{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:GEZMXOELQDLJ6AY72EYQ76LOUU","short_pith_number":"pith:GEZMXOEL","schema_version":"1.0","canonical_sha256":"3132cbb88b80d69f031fd1310ff96ea532023ae298047f3ed6ecafe8257e2996","source":{"kind":"arxiv","id":"1902.10210","version":2},"attestation_state":"computed","paper":{"title":"Adaptive Robust Energy Management Strategy for Campus-Based Commercial Buildings Considering Comprehensive Comfort Levels","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Dawei Su, Desong Bian, Di Shi, Ruisheng Diao, Wencong Su, Zheming Liang, Zhiwei Wang","submitted_at":"2019-02-26T20:44:26Z","abstract_excerpt":"Neglecting consumers' comfort always leads to failure or slow-response to demand response request. In this paper, we propose several comprehensive comfort level models for various appliances in campus-based commercial buildings (CBs). The objective of the proposed system is to minimize O\\&M costs of campus-based CBs and maximize various comfort levels simultaneously under the worst-case scenarios. Adaptive robust optimization (ARO) is leveraged to handle various uncertainties within the proposed system: (i) demand response signals sending from the distribution system operator (DSO); (ii) arriv"},"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":"1902.10210","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.OC","submitted_at":"2019-02-26T20:44:26Z","cross_cats_sorted":[],"title_canon_sha256":"e391968228de13eed455569d3d36ab693e1883368a9cc47c50260c8adff6835b","abstract_canon_sha256":"01cfda40028f69e641ef1a038786740eaa8c8d41d2cb6f0780ae97865c4178bc"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:50:04.492367Z","signature_b64":"kwvm8NgQlWI0YqXuecjS26U8hregI2gs3mq4ATsTfMFKxXOCcN+bA/QnjO/oWXg3Q/t1m8ivsXeIYbusoYfVCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3132cbb88b80d69f031fd1310ff96ea532023ae298047f3ed6ecafe8257e2996","last_reissued_at":"2026-05-17T23:50:04.491746Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:50:04.491746Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Adaptive Robust Energy Management Strategy for Campus-Based Commercial Buildings Considering Comprehensive Comfort Levels","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Dawei Su, Desong Bian, Di Shi, Ruisheng Diao, Wencong Su, Zheming Liang, Zhiwei Wang","submitted_at":"2019-02-26T20:44:26Z","abstract_excerpt":"Neglecting consumers' comfort always leads to failure or slow-response to demand response request. In this paper, we propose several comprehensive comfort level models for various appliances in campus-based commercial buildings (CBs). The objective of the proposed system is to minimize O\\&M costs of campus-based CBs and maximize various comfort levels simultaneously under the worst-case scenarios. Adaptive robust optimization (ARO) is leveraged to handle various uncertainties within the proposed system: (i) demand response signals sending from the distribution system operator (DSO); (ii) arriv"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.10210","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":""},"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":"1902.10210","created_at":"2026-05-17T23:50:04.491847+00:00"},{"alias_kind":"arxiv_version","alias_value":"1902.10210v2","created_at":"2026-05-17T23:50:04.491847+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.10210","created_at":"2026-05-17T23:50:04.491847+00:00"},{"alias_kind":"pith_short_12","alias_value":"GEZMXOELQDLJ","created_at":"2026-05-18T12:33:18.533446+00:00"},{"alias_kind":"pith_short_16","alias_value":"GEZMXOELQDLJ6AY7","created_at":"2026-05-18T12:33:18.533446+00:00"},{"alias_kind":"pith_short_8","alias_value":"GEZMXOEL","created_at":"2026-05-18T12:33:18.533446+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/GEZMXOELQDLJ6AY72EYQ76LOUU","json":"https://pith.science/pith/GEZMXOELQDLJ6AY72EYQ76LOUU.json","graph_json":"https://pith.science/api/pith-number/GEZMXOELQDLJ6AY72EYQ76LOUU/graph.json","events_json":"https://pith.science/api/pith-number/GEZMXOELQDLJ6AY72EYQ76LOUU/events.json","paper":"https://pith.science/paper/GEZMXOEL"},"agent_actions":{"view_html":"https://pith.science/pith/GEZMXOELQDLJ6AY72EYQ76LOUU","download_json":"https://pith.science/pith/GEZMXOELQDLJ6AY72EYQ76LOUU.json","view_paper":"https://pith.science/paper/GEZMXOEL","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1902.10210&json=true","fetch_graph":"https://pith.science/api/pith-number/GEZMXOELQDLJ6AY72EYQ76LOUU/graph.json","fetch_events":"https://pith.science/api/pith-number/GEZMXOELQDLJ6AY72EYQ76LOUU/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/GEZMXOELQDLJ6AY72EYQ76LOUU/action/timestamp_anchor","attest_storage":"https://pith.science/pith/GEZMXOELQDLJ6AY72EYQ76LOUU/action/storage_attestation","attest_author":"https://pith.science/pith/GEZMXOELQDLJ6AY72EYQ76LOUU/action/author_attestation","sign_citation":"https://pith.science/pith/GEZMXOELQDLJ6AY72EYQ76LOUU/action/citation_signature","submit_replication":"https://pith.science/pith/GEZMXOELQDLJ6AY72EYQ76LOUU/action/replication_record"}},"created_at":"2026-05-17T23:50:04.491847+00:00","updated_at":"2026-05-17T23:50:04.491847+00:00"}