FV-termal güç sistemlerinde balina optimizasyon algoritması tabanlı otomatik üretim kontrolörü

Öz

Güç sistemlerinde üretilen güç ile tüketilen güç arasında denge sağlanması amacıyla otomatik üretim kontrolü (OÜK) adı verilen bir kontrol sürecinin gerçekleştirilmesi gerekmektedir. Rüzgâr türbinleri (RT) ve fotovoltaik (FV) paneller gibi yenilenebilir enerji kaynaklarının (YEK) kullanımının artması bu süreci daha zor hale getirmektedir. Bu nedenle, OÜK sürecinin daha hassas bir şekilde gerçekleştirilmesi gerekmektedir. Bu çalışmada, fotovoltaik (FV) sistem ve termal generatörden meydana gelen hibrit bir güç sisteminde OÜK işlemi için balina algoritması (BA) kullanılarak PID kontrolörün parametrelerinin belirlenmesi amaçlanmıştır. Alan-1 ve alan-2’de meydana gelen yük değişimleri durumunda amaçlanan BA ayarlı PID kontrolörün performansının yeterliliği incelenmiştir. Ayrıca, ateşböceği algoritması (ABA), genetik algoritma (GA) ve aşırı nüfus optimizasyonu (ANO) gibi optimizasyon tekniklerinin performanslarıyla bir karşılaştırma yapılmıştır. Elde edilen sonuçlar, çalışmada önerilen BA ayarlı PID kontrolörün, sistem frekansının aşma değeri ve oturma süresi bakımından diğer yöntemlere göre daha iyi sonuçlar verdiğini göstermiştir.

Anahtar Kelimeler

• Otomatik üretim kontrolü (OÜK)
• balina algoritması (BA)
• PID kontrolör
• FV sistem
• frekans sapması

The automatic generation controller based on whale optimization algorithm in PV-thermal power systems

Öz

To ensure a balance between the power generated and the consumed power in power systems, a control process namely automatic generation control (AGC) must be carried out. This process becomes more challenging due to increasing use of renewable energy sources (RES) such as wind turbines (WT) and photovoltaic (PV) panels. Therefore, AGC needs to be performed more sensitively. In this study, it has been aimed to determine the parameters of the PID controller by using the whale optimization algorithm (WOA) for the AGC in a hybrid power system consisting of photovoltaic (PV) system and thermal generator. The performance of WOA tuned PID controller is tested under load change in area-1 and area-2. Additionally, comparisons have been made with the performances of other optimization techniques such as firefly algorithm (FA), genetic algorithm (GA) and population extremal algorithm (PEO). The results obtained indicated that the WOA tuned PID controller proposed in the study gave better results than the other methods in terms of overshoot values and settling time of system frequency.

Anahtar Kelimeler

• Automatic generation control (AGC)
• whale optimization algorithm (WOA)
• PID controller
• PV system
• frequency deviation

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