Hydropower Optimization Test-Case Solved with Nature-Inspired Algorithms
| Autor: | Sanda-Carmen Georgescu, Ionut Stelian Grecu, Eliza Isabela Tica, Catalin-Gabriel Andrei, Angela Neagoe, Silvia Nastase |
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| Rok vydání: | 2019 |
| Předmět: |
Optimization problem
business.industry Computer science 020209 energy 0208 environmental biotechnology Particle swarm optimization 02 engineering and technology 020801 environmental engineering Bounded function Genetic algorithm 0202 electrical engineering electronic engineering information engineering Firefly algorithm Nature inspired business Cuckoo search Algorithm Hydropower |
| Zdroj: | 2019 International Conference on ENERGY and ENVIRONMENT (CIEM). |
| DOI: | 10.1109/ciem46456.2019.8937643 |
| Popis: | The computational efficiency of various nature-inspired algorithms is compared here for a specific hydropower optimization problem, selected as test-case due to its accurate reference solution yielded by the Newton-Raphson method. The above test-case is attached to a hydropower development in Romania, bounded by Vidraru Reservoir (on Arges river) and Vidraru Hydro-Power Plant. The results obtained in this paper using four algorithms, namely Genetic Algorithm, Particle Swarm Optimization (PSO), Flower Pollination Algorithm, and Shark Smell Optimization, are compared with previous results obtained on the same test-case using other algorithms (Honey Bees Mating Optimization Algorithm, Firefly Algorithm, Cuckoo Search Algorithm, Bat-Inspired Algorithm). It turned out that PSO is the most efficient algorithm among the 8 tested algorithms. |
| Databáze: | OpenAIRE |
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