Hybrid PSO–ANN algorithm to control TCR for voltage balancing
| Autor: | Malek Alkayyali, Jasim A. Ghaeb |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Artificial neural network
Computer science 020209 energy Computer Science::Neural and Evolutionary Computation 020208 electrical & electronic engineering Thyristor controlled reactor Energy Engineering and Power Technology Particle swarm optimization 02 engineering and technology AC power Electric power system Control and Systems Engineering Transmission line 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering MATLAB computer Algorithm computer.programming_language Voltage |
| Zdroj: | IET Generation, Transmission & Distribution. 14:863-872 |
| ISSN: | 1751-8695 |
| Popis: | Voltage unbalance is an important power quality issue, which occurs in electrical power systems (EPSs) and causes severe problems for them. In this work, a general mathematical model for EPS including its long transmission line is developed using the generalised circuit parameters method. Then, a hybrid Particle Swarm Optimisation–Artificial Neural Network (PSO–ANN) algorithm is proposed to overcome the voltage unbalance problem by controlling the firing angles of thyristor-controlled reactor (TCR) which varies the amount of reactive power at the load side. PSO algorithm is responsible for determining the optimal set of TCR firing angles required to retrieve the balance conditions in offline mode for different load changes, employing the developed mathematical model of the EPS. Then, a dataset is taken as training samples for the ANN to be used in online mode. Aqaba Qatranah South-Amman (AQSA) EPS is considered as a real case study and simulated in MATLAB environment to validate the proposed algorithm. The simulation results are compared with other ANN algorithms available in the literature. Finally, a laboratory prototype is built for AQSA EPS including its long transmission line to test the proposed hybrid PSO–ANN algorithm for real unbalance conditions acquired from the laboratory prototype. |
| Databáze: | OpenAIRE |
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