Unit Commitment using Nearest Neighbor as a Short-Term Proxy
| Autor: | Elad Gilboa, Louis Wehenkel, Gal Dalal, Shie Mannor |
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| Rok vydání: | 2016 |
| Předmět: |
FOS: Computer and information sciences
Mathematical optimization Computer Science - Artificial Intelligence Computer science 020209 energy Supervised learning 02 engineering and technology Term (time) k-nearest neighbors algorithm Machine Learning (cs.LG) Orders of magnitude (bit rate) Computer Science - Learning Electric power system Power system simulation Artificial Intelligence (cs.AI) 0202 electrical engineering electronic engineering information engineering Operational costs Proxy (statistics) |
| DOI: | 10.48550/arxiv.1611.10215 |
| Popis: | We devise the Unit Commitment Nearest Neighbor (UCNN) algorithm to be used as a proxy for quickly approximating outcomes of short-term decisions, to make tractable hierarchical long-term assessment and planning for large power systems. Experimental results on updated versions of IEEE-RTS79 and IEEE-RTS96 show high accuracy measured on operational cost, achieved in runtimes that are lower in several orders of magnitude than the traditional approach. |
| Databáze: | OpenAIRE |
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