Power Loss In Distribution System Research Articles

Application of Optimal Network Reconfiguration for Loss Minimization and Voltage Profile Enhancement of Distribution System Using Heap-Based Optimizer

A distribution system’s network reconfiguration (NR) is the process of changing the status of the switches to change the topology of the feeders. Using optimal NR at various network load levels, this research proposed an economical way for improving the voltage profile and reducing power loss in distribution systems. A new metaheuristic Heap-based optimizer based on the corporate rank hierarchy is used to solve the optimization problem in order to find the optimal radial distribution network. The objective functions used in this article include voltage profile improvement, power loss reduction, reduction of operation cost, and minimization of gas emissions. This novel technique provides accurate results while avoiding the issue of premature convergence and requires fewer control parameter settings. The proposed method is evaluated at three different load levels on a standard IEEE 33-bus test system, and the simulation results are compared to those of other optimization methods published in the literature, demonstrating that the proposed method improves the system voltage profile while minimizing losses and power costs, establishing that this technique is effective in finding the best result. The Wilcoxon and Friedman tests are also used to verify the effectiveness of the proposed technique.

Analyzing Power Losses in Ghazni City's Electricity Distribution Network and Strategies for Minimizing Them

Electricity is a vital source of energy that plays a crucial role in the economic and social development of a country. However, the distribution of electricity from power plants to consumers is a complex process that involves a network of electricity transmission and distribution systems. These systems are susceptible to losses that occur at various stages of the distribution process, such as transmission, conversion, and distribution. Power losses in distribution systems can be caused by technical and non-technical factors. Technical factors include conductor resistance, voltage drops, and transformer losses, while non-technical factors include theft and defective equipment. These losses can have significant economic consequences, such as lower reliability, higher costs, and lower revenues for utilities. Therefore, it is important to study and analyze the causes of power losses in distribution systems and develop strategies to reduce them. In this research, real field data of Ghazni Breshna Company was used to calculate electricity losses. In the case of Ghazni city electricity distribution network, the research shows that there is an energy loss of 11.7%, which amounts to 1,093,736 kWh per year. This energy loss results in a financial loss of 6,835,850 Afghanis for Barshna Company. The real field data obtained from Ghazni Breshna Company was used for the energy loss calculations. Several strategies can be used to reduce power losses, including reducing technical losses by improving equipment and maintenance practices, reducing non-technical losses by combating theft and illegal connections, and increasing the efficiency of the distribution network. In addition, improving energy management practices such as demand response, load balancing, and power factor correction can also help reduce power losses. Reducing power losses in the electric distribution system is critical to improving electric power reliability and quality and minimizing economic losses for utilities. In addition, high investment in this area can contribute to the growth of the nation's economy. The results of this study demonstrate the importance of understanding power losses in distribution systems and the need for effective measures to minimize these losses.

Minimization of Power Loss in Distribution System by Tap Changing Transformer using PSO Algorithm

Energy is a primary requirement for everyone and it is available in different forms in nature, in all forms of energy “Electrical Energy” is the most significant and useful in the daily life of humans. In the last two decades, the usages of electrical & electronic devices are rapidly increased and technology modernizes lifestyles as well as simplified their lives. In this way, the load demand also significantly increased and leads to an imbalance between generated power and load demand. Load uncertainty also increased with the rise of load demand; it leads higher power losses & poor voltage in distribution system (DS). The main objective of this paper is going to discuss the minimization of losses by adjusting tap settings of the distribution transformer with the help of particle swarm optimization (PSO) algorithm. The proposed approach verified on 15 bus distribution system using MATLAB. Electric vehicle charging stations are located in the distribution system to represent the load uncertainty.

A Dynamic Reconfiguration Method based on a Deterministic Optimization Approach in Active Distribution Systems

This article proposes a method for dynamic distribution network reconfiguration (DDNR) with distributed generation for loss reduction. Advantages and conceptual principles of a deterministic optimization method are exposed, which allows the minimization of technical power losses in distribution systems based on a linear approximation of the loads. In this work is proposed the application of this approach for the modelling of distributed generation sources, obtaining a mathematical formulation that exploits mixed-integer nonlinear programming in solving the optimal reconfiguration problem. The DDNR method is implemented in an automatic tool integrating OpenDSS and GAMS software. IEEE69-Bus test system is considered to demonstrate the effectiveness of the technique. Dynamic results are obtained by implementing the optimal reconfiguration strategy, making the dynamic adjustments of the mathematical modelling in the face of variations in distributed generation and demand profiles. The results reveal schemes that range from one to twenty-four daily control actions.

