A lagrange-multiplier-based fast planning method for integrated community energy systems considering multiple uncertainties

Integrated Community Energy Systems (ICES) facilitate the connection of multiple energy networks, including electricity, gas, heat, and cold networks. However, with the increasing complexity and uncertainty of loads and renewable generations, a vast number of operation scenarios must be considered for ICES planning. Although a few representative scenarios are often selected to reduce the computational burden, it can overlook scenarios that may have a significant impact on the ICES planning results. To address this issue, a Lagrange-multiplier-based fast planning method (LM) is proposed for ICES that considers massive operation scenarios without reduction. This method constructs a double-layer model to determine optimal planning schemes of ICES, including a planning configuration problem and massive operation optimization problems considering multiple uncertainties. The LM approach is applied to directly obtain the results of massive scenarios instead of time-consuming optimizations. Additionally, the optimality criteria are used to match the scenarios with Lagrange multipliers, which ensures the accuracy of planning schemes. The efficiency and effectiveness of the proposed method are validated by a typical ICES, and the planning results are analyzed in detail.