Effects of herding behavior of tradable green certificate market players on market efficiency:insights from heterogeneous agent model

Tradable green certificate(TGC)scheme promotes the development of renewable energy industry which currently has a dual effect on economy and environment.TGC market efficiency is reflected in stimulating renewable energy investment,but may be reduced by the herding behavior of market players.This paper proposes and simulates an artificial TGC market model which contains heterogeneous agents,communication structure,and regulatory rules to explore the characteristics of herding behavior and its effects on market efficiency.The results show that the evolution of herding behavior reduces information asymmetry and improves market efficiency,especially when the borrowing is allowed.In addition,the fundamental strategy is diffused by herding evolution,but TGC market efficiency may be remarkably reduced by herding with borrowing mechanism.Moreover,the herding behavior may evolve to an equilibrium where the revenue of market players is comparable,thus the fairness in TGC market is improved.

How will tradable green certificates affect electricity trading markets under renewable portfolio standards?A China perspective

Renewable portfolio standards(RPS)are important guarantees to promote renewable energy(RE)consumption.The tradable green certificate(TGC)trading mechanism is a supporting mechanism of RPS,but the rate of TGC trading is low and there is a double-metering problem of RE consumption.With the introduction of new policies in China,we innovatively take the electricity-selling side as the subject of RE consumption responsibility and biomass-based electricity-generation(BEG)projects are considered to participate in TGC trading.To explore the interaction between the TGC market and the electricity market,this paper sets up a day-ahead spot market-trading structure combining both markets under RPS and establishes a market equilibrium model.The established model is solved and validated based on the particle swarm optimization algorithm and the profits of each market player under different influencing factors are analysed.The main conclusions are as follows.(i)The established market structure and model effectively solve the double-metering problem of RE consumption,making the TGC turnover rate reach 82.97%,greatly improving the market efficiency.(ii)Increased demand for TGC will increase demand for RE electricity.The participation of BEG projects in the TGC market can effectively improve the profit of biomass-based electricity producers(BEPs),reduce the burden of government financial subsidies and will not affect the consumption of wind-based electricity and photovoltaic-based electricity.This will help promote the rapid development of China’s RE,especially the BEG industry.(iii)Among the influencing factors,the increase in renewable-energy consumption responsibility weight and the decrease in electricity-generation cost can increase the profit of BEPs.The decline in TGC price and subsidy price will reduce the profit of BEPs.Finally,we put forward policy recommendations for China’s RPS and TGC trading mechanism.This study can provide a reference for the construction of China’s TGC market and electricity market and the development of RE.