scholarly journals Improvement of the Voltage Profile and Loss Reduction in Distribution Network Using Moth Flame Algorithm: Wolaita Sodo, Ethiopia

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
S. Balakumar ◽  
Akililu Getahun ◽  
Samuel Kefale ◽  
K. Ramash Kumar

Voltage stability and line losses are inevitable issues even in modern power systems. There are several techniques that emerged to solve problems in the power system to provide quality and uninterrupted supply to customers. The algorithms used in this paper to determine the appropriate location and size of the Static Var Compensator (SVC) in the Distribution Network (DN) are Moth Flame Optimization (MFO) and Particle Swarm Optimization (PSO). The objective function is defined to minimize voltage deviation and power loss. The burning problem of voltage stability improvement current scenario is because of a rise in electricity demands in all sectors. Paramount duties of power engineers are to keep the system stable and maintain voltage magnitude constant even during peak hours. The results were checked with the aid of MATLAB on Wolaita Sodo radial distribution of 34 bus data networks. The potential use of SVC is key to solve distribution system power quality issues and estimating the advantage of the installation. The results obtained from the test system were compared with PSO results. This comparison was done to know the computational time of proposed techniques. The performance of the MFA based SVC was superior in distribution system and highlighted the importance of device.

2021 ◽  
Vol 13 (20) ◽  
pp. 11407
Author(s):  
Sanaullah Ahmad ◽  
Azzam ul Asar

As energy demand is increasing, power systems’ complexities are also increasing. With growing energy demand, new ways and techniques are formulated by researchers to increase the efficiency and reliability of power systems. A distribution system, which is one of the most important entities in a power system, contributes up to 90% of reliability problems. For a sustainable supply of power to customers, the distribution system reliability must be enhanced. Distributed generation (DG) is a new way to improve distribution system reliability by bringing generation nearer to the load centers. Artificial intelligence (AI) is an area in which much innovation and research is going on. Different scientific areas are utilizing AI techniques to enhance system performance and reliability. This work aims to apply DG as a distributed source in a distribution system to evaluate its impacts on reliability. The location of the DG is a design criteria problem that has a relevant effect on the reliability of the distribution system. As the distance of load centers from the feeder increases, outage durations also increase. The reliability was enhanced, as the SAIFI value was reduced by almost 40%, the SAIDI value by 25%, and the EENS value by 25% after injecting DG into the distribution network. The artificial neural network (ANN) technique was utilized to find the optimal location of the DG; the results were validated by installing DG at prescribed localities. The results showed that the injection of DG at proper locations enhances the reliability of a distribution system. The proposed approach was applied to thte Roy Billinton Test System (RBTS). The implementation of the ANN technique is a unique approach to the selection of a location for a DG unit, which confirms that applying this computational technique could decrease human errors that are associated with the hit and trial methods and could also decrease the computational complexities and computational time. This research can assist distribution companies in determining the reliability of an actual distribution system for planning and expansion purposes, as well as in injecting a DG at the most optimal location in order to enhance the distribution system reliability.


Author(s):  
Silvia Tasnim ◽  
Md. Jashim Uddin ◽  
Synthia Tahsin ◽  
Khairul Anam

— The penetration of Electric Vehicle (EV) on the distribution network has been increased worldwide and this has also boosted up the impacts on power system performance affecting voltage profile, voltage sensitivity factor, harmonics, overloading, increased grid loss resulting in reduced efficiency and power quality. A coordinated charging schedule can reduce this stress on the power grid and show significant improvement of network parameters. In this study, by simulating through Power Factory built-in MV/LV distribution test system, the impact of increasing EV on the distribution system has been analyzed and a simple approach of charging schedule for a centralized charging station has been proposed that will minimize the deteriorating impacts on connected distribution system due to EV charging.


