Unit Commitment Without Commitment: A Dynamic Programming Approach for Managing an Integrated Energy System Under Uncertainty

Building Flexibility into Energy System Dispatch The growing use of renewable energy is forcing power system operators to grapple with increasing uncertainty and intermittency in their energy supplies and demands. In “Unit Commitment without Commitment: A Dynamic Programming Approach for Managing an Integrated Energy System Under Uncertainty,” Brown and Smith develop a dynamic programming (DP) framework for balancing supply and demand over time. The approach introduces stochastic Lagrange multipliers as surrogate energy prices, which reduces the system-wide DP to a collection of unit-specific DPs, where each unit is managed to maximize its expected profit over a long time horizon, given these uncertain prices. Real-time dispatch decisions are then made using the unit-specific value functions to capture the longer-term impacts of the dispatch decisions. Using data from the Duke Energy Carolinas and Progress systems, this new approach reduced operational costs by 2% in current systems and 4%–5% in example future scenarios with increased solar and storage capabilities. Strikingly, the proposed methods performed within 0.2%–0.3% of plans based on perfect foresight, across a wide variety of scenarios.

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Publication Details

Journal
Operations Research
Published
2025-03-05
DOI
https://doi.org/10.1287/opre.2023.0546
Citations
4
Primary Topic
Electric Power System Optimization
Type
article
Field-Weighted Citation Impact
2.92
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article

Unit Commitment Without Commitment: A Dynamic Programming Approach for Managing an Integrated Energy System Under Uncertainty

David B. Brown, James E. Smith
4 citations
Operations Research
Electric Power System Optimization
2.92
article

Unit Commitment Without Commitment: A Dynamic Programming Approach for Managing an Integrated Energy System Under Uncertainty

David B. Brown, James E. Smith
article en
4 citations

Abstract

Building Flexibility into Energy System Dispatch The growing use of renewable energy is forcing power system operators to grapple with increasing uncertainty and intermittency in their energy supplies and demands. In “Unit Commitment without Commitment: A Dynamic Programming Approach for Managing an Integrated Energy System Under Uncertainty,” Brown and Smith develop a dynamic programming (DP) framework for balancing supply and demand over time. The approach introduces stochastic Lagrange multipliers as surrogate energy prices, which reduces the system-wide DP to a collection of unit-specific DPs, where each unit is managed to maximize its expected profit over a long time horizon, given these uncertain prices. Real-time dispatch decisions are then made using the unit-specific value functions to capture the longer-term impacts of the dispatch decisions. Using data from the Duke Energy Carolinas and Progress systems, this new approach reduced operational costs by 2% in current systems and 4%–5% in example future scenarios with increased solar and storage capabilities. Strikingly, the proposed methods performed within 0.2%–0.3% of plans based on perfect foresight, across a wide variety of scenarios.

Operations ResearchVol. 73(4)
Dartmouth College (US), Duke University (US)
Affordable and clean energy
Openalex Percentile: Top 10%
Electric Power System Optimization
2.92
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