{"paper":{"title":"Modeling Coincident Peak Pricing in Electricity Markets: Challenges and Peak Shaving Effectiveness","license":"http://creativecommons.org/licenses/by/4.0/","headline":"Fictitious-play dynamics in a game model of coincident peak pricing reliably reduce system peaks, while best-response dynamics can increase them under tight capacity.","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Conleigh Byers, Derya Cansever, Le Xie, Lucy Diao, Qian Zhang, Sadie Zhao, Yiling Chen","submitted_at":"2026-05-16T03:56:31Z","abstract_excerpt":"Coincident Peak (CP) pricing is widely used in U.S. electricity markets to allocate capacity and transmission costs. This paper develops a behavioral game-theoretic framework for CP-driven load shifting that couples a nonlinear cost-allocation model with day-ahead (one-shot) and real-time (sequential-learning) decision processes. We examine two update rules, namely best-response dynamics (BRD) and fictitious-play dynamics (FPD), across continuous and finite action spaces to quantify how flexibility, action resolution, and participation influence peak outcomes. Using ERCOT peak-day data, we fin"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"Using ERCOT peak-day data, we find that FPD reliably reduces system peaks, whereas BRD is more variable and can increase peaks under tight-capacity conditions.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"The framework assumes that real consumers will update their load-shifting decisions according to the modeled best-response or fictitious-play dynamics rather than other behavioral patterns.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"Simulations with a behavioral game-theoretic framework on ERCOT peak-day data show fictitious-play dynamics reduce peaks more reliably than best-response dynamics, with finer action resolution and careful signals improving outcomes.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"Fictitious-play dynamics in a game model of coincident peak pricing reliably reduce system peaks, while best-response dynamics can increase them under tight capacity.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"2ea3012f459ea061d6fdfd677dbd15196f079fe2da4bf79d1ac1ec4bc92c6f67"},"source":{"id":"2605.16794","kind":"arxiv","version":1},"verdict":{"id":"1e356cb3-82bf-4074-9048-2b97832e1d2d","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-19T21:17:12.161853Z","strongest_claim":"Using ERCOT peak-day data, we find that FPD reliably reduces system peaks, whereas BRD is more variable and can increase peaks under tight-capacity conditions.","one_line_summary":"Simulations with a behavioral game-theoretic framework on ERCOT peak-day data show fictitious-play dynamics reduce peaks more reliably than best-response dynamics, with finer action resolution and careful signals improving outcomes.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"The framework assumes that real consumers will update their load-shifting decisions according to the modeled best-response or fictitious-play dynamics rather than other behavioral patterns.","pith_extraction_headline":"Fictitious-play dynamics in a game model of coincident peak pricing reliably reduce system peaks, while best-response dynamics can increase them under tight capacity."},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2605.16794/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"doi_title_agreement","ran_at":"2026-05-19T21:31:19.323054Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"doi_compliance","ran_at":"2026-05-19T21:31:00.506672Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"claim_evidence","ran_at":"2026-05-19T19:01:56.292514Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"ai_meta_artifact","ran_at":"2026-05-19T18:33:26.428473Z","status":"skipped","version":"1.0.0","findings_count":0}],"snapshot_sha256":"a6b498c7d1ea0fd349c1863f59edc51b0c4065ce8e5a5d5ebd276dac1e2bfc55"},"references":{"count":27,"sample":[{"doi":"","year":2018,"title":"Incentive properties of coincident peak pricing,","work_id":"58fb1ca7-79be-4a83-9a87-0cb39167ac9d","ref_index":1,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2023,"title":"Manual M-20: ISO New England Manual for the Forward Capacity Market (FCM), Revision 27,","work_id":"ee430f82-3467-449e-9315-94e4e228a747","ref_index":2,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2017,"title":"Priorities for the evolution of an energy-only electricity market design in ercot,","work_id":"4adf4d98-1fcd-4bd2-b9d2-ca046ab9f382","ref_index":3,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2019,"title":"Demand responses in ercot,","work_id":"7fc988ce-6776-4cc3-9894-25052286896b","ref_index":4,"cited_arxiv_id":"","is_internal_anchor":false},{"doi":"","year":2018,"title":"Re- view Transmission Access Charge Structure: Revised Straw Proposal,","work_id":"8248fa0b-49ac-44e7-9f98-47a53b2f04cc","ref_index":5,"cited_arxiv_id":"","is_internal_anchor":false}],"resolved_work":27,"snapshot_sha256":"55835fea516762bea16ced3b0d206ccdd3a424e84aeb2b935c04afc1e74a65b4","internal_anchors":0},"formal_canon":{"evidence_count":2,"snapshot_sha256":"ff722be81907e46bfa53669163ef9011098937423699b2157666b3c151641909"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}