Distributed Collaborative Optimization for Integrated Energy System Clusters: A Power Allocation Strategy Based on Consensus Algorithm and Logistic Function

With the increasing penetration of renewable energy into integrated energy systems (IES), the intensifying source-load mismatch has led to real-time power imbalance in off-grid IES clusters, decrease in system energy utilization efficiency and power supply reliability, thereby affecting the safe and stable operation of IES clusters. To address this gap, by fully utilizing the information transmission and energy complementarity between IES, a two-stage distributed collaborative optimization strategy for IES clusters is proposed in this paper. In the first stage, the load capacity of IES is evaluated based on the load margin, and a power allocation model based on a consensus algorithm is established. The real-time power of each controllable unit of IES is obtained through iterative processes, the reasonable output and minimum adjustment cost of multiple IES devices can be achieved, and the total power command of the electric-hydrogen hybrid energy storage system (HESS) is transmitted to the second stage. In the second stage, a HESS energy management strategy is developed considering the operational characteristics of alkaline electrolyzers. Furthermore, dynamic adjustment rule for charging and discharging power weighting factors is designed based on a logistic function, and a multi-mode real-time power allocation strategy for HESS is proposed, adjusting the output of two types of energy storage in real time. Finally, numerical simulation verified the feasibility and superiority of the proposed power allocation strategy of IES clusters.