Optimizing the Structure of Distribution Smart Grids with Renewable Generation against Abnormal Conditions: A Complex Networks Approach with Evolutionary Algorithms

Lucas Cuadra, Miguel Del Pino, José Carlos Nieto-Borge and Sancho Salcedo-Sanz
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Lucas Cuadra: Department of Signal Processing and Communications, University of Alcalá, Alcalá de Henares, 28805 Madrid, Spain
Miguel Del Pino: Department of Signal Processing and Communications, University of Alcalá, Alcalá de Henares, 28805 Madrid, Spain
José Carlos Nieto-Borge: Department of Physics and Mathematics, University of Alcalá, Alcalá de Henares, 28805 Madrid, Spain
Sancho Salcedo-Sanz: Department of Signal Processing and Communications, University of Alcalá, Alcalá de Henares, 28805 Madrid, Spain

Energies, 2017, vol. 10, issue 8, 1-31

Abstract: In this work, we describe an approach that allows for optimizing the structure of a smart grid (SG) with renewable energy (RE) generation against abnormal conditions (imbalances between generation and consumption, overloads or failures arising from the inherent SG complexity) by combining the complex network (CN) and evolutionary algorithm (EA) concepts. We propose a novel objective function (to be minimized) that combines cost elements, related to the number of electric cables, and several metrics that quantify properties that are beneficial for SGs (energy exchange at the local scale and high robustness and resilience). The optimized SG structure is obtained by applying an EA in which the chromosome that encodes each potential network (or individual) is the upper triangular matrix of its adjacency matrix. This allows for fully tailoring the crossover and mutation operators. We also propose a domain-specific initial population that includes both small-world and random networks, helping the EA converge quickly. The experimental work points out that the proposed method works well and generates the optimum, synthetic, small-world structure that leads to beneficial properties such as improving both the local energy exchange and the robustness. The optimum structure fulfills a balance between moderate cost and robustness against abnormal conditions. Our approach should be considered as an analysis, planning and decision-making tool to gain insight into smart grid structures so that the low level detailed design is carried out by using electrical engineering techniques.

Keywords: robustness; abnormal conditions; smart grid; complex network; evolutionary algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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