Risk Evaluation Of Biomass Power Generation Project Based On BP Neural Network

With the proposal of carbon peak and carbon neutrality in China,more and more attention is paid to the utilization of clean energy at the national level.As a kind of clean energy,biomass energy has the characteristics of rich resources,low carbon and easy to obtain.The power generation technology based on biomass fuel has received extensive attention and become the research object of scholars in recent years.With the development concept of "green mountains are gold and silver mountains" more and more popular,the government has formulated and introduced a large number of regulations and support policies related to biomass power generation.During the "13th Five-Year" period,the biomass power generation industry has entered a period of rapid development,and the "14th Five-year" period is determined to be green and low-carbon energy development planning.The scale of China’s biomass power generation industry continues to expand,and biomass power generation technology and facilities continue to improve.At the same time,the risks of biomass power generation investment projects are becoming more and more obvious.Through in-depth research on the risk assessment of biomass power generation projects,this thesis established risk assessment indicators and models suitable for the development of biomass power generation projects,and took A biomass power generation project as an example to verify,and put forward corresponding countermeasures.First of all,this thesis introduces the background and development direction of the topic research,and explains the research methods,technology roadmap and innovation points used in this thesis.Combined with the theory of project risk management,this thesis summarizes the three processes of risk identification,risk evaluation and risk response in risk management.Secondly,the risk factors of biomass power generation projects are selected by using brainstorming method and literature analysis method,and then the primary indicators are summarized,and then the Delphi method is used to screen them,and the risk evaluation index system suitable for biomass power generation projects is constructed.Then,BP neural network is used to construct the risk assessment model of biomass power generation project.Chose 20 biomass power generation project as sample,by fuzzy evaluation method and analytic hierarchy process(AHP)to determine the input and output values of BP neural network,the top 15 as training data,the remaining five as the test data,through the verification,the use this article build the risk assessment model of biomass power generation project risk evaluation is correct and effective.Finally,the situation of A biomass power generation project is briefly introduced,and the risk data of A biomass power generation project is substituted into the model constructed in this paper.After analysis,the risk level of A biomass power generation project is "general".According to the weight under the risk assessment set of A biomass power generation project,the largest 5 risk indicators are selected,and the risk control strategies are put forward for them.