A meta‐heuristic approach to the unit commitment problem under network constraints

Abstract

Purpose

The purpose of this paper is to solve the problem of committing electric power generators (unit commitment, UC), considering network constraints.

Design/methodology/approach

The UC is first solved with a local search based meta‐heuristic, following the assumption that all generators and loads are connected to a single network node. For evaluation purposes, the economical production levels of the units committed are computed by running a pre‐dispatch algorithm where network constraints are not included. If a good quality solution is reached, an economic dispatch (ED) with network constraints is performed, where the geographic location of generators and loads are considered. Therefore, the production level of each committed generator is performed that leads to the global lowest solution cost, regarding both the generators' costs and constraints and the power system network constraints.

Findings

The algorithm proposed is computationally efficient, given the time available for decision making. In addition, the solution for this algorithm, in terms of minimization of total costs, is generally better than the solution of the two phases approach. Some contractual and legal aspects related with the injection in network connections can also be included in the model.

Practical implications

UC with network constraints has a large potential of use, especially for small and medium size power systems. It reflects reality in a closer way and provides a more complete and realistic knowledge about the system in operation.

Originality/value

The paper presents an approach where the ED with network constraints is integrated with the UC procedure. The model described is currently implemented in an EMS package offered in the market – making it a case of successful transfer from science to industry.

Citation

Pereira, J., Viana, A., Lucus, B.G. and Matos, M. (2008), "A meta‐heuristic approach to the unit commitment problem under network constraints", International Journal of Energy Sector Management, Vol. 2 No. 3, pp. 449-467. https://doi.org/10.1108/17506220810892973