A decision-making model for emission trading based on ABM

Abstract

Carbon price forecasting is used to assist emission-regulated firms in decision-making in trading. Based on the ABM method and trading rules of China's emission trading markets, in this study, we build a decision-making model for emission trading. The model takes into account factors such as risk preference and emission reduction costs for different types of emission-regulated firms. By setting initial values, adjustable parameters, and input variables, the model simulates emission trading decision-making strategies and carbon price trends in different scenarios. In this article, we selected 2,162 emission-regulated firms in China's national emission trading market for simulation. The results show that the proportion of sellers participating in the market and the proportion of free allowance allocation have a significant impact on the carbon price fluctuations; the introduction of the auction mechanism will cause short-term fluctuations in carbon prices. Through simulation of emission trading decision-making and carbon price forecasting, the model assists emission-regulated firms to minimize their emission regulation compliance costs, and prevent in advance the price and liquidity risks in emission trading markets.

Process simulation on the planning of wind-PV storage for near-zero carbon emission

“…The amount of abandoned wind and solar energy is the electricity that has not been consumed and stored in time. The amount of abandoned wind and solar power generation the amount of unconsumed clean power generation − storage energy increment (13) 4) Carbon emission subsystem Saving electricity or using clean electricity is equivalent to reducing the environmental cost, which is assumed as 44 yuan/ ton (Liu et al, 2023).…”