A New Load-Flow Method in Distribution Networks based on an Approximation Voltage-Dependent Load model in Extensive Presence of Distributed Generation Sources

Document Type : Research Article

Authors

1 Department of Electrical Engineering, Amirkabir University of Technology

2 Department of Electrical Eng., Amirkabir University of Technology

3 Dept. of Elect. Eng., Shahid Behshti University

4 Dept. of EE, Amirkabir University of Technology

5 Dept. of EE, Shahid Behshti University

Abstract

The power-flow (PF) solution is a basic and powerful tool in power system analysis. Distribution networks (DNs), compared to transmission systems, have many fundamental distinctions that cause the conventional PF to be ineffective on these networks. This paper presents a new fast and efficient PF method which provides all different models of Distributed Generations (DGs) and their operational modes (P-V and P-Q nodes) in DNs. This study uses voltage-dependent load model instead of traditional load model (constant P-Q) which is modelled as the combination of a current source in parallel with a constant admittance. This kind of load model is closer to reality and makes the powerflow equations closer to linear conditions. To calculate the angles of the P-V buses, the numerical method (Newton-Raphson method) is applied by separating the PF equations for P-V and P-Q buses. Considering a series of approximations on the angles of these buses, the non-diagonal elements of the Jacobin matrix in Newton-Raphson method are fixed. Hence, the proposed numerical method converges toward an appropriate response in a very low number of iterations and high speed. The voltages of other buses (P-Q buses) are calculated linearly without needing any numerical methods. The presented method proves to be robust and reliable against reconfigured structures and meshed networks. Simulations have been carried out on 14-, 33- and 70-node IEEE test systems and large scale networks such as 6118-buses. The results show that the proposed method is at least 100 and 10 times faster than Gauss-Seidel and Newton-Raphson methods, respectively

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