A master-slave game-based regional integrated energy system considering the uncertainty of source-load

Abstract A master-slave game model that accounts for the unpredictability of source-load dynamics is proposed to tackle the complexity of energy scheduling in regional integrated energy systems, along with the uncertainty in renewable energy generation and load variations. This model specifically addresses the uncertainties associated with wind power output and load fluctuations. Lagrangian multiplier dual factors are introduced. For the energy scheduling optimization problem in regional integrated energy systems, a master-slave game energy scheduling model with upper and lower layers is constructed. The upper-layer energy operator aims to maximize profits, while the lower-layer integrated energy system aims to minimize costs. The upper layer searches for the optimal trading electricity price using a genetic algorithm, while the lower layer solves the energy scheduling problem with the CPLEX solver. The interaction between the upper and lower layers is dynamically established by trading electricity prices. The case study shows that the two-layer energy scheduling effectively solves the energy scheduling issue in regional integrated energy systems, ensuring stability, consistency, and balance in the system’s operation between the upper and lower-layer participants.