Technological,Behavioral And Policy Insights On Low-carbon Electricity Transition In China

As the largest emission source,electricity production releases more than 40%of the total CO₂emissions in the world.Low-carbon transition is thus essential for the future development of power sector.Referring to other industries,it can be found that technological innovation is the foundation and motivation of revolutionary transition.As emerging technologies continue to mature,electricity market unexpectedly shows slow low-carbon transition due to both corporate behavior and supportive policy.On one hand,electricity production that relies on fossil energy for the long-term leads to technology lock-in,which limits the low-carbon behaviors of companies.On the other hand,supportive policies need to be constantly explored to achieve expected targets.But low-carbon transition is sensitive to these policies and vulnerable to imperfect policy measures in the exploration.Against these backgrounds,this dissertation applies theoretical and experimental methods from management science to address the low-carbon electricity transition in China at technological,behavioral and policy perspective,thereby depicting a panoramic view of China's low-carbon electricity.The first aim focuses on how to achieve the large-scale application of renewable energy technologies.Taking photovoltaic(PV)power generation as an example,the Technological Innovation System analysis provides a theoretical framework and sheds light on the blocking and inducement mechanism of China's PV industry.At a practical level,the study evaluates the technical and economic feasibility of grid-connected and off-grid PV power systems.The study also forecasts cost reduction for PV power generation with learning curve model and estimates the period of grid parity.This estimation provides policy recommendations for PV market diffusion in China.However,renewable energy market is limited by the preference or behavior of power generation companies rather than ideally developed with the advantage of the declining cost(Chen et al.,2018).Against the background,the second study uses agent-based model to embed an adaptive cap-and-trade system into electricity supply market and estimate the capacity expansion and emission reduction driven by the heterogeneous investment of power generation companies.On one hand,an efficient and reliable cap-and-trade system in power sector is found to be sensitive to the annual electricity demand and the long-term forecast for CO₂ emissions per unit power generation.On the other hand,the identification of technology preference for power generation companies help fulfill their future development strategy.The third study expands the electricity supply simulated in the second study into the entire power industry that covers generation,transmission,distribution and load centers.The study links agent-based model,which simulate the CO₂ emission trading among power plants,with SWITCH model that aims to examine least-cost electricity system.The combined model can not only estimate the regional carbon pass-through rates that demonstrates the impact of CO₂ emission trading on the electricity cost of users,but also compare the effect of different policies on low-carbon electricity transition.Results show that the combination of CO₂ emission trading and renewable electricity target can generate synergistic effect,thereby achieving the effective and efficient low-carbon electricity transition.