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Yet, it remains a dataset-specific task, requiring comprehensive training data, limiting scalability, and resulting in high model development and maintenance effort. Recently, foundation models aiming to learn generalizable patterns via extensive pretraining have shown strong performance in multiple prediction tasks. Despite their success and strong potential in energy forecasting, a systematic, use-case-differentiated evaluation is still missing. We address this gap by presenting the Foundation Models in Energy Time Series Forecasting (FETS) benchmark. We (1) provide a structured overview of energy forecasting use cases along three main dimensions, i.e., stakeholders, attributes, and data categories, (2) curate 54 datasets across 9 data categories, guided by typical stakeholder inte","title":"FETS Benchmark: Foundation Models Enable Scalable and Generalizable Energy Time Series Forecasting","url":"https://arxiv.org/abs/2604.22328","vendor":"arxiv_cs_ai"},"summary":"arXiv:2604.22328v2 Announce Type: replace-cross \nAbstract: Driven by the transition towards a climate-neutral energy system, accurate energy time series forecasting is critical for planning and operations. Yet, it remains a dataset-specific task, requiring comprehensive training data, limiting scalability, and resulting in high model development and maintenance effort. Recently, foundation models aiming to learn generalizable patterns via extensive pretraining have shown strong performance in multiple prediction tasks. Despite their success and strong potential in energy forecasting, a systematic, use-case-differentiated evaluation is still missing. We address this gap by presenting the Foundation Models in Energy Time Series Forecasting (FETS) benchmark. We (1) provide a structured overview of energy forecasting use cases along three main dimensions, i.e., stakeholders, attributes, and data categories, (2) curate 54 datasets across 9 data categories, guided by typical stakeholder inte","title":"FETS Benchmark: Foundation Models Enable Scalable and Generalizable Energy Time Series Forecasting","vendor":"arxiv_cs_ai"},"confidence":{"method":"deterministic"},"decision":"POSITIVE","issued_at":"2026-07-21T04:43:35Z","notes":"Spider vendor_press (news) news.vendor_press.v1","object":{"captured_by":"crovia.spider.vendor_press","primary_source_url":"https://arxiv.org/abs/2604.22328"},"predecessors":[],"schema":"crovia.axiom.v1","signature":"ed25519:939b51888f9b5579e0984e67ccb7f65040d5593175a2402adf14aaff6aa3b01850f986610fa1af2fc7ca5dc89ebf8c36ba7fbcbc1053e35cb487de7d7575fa06","signer":"crovia.substrate","subject":{"observed_at":"2026-07-21T04:43:35Z","source_collector":"spider:vendor_press","target_id":"https://arxiv.org/abs/2604.22328"},"tsa":{"authority":"crovia.substrate.bootstrap","rfc3161_token":"{\"kind\":\"crovia.bootstrap.tsa\",\"source_jsonl\":\"/opt/crovia/spider/data/news/vendor_press_v1.jsonl\",\"source_seal_merkle_root\":\"spider_vendor_press_v1\",\"upgrade_path\":\"Sessione H \\u2014 OpenTimestamps weekly