewable energy integration in buildings. Creating microgrids with backup power from closely spaced solar buildings is widely recognized as an effective strategy. Nevertheless, a notable gap exists between the preferences and priorities of electricity consumers residing in these solar-powered buildings and the interests of microgrid investors. The electricity consumers focus on decreasing the levelized cost of energy, while the microgrid investors focuses on achieving high net profit. This study proposes a novel game theory-based microgrid optimal design approach for designing power generations of the microgrid system and PV installation with battery storage on the building roofs, considering the different requirements and interests of electricity consumers and microgrid investors. The design optimization is framed around the Nash Equilibrium of the Stackelberg game, incorporating a bi-level optimization cycle that addresses the conflict and cooperation of electricity consumers and microgrid investors. A win-win situation can be yielded using the developed optimal design approach compared to conventional optimal design approaches. The results demonstrate a significant improvement, with the microgrid power generation yielding a large net profit (up to 0.08 USD/kWh) and concurrently reducing the levelized cost of energy by approximately 14%. • A game theory-based microgrid optimal design approach with bi-level optimization is proposed. • Requirements and interests of the electricity consumers and microgrid investors are quantified. • A win-win situation can be yielded considering their requirements and interests in optimal design. • From electricity consumers’ perspective, the levelized cost of energy is effectively reduced to 14%. • From microgrid investors’ perspective, a large net profit (up to 0.08 USD/kWh) is possible.