A Novel Technique for Optimal siting and Rating of Shunt Capacitors Placed to the Radial Distribution Systems

The overall efficacy of power distribution is reduced through power loss in distribution systems owing to branch resistance. For providing quality power to customers, power losses must be diminished, and voltages must be enhanced. This paper introduces a novel improvement for the traditional Salps Swarm Algorithm (SSA) called Enhance SSA (ESSA) for selecting Optimal Shunt Capacitor Ratings and their Locations (OSCRL). ESSA is viewed as an enhanced version of SSA with the aim of improving the SSA's poor performance. A multi-objective function was designed in this work for reducing real power loss and Total System Cost (TSC), as well as, improving feeder voltage profile and maximizing Net Savings (NSs) per year under security restrictions. For validating and evaluating the proposed ESSA technique, a practical 33-bus local Iraqi and standard IEEE 69-bus Radial Distribution Systems (RDSs) were used as test systems through utilizing MATLAB. The experimental results attained by the proposed ESSA are compared with other approaches currently available in the literature for addressing OSCRL problem. The experimental results prove the efficacy and supremacy of the ESSA to other literature algorithms with respect to diminishing power loss as well as TSC, reinforce bus voltage profile and increase NSs per year for multiple RDSs.

Reliability improvement and loss reduction in radial distribution system with network reconfiguration algorithms using loss sensitivity factor

<p>Studies on load flow in electrical distribution system have always been an area of interest for research from the previous few years. Various approaches and techniques are brought into light for load flow studies within the system and simulation tools are being used to work out on varied characteristics of system. This study concentrates on these approaches and the improvements made to the already existing techniques considering time and the algorithms complexity. Also, the paper explains the network reconfiguration (NR) techniques considered in reconfiguring radial distribution network (RDN) to reduce power losses in distribution system and delivers an approach to how various network reconfiguration techniques support loss reduction and improvement of reliability in the electrical distribution network.</p>

Strategic integration of photovoltaic, battery energy storage and switchable capacitor for multi-objective optimization of low voltage electricity grid: Assessing grid benefits

Battery energy storage system has become an inevitable element in smart distribution network due to massive deployment of community level distributed photovoltaic power generation system. The battery energy storage system not only participates in the backup power supply but also have the potential to provide numerous distributed ancillary services. In this paper, Slime mold optimization algorithm is applied to optimally allocate the photovoltaic generation units, battery energy storage systems and switchable shunt capacitor banks in distribution network while minimizing the two objective functions i.e., active power loss of distribution system and annualized capital cost of integrated equipments (photovoltaic units, battery energy storage systems and shunt capacitors) simultaneously. The proposed optimization framework is implemented on an IEEE 33 bus distribution network for different cases and compared with Non-dominated Sorting Genetic Algorithm II. The comparison of simulation results for different cases reveals the promising advantages in various technical and economic issues along with an additional benefit of investment deferral for distribution feeder up-gradation up to a significant span of years.

Optimal Photovoltaic Generation Allocation for Minimum Active Power Loss in Distribution Systems Based on an Improved Backtracking Search Optimization Algorithm

Optimal Photovoltaic Generation Allocation for Minimum Active Power Loss in Distribution Systems Based on an Improved Backtracking Search Optimization Algorithm

Optimization of Three-Phase Feeder Load Balancing Using Smart Meters

Power losses in distribution systems are among the most important performance indicators of electricity distribution companies’ economic operations. Therefore, the distribution system should be planned adequately to ensure working within permissible limits. Suppose that the actual losses are higher than the standard ones; the companies are economically penalized; otherwise, they obtain a profit. Continuous improvement for the grid is needed to keep the losses within reasonable limits. Companies invest in projects that are dedicated to reducing losses and keep them under control. Literature review states that load balancing is considered a critical issue in minimizing these losses. Feeder automation becomes much simple and more reliable due to the rapid penetration of artificial intelligence, smart grids, and telecommunication in the power system. This work shows that automated feeder reconfiguration is technically advantageous and economical for both customers and utilities. A case study from Irbid District Electricity Company (IDECO) is presented. The losses are reduced by around 253 JDs/year by balancing the loads over a specific three-phase feeder using smart meters’ installation. A mathematical model for three-phase balancing is formulated using many heuristic techniques and an optimized neural network (ONN). These model integrations are established using CYME load flow software, MATLAB/Simulink, and C programming language.

An Improved Lightning Search Algorithm Employed Performance Enhancement in Distribution System

The proposed research work minimizes the power loss in distribution system under load conditions which is the major issue nowadays that has been reduced to reach the maximum possible power for satisfying the customer needs. Optimal siting of Distribution Static Compensator (DSTATCOM) and Photo-Voltaic (PV) array in distribution system is used to attain voltage profile improvement, reduced voltage instability and less power loss. For this, Improved Lightning Search Algorithm (ILSA) has been proposed to accomplish the objectives. The proposed ILSA has reached the Voltage Stability Index (VSI) value as 0.9877 and it outstandingly decreased the power loss to 55.92 kW which are validated with IEEE 30-bus system using MATLAB toolbox. The obtained results are compared with the existing optimization algorithms and it depicts that the proposed ILSA is more advantageous than other optimization algorithms.

