Bin Cai

  • Bin Cai received his Ph.D. degree in automation from Nanjing University of Science and Technology (NJUST), China, in 2014. Since then, he worked in State Grid Electric Power Research Institute (SGEPRI). He joined the Commonwealth Scientific and Industrial Research Organisation (CSIRO), North Ryde, NSW, Australia, to pursue his Ph.D. project sponsored by the China Scholarship Council (CSC) from 2011 to 2012. His research interests include comprehensive energy system, energy transition, power system adequacy and control, power market.

     

    Energy systems simulation is an important method used to generate a range of insight and analysis on the energy transition. However, any transition of today’s energy system to a clean future is not only a technical-economic matter. The behaviors of individual actors such as energy supplier, energy consumers, and policy makers also shape energy system transitions. However, mathematical agent-based models can hardly reflect the behaviors of individual actors, especially their “bound-rationality” characteristics. Experimental economics is a useful methodology to study heterogeneous human behaviors under a controlled experiment environment. However, the scale of experiment is limited due to the difficulty to have enough qualified human participants to be involved in the simulation as actors. Therefore, we propose a hybrid simulation methodology combining experimental and agent-based computational methods, and develop a Dynamic Simulation platform for Macro-Energy Systems (DSMES). Obligatory indexes and performance indexes are extracted from simulation trajectories to assess the energy transition goals and pathways of a nation, a region, or an energy enterprises, proving decision support for energy supplier, energy consumers, and policy makers.

 

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