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考虑跨季节钻孔热能储存的混合可再生能源-CCHP系统容量优化规划
Optimal Capacity Planning of Hybrid Renewable Energy - CCHP System Considering Inter Seasonal Borehole Thermal Energy Storage
| 作者 | Yuan Du · Yixun Xue · Lei Chen · Mohammad Shahidehpour · Lei Yang · Xinrong Zhang |
| 期刊 | IEEE Transactions on Sustainable Energy |
| 出版日期 | 2025年5月 |
| 技术分类 | 储能系统技术 |
| 技术标签 | 储能系统 |
| 相关度评分 | ★★★★★ 5.0 / 5.0 |
| 关键词 | 冷热电联供系统 混合可再生能源 地下热能储存 两阶段鲁棒模型 Benders分解算法 |
语言:
中文摘要
冷热电三联供(CCHP)系统能源利用效率高,通常超过80%。然而,传统CCHP依赖微型燃气轮机,导致碳排放问题。本文设计了一种混合可再生能源-CCHP系统,电力负荷由光伏与风电提供,冷热负荷通过热泵电转热满足。针对可再生能源的季节性波动,引入钻孔热能储存(BTES),将夏季多余能量储于地下供冬季使用。构建了基于决策相关不确定性的两阶段鲁棒优化模型,并采用改进的Benders分解算法求解。通过中国鄂尔多斯实际案例验证方法有效性,分析了BTES集成、不确定性预算及可再生能源比例的影响。
English Abstract
Combined cooling, heating, and power (CCHP) systems are recognized for their high energy efficiency, with utilization rates exceeding 80%. However, traditional CCHP systems often rely on microgas turbines, contributing to carbon emissions. In this paper, we design a hybrid renewable energy - CCHP system, where the electric load is provided by photovoltaic and wind power, and the heating/cooling loads are supplied by converting power to heat by heat pumps. Considering the seasonal variability of renewable energy generation, we introduce borehole thermal energy storage (BTES) into the CCHP system, transforming the ground into a thermal storage that stores excess energy during summer for use in winter. We formulate the problem as a two-stage robust model with decision-dependent uncertainty. Then, we develop a customized algorithm based on Benders decomposition to effectively solve this model and discuss the algorithm improvement techniques. Our approach is validated through a case study of an actual system in Ordos, China, where the effects of BTES integration, uncertainty budget value, and varying ratios of renewable energy are analyzed.
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SunView 深度解读
该混合可再生能源-CCHP系统与阳光电源多产品线深度契合。钻孔热能储存(BTES)的跨季节储能理念可启发ST系列储能系统开发长周期储能解决方案,突破现有电化学储能的时长限制。两阶段鲁棒优化模型可直接应用于PowerTitan大型储能系统的容量配置优化,提升光伏-风电-储能混合系统的经济性。热泵电转热技术与阳光电源SG逆变器的直流耦合可构建高效冷热电联供方案,拓展工商业园区应用场景。决策相关不确定性建模方法可集成至iSolarCloud平台,增强多能互补系统的智能调度能力,为综合能源服务业务提供核心算法支撑。