Optimization of location and size of distributed generations for maximizing their capacity and minimizing power loss of distribution system based on cuckoo search algorithm

Maximizing capacity of distributed generations (DGs) embed into distribution network is a solution to attract investment for DGs installation on the distribution system. This paper introduces a approach of optimizing location and capacity of DGs for maximizing DGs capacity and minimizing the system’s power loss based on cuckoo search algorithm (CSA). The proposed problem and method are simulated on two test systems including the 33-node and 69-node networks. The numerical results have demonstrated that the proposed method not only reduces power losses but also maximizes the power of DGs embed into the distribution network. The results also introduce that the proposed CSA method is better performance that some previous methods in terms of power loss and DGs capacity. The results obtained in many independent runs for two test systems indicate that CSA in one of the reliable methods for the DGs placement problems.

Utilizing Load and Loss Factors in Determination of the Technical Power Losses in Distribution System’s Feeders: Case Study

This study uses load factor and loss factor to determine the power losses of the electrical feeders. An approach is presented to calculate the power losses in the distribution system. The feeder’s technical data and daily operation recorded data are used to calculate and analyze power losses.
 This paper presents more realistic method for calculating the power losses based on load and loss factors instead of the traditional methods of calculating the power losses that uses the RMS value of the load current which not consider the load varying with respect to the time. Eight 11kV feeders are taken as a case study for our work to calculate load factor, loss factor and power losses. Four of them (F40, F42, F43 and F45) are overhead lines while the others (F185, F186, F187 and F188) are underground cables. The greater differences between their losses were obtained, due to various types of route length, type, and dimension of conductors. The study takes different configuration feeders for computation with determination in power losses.

Supervised evolutionary programming based technique for multi-DG installation in distribution system

<span lang="EN-US">Installing DG in network system, has supported the distribution system to provide the increasing number of consumer demand and load, in order to achieve that this paper presents an efficient and fast converging optimization technique based on a modification of traditional evolutionary programming method for obtain the finest optimal location and power loss in distribution systems. The proposed algorithm that is supervised evolutionary programming is implemented in MATLAB and apply on the 69-bus feeder system in order to minimize the system power loss and obtaining the best optimal location of the distributed generators. </span>

A Coordinated Voltage Control Scheme of Distribution Networks with Distributed Generation Based on On-Load Tap Changers and Shunt Capacitors by Particle Swarm Optimization

AbstractRecently, the voltage stability and control of distribution networks become challenges due to the large line impedance, load variations and particularly the presence of distributed generation. This paper presents a coordinated voltage control scheme of distribution systems with distributed generation based on on-load tap changer and shunt capacitors. The problem is to determine the optimal operation of voltage regulation devices to minimize a multi-objective function including power losses, voltage deviations and operation stresses while subject to the allowable voltage ranges, line capacity and switching stresses, etc. The problem is formulated and solved by a modified particle swarm optimization algorithm to treat the large-scale and high nonlinearity property. The proposed scheme is applied to a typical 48-bus distribution network in Vietnam. The result of simulation shows that the voltage profile can be improved while the power loss of distribution systems can be reduced significantly.

Flower pollination algorithm for distribution system phase balancing considering variable demand

Power Distribution systems are one of the most critical links between utility and utility customer. Control of power loss in distribution systems are very much essential considering the economical aspects. Reconfiguration, Capacitor Placement and Phase Balancing are the different methods practiced for power loss reduction. Due to the unbalanced nature of the distribution system, phase balancing is considered as the effective one amongst the above mentioned three methods. Unbalanced feeders not only increase power losses and the risk of overload situations, but they also affect power quality and electricity price. A severely unbalanced circuit can result in excessive voltage drops on the heavily phase. Even a feeder system is designed as a balanced feeder based on the given load data, load prediction errors and unbalanced load growth will induce feeder imbalance. Phase swapping is a direct and effective way to balance a feeder in terms of phases. It has been practiced by engineers based on their previous experiences, and trial and error for phase balancing. In this paper, a phase swapping algorithm based on hybrid Fuzzy-Flower Pollination Algorithm (FFPA) has been developed to minimize the phase current deviation amongst the phases. Flower Pollination Algorithm is used to optimize the fitness value and fuzzy used to format the fitness function integrating multi-objectives. The validation of the proposed algorithm is done through two standard test cases and simulation results are compared with literature.

