Sizing Of Capacitor Banks Research Articles

Research on Step-Down Aviation Three-Phase Power Factor Correction based on Machine Learning and Optimization Algorithm

Objectives: The study looks at power quality issues, such as phase imbalance, voltage sags, and power factor issues, in aircraft systems. It highlights how immediate power factor correction steps are required to avoid equipment longevity problems and boost system efficiency, which will ultimately improve the performance of the entire aviation system. Methodology: Using a variety of data sources, real-time data gathering, and machine learning approaches, this study focuses on data collecting and real-time monitoring in aviation systems. Predictive modeling, testing methods for data preparation and analysis, and optimization algorithms for capacitor bank size and placement are all included. Considerations for privacy and security are covered. Result: Salp Swarm Optimization and the Dragonfly Algorithm are used in the study to assess the ideal capacitor sizes and positions, which results in better voltage profiles and lower active power losses. Aviation systems benefit from improved power factor correction through the application of integrated machine learning and optimization, which promotes sustainability and energy efficiency. Conclusion: The study demonstrated the significance of power factor correction in aviation by successfully addressing power quality issues in aircraft electrical systems through the use of optimization algorithms for capacitor sizing and location.

Optimal Allocation and Sizing of Capacitor Banks in Distribution System to Reduce the Power Loss Using Beluga Whale Optimization

One portion of the distribution system is the distribution feeder. Buses carrying more loads and having long‐distance route lines are significant problems due to the presence of power loss and the increase in the overall cost of the transportation process. Hence, the overall power loss minimization is taken as the major objective. The best sizing and allocation of capacitors in a bank in the distribution line are used to minimize the total loss. BWO technique is utilized in this optimization process. The backward‐forward sweep load flow is used for the computation of the power flow in MATLAB. The sensitive buses have been chosen according to the factor of loss sensitivity (LSF) and using BWO. The validity of the test has been made on the standard IEEE 34 and 85 bus radial distribution system. The simulation results in the 34‐bus radial system are much different from the results of PSO, GWO, WO, and IWO. In the 85‐bus radial system, the results are seen with the outcomes of PSO, WO, and BFOA. In both cases, the results of the proposed technique are found to be better than the existing methods. Therefore, the result shows that BWO can be