Multi-agent Optimization Model of Power Spot Market under Renewable Portfolio Standard

China officially began to implement the Renewable Portfolio Standard (RPS) in 2021, which requires power users to take the actual consumption of renewable energy electricity as the main way to achieve the target. At the same time power users can also purchase Renewable energy certificate (REC) and surplus renewable energy consumption as a supplementary means. Based on the above framework, a bilevel multi-agent decision optimization model including renewable energy day-ahead market, conventional energy day-ahead market and real-time market is established under the RPS, and transformed by the Karush-Kuhn-Tucker condition, strong duality theorem and binary expansion method. It is transformed into mixed integer linear programming to find the market equilibrium. The effects of assessment index of RPS, REC price and renewable power penetration on market equilibrium characteristics are discussed. The results show that in the market equilibrium state, the day-ahead market clearing price of renewable energy is equal to the conventional energy clearing price plus the REC price, and with the increase of the penetration rate of renewable energy, the power spot market clearing price of electricity shows a downward trend.