Reducing computation time with a rolling horizon approach applied to a MILP formulation of multiple urban energy hub system

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Abstract

Energy hub model is a powerful concept allowing the interactions of many energy conversion and storage systems to be optimized. Solving the optimal configuration and operating strategy of an energy hub combining multiple energy sources for a whole year can become computationally demanding. Indeed the effort to solve a mixed-integer linear programming (MILP) problem grows dramatically with the number of integer variables. This paper presents a rolling horizon approach applied to the optimisation of the operating strategy of an energy hub. The focus is on the computational time saving realized by applying a rolling horizon methodology to solve problems over many time-periods. The choice of rolling horizon parameters is addressed, and the approach is applied to a model consisting of a multiple energy hubs. This work highlights the potential to reduce the computational burden for the simulation of detailed optimal operating strategies without using typical-periods representations. Results demonstrate the possibility to improve by 15 to 100 times the computational time required to solve energy optimisation problems without affecting the quality of the results.

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APA

Marquant, J. F., Evins, R., & Carmeliet, J. (2015). Reducing computation time with a rolling horizon approach applied to a MILP formulation of multiple urban energy hub system. In Procedia Computer Science (Vol. 51, pp. 2137–2146). Elsevier B.V. https://doi.org/10.1016/j.procs.2015.05.486

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