Title A Genetic Algorithm To Optimize Penstocks For Micro-Hydro Power Plants
Authors TAPIA CÓRDOBA, ALEJANDRO, RODRÍGUEZ DEL NOZAL, ÁLVARO, GUTIÉRREZ REINA, DANIEL, MILLÁN GATA, PABLO, IEEE
External publication No
Means 2021 Ieee Congress On Evolutionary Computation (cec 2021)
Scope Conference Paper
Nature Científica
Web https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124601816&doi=10.1109%2fCEC45853.2021.9504994&partnerID=40&md5=64d0d40c5a82268967f87c81f84a600d
Publication date 01/01/2021
ISI 000703866100007
Scopus Id 2-s2.0-85124601816
DOI 10.1109/CEC45853.2021.9504994
Abstract A Micro Hydropower Plant (MHPP) is a suitable and effective mean to provide electric power to rural remote communities without harming the environment. However, the lack of resources and technical training in these communities frequently leads to designs based of rules of thumb, compromising both the generation capacity and efficiency. This work makes an attempt to address this problem developing a new tool to design the layout of MHPP. The tool relies on a discrete topographic survey of the terrain and makes use of a Genetic Algorithm (GA) to optimize the installation layout, making it possible to explicitly incorporate needs and constraints such as power supply requirement, cost of the installation, available water flow, and layout feasibility in accordance with the real terrain profile. The algorithm is applied to a real scenario in a remote community in Honduras, demonstrating its capability to optimize these kind of installations.
Keywords hydropower plant; renewable energy; optimization; genetic algorithm
Universidad Loyola members

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