A Ladder-Type Carbon Trading-Based Low-Carbon Economic Dispatch Model for Integrated Energy Systems with Flexible Load and Hybrid Energy Storage Optimization

碳纤维 储能 经济调度 能量(信号处理) 计算机科学 数学优化 电力系统 数学 功率(物理) 算法 物理 复合数 统计 量子力学
作者
Zhiheng Huang,Fan Zhong,Chun Sing Lai,Bang Zhong,Qijun Xiao,Wei-Tai Hsu
出处
期刊:Energies [Multidisciplinary Digital Publishing Institute]
卷期号:18 (14): 3679-3679 被引量:1
标识
DOI:10.3390/en18143679
摘要

This paper proposes a ladder carbon trading-based low-carbon economic dispatch model for integrated energy systems (IESs), incorporating flexible load optimization and hybrid energy storage systems consisting of battery and thermal energy storage. First, a ladder-type carbon trading mechanism is introduced, in which the carbon trading cost increases progressively with emission levels, thereby providing stronger incentives for emission reduction. Second, flexible loads are categorized and modeled as shiftable, transferable, and reducible types, each with distinct operational constraints and compensation mechanisms. Third, both battery and thermal energy storage systems are considered to improve system flexibility by storing excess energy and supplying it when needed. Finally, a unified optimization framework is developed to coordinate the dispatch of renewable generation, gas turbines, waste heat recovery units, and multi-energy storage devices while integrating flexible load flexibility. The objective is to minimize the total system cost, which includes energy procurement, carbon trading expenditures, and demand response compensation. Three comparative case studies are conducted to evaluate system performance under different operational configurations: the proposed comprehensive model, a carbon trading-only approach, and a conventional baseline scenario. Results demonstrate that the proposed framework effectively balances economic and environmental objectives through coordinated demand-side management, hybrid storage utilization, and the ladder-type carbon trading market mechanism. It reshapes the system load profile via peak shaving and valley filling, improves renewable energy integration, and enhances overall system efficiency.
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