Optimal placement and sizing of energy storage systems to improve the reliability of hybrid power distribution network with renewable energy sources

Concept of renewable hybrid energy systems have attracted many utilities and implemented by them too. With such energy systems, customers are not only supplied more economically but also more reliably. Moreover, optimal placements of energy storage systems (ESSs) increase the reliability of such hybrid renewable system up to a great extent. Therefore, this paper presents a new approach for optimal placement and sizing of energy storage systems (ESSs) in hybrid renewable radial distribution system to improve the reliability of such system without violating the system constraints. The cost of energy not supplied (CENS) associated with power service interruption and power shortage is also been considered in the objective function during placement of ESSs. Hence, the proposed optimal placement planning of ESSs is presented with an aim of minimizing the objective function includes cost of energy not supplied (CENS), investment cost and operational cost of ESSs, and power loss in distribution system. It is to be noted that the Particle swarm optimization (PSO) technique is adopted to minimize the objective function. The presented methodology is demonstrated by considering several case studies on 11 kV, 30 bus radial distribution system. Further, a rigorous sensitivity analysis is performed by limiting the number of applied ESSs and varying the maximum capacity of participating ESSs.

An Enhanced Artificial Ecosystem-Based Optimization for Optimal Allocation of Multiple Distributed Generations

Optimal allocation of distributed generations (DGs) is vital to the proper operation of the distribution systems, which leads to power loss minimization and acceptable voltage regulation. In this paper, an Enhanced Artificial Ecosystem-based Optimization (EAEO) algorithm is proposed and used to solve the optimization problem of DG allocations to minimize the power loss in distribution systems. In the suggested algorithm, the search space is reduced using operator G and sine-cosine function. The G-operator affects the balance between explorative and exploitative phases. At the same time, it gradually decreases during the iterative process in order to converge to the optimal global solutions. On the other hand, the sine-cosine function creates different and random solutions. The EAEO algorithm is applied for solving the standard 33-bus 69-bus, and 119-bus distribution systems with the aim of minimizing the total power losses. Multiple DG units operating at various power factors, including unity-, fixed-, and optimal-power factors, are considered. Both single and multiple objectives are considered to minimize the total voltage deviation (TVD), maximize the system stability, and reduce the total power losses. The obtained results are compared with those obtained by the AEO and other algorithms. The results demonstrate a significant reduction of total power losses and improvement of the voltage profile of the network, especially for the DGs operating at their optimal power factors. Comparisons show the dominance of the proposed EAEO algorithm against other analytical, metaheuristic, or hybrid algorithms. Moreover, the EAEO outperforms the original AEO algorithm with a faster convergence speed and better system performance.

Distribution System Reconfiguration for Loss Minimization and Voltage Profile Enhancement by using Discrete – Improved Binary Particle Swarm Optimization Algorithm

Distribution system reconfiguration is done by altering the open / close position of two kinds of switches: usually open tie switches and sectionalizing switches usually closed. Its main purpose is restoration of supply via other route to improve reliability, sometimes for load balancing by relieving overloads. Feeder reconfiguration is very good alternative to reduce power losses and improve voltage profile to improve overall performance. Distribution system reconfiguration is a very cost effective way to reduce the distribution system power losses, enhance voltage profile and system reliability. This paper presents application of novel Discrete - improved binary particle swarm optimization (D-IBPSO) algorithm for distribution system reconfiguration for minimization of real power loss and improvement of voltage profile. The algorithm is implemented to a 16-bus, 33-bus system and a 69-bus system considering different loading conditions. The simulation results indicate that the suggested technique can accomplish optimal reconfiguration and significantly reduce power losses on the supply scheme and enhance the voltage profile.

Integrated monte carlo-evolutionary programming technique for distributed generation studies in distribution system

This paper presents the optimal multiple distributed generations (MDGs) installation for improving the voltage profile and minimizing power losses of distribution system using the integrated monte-carlo evolutionary programming (EP). EP was used as the optimization technique while monte carlo simulation is used to find the random number of locations of MDGs. This involved the testing of the proposed technique on IEEE 69-bus distribution test system. It is found that the proposed approach successfully solved the MDGs installation problem by reducing the power losses and improving the minimum voltage of the distribution system.

Power Quality Enhancement by Integrating Distributed Generation in Distribution System

This research is to enhance the quality of power by reduce real power loss in distribution system and enables voltage profile enhancement at each bus. This will achieve by integrating Distributed Generation (DG) in optimal place with suitable size. In order to overcome the disadvantage of sluggish convergence of conventional algorithms the BAT Algorithm (BA) is used. In this paper the week buses are finding by using Backward/Forward (BW/FW) sweep approach based on real power loss. Later by using BA approach determination of optimal capacity and location will be done. This optimal size and location will leads to great minimization in real power loss and improvement of voltage at each bus. In this research the wind energy and Photo Voltaic (PV) energies are consider as DGs. This research is to determine the advantage of the proposed analysis on IEEE-69 radial bus using MATLAB software. The results were evaluated with the GSA approach existing in literature. Finally simulation outcomes prove that the proposed approach performance is superior in enhancing the power quality by optimal placement of DG and capacity of the DG.