Research On The Forecast Of Distributed Photovoltaic Electricity Price Subsidy In China Based On The Net Present Value Method

With the development of China’s economy,the pressure on energy and the environment is increasing.The large-scale application of renewable energy such as photovoltaics and wind power can partially replace and reduce the use of traditional fossil energy,thus alleviating the dual pressures of local energy supply shortage and environmental protection.As a kind of effective policy means,the price subsidy is beneficial to promote the healthy development of China’s photovoltaic industry.At present,China’s subsidies for the PV industry are relatively high.The high subsidies have triggered a series of problems such as the renewable energy fund’s insufficiency and user fraud.In June 2018,the National Development and Reform Commission,the Ministry of Finance,and the National Energy Administration issued the "Notice on Matters Related to Photovoltaic Power Generation in 2018",which mentioned that the scale of China’s photovoltaic power generation is expanding,the speed of technological progress and cost reduction is accelerating,and PV subsidies will be retreated more quickly and the subsidy intensity will be reduced.Therefore,this paper predicts China’s distributed PV price subsidies based on the declining cost of photovoltaic equipment.On the one hand,it provides policy reference for the state to improve the subsidy mechanism for electricity price subsidies,and on the other hand,it also provides opinions for investment decisions of investors in DPV projects.The current research focuses on PV initial investment subsidies and Feed-in-Tariff subsidy policies.This paper mainly focuses on DPV subsidy policies.The paper firstly combs the definition and related policies of DPV in China,and then makes a systematic dynamic analysis of the factors affecting the DPV tariff in China.It is found that the cost of PV equipment is the most direct factor affecting PV subsidies.The cost prediction model of PV equipment was constructed based on the two-factor learning curve and then the cost of photovoltaic equipment in China was predicted.The DPV electricity price subsidy forecasting model was constructed by using the net present value(NPV)method.Firstly,the general industrial and commercial DPV users in Zhejiang province were used as examples to forecast the electricity subsidy.The different loan method,the subsidy period,the self-use ratio,sunshine time and region were also considered.Then the forecasting model was applied to the other 24 provinces in our country and the results of the electricity subsidies were obtained.The study found that the subsidies for residents and large industrial users in Zhejiang province are 0.14 yuan/kWh and 0.08 yuan/kWh higher than the subsidies required by the general industrial and commercial user in 2018.Increasing the loan ratio and extending the loan period and increasing the proportion of self-use can reduce the amount of subsidies for electricity.The general industrial and commercial user in whole country will not require subsidy in 2022.The contribution of this research is to establish a DPV subsidy forecast model used NPV method with consideration of a variety of factors and apply it to China’s DPV subsidy forecast.The research results provide references for the government to optimize the subsidy policy and the user investment decision.