Feed-in tariffs for solar microgeneration: Policy evaluation and capacity projections using a realistic agent-based model. (May 2018) - Pearce, Phoebe; Slade, Raphael
Abstract: Since 2010, over 700, 000 small-scale solar photovoltaic (PV) systems have been installed by households in Great Britain and registered under the feed-in tariff (FiT) scheme. This paper introduces a new agent-based model which simulates this adoption by considering decision-making of individual households based on household income, social network, total capital cost of the PV system, and the payback period of the investment, where the final factor takes into account the economic effect of FiTs. After calibration using Approximate Bayesian Computation, the model successfully simulates observed cumulative and average capacity installed over the period 2010–2016 using historically accurate FiTs; setting different tariffs allows investigation of alternative policy scenarios. Model results show that using simple cost control measures, more installation by October 2016 could have been achieved at lower subsidy cost. The total cost of supporting capacity installed during the period 2010–2016, totalling 2.4 GW, is predicted to be £14 billion, and costs to consumers significantly exceed predictions. The model is further used to project capacity installed up to 2022 for several PV cost, electricity price, and FiT policy scenarios, showing that current tariffs are too low to significantly impact adoption, and falling PV costs are the most important driver of installation. Highlights: An agent-based model can accurately model adoption of domestic PV systems. Great Britain's FiT scheme suffered from cost escalation in 2011–2012. Alternative degression methods encourage more installation at lower subsidy cost. Projections show that PV cost is the key driver of future installation. FiTs are currently so low that their impact is minimal.