Long-Term Impacts of Carbon Tax and Feed-in Tariff Policies on China's Generating Portfolio and Carbon Emissions: A Multi-Agent-Based Analysis

Abstract

Using agent-based modelling, this paper established an adaptive simulation model of China's wholesale electricity market with endogenous investment decisions and technical progress. The model took into account the heterogeneities of power generators, including emission reduction attitudes and risk appetites. Using this model, we simulated how carbon tax and feed-in tariff (FIT) policies will affect each single generator in terms of market behaviours (price bidding and investment) to explore the evolution of power generating portfolio and emissions differently in the time horizon 2010–2050. The validity of the model was tested according to China's electricity market data. We found that FIT for wind power and solar power will crowd out the investment in gas power and nuclear power, rather than replacing coal power. Compared to FIT, carbon tax is a more effective tool for emission abatement and incentivize multiple low carbon generating technologies. And optimal rate of carbon tax should be no more than 250 CNY/t CO2.