Research On Investment Risk Comprehensive Evaluation Of Photovoltaic Power Generation

Along with the traditional energy draining and the worsening of ecological environment, the nations of the world have an increasing demand for new energy.Solar energy, as a kind of clean and renewable new energy, attracts much attention in the energy sector in the world today. Our country is rich in solar energy resources, policy guide and abundant solar energy resources, lead to a rapid development of photovoltaic industry in our country. Photovoltaic field in recent years in our country investment boom, and a large number of photovoltaic power generation project have sprung up. However, huge investment risk often hidden behind the blindly investments, the risk makes photovoltaic power generation enterprises in our country have business crisis, which leads to a lot of photovoltaic power generation enterprises in our country loss or even bankruptcy.Therefore, the investment risk evaluation on the photovoltaic power generation is indeed necessary. Photovoltaic power generation investment risk assessment can predict risk of investment of photovoltaic power generation project, provide project risk level reference for investment decision makers, help investment decision makers weigh the risks and carefully make the investment decisions.Based on the full investigation of the research status at home and abroad of photovoltaic power generation investment risk, and through referring to a large number of related literature at home and abroad, this paper established a scientific and reasonable photovoltaic investment risk comprehensive evaluation index system, and chose to use support vector machine(SVM) model for comprehensive assessment of photovoltaic power generation investment risk. But by studying the previous application study on support vector machine model found that using support vector machine model separately tends to exist the blindness of support vector machine parameter selection, which leads to the evaluation result is not accurate enough. Therefore, this article choose using particle swarm algorithm to optimize the parameters of support vector machine,and using the optimized support vector machine to make the comprehensive assessment for photovoltaic power generation investment risk. The example implementation proves the support vector machine were improved by the particle swarm optimization(PSO), and the evaluation result is more accurate than the support vector machine not optimized by particle swarm optimization. At last,aiming at the defects in photovoltaic investment risk comprehensive evaluation research field in our country at present, the paper pointed out the direction can be improved, and put forward the prospects.