Showing 5 results for Optimal Power Flow
M. R. Baghayipour, A. Akbari Foroud,
Volume 8, Issue 1 (3-2012)
Abstract
This paper presents a method to improve the accuracy of DC Optimal Power Flow problem, based on evaluating some nodal shares of transmission losses, and illustrates its efficiency through comparing with the conventional DCOPF solution, as well as the full AC one. This method provides three main advantages, confirming its efficiency:
1- It results in such generation levels, line flows, and nodal voltage angles that are more accurate than the conventional DCOPF solution.
2- Like the previous DCOPF problem, the new method is derived from a non-iterative DC power flow algorithm, and thus its solution requires no long run time.
3- Its formulation is simple and easy to understand. Moreover, it can simply be realized in the form of Lagrange representation, makes it possible to be considered as some constraints in the body of any bi-level optimization problem, with its internal level including the OPF problem satisfaction.
F. Azma, H. Rajabi-Mashhadi,
Volume 11, Issue 2 (6-2015)
Abstract
This paper develops an effective control framework for DC voltage control and power-sharing of multi-terminal DC (MTDC) grids based on an optimal power flow (OPF) procedure and the voltage-droop control. In the proposed approach, an OPF algorithm is executed at the secondary level to find optimal reference of DC voltages and active powers of all voltage-regulating converters. Then, the voltage droop characteristics of voltage-regulating converters, at the primary level, are tuned based on the OPF results such that the operating point of the MTDC grid lies on the voltage droop characteristics. Consequently, the optimally-tuned voltage droop controller leads to the optimal operation of the MTDC grid. In case of variation in load or generation of the grid, a new stable operating point is achieved based on the voltage droop characteristics. By execution of a new OPF, the voltage droop characteristics are re-tuned for optimal operation of the MTDC grid after the occurrence of the load or generation variations. The results of simulation on a grid inspired by CIGRE B4 DC grid test system demonstrate efficient grid performance under the proposed control strategy.
O. Herbadji, L. Slimani, T. Bouktir,
Volume 15, Issue 1 (3-2019)
Abstract
In this study, a multiobjective optimization is applied to Optimal Power Flow Problem (OPF). To effectively achieve this goal, a Multiobjective Ant Lion algorithm (MOALO) is proposed to find the Pareto optimal front for the multiobjective OPF. The aim of this work is to reach good solutions of Active and Reactive OPF problem by optimizing 4-conflicting objective functions simultaneously. Here are generation cost, environmental pollution emission, active power losses, and voltage deviation. The performance of the proposed MOALO algorithm has been tested on various electrical power systems with different sizes such as IEEE 30-bus, IEEE 57-bus, IEEE 118-bus, IEEE 300-bus systems and on practical Algerian DZ114-bus system. The results of the tests proved the versatility of the algorithm when applied to large systems. The effectiveness of the proposed method has been confirmed by comparing the results obtained with those obtained by other algorithms given in the literature for the same test systems.
M. Najjarpour, B. Tousi, S. Jamali,
Volume 18, Issue 4 (12-2022)
Abstract
Optimal power flow is an essential tool in the study of power systems. Distributed generation sources increase network uncertainties due to their random behavior, so the optimal power flow is no longer responsive and the probabilistic optimal power flow must be used. This paper presents a probabilistic optimal power flow algorithm using the Taguchi method based on orthogonal arrays and genetic algorithms. This method can apply correlations and is validated by simulation experiments in the IEEE 30-bus network. The test results of this method are compared with the Monte Carlo simulation results and the two-point estimation method. The purpose of this paper is to reduce the losses of the entire IEEE 30-bus network. The accuracy and efficiency of the proposed Taguchi correlation method and the genetic algorithm are confirmed by comparison with the Monte Carlo simulation and the two-point estimation method. Finally, with this method, we see a reduction of 5.5 MW of losses.
Majid Najjarpour, Behrouz Tousi, Shahaboddin Yazdandoust Moghanlou,
Volume 20, Issue 1 (3-2024)
Abstract
In recent decades, because of the rapid population growth of the world, considerable changes in climate, the reduction of fossil fuel sources to consume the traditional power plants and their high depreciation, and the increase in fuel prices. Due to the increased penetration of DG units which have a random nature into the power system, the ordinary equations of power flow must be changed. For the power system to operate in a stable condition estimating future demand and calculating the important and operational indexes such as losses of the power system is an important duty that must be done precisely and rapidly. In this paper, the Improved Taguchi method and phasor measurement unit are used to model the uncertainties of DGs and estimate the error of voltage, respectively. The results show that the magnitude error and the angle error of voltage are decreased using PMU. The applied optimal power flow and state estimations are analyzed and verified using standard IEEE 30-bus and 14-bus test power systems by MATLAB, and MINITAB softwares. The Made Strides Taguchi strategy appears to have modeled the DG units precisely and successfully, and using the PMU, the mistake of the point and greatness estimation is exceptionally moot. The values that were evaluated are very close to the values that were done by the Newton-Raphson stack stream.
