Automatic Generation Control of Multi-area Interconnected Power Systems Using ANN Controller

Abstract

Load as well as power flow in tie-line are continuously varying in interconnection power systems. This paper presents an efficient method based on artificial intelligence control for automatic generation control (AGC) of a three-area power network. The control method implements Artificial Neural Network (ANN) to damp the frequency deviation and the fluctuation in the tie line power caused by load disturbances. The performance of the proposed controller is compared with classical control methods (PI and PID). The results showed that ANN-based control method is more efficient than others approaches. In this paper, MATLAB/SIMULINK package is used to investigate the results.

Optimal Design of Automatic Generation Control Based on Simulated Annealing in Interconnected Two-Area Power System Using Hybrid PID—Fuzzy Control

“…Additionally, in current power grids, electric loads are becoming more managed, and the rising penetration of renewable with power electronics, which minimizes the inertia of bulk power systems, necessitates the inclusion of fast dynamics in power system research and modeling. Finally, we double-checked our findings using multiple references from various authors as [15,17,21,23,28,33], and the results were excellent. However, because to space constraints, some articles do not provide sufficient details on how the results were produced, and others provided results by doing only single load disturbances and using a simple integrator with fixed parameters.…”

“…In order to improve the performance of a single-area AGC in [19] uses a more appropriate technique based on increasing the controller's transfer function using Laurent series to boost the controller performance of two-area AGC systems, the Firefly Algorithm outperformed various optimization strategies [20]. The gravity search technique was designed in [21,22] to increase the reaction to a deviation in frequency between multi-area power systems. This algorithm is based on certain advanced controllers such as ISE and PI.The authors of [23,24] compared the implementation of a PI controller with a fuzzy logic controller in two and three areas with diverse sources for each area.…”

Automatic Control Model of Power Information System Access Based on Artificial Intelligence Technology

“…Compared with the PKI model, the IBE model can manage visitor information without providing a public key or private key and issuing a certificate for visitors during initialization [18]. However, the IBE model needs to assign the secret key to each visitor, which has high overhead and low degree of automation and has an impact on system security [16]. For the power information system, 100 legal users and 50 nonillegal users are added [18].…”

“…e input vector is mapped into the hidden space by using the radial basis function. It is a linear mapping relationship between the hidden space and the output space of the artificial neural network [16]. e output of the artificial neural network is formed by the linear weighting processing in the hidden unit, and the output result is whether the accessing user is a legitimate user.…”

Tek Bölgeli Bir Güç Sisteminde Bulanık Mantık Tabanlı Yük Frekans Kontrolü (YFK)

“…Yerçekimi arama algoritması (YAA) yönteminin kullanıldığı çalışmalarda ise klasik PID parametreleri bu yöntemle optimize edilerek YFK işlemi gerçekleştirilmiştir [12][13][14][15]. Yapay sinir ağları (YSA) kullanarak gerçekleştirilen YFK işlemlerinde, kullanılan yöntemin klasik integral veya bulanık mantık yöntemine göre daha iyi sonuçlar verdiği gözlemlenmiştir [16][17][18][19][20]. YAA'ya benzer olarak PID parametrelerinin optimizasyonunda farklı teknikler kullanılarak YFK gerçekleştirilmiştir [21][22][23].…”