基于改进Line-Pack模型的综合能源系统优化调度

基于改进Line-Pack模型的综合能源系统优化调度Title: Optimization of Integrated Energy System Scheduling based on Improv

Line-Pack 基于改进模型的综合能源系统优化调度 Title: Optimization of Integrated Energy System Scheduling based on Improved Line-Pack Model 1. Introduction (150 words) The increasing demand for asustainable and efficient energy system has led to the integration of various energy resources, such as electricity, natural gas, and heating/cooling systems. The optimization of integrated energy systems plays acrucial role in achieving cost-efficiency, reducing greenhouse gas emissions, and ensuring a reliable energy supply. This paper focuses on the optimization of integrated energy system scheduling, specifically using the improved Line-Pack model. 2. Background (200 words) The Line-Pack model is widely used in the natural gas industry for optimizing the scheduling of gas transmission and storage systems, considering the pipeline pressure dynamics and gas flow constraints. However, existing Line-Pack models often overlook the potential benefits of integrating other energy resources, such as electricity and heat. Therefore, an improved Line-Pack model is proposed to optimize the scheduling of integrated energy systems. 3. Methodology (300 words) The improved Line-Pack model incorporates the constraints and dynamics of multiple energy resources, including electricity, natural gas, and heat. The objective is to minimize the total cost of operation while meeting the energy demands of different sectors, such as industry, residential, and transportation. The optimization algorithm integrates mathematical programming techniques, such as mixed-integer linear programming (MILP) and dynamic programming, to solve the scheduling problem. The algorithm considers the interactions between different energy resources, such as the electricity-to-gas conversion efficiency and the heat recovery from gas networks. 4. Case Study (300 words) Acase study is conducted to demonstrate the effectiveness of the proposed improved Line-Pack model. The case study includes arealistic representation of an integrated energy system consisting of electricity