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储能系统技术 储能系统 ★ 5.0

需求侧管理背景下可再生能源来源对储能系统优化方案的敏感性研究:表后案例分析

Sensitivity of energy storage system optimization program to the source of renewable energy in the presence of demand side management: A behind-the-meter case study

作者 Yogesh Manoharan · Keith Olson · Alexander John Headley
期刊 Applied Energy
出版日期 2025年1月
卷/期 第 388 卷
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 While energy storage systems are helpful demand side management (DSM) can satisfy similar goals with limitations.
语言:

中文摘要

摘要 安装表后(behind-the-meter, BTM)可再生能源的趋势日益增强,以支持能源转型。节能方法如储能系统(ESS)和需求侧管理(DSM)可用于增强可再生能源的利用并最大化其效益。本研究探讨了不同可再生能源来源对节能策略、系统安装及长期规划决策的影响。本文提出了一种优化框架,用于确定储能系统(ESS)容量和需求侧管理(DSM)策略。通过比较太阳能和风能可再生能源对优化方案结果的影响,有助于为特定用电负荷曲线选择合适的可再生能源和节能方法。研究基于可再生能源类型及其渗透率,分析其对电力采购、系统安装规模、节能效益、可再生能源削减量以及储能平准化成本(LCOS)的影响。文中对比了ESS与DSM选项,并探索其协同效应,以最小化电力采购并控制峰值功率。此外,关键影响因素(如电价、电池成本和往返效率)的持续变化凸显了这些参数在系统安装规划中的重要性,以及保持对其现实认知的必要性。因此,本文对这些影响因素进行了分析,作为所提模型的敏感性分析。结果表明,系统估算值可能增加至原来的三倍,突显了在规划中真实考虑这些因素以避免潜在失败或经济损失的必要性。本研究以夏威夷自然能源实验室(Natural Energy Laboratory of Hawaii Authority, NELHA)为案例,该机构是全球最大的多区域海水公用事业设施。所提出的优化框架为该案例选择了合适的可再生能源和节能方法,并使用先进工具对模型进行了验证。本研究提出的优化框架将为有意安装可再生能源和储能系统的水务公用事业部门提供支持。

English Abstract

Abstract The trend of installing renewable energy in behind-the-meter (BTM) has increased to support energy transition. Energy-saving methodologies, such as energy storage systems (ESSs) and demand side management (DSM), are available to augment renewable energies and maximize their benefits. This research examines the impact of different renewable energy sources on energy-saving strategies, system installations, and long-term planning decisions. This study presents an optimization framework to determine the Energy Storage Systems (ESS) capacity and Demand Side Management (DSM) strategies. The effect of solar and wind renewable energies on the optimization program results was compared to aid the selection of suitable renewable energy and energy-saving methodologies for an energy load profile. Renewable energy and its penetration were studied based on its impact on energy purchase, system installation size, savings, renewable curtailment , and levelized cost of storage (LCOS). ESS and DSM options are compared, and their synergies are explored to minimize energy purchases and control peak power. Furthermore, the ongoing changes in influential factors, such as electricity prices, battery costs, and roundtrip efficiency, underscore their importance in system installation planning and to maintain a realistic perspective on these parameters. Therefore, an analysis of these influential factors is conducted, serving as a sensitivity analysis for the proposed model. This shows that system estimates can triple, highlighting the necessity of realistically considering these factors to avert potential failure or loss. This study is performed on the case of the Natural Energy Laboratory of Hawaii Authority (NELHA), the world's largest multizone seawater utility. The proposed optimization framework selects suitable renewable energy and energy-saving methodologies for the considered case and is validated with the state-of-the-art tool. The proposed optimization framework in this study will support water utilities interested in installing renewable energy and energy storage systems.
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SunView 深度解读

该研究对阳光电源表后储能解决方案具有重要指导意义。文章验证了ESS与DSM协同优化在降低购电成本和削峰方面的价值,与我司PowerTitan储能系统和ST系列PCS的应用场景高度契合。研究强调电池成本、往返效率等参数对系统配置的敏感性,可为我司储能系统容量优化算法提供参考。针对海水公用事业的多区域负荷特性,我司可结合iSolarCloud平台开发面向工业用户的源-储-荷协同优化工具,提升光伏+储能系统经济性,支持能源转型目标。