Towards Sustainable Energy Communities

Abstract

The growing adoption of clean solar energy in urban environments emphasizes the critical importance of efficient capacity planning in the development of building-integrated photovoltaic (BIPV) systems. Nevertheless, uncertainties associated with solar generation and demand pose substantial obstacles to systems planning. In response to these challenges, this paper introduces a novel approach: an optimization model that leverages ambiguity sets based on scenarios and is robust to distributional uncertainty for the expansion planning of building-integrated photovoltaic (BIPV) system. The distinctiveness of the model lies in its consideration of the non-linearity between global horizontal irradiance as well as PV solar power generation potential. A case study conducted in Singapore demonstrates the proposed model's substantial advantages including a 2 % -5 % improvement in self-sufficiency, 3 % -8 % electricity cost savings, and 3 % -8 % reduction in carbon dioxide emissions compared to benchmark models.