发表机构
University of Oxford; Oxford Martin School, University of Oxford; Bocconi University（牛津大学; 牛津马丁学院; 博科尼大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出考虑老化的滚动时域框架，将其应用于英国市场的电池储能多服务叠加优化，发现考虑老化及高保真建模可显著提升收益，且最优服务组合需随电池老化调整以最大化生命周期利润。
AI 中文摘要
电网级电池储能可通过在电力与频率响应市场中叠加多种服务来获取收益，但确定生命周期内利润最大化的叠加策略仍颇具挑战。各类服务的决策因共享电池系统容量而相互耦合，同时受系统运营商的能源管理规则约束，还受决定系统运行、衰减及生命周期盈利能力的产品特定技术要求影响。本文提出一种考虑老化的滚动时域框架，用于多服务叠加的协同优化，该框架明确纳入产品特定特性与荷电状态合规规则。该框架应用于英国市场，在该市场中，储能运营商可将电力交易与通过新推出的“持久拍卖能力”平台采购的多种动态频率响应服务叠加，同时需遵守国家能源系统运营商设定的能源管理要求。利用真实市场数据，研究表明，衰减建模、贴现率与电池老化共同决定生命周期价值与最优叠加策略；与不考虑衰减的基准方法相比，考虑老化可使生命周期收益提升至多32%，而更高保真度的老化建模较简化模型可进一步使收益提升至多16%；较低贴现率倾向于平衡日历老化与循环老化的策略，较高贴现率则倾向于激进运行策略；在所有策略中，响应正频率偏差的服务始终比响应负频率偏差的服务更受青睐；生命周期利润的最大化需随电池老化调整最优服务组合。
英文摘要
Grid-scale battery energy storage can generate revenue by stacking services across electricity and frequency response markets, yet identifying the lifetime profit-maximising stacking strategy remains challenging. Decisions across services are coupled through shared battery system capacity, constrained by system operator energy management rules, and further shaped by product-specific technical requirements that govern system operation, degradation, and lifetime profitability. This paper presents an ageing-aware receding-horizon framework for co-optimising multi-service stacking that explicitly captures product-specific characteristics and state-of-energy compliance rules. The framework is applied to the Great Britain market, where storage operators can stack electricity trading with multiple dynamic frequency response services procured through the newly introduced 'Enduring Auction Capability' platform under energy management requirements imposed by the National Energy System Operator. Using real market data, we demonstrate that degradation modelling, discount rate, and battery ageing jointly govern both lifetime value and optimal stacking strategy. Accounting for ageing increases lifetime revenue by up to 32% relative to a degradation-agnostic benchmark, while higher-fidelity ageing modelling can provide a further revenue improvement of up to 16% over simpler formulations. Lower discount rates favour strategies that balance calendar and cycling ageing, while higher discount rates favour aggressive operation. Across all strategies, services responding to positive frequency deviations are consistently preferred over those responding to negative deviations. Lifetime profit is maximised by adapting the optimal service mix as the battery ages.
Comments36 pages, 13 figures
