Renewable Energy Technologies Change And Diffusion Process Modelling And Policy Optimization

The energy transition from high pollution and high carbon emission to clean and low carbon emission is a complex system transition process.It relates to various technologies,different industries,and multi agents.This process is mainly determined by the technical change and market diffusion of renewable energy technology(RET).Renewable energy refers to the energy that could be renewed and reproduced without human interference.RET could present characteristics of clean,low carbon emission,and sustainability.It is then necessary to get insights into the questions such like ‘What factors would influence RETs’ technical change and diffusion process?’ and ‘How these factors influence RETs’ development process?’.Combining these questions with the main trends,key characteristics,and market demands of RETs’ development in China,this study selects wind turbine and photovoltaic(PV)as the main research object.It focuses on the general rules of RETs’ development in both supply side and demand side.This study firstly makes a study on government research and development(R&D)policies’ performances in driving RETs’ developments.Government policies and their investments in RETs(e.g.,PV)R&D activities have contributed to the rapid development of PV industry through technology push over past decade.It is worthwhile investigating the effectiveness of the investmentdrive R&D policies at global level,especially how they work in reducing the costs of PV technologies.This study constructs a learning curve model to assess the performances of PV R&D policies in China,Germany,the United States and Japan.Market information,e.g.,PV module production,PV installation and PV technology improvement,is utilized to help analyse how these policies make effects.The results show that PV R&D investments are efficient in decreasing the production costs of PV modules that positively affect the development of PV module markets.However,the weak PV technology conditions and low PV electricity penetration levels have resulted in surpluses in PV module markets,as well as PV electricity curtailments around the world.It is suggested that future R&D policies should contribute more to improve conversion efficiencies(the structure of technology push power)and grid-integration technologies for PV system(demand pull power).Secondly,it further analyzes how to model RETs’ technical change process in the supply side.A well understanding of renewable energy technical change is essential for promoting the energy transition and mitigating climate change.As an effective tool in stimulating the endogenous technical change processes,learning curve has been widely used in renewable energy technology(RET)studies.Despite this,it has been rarely analyzed in the literature about the utilization rules of learning curves’ application in RET studies.This study proposes a comprehensive review of the literature to analyze the rules for applying learning curves in RET studies.The reasons and prerequisites for utilizing learning curves in RETs are discussed at first.It also presents a discussion on how to construct learning curves in RET studies,including the selection of model formulations,variables,as well as data sets.Additionally,some challenges are further discussed to provide implications for future studies.In conclusion,it comprehensively analyzes the literature to give an insight into the utilization of learning curves in RET studies.Rules and theoretical implications are derived for further studies.Thirdly,this study tries to model RETs’ diffusion process to get a better understanding of RETs’ development in the demand side.A well understanding of the rule and key characteristics of RETs’ diffusion process is the basis for managing and optimizing RETs’ developments.This study then makes an analysis on these rules and characteristics.It divides RETs’ diffusion process into three different periods,including information achievement,benefit calculation and technology acceptance.A mathematical model of RETs’ diffusion that presents how potential investors transit into final investors is constructed.With this model,it additionally presents the limitation of diffusion rates,diminishing policy efficiency,and regional difference in RETs’ diffusion.Combined with case study,it also analyzes the influences of different driving forces and how they work in RETs’ diffusion.The model provides a valuable tool for analyzing RETs’ development in the demand side.The results also present important theoretical supports and implications for policy design.Integrating former researches,this study further constructs a dynamic development model to optimize RETs’ policy supports.Policy support has played a significant role in driving the rapid development of RETs.This study constructed a dynamic programming model to derive the optimal policy supports for RETs,integrating both supply and demand sides.The sensitivity of policy performance on the cost and price elasticities of RET diffusion was also analyzed.The results show that policy supports could be a main force for RET development in their initial periods.In the long run,policy makers need to decrease the support level faster than the decrease in RET cost to maintain a high policy efficiency.Further improving the efficiency of policy is possible considering the influences of technical change on RET development.