Showing 10 results for Distribution Network
M. Aliakbar-Golkar, Y. Raisee-Gahrooyi,
Volume 4, Issue 4 (12-2008)
Abstract
This paper compares fault position and Monte Carlo methods as the most
common methods in stochastic assessment of voltage sags. To compare their abilities,
symmetrical and unsymmetrical faults with different probability distribution of fault
positions along the lines are applied in a test system. The voltage sag magnitude in different
nodes of test system is calculated. The problem with these two methods is that they require
unknown number of iteration in Monte Carlo Method and number of fault position to
converge to an acceptable solution. This paper proposes a method based on characteristic
behavior of Monte Carlo simulations for determination required number of iteration in
Monte Carlo method.
Mahdi Sedghi, Masoud Aliakbar-Golkar,
Volume 5, Issue 2 (6-2009)
Abstract
Optimal expansion of medium-voltage power networks is a common issue in electrical distribution planning. Minimizing total cost of the objective function with technical constraints and reliability limits, make it a combinatorial problem which should be solved by optimization algorithms. This paper presents a new hybrid simulated annealing and tabu search algorithm for distribution network expansion problem. Proposed hybrid algorithm is based on tabu search and an auxiliary simulated annealing algorithm controls the tabu list of the main algorithm. Also, another auxiliary simulated annealing based algorithm has been added to local searches of the main algorithm to make it more efficient. The numerical results show that the method is very accurate and fast comparing with the other algorithms.
H. Afkar, M. A. Shamsi Nejad, M. Ebadian,
Volume 12, Issue 2 (6-2016)
Abstract
Load balancing is an important issue in distributed systems. In addition, using distributed generation sources such as photovoltaic is increasing. Power electronic converters are main interfaces between the sources and the grid. In this paper, a method has been proposed to reduce the load imbalancing in distribution networks using PV Grid Interface Converter. Two DC/DC and DC/AC converters have been utilized for connecting PV to the grid. A control strategy is presented which enables the converter to compensate the load imbalancing by injecting power of solar cells to the load and grid. Simulation results by MATLAB/SIMULINK software indicate the ability of the proposed control method to reduce the load imbalancing.
F. Amini, R. Kazemzadeh,
Volume 13, Issue 1 (3-2017)
Abstract
Development of distributed generations’ technology, trends in the use of these sources to improve some of the problems such as high losses, low reliability, low power quality and high costs in distributed networks. Choose the correct location to install and proper capacity of these sources, such as important things that must be considered in their use. Since distribution networks are actually unbalanced and asymmetric consumption loads are different, so in this paper with optimal placement and sizing of distributed generation sources that dependent on the load model and type of load connection and the uncertainties which caused by the generated power of wind turbines and solar panels, the positive effects of these sources have been examined on unbalanced distribution network. Hence with linear three-phase unbalanced load flow method and IPSO algorithm, allocation of distributed generation sources in IEEE standard of 37 bus unbalanced network have been done. Obtained results show improvement of voltage profile in each phase and reduction of network power losses and buses’ voltage unbalance factor.
F. Nazari, A. Zangeneh, A. Shayegan-Rad,
Volume 13, Issue 1 (3-2017)
Abstract
By increasing the use of distributed generation (DG) in the distribution network operation, an entity called virtual power plant (VPP) has been introduced to control, dispatch and aggregate the generation of DGs, enabling them to participate either in the electricity market or the distribution network operation. The participation of VPPs in the electricity market has made challenges to fairly allocate payments and benefits between VPPs and distribution network operator (DNO). This paper presents a bilevel scheduling approach to model the energy transaction between VPPs and DNO. The upper level corresponds to the decision making of VPPs which bid their long- term contract prices so that their own profits are maximized and the lower level represents the DNO decision making to supply electricity demand of the network by minimizing its overall cost. The proposed bilevel scheduling approach is transformed to a single level optimizing problem using its Karush-Kuhn-Tucker (KKT) optimality conditions. Several scenarios are applied to scrutinize the effectiveness and usefulness of the proposed model.
