Abstract:  It is an inevitable trend for thermal power enterprises to enter the power spot market, and market mechanisms such as electricity bidding, green certificates, quotas and carbon trading are bound to increase the competitive pressure of thermal power enterprises. In order to make thermal power enterprises better adapt to market changes, this paper puts forward a ladder bidding strategy model based on improved genetic algorithm and evolutionary game according to the bidding and clearing rules in the spot market of electric power, so as to make auxiliary decision for thermal power enterprises in different power market supply and demand situations. By setting a classic example, we simulated the bidding strategies of thermal power enterprises with different technical levels and sizes under three supply and demand conditions: standard supply and demand, tight supply and demand and loose supply and demand. We found that the bidding strategy based on evolutionary game theory can assist the enterprises to find a ladder quotation suitable for the current background and gain advantages in market competition. It shows that the bidding strategy based on evolutionary game theory has strong applicability, which provides valuable strategic reference for thermal power enterprises to enter the spot market.

Key words:  , thermal power generation enterprise, spot electricity market, evolutionary game, ladder quotation