A Study On Key Factors And Simulation Analysis Based On System Dynamics Of Chinese Rural Residential Electricity Price

Electricity pricing for rural areas has been a worldwide challenge,and a more complex one in China, since policies and national strategies have to be considered integratedly, such as to reduce poverty, narrow the gap between urban and rural areas, support modern agriculture and new rural areas, promote power service, improve people's livelihood, and energy conservation. Based on China's national conditions, for the status of rural residents in tariff policy, a forecasting simulation model has been established on the basis of studies on the key factors and pathways for rural residential electricity prices, and a series of policy recommendations have been put forward on the basis of the simulation results. This plays a certain reference for government to develop a scientific and rational pricing policy.This paper begins with introducing the present tariff policies of China's rural residents, the logic behind them and their features.Analysis of factors affecting the price have been made, from the perspective of generation side, the transmission side and demand side respectively. After applying gray correlation method and analyze relevant statistical data, the author found key factors affecting China's rural residential electricity prices include: average air conditioners per household, average lending rates, average rural residents' net income,natural gas prices, coal price for power generation, average household electricity consumption, total electricity consumption, the national electricity grid investment, and cross-price subsidies. Further, how these key factors affected the tariff have been analyzed.Moreover, based on the key factors and affecting mechanism, a dynamic simulation model of China's rural residential electricity prices has been established. The model simulate and analysis how the variables, like the key factors and on-grid price can affect electricity price, which provide theoretic and practical assistance to government policy making in analyzing pricing adjustments reasons, choosing appropriate adjustment frequency and range, and promoting market reform of power policies.Finally, a series of policy recommendations have been put forward onthe basis of the simulation results, with considerations of the present price policy. Recommendations include:Factors supporting decrease power price, like increase of average electricity consumption, should also be taken into consideration when the government making price decisions, as well as take account of raising price factors-increased costs and residents affordability.Using real-time monitoring of average power price and residential price changes, and keep the difference between the two prices reasonable,so as to avoid excessive difference growth, which would strengthen cross-subsidization.