2020 ◽  
Vol 38 (11A) ◽  
pp. 1730-1743
Author(s):  
Ahmed H. Mashal ◽  
Rashid H. AL-Rubayi ◽  
Mohammed K. Abd

Contemporary researches offer that most researchers have concentrated on either network reconfiguration or Distributed Generation (DG) units insertion for boosting the performance of the distribution system (DS). However, very few researchers have been studied optimum simultaneous distributed generation units insertion and distribution networks reconfiguration (OSDGIR). In this paper, the stochastic meta-heuristic technique belong to swarm intelligence algorithms is proposed. Salp Swarm Algorithm (SSA) is inspired by the behavior of salps when navigating and foraging in the depth of the ocean. It utilized in solving OSDGIR. The objective function is to reduce power loss and voltage deviation in the Distribution System. The SSA is carried out on two different systems: IEEE 33-bus and local Iraqi radial (AL-Fuhood distribution network). Three cases are implemented; only reconfiguration, only DG units insertion, and OSDGIR. Promising results were obtained, where that power loss reduced by 93.1% and recovery voltage index enhanced by 5.4% for the test system and by 78.77% reduction in power loss and 8.2% improvement in recovery voltage for AL-Fuhood distribution network after applying OSDGIR using SSA. Finally, SSA proved effectiveness after an increase in test system loads by different levels in terms of reduced power loss and voltage deviation comparison with other methods


2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Varaprasad Janamala

AbstractA new meta-heuristic Pathfinder Algorithm (PFA) is adopted in this paper for optimal allocation and simultaneous integration of a solar photovoltaic system among multi-laterals, called interline-photovoltaic (I-PV) system. At first, the performance of PFA is evaluated by solving the optimal allocation of distribution generation problem in IEEE 33- and 69-bus systems for loss minimization. The obtained results show that the performance of proposed PFA is superior to PSO, TLBO, CSA, and GOA and other approaches cited in literature. The comparison of different performance measures of 50 independent trail runs predominantly shows the effectiveness of PFA and its efficiency for global optima. Subsequently, PFA is implemented for determining the optimal I-PV configuration considering the resilience without compromising the various operational and radiality constraints. Different case studies are simulated and the impact of the I-PV system is analyzed in terms of voltage profile and voltage stability. The proposed optimal I-PV configuration resulted in loss reduction of 77.87% and 98.33% in IEEE 33- and 69-bus systems, respectively. Further, the reduced average voltage deviation index and increased voltage stability index result in an improved voltage profile and enhanced voltage stability margin in radial distribution systems and its suitability for practical applications.


2012 ◽  
Vol 61 (2) ◽  
pp. 239-250 ◽  
Author(s):  
M. Kumar ◽  
P. Renuga

Application of UPFC for enhancement of voltage profile and minimization of losses using Fast Voltage Stability Index (FVSI)Transmission line loss minimization in a power system is an important research issue and it can be achieved by means of reactive power compensation. The unscheduled increment of load in a power system has driven the system to experience stressed conditions. This phenomenon has also led to voltage profile depreciation below the acceptable secure limit. The significance and use of Flexible AC Transmission System (FACTS) devices and capacitor placement is in order to alleviate the voltage profile decay problem. The optimal value of compensating devices requires proper optimization technique, able to search the optimal solution with less computational burden. This paper presents a technique to provide simultaneous or individual controls of basic system parameter like transmission voltage, impedance and phase angle, thereby controlling the transmitted power using Unified Power Flow Controller (UPFC) based on Bacterial Foraging (BF) algorithm. Voltage stability level of the system is defined on the Fast Voltage Stability Index (FVSI) of the lines. The IEEE 14-bus system is used as the test system to demonstrate the applicability and efficiency of the proposed system. The test result showed that the location of UPFC improves the voltage profile and also minimize the real power loss.


2014 ◽  
Vol 672-674 ◽  
pp. 1085-1089
Author(s):  
Jia Meng ◽  
Zai Lin Piao ◽  
Feng Zhou

The access of DG changes the operation and structure of traditional distribution network. This study mainly focused on controlling DG output current to reduce network loss of the system. Select a simple radial distribution system as example for theoretical analysis and derive the expressions of load current and node voltage. Assuming that there exists a real number k between DG output current and load. Then list the network loss and voltage deviation expressions. For the purpose of operation optimization, k can be determined by mathematical calculations. It proves that the method has a certain rationality to be effective in controlling network loss.


