China is currently engaged in a nationwide electricity market reform, aiming to reduce electricity price and improve clean energy consumption. In many areas, thousands of members are participating these special markets; they are all facing with bidding decision-making problems in these unanticipated markets. Due to the particularity of market rules and the shortness of data history and real-time info, plants' bidding is lacking in theoretical support, their fate in the market is unknown. In this paper, an evolutionary game based electricity market-bidding model is proposed, in which all market members are bidding under limited market info. Each bidding strategy is an exploration of the market. The power plants take 'market' itself as their game opponent, instead of 'other plants' in normal game theory models. They adjust decisions according to market feedback and attempt to get some payoff from next market. Loss-making power plants will be acquired by other plants and inherit their bidding strategies. By simulating Chinese typical electricity market, the most competitive strategies are found and power generation groups are formed. Furthermore, this paper takes into account the possible impact of different type of demand and the supply-demand ratio. Comparing with constant demand, the demand curve can prevent clearing price from rising effectively. With a certain demand curve and the acquisition mechanism, the market systems achieve stability, in which the clearing point fluctuate little and periodically, the final clearing price is much lower than that before the reform, and the reform goal was achieved.