Title |
Optimized micro-hydro power plants layout design using messy genetic algorithms |
Authors |
TAPIA CÓRDOBA, ALEJANDRO, Reina D.G. , MILLÁN GATA, PABLO |
External publication |
No |
Means |
Expert Syst. Appl. |
Scope |
Article |
Nature |
Científica |
JCR Quartile |
1 |
SJR Quartile |
1 |
JCR Impact |
6.954 |
SJR Impact |
1.368 |
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 |
23/11/2020 |
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; Optimization problems; Physical feasibility; Shape-preserving interpolation; Hydroelectric power plants |
Universidad Loyola members |
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