Long-term solar PhotoVoltaic (PV) planning

Renewable energy represents an excellent opportunity for improving the living standard of communities. This is even more important in high-density urban systems like Singapore, where a city’s land capacity becomes limited and a growing population drives the demand to levels that traditional electricity sources cannot manage. In this situation, the presence of multiple stakeholders, like government agencies, private business groups and residential community, who may have competing objectives needs to be taken into account for long-term planning. Moreover, as the decisions of adopting renewable energy options may be driven by economic considerations, the risk-aversion of consumers when facing uncertain future scenarios should be included. 

To address these challenges, we propose an efficient robust-optimisation-based approach for long-term solar PhotoVoltaic (PV) planning. The objective is the maximisation of the total economic surplus between producers and consumers of solar PV systems when looking at the worst-case scenario over an uncertainty set.. The uncertainty affects the price that risk-averse consumers (i.e., residential, commercial, and industrial) are willing to pay for solar-PV systems. Land-space constraints are included to describe the relationship between installed capacity and available space, which is a scarce resource. Singapore is employed as a case study because of its potential to produce high volume of solar energy, limited land capacity, ambitious solar PV capacity installation targets by government planning, and availability of data that made it possible to calibrate the model. Our research shows that the model’s projections are compatible with existing assumptions. The analysis of the solution allowed us to quantify the incentives required for achieving national capacity installation targets in 2025 and 2030, which may otherwise be underestimated by 20–30%.