Title Optimized micro-hydro power plants layout design using messy genetic algorithms
Authors TAPIA CÓRDOBA, ALEJANDRO, Reina D.G., MILLÁN GATA, PABLO, MILLÁN GATA, PABLO, TAPIA CÓRDOBA, ALEJANDRO
External publication No
Means Expert Syst. Appl.
Scope Article
Nature Científica
JCR Quartile 1
SJR Quartile 1
Area International
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085604960&doi=10.1016%2fj.eswa.2020.113539&partnerID=40&md5=e87b4bd454c97c8422a564f2197c78e1
Publication date 01/01/2020
ISI 000583204100011
Scopus Id 2-s2.0-85085604960
DOI 10.1016/j.eswa.2020.113539
Abstract Micro Hydro-Power Plants (MHPP) represent a powerful and effective solution to address the problem of energy poverty in rural remote areas, with the advantage of preserving the natural resources and minimizing the impact on the environment. Nevertheless, the lack of resources and qualified manpower usually constitutes a big obstacle to its adequate application, generally translating into sub-optimal generation systems with poor levels of efficiency. Therefore, the study and development of expert, simple and efficient strategies to assist the design of these installations is of especial relevance. This work proposes a design methodology based on a tailored messy evolutionary computational approach, with the objective of finding the most suitable layout of MHPP, considering several constraints derived from a minimal power supply requirement, the maximum flow usage, and the physical feasibility of the plant in accordance with the real terrain profile. This profile is built on the basis of a discrete topographic survey, by means of a shape-preserving interpolation, which permits the application of a continuous variable-length Messy Genetic Algorithm (MGA). The optimization problem is then formulated in both single-objective (cost minimization) and multi-objective (cost minimization and power supply maximization) modes, including the study of the Pareto dominance. The algorithm is applied to a real scenario in a remote community in Honduras, obtaining a 56.96% of cost reduction with respect to previous works. © 2020
Keywords Cost reduction; Design; Genetic algorithms; Hydroelectric power; Computational approach; Continuous variables; Impact on the environment; Messy genetic algorithms; Microhydro power plants; Optimizatio
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