Optimized Operation of an Integrated Energy System Based on Adaptive Probability Planning

Abstract

This paper proposes an optimized operation method based on adaptive probability planning for the uncertainty of renewable energy output in integrated energy systems. Firstly, by analyzing the architecture of the comprehensive energy system of the park, the corresponding equipment model and the probability model of renewable energy output are established, the lowest daily operation cost of the park is taken as the target function, and the optimal scheduling model of the park is established with the rated operating state of each equipment as the constraint condition, then the scheduling decision problem is expressed under the Markov decision process, defining the observation state, scheduling action and reward function of the system, and the adaptive probabilistic planning algorithm is adopted to obtain the optimization strategy of the Markov decision process, and optimize the integrated energy system. Finally, the effectiveness of the proposed model and algorithm is verified.