Regional PV installed capacity forecasting considering generation costs and time lag of influential factors

Abstract

The forecasting results of regional photovoltaic (PV) installed capacity can provide important references for electric utilities, photovoltaic agents, and energy authorities. This paper proposes a three‐step forecasting methodology of regional PV installed capacity considering generation costs and time lag of influential factors. As the generation costs play a key role in PV installation, in the first step, cost indicators of PV projects are analyzed and a modified formula of levelized cost of electricity (LCOE) is proposed, for the aim of PV generation costs assessment and forecasting. Subsidy coefficient, which is mainly dependent on local government's energy policies and load curves, is introduced into the formula of LCOE. Apart from generation costs, the second step is to study the relationship between regional PV installed capacity and a series of outside‐ and inside‐region factors using co‐integration analysis and Granger causality test, attempting to comb through that data for other influential factors of PV installed capacity. Time lags of influential factors are determined during this step. In the last step, cross‐correlation analysis and principal components regression are carried out to eliminate collinearity of independent variables, quantify the influence of different factors, and construct the forecast model of regional PV installed capacity. In this paper, the example of Shanghai is given to illustrate the proposed methodology. The LCOE of PV systems and PV installed capacity of Shanghai from 2015 to 2030 were forecasted under several scenarios distinguished by subsidy coefficient. The results of Granger test and cross‐correlation analysis show that factors such as generation costs, environmental protection investment by local government and technical progress are closely related to regional PV installed capacity, nevertheless, sunshine duration and average temperature are not the Granger reasons for it. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.