Research on the Optimal Dispatching Model of Smart Energy System Based on the Introduction of Risk Factor Master-Slave Game Model

Minimizing the impact of clean energy volatility and maximizing the benefits to owners are hot issues to be solved in current smart energy systems. This paper introduces a risk factor based on master-slave game theory, and establishes an optimal scheduling model of smart energy system based on the master-slave game model with the system as the leader and the end-users as the followers, and uses the conditional value-at-risk theory in economics to quantitatively analyze the risk cost brought by the uncertainty of clean energy output to the scheduling of smart energy system before the day. Using this risk cost as a risk factor, a two-tier optimal dispatching model for smart energy systems and end-users is established based on the introduction of a risk factor master-slave game model. Simulation of the operational data of a domestic smart energy system shows that the model established in this paper can effectively reduce the risk caused of clean energy output and achieve a win-win situation for both the system and the electric vehicle owners, which is economical and feasible.