[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-84161-en":3,"doc-seo-84161-105":29,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},84161,2336464648746,"Skyler","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","Degradation-Aware Pumping Control of Variable-Speed Pumped Storage via Residual Reinforcement Learning","Variable-speed pumped storage hydropower must meet short-block dispatch commitments while limiting degradation caused by intensified regulation. When a single controller optimizes tracking and wear simultaneously, tracking gains trade off against degradation even with full model knowledge and lookahead. The work introduces a two-layer architecture separating a certifiable commitment-guarantee controller from bounded residual learning. The residual policy adjusts rotor speed within a fixed bound, trained with an operation-degradation index, reducing BEP tracking error by about 96% and cutting total degradation by up to about 56%.","Degradation-Aware Pumping Control of Variable-Speed Pumped Storage via Residual Reinforcement Learning  \nKyung-bin Kwon, Member, IEEE, SangWoo Park, Member, IEEE, and Dam Kim, Member, IEEE  \narXiv :2607 .06911v1 [ ee ss . SY] 8 Jul 2026  \nAbstract—Variable-speed pumped storage hydropower (VSPSH) must honor short-block dispatch commitments while limiting the operational degradation that intensified regulation duty inflicts on its components. When a single controller pursues both aims at once, every tracking gain is paid for in degradation, a conflict that persists even under full model knowledge and lookahead. This paper proposes a two-layer control architecture that separates the guaranteed commitment from the bounded learning. A deterministic feedforward-PI gate controller, auditable and certifiable for grid-connected operation, secures average power delivery over each five-minute block, while a residual reinforcement learning policy adjusts only the rotor speed within a fixed bound the gate loop can always absorb, so the worstcase command is bounded by construction. The speed policy tracks a demand-dependent best-efficiency-point reference and is trained against an operation-degradation index that combines offbest-efficiency hydraulic loss with power and actuation variation into one physically interpretable signal. Across normal and stressed dispatch, the proposed policy lowers best-efficiency-point tracking error by roughly 96% relative to a fixed-speed baseline and cuts total degradation by up to about 56% under the most demanding dispatch. It matches or slightly exceeds a fullinformation model-based optimizer in efficiency while preserving substantially tighter block tracking.  \nIndex Terms—Variable-speed pumped storage hydropower, degradation-aware control, best efficiency point tracking, reinforcement learning  \nI. INTRODUCTION  \nThe accelerating integration of variable renewable energy is reshaping the operating environment of modern power systems. Deepening net-load variability intensifies the demand for fast, dispatchable flexibility [1], [2] . Pumped storage hydropower (PSH) provides more than 90% of global electricity storage volume and remains the backbone resource for absorbing this variability [3] . Flexible resources are coupled to system operations through market dispatch. Units participating in energy and balancing markets must deliver contracted power over short settlement blocks, often five minutes, and balancingmarket penalties are typically assessed on block-average rather than instantaneous deviations [4] . Faithful dispatch compliance is therefore not only a control objective but a market obligation. At the same time, a growing body of evidence shows  \nAll authors contributed equally to this work. (Corresponding author: Dam Kim)  \nK. Kwon is with the Optimization and Control Group, Pacific Northwest National Laboratory, Richland, WA 99352, USA (e-mail: kyung[bin.kwon@pnnl.gov](bin.kwon@pnnl.gov))  \nS. Park is with the Department of Mechanical and Industrial Engineering, New Jersey Institute of Technology, Newark, NJ 07103, USA (e-mail: [sangwoo.park@njit.edu](sangwoo.park@njit.edu))  \nD. Kim is with the Department of Convergence System Engineering, Chungnam National University, Daejeon 34134, South Korea (e-mail: [damkim@cnu.ac.kr](damkim@cnu.ac.kr))  \nthat the intensified regulation duty imposed by renewablerich systems accelerates wear, fatigue, and efficiency loss in hydropower units, which raises maintenance costs and shortens overhaul intervals [5], [6] . Thus, how a flexibility resource executes its dispatch, and not only whether it does, becomesan operational question of direct relevance to power system operations.  \nVariable-speed pumped storage hydropower (VS-PSH) is particularly well positioned to address this tension. In conventional fixed-speed units, the pumping power is essentially dictated by the prevailing head, which leaves no continuous control authority and confines the machine to con","cbCaidSYMeDGa5jU","https://ap.wps.com/l/cbCaidSYMeDGa5jU","pdf",7668608,1,11,"English","en",105,"# Introduction\n## Motivation: dispatch compliance vs degradation\n## Control opportunity from rotor speed degree of freedom\n# Related work and gap","[{\"question\":\"What problem does the paper address for variable-speed pumped storage hydropower?\",\"answer\":\"It addresses the conflict between honoring short-block dispatch commitments and limiting operational degradation from intensified regulation duties.\"},{\"question\":\"How does the proposed two-layer controller architecture work?\",\"answer\":\"A deterministic feedforward-PI gate controller guarantees block-average power delivery, while a residual reinforcement learning policy adjusts only rotor speed within a bounded range that the gate loop can absorb.\"},{\"question\":\"How is degradation considered during reinforcement learning training?\",\"answer\":\"The speed policy is trained against an operation-degradation index that combines off-best-efficiency hydraulic loss with power and actuation variation into one physically interpretable 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problem does the paper address for variable-speed pumped storage hydropower?","Question",{"text":75,"@type":76},"It addresses the conflict between honoring short-block dispatch commitments and limiting operational degradation from intensified regulation duties.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the proposed two-layer controller architecture work?",{"text":80,"@type":76},"A deterministic feedforward-PI gate controller guarantees block-average power delivery, while a residual reinforcement learning policy adjusts only rotor speed within a bounded range that the gate loop can absorb.",{"name":82,"@type":73,"acceptedAnswer":83},"How is degradation considered during reinforcement learning training?",{"text":84,"@type":76},"The speed policy is trained against an operation-degradation index that combines off-best-efficiency hydraulic loss with power and actuation variation into one physically interpretable 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