{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:QY723CNNR2XTAWMGNW34KI2GMX","short_pith_number":"pith:QY723CNN","schema_version":"1.0","canonical_sha256":"863fad89ad8eaf3059866db7c5234665d03c046abb90c3d90f2ebf2ec6a9a2ab","source":{"kind":"arxiv","id":"1908.09034","version":2},"attestation_state":"computed","paper":{"title":"Stochastic Dynamic Programming for Wind Farm Power Maximization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","eess.SY"],"primary_cat":"math.OC","authors_text":"Mario Rotea, Tyler Summers, Yi Guo","submitted_at":"2019-08-23T20:44:03Z","abstract_excerpt":"Wind farms can increase annual energy production (AEP) with advanced control algorithms by coordinating the set points of individual turbine controllers across the farm. However, it remains a significant challenge to achieve performance improvements in practice because of the difficulty of utilizing models that capture pertinent complex aerodynamic phenomena while remaining amenable to control design. We formulate a multi-stage stochastic optimal control problem for wind farm power maximization and show that it can be solved analytically via dynamic programming. In particular, our model incorp"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1908.09034","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2019-08-23T20:44:03Z","cross_cats_sorted":["cs.SY","eess.SY"],"title_canon_sha256":"32a8803a507c67e4c070a8f76d275df5bcb81509b26264260fe01cca83665059","abstract_canon_sha256":"b20ea08c1b36851354340f8c85beef2425d181264ab2fa0900169334eaa5eb52"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:48:17.983813Z","signature_b64":"cdNJ1Ntk31NYq4zktj5sEkc+XQzbA1jl0MNLpuyYszU7xNYO5OTuq6u4F66q1GAKBy9jPWkrl/ByCTtpr0QaCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"863fad89ad8eaf3059866db7c5234665d03c046abb90c3d90f2ebf2ec6a9a2ab","last_reissued_at":"2026-07-05T00:48:17.983309Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:48:17.983309Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Stochastic Dynamic Programming for Wind Farm Power Maximization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY","eess.SY"],"primary_cat":"math.OC","authors_text":"Mario Rotea, Tyler Summers, Yi Guo","submitted_at":"2019-08-23T20:44:03Z","abstract_excerpt":"Wind farms can increase annual energy production (AEP) with advanced control algorithms by coordinating the set points of individual turbine controllers across the farm. However, it remains a significant challenge to achieve performance improvements in practice because of the difficulty of utilizing models that capture pertinent complex aerodynamic phenomena while remaining amenable to control design. We formulate a multi-stage stochastic optimal control problem for wind farm power maximization and show that it can be solved analytically via dynamic programming. In particular, our model incorp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.09034","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/1908.09034/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1908.09034","created_at":"2026-07-05T00:48:17.983388+00:00"},{"alias_kind":"arxiv_version","alias_value":"1908.09034v2","created_at":"2026-07-05T00:48:17.983388+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.09034","created_at":"2026-07-05T00:48:17.983388+00:00"},{"alias_kind":"pith_short_12","alias_value":"QY723CNNR2XT","created_at":"2026-07-05T00:48:17.983388+00:00"},{"alias_kind":"pith_short_16","alias_value":"QY723CNNR2XTAWMG","created_at":"2026-07-05T00:48:17.983388+00:00"},{"alias_kind":"pith_short_8","alias_value":"QY723CNN","created_at":"2026-07-05T00:48:17.983388+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/QY723CNNR2XTAWMGNW34KI2GMX","json":"https://pith.science/pith/QY723CNNR2XTAWMGNW34KI2GMX.json","graph_json":"https://pith.science/api/pith-number/QY723CNNR2XTAWMGNW34KI2GMX/graph.json","events_json":"https://pith.science/api/pith-number/QY723CNNR2XTAWMGNW34KI2GMX/events.json","paper":"https://pith.science/paper/QY723CNN"},"agent_actions":{"view_html":"https://pith.science/pith/QY723CNNR2XTAWMGNW34KI2GMX","download_json":"https://pith.science/pith/QY723CNNR2XTAWMGNW34KI2GMX.json","view_paper":"https://pith.science/paper/QY723CNN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1908.09034&json=true","fetch_graph":"https://pith.science/api/pith-number/QY723CNNR2XTAWMGNW34KI2GMX/graph.json","fetch_events":"https://pith.science/api/pith-number/QY723CNNR2XTAWMGNW34KI2GMX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QY723CNNR2XTAWMGNW34KI2GMX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QY723CNNR2XTAWMGNW34KI2GMX/action/storage_attestation","attest_author":"https://pith.science/pith/QY723CNNR2XTAWMGNW34KI2GMX/action/author_attestation","sign_citation":"https://pith.science/pith/QY723CNNR2XTAWMGNW34KI2GMX/action/citation_signature","submit_replication":"https://pith.science/pith/QY723CNNR2XTAWMGNW34KI2GMX/action/replication_record"}},"created_at":"2026-07-05T00:48:17.983388+00:00","updated_at":"2026-07-05T00:48:17.983388+00:00"}