Unit Commitment using Nearest Neighbor as a Short-Term Proxy

2016-11-30 · Gal Dalal, Elad Gilboa, Shie Mannor, Louis Wehenkel

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.

📄 PDF Abstract BibTeX arXiv:1611.10215

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Feasibility Layer Aided Machine Learning Approach for Day-Ahead Operations

2022-08-13 · Arun Venkatesh Ramesh, Xingpeng Li

Day-ahead operations involves a complex and computationally intensive optimization process to determine the generator commitment schedule and dispatch. The optimization process is a mixed-integer linear program (MILP) al…

Projected Autoregression: Autoregressive Language Generation in Continuous State Space

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Standard autoregressive language models generate text by repeatedly selecting a discrete next token, coupling prediction with irreversible commitment at every step. We show that token selection is not the only viable aut…

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This paper is concerned with nearest neighbor search in distributional semantic models. A normal nearest neighbor search only returns a ranked list of neighbors, with no information about the structure or topology of the…

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In this paper we present an extension of existing Nearest-Neighbor heuristics to an algorithm called k-Repetitive-Nearest-Neighbor. The idea is to start with a tour of k nodes and then perform a Nearest-Neighbor search f…

Short-Term Pain for Long-Term Gain: Adaptive Experiment with Post-Commitment Reward Shift

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Decision-makers in learning environments face a dilemma when their short-term optimal actions may not favor their long-term benefits the most. To understand the fundamental tradeoff behind the dilemma, we study adaptive …