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Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Decomposing a renewable energy design and dispatch model
Decomposing a renewable energy design and dispatch model J. Wales et al.
We address a mixed-integer linear programming model which selects a cost-minimizing set of available technologies with which to design a renewable energy system and prescribe their associated dispatch decisions. Realistically sized instances of such models pose computational challenges. To this end, we develop a Lagrangian heuristic based on a decomposition methodology which partitions the model into blocks and optimizes these more manageable, smaller subproblems. It also provides a lower bound to assess solution quality. We apply this methodology to the National Renewable Energy Laboratory’s Renewable Energy Integration and Optimization (REoptTM) model to generate near-optimal solutions to realistic instances containing, on average, approximately 300,000 variables and at least as many constraints, with a mean 30% optimality gap improvement using a five-minute solution time limit, compared to directly solving the original monolith.
Decomposing a renewable energy design and dispatch model
Decomposing a renewable energy design and dispatch model J. Wales et al.
We address a mixed-integer linear programming model which selects a cost-minimizing set of available technologies with which to design a renewable energy system and prescribe their associated dispatch decisions. Realistically sized instances of such models pose computational challenges. To this end, we develop a Lagrangian heuristic based on a decomposition methodology which partitions the model into blocks and optimizes these more manageable, smaller subproblems. It also provides a lower bound to assess solution quality. We apply this methodology to the National Renewable Energy Laboratory’s Renewable Energy Integration and Optimization (REoptTM) model to generate near-optimal solutions to realistic instances containing, on average, approximately 300,000 variables and at least as many constraints, with a mean 30% optimality gap improvement using a five-minute solution time limit, compared to directly solving the original monolith.
Decomposing a renewable energy design and dispatch model
Decomposing a renewable energy design and dispatch model J. Wales et al.
Optim Eng
Wales, Jesse (Autor:in) / Zolan, Alexander (Autor:in) / Flamand, Tülay (Autor:in) / Newman, Alexandra (Autor:in)
Optimization and Engineering ; 26 ; 613-653
01.03.2025
41 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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