Metaheuristics and transmission expansion planning: a comparative case study

M. Moradi, H. Abdi, S. Lumbreras

Energies Vol. 14, nº. 12, pp. 3618-1 - 3618-23

Summary:

Transmission expansion planning (TEP), the determination of the new transmission lines to be added to an existing power network, is a key element in power systems strategy. Using classical optimization to define the most suitable reinforcements is the most desirable alternative. However, the size of the problems under study is growing, because of the uncertainties introduced by renewable generation or electric vehicles (EVs) and because of the larger sizes under consideration given the trends for higher renewable shares and stronger market integration. This means that classical optimization, even using efficient techniques such as stochastic decomposition, can have issues when solving large problems. This is compounded by the fact that, in many cases, it is necessary to solve a large number of instances of the problem in order to incorporate further considerations. Thus, it can be interesting to resort to metaheuristics, which can offer quick solutions at the expense of an optimality guarantee. Metaheuristics can even be combined with classical optimization to try to extract the best of both worlds. There is a vast literature that tests individual metaheuristics on a specific case study, but wide comparisons are missing. In this paper, we test a Genetic Algorithm (GA), Orthogonal Crossover based Differential Evolution (OXDE), Grey Wolf Optimizer (GWO), Moth-Flame Optimization (MFO), Exchange Market Algorithm (EMA), Sine Cosine Algorithm (SCA) optimization and Imperialistic Competitive Algorithm (ICA). The algorithms were applied to the standard test systems of IEEE 24, and 118 buses. Results indicate that, although all metaheuristics are effective, they have diverging profiles in computational time and finding optimal plans of TEP.

Spanish layman's summary:

Comparamos distintos metaheurísticos en el problema de expansión del transporte. Varios de ellos tienen un buen comportamiento.

English layman's summary:

We compare different metaheuristics in the transmission expansion planning problem. Several of them have a good performance.

Keywords: Transmission Expansion Planning (TEP), Optimization Algorithms, Uncertainty, Wind Farms, Electrical Vehicles (EVs).

JCR Impact Factor and WoS quartile: 3,252 - Q3 (2021); 3,000 - Q3 (2023)

DOI reference: https://doi.org/10.3390/en14123618

Published on paper: June 2021.

Published on-line: June 2021.

Citation:
M. Moradi, H. Abdi, S. Lumbreras, Metaheuristics and transmission expansion planning: a comparative case study. Energies. Vol. 14, nº. 12, pp. 3618-1 - 3618-23, June 2021. [Online: June 2021]