O. Honarfar, A. Karimi,
Volume 16, Issue 3 (9-2020)
Abstract
Distribution load flow (DLF) calculation is one of the most important tools in distribution networks. DLF tools must be able to perform fast calculations in real-time studies at the presence of distributed generators (DGs) in a smart grid environment even in conditions of change in the network topology. In this paper, a new method for DLF in radial active distribution networks is proposed. The method performs a very fast DLF using zooming algorithm associated with a fast-decoupled reactive power compensation (ZAFDRC) technique, not in all of the buses of the grid, causes to reduce the solution time, which is the most important issue in the real-time studies. The proposed method is based on the zooming algorithm and does not require to calculate the bus-injection to branch-current (BIBC) matrix which reduces the computational burden and helps to decrease the solution time. The method is tested on the IEEE 69-bus systems as a balanced network and the IEEE 123-bus as a very unbalanced system. The results confirm the high accuracy and high speed of the proposed method.
A. Hassannejad Marzouni, A. Zakariazadeh,
Volume 16, Issue 3 (9-2020)
Abstract
State estimation is essential to access observable network models for online monitoring and analyzing of power systems. Due to the integration of distributed energy resources and new technologies, state estimation in distribution systems would be necessary. However, accurate input data are essential for an accurate estimation along with knowledge on the possible correlation between the real and pseudo measurements data. This study presents a new approach to model errors for the distribution system state estimation purpose. In this paper, pseudo measurements are generated using a couple of real measurements data by means of the artificial neural network method. In the proposed method, the radial basis function network with the Gaussian kernel is also implemented to decompose pseudo measurements into several components. The robustness of the proposed error modeling method is assessed on IEEE 123-bus distribution test system where the problem is optimized by the imperialist competitive algorithm. The results evidence that the proposed method causes to increase in detachment accuracy of error components which results in presenting higher quality output in the distribution state estimation.
A. Boukaroura, L. Slimani, T. Bouktir,
Volume 16, Issue 3 (9-2020)
Abstract
The progression towards smart grids, integrating renewable energy resources, has increased the integration of distributed generators (DGs) into power distribution networks. However, several economic and technical challenges can result from the unsuitable incorporation of DGs in existing distribution networks. Therefore, optimal placement and sizing of DGs are of paramount importance to improve the performance of distribution systems in terms of power loss reduction, voltage profile, and voltage stability enhancement. This paper proposes a methodology based on Dragonfly Optimization Algorithm (DA) for optimal allocation and sizing of DG units in distribution networks to minimize power losses considering variations of load demand profile. Load variations are represented as lower and upper bounds around base levels. Efficiency of the proposed method is demonstrated on IEEE 33-bus and IEEE 69-bus radial distribution test networks. The results show the performance of this method over other existing methods in the literature.
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.
Mohamad Almas Prakasa, Mohamad Idam Fuadi, Muhammad Ruswandi Djalal, Imam Robandi, Dimas Fajar Uman Putra,
Volume 20, Issue 3 (9-2024)
Abstract
The unbalanced load distribution in the electrical distribution network caused crucial power losses. This condition occurs in one of the electrical distribution networks, 20 kV Tarahan Substation, Province of Bandar Lampung, Indonesia. This condition can be maintained using optimal reconfiguration with the integration of Distributed Generation (DG) based on Renewable Energy (RE). This study demonstrates the optimal reconfiguration of the 20 kV Tarahan Substation with the integration of the Photovoltaic (PV) and Battery Energy Storage System (BESS). The reconfiguration process is optimized by using the Firefly Algorithm (FA). This process is conducted in the 24-hour simulation with various load profiles. The optimal reconfiguration is investigated in two scenarios based on without and with DG integration. The optimal configuration with more balanced load distribution conducted by FA reduces the power losses by up to 31.39% and 32.38% in without and with DG integration, respectively. Besides that, the DG integration improves the lowest voltage bus in the electrical distribution network from 0.95 p.u to 0.97 p.u.
