Due to the deregulation of retail electricity market, consumers can choose retail electric suppliers freely, and market entities are facing fierce competition because of the increasing number of new entrants. Under these circumstances, forecasting the changes in all market entities, when market share stabilized, is important for suppliers making marketing decisions. In this paper, a market share forecasting model was established based on Markov chain, and a system dynamics model was constructed to forecast the electricity consumption based on the analysis of five factors which are economic development, policy factors, environmental factors, power energy substitution, and power grid development. For a real application, the retail electricity market of Guangdong province in China was selected. The total, industrial, and commercial electricity consumption in Guangdong from 2016 to 2020 were predicted under different scenarios, and the market shares of the main market entities were analyzed using Markov chain model. Results indicated that the direct trading electricity would account for 70% to 90% of the total electricity consumption in the future. This provided valuable reference for the decision-making of suppliers and the development of electricity industry.

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Abstract. Since 2015, China's economic downward pressure continues to increase. Facing a more complex internal and external environment, power grid enterprises are paying more attention to their business performance. Through the effective monitoring and prevention of potential risks in economic activities, the abnormality of indicators and risk source tracking can realize. It is helpful for the power grid enterprises to find the work short-board and remedy the situation, so as to effectively enhance the competitiveness of the enterprises and adapt them to the new normal.Here, we firstly studied the benefit decomposition analysis model of power purchasing and selling, we found out the key factors that affected the purchasing and sales electrical benefit. Then, in order to find the abnormality in the electricity business process and trace the reason, we constructed a risk monitoring model of electricity purchasing and selling. In addition, we selected key indicators to be the real-time monitoring objectives. At last, we suggested the power grids to put emphasis upon retail market monitoring.