A near-optimal solution method for coordinated operation planning problem of power- and heat-interchange networks using column generation-based decomposition

Tetsuya Wakui, Moe Hashiguchi and Ryohei Yokoyama

Energy, 2020, vol. 197, issue C

Abstract: A near-optimal solution method for coordinated operation-planning problems of power- and heat-interchange networks using column generation-based decomposition was developed to enhance computational efficiency and scalability. The coordinated operation-planning problem, based on a mixed-integer linear programming (MILP) approach, was decomposed into a master problem concerning power and heat interchanges and subproblems for energy-supply systems on the basis of the Dantzig-Wolfe reformulation. To determine a near-optimal solution, heuristic finalization was developed, in which a final MILP problem is solved after fixing part of binary variables based on the lower bound result obtained through two-stage iterative column generation. The developed method was then applied to the coordinated operation planning of power- and heat-interchange networks consisting of 5–100 cogeneration systems using a 150-kWe gas engine and a 45-kWe polymer electrolyte fuel cell on a winter representative day. In the case of using 100 cogeneration systems, 93% of the binary variables expressing the on/off status of the cogeneration units and heat-interchange pumps were fixed in the heuristic finalization. The near-optimal solution, which has a lower daily energy cost than in the conventional solution method, can be obtained without optimization termination due to limits of computation time and memory usage.

Keywords: Optimization; Coordinated operation planning; Energy network; Dantzig-Wolfe decomposition; Column generation; Mixed-integer linear programming (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:197:y:2020:i:c:s0360544220302255

DOI: 10.1016/j.energy.2020.117118

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