Detailed Non-Linear Constrained Multi-Objective Optimal Operation of Power Systems Including Renewable Energy Sources
| Autor: | Hong V. Nguyen, Matthew W. Dunnigan, Duy C. Huynh |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Mathematical optimization
Wind power Computer science business.industry 020209 energy Particle swarm optimization 02 engineering and technology 010501 environmental sciences 01 natural sciences Renewable energy Nonlinear system Electric power system Rate of convergence Physics::Space Physics 0202 electrical engineering electronic engineering information engineering Cuckoo search business MCS algorithm 0105 earth and related environmental sciences |
| Zdroj: | Lecture Notes in Electrical Engineering ISBN: 9789811523168 |
| DOI: | 10.1007/978-981-15-2317-5_66 |
| Popis: | A modified cuckoo search (MCS) algorithm is proposed in this paper for an optimal operation problem of power systems with renewable energy sources including solar and wind energy sources. A non-linear constrained multi-objective optimal operation problem is formulated and detailed for an integrated power system in order to make it more realistic. Furthermore, the cuckoo search (CS) algorithm is modified to increase the convergence rate that is called the MCS algorithm. This variant mentions the step size of the Levy flight. The modified IEEE 10-generator power system with integrated solar and wind power sources is considered in this paper. The numerical results on the above power system confirm the effectiveness of the proposal for the optimal operation of the integrated power system. A comparison with the CS algorithm and variants of the particle swarm optimization (PSO) algorithm indicates the superiority of the MCS algorithm for resolving complicated optimal operation problems of integrated power systems. |
| Databáze: | OpenAIRE |
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