2021 ◽  
Vol 12 (3) ◽  
pp. 1-36
Author(s):  
Provas Kumar Roy ◽  
Moumita Pradhan ◽  
Tandra Pal

This article describes an efficient and reliable strategy for the scheduling of nonlinear multi-objective hydrothermal power systems using the grey wolf optimization (GWO) technique. Moreover, the theory of oppositional-based learning (OBL) is integrated with original GWO for further enhancing its convergence rate and solution accuracy. The constraints related to hydro and thermal plants and environmental aspects are also considered in this paper. To show its efficiency and effectiveness, the proposed GWO and OGWO algorithms are authenticated for the test system consisting of a multi-chain cascade of 4 hydro and 3 thermal units whose valve-point loading effects are also taken into account. Furthermore, statistical outcomes of the conventional heuristic approaches available in the literature are compared with the proposed GWO and OGWO approaches, and these methods give moderately better operational fuel cost and emission in less computational time.


2021 ◽  
Author(s):  
Arnab Pal ◽  
Aniruddha Bhattacharya ◽  
Ajoy Kumar Chakraborty

Abstract Electric vehicle (EV) is the growing vehicular technology for sustainable development to reduce carbon emission and to save fossil fuel. The charging station (CS) is necessary at appropriate locations to facilitate the EV owners to charge their vehicle as well as to keep the distribution system parameters within permissible limits. Besides that, the selection of a charging station is also a significant task for the EV user to reduce battery energy wastage while reaching the EV charging station. This paper presents a realistic solution for the allocation of public fast-charging stations (PFCS) along with solar distributed generation (SDG). A 33 node radial distribution network is superimposed with the corresponding traffic network to allocate PFCSs and SDGs. Two interconnected stages of optimization are used in this work. The first part deals with the optimization of PFCS’s locations and SDG’s locations with sizes, to minimize the energy loss and to improve voltage profile using harris hawk optimization (HHO) and few other soft computing techniques. The second part handles the proper assignment of EVs to the PFCSs with less consumption of the EV’s energy considering the road distances with traffic congestion using linear programming (LP), where the shortest paths are decided by Dijkstra's algorithm. The 2m point estimation method (2m PEM) is employed to handle the uncertainties associated with EVs and SDGs. The robustness of solutions are tested using wilcoxon signed rank test and quade test.


2018 ◽  
Vol 1 (2) ◽  
Author(s):  
Dalila M.S. ◽  
Zaris I.M.Y. ◽  
Nasarudin A. ◽  
Faridah H.

This paper purposely to examine and analyse the impact of the distribution capacitors banks operation to the transition of total harmonic distortion (THD) level in distribution network system. The main advantage of this work is the simplicity algorithm of the method and the system being analysed using free access open software which is known as electric power distribution system simulator (OpenDSS). In this paper, the harmonic current spectrum which is collected from the commercial site was injected to a node point on IEEE13 bus in order to provide the initial measurement of THD for the network. The proper sizing of the capacitors banks has been set and being deactivated and activated throughout the network to see the transistion in the THD level in the system. The results were achieved by simulation of the data on the configured IEEE13 bus. The simulation work was done by using the combination of C++ source codes, OpenDSS and Microsoft Excel software. From the output results, the THD current has increased up to two times from the initial value in certain phases and for the THD voltage, the THD has increased up to three times from its initial value in all phases.


Author(s):  
Mahesh Kumar ◽  
Perumal Nallagownden ◽  
Irraivan Elamvazuthi ◽  
Pandian Vasant ◽  
Luqman Hakim Rahman

In the distribution system, distributed generation (DG) are getting more important because of the electricity demands, fossil fuel depletion and environment concerns. The placement and sizing of DGs have greatly impact on the voltage stability and losses in the distribution network. In this chapter, a particle swarm optimization (PSO) algorithm has been proposed for optimal placement and sizing of DG to improve voltage stability index in the radial distribution system. The two i.e. active power and combination of active and reactive power types of DGs are proposed to realize the effect of DG integration. A specific analysis has been applied on IEEE 33 bus system radial distribution networks using MATLAB 2015a software.


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