The adoption of solar photovoltaic panels and batteries greatly reduces a grid customer's carbon footprint, while simultaneously reducing their dependency on conventional electricity supply. Given the significance of both outcomes, it is important to understand the potential effect of energy policies on the adoption of these 'PV-battery systems' before they are actually implemented. We therefore design and implement an Agent-Based Model (ABM) that captures the purchase and usage of PV-battery systems. Focusing on Ontario, we use a survey to elicit the responsiveness of residents to potential energy policies. We parameterize the ABM based on survey results to forecast the relative performance of different energy policies. We find that PV-battery system adoption in Ontario is likely to be incremental rather than exponential. Moreover, we find that, of all the policies we evaluated, the most effective way to improve PV-battery system adoption is to significantly reduce its price.
['Adedamola Adepetu', 'Srinivasan Keshav']
Understanding solar PV and battery adoption in Ontario: an agent-based approach