anchor\"}"},"zk_mode":"clear","zk_proof":null},"ledger":{"leaf_hash":"b590a84a530219c2b7b34d75b455f2a30a40b9796e2ebf9d2be7852337c8c712","leaf_index":336969,"ledger_path":"/opt/crovia/substrate/axiom_ledger.jsonl"},"merkle_proof":{"hash_alg":"sha256","leaf_prefix":"0x00","node_prefix":"0x01","odd_leaf_rule":"duplicate_last","path":[{"sibling":"3848bbd2f36d77a371c49f9ebb98454beb6d1443acc49f3dfc979b6ca3b4ed38","side":"left"},{"sibling":"123c1377b87344afd7f271f3b9ca3bfc9e0d137895c38552d70d8581a1130e2a","side":"right"},{"sibling":"a9faf62b4d0d60d7648bd5a523b1cb7a5f749e4cb1ce91d5c0ab4120bbd24e3b","side":"right"},{"sibling":"766e7f1c0f512b5c56cd8fe26c9e4a36d5a67faf4f95af91e9f64b2566ba80f2","side":"left"},{"sibling":"cf8fd672f0b99106860288e683595c197bf2013eea89a0cf199b824996c50e67","side":"right"},{"sibling":"0fa380948580c9963d43a0764436b6d6459eb424e5f3c9e58b70d177527d9904","side":"right"},{"sibling":"34efd454df46a7476d0bc83ac9843e7409ddde5c8ee1426de19ece35f23d2d83","side":"left"},{"sibling":"45255096c5a08e740a615b6e3c262589a170dbfc373bdeaceae175916dd2ab97","side":"right"},{"sibling":"1298242aa509bc13b92160250ead2d95a721941ca6310e33b9eb0bf0821557d0","side":"right"},{"sibling":"61d44c6d16b87de577db53cff0dba2f003c50c036d92dc335120aa70124c8788","side":"right"},{"sibling":"5d0b792dbe69fd0a7cd8d79b467aa10204d1f25be602c06190f3423bc22727b8","side":"left"},{"sibling":"9eb5077edfb3dc553857d4794b925bfce117e0f8a1d049af5d0dd9026b470eef","side":"right"},{"sibling":"414b1a70fd1dcb25489a194714b97492b066684b15d0b7a48a176c4b9b5bc713","side":"right"},{"sibling":"21d66dd41003813f710b7617944f1bfba3258658a5d3370c21cad8f9e945bc99","side":"left"},{"sibling":"613f015699131eb89bd755dee67133be95af25cf5f16c1c8ce4b99d963b8dd86","side":"right"},{"sibling":"a729b574b1135956436ded5eef1fe8f08014ff6a0729749d307ab1bca93fcdc9","side":"right"},{"sibling":"77025bcb374a7ad74f520643e20a8ae1205a7ee78507b0beb93117760f1c29d3","side":"left"},{"sibling":"4bf21052e085e8ac81f1dec1d2b310bd12bf948992de6177d12e9d2fda8d39f0","side":"right"},{"sibling":"1cecb7f447febd025aac272837c80de218aecc6485d2395a509b2a1f1b9c746e","side":"left"}]},"schema":"crovia.axiom_proof.v1","seal":{"first_collector_run_id":"","first_receipt_hash":"","jsonl_path":"/opt/crovia/substrate/axiom_ledger.jsonl","key_id":"430895f101d38164","last_collector_run_id":"","last_receipt_hash":"","leaf_count":337144,"merkle_root":"5e969cc01afa67e4dbe5d37b712cdb10f4aa1fd74404e02eab724cf487c8d6d9","public_key_hex":"cf742e26f75669dc673cb5c0786a1ae23ae8ca19c347317192ce40c28a7ff25c","run_id":"hourly_json_retrofit_20260721T053701Z","schema":"crovia.seal.v1","seal_family_version":"crovia-seal-family/1","seal_kind":"substrate_batch","sealed_at":"2026-07-21T05:38:38Z","sig_algorithm":"ed25519","signature":"5c0c1a8dd2793d787ccd5e49e8b4d70eed136352555518589f05c74be357fc171702e42a76c3a556d90e3d51ff36cb3d292aaac83c66566de7b943f318bda50c","signer_version":"1.1.0"},"trust_root":{"key_id":"430895f101d38164","public_key_hex":"cf742e26f75669dc673cb5c0786a1ae23ae8ca19c347317192ce40c28a7ff25c","signature_algorithm":"ed25519","url":"/registry/canon/TRUST_ROOT.md"},"verifier":{"spec":"/registry/canon/AXIOM_RECEIPT_v1.md","url":"/v/axm_8fdf44ed368d21ec43e99a3c06ae6a57e13ec24ab9de1dd3159d8e86a112b51e"}}