EVALUATING THE EFFECTIVENESS OF PAST AND FUTURE FEED-IN TARIFF POLICY IN GREAT BRITAIN USING AN AGENT-BASED MODEL

摘要

A new agent-based model was used to investigate the effect of feed-in tariffs on the adoption of small-scale solar photovoltaic arrays by households in Great Britain. Both historical (2010-2016) and future (2016-2021) scenarios are modelled, allowing comparison with actual installation data and near-future projections. Agent-based models provide a natural modelling paradigm to include population heterogeneity, non-optimization decision-making and the effect of a social network. Observed installation patterns in the period 2010-2016 can be modelled accurately by considering decision-making based on four factors: household income, the payback period of the investment in the array, the number of adopters in a household's social network, and the capital cost of the installation. The level of feed-in tariffs significantly affects the adoption rate, so a realistic historical subsidy scenario was compared with several alternative scenarios. This indicates that an improved strategy for reducing feed-in tariffs over time could have given higher deployment at lower cost. The model is also used to project future deployment considering the effect of different feed-in tariff levels, electricity prices, and the cost of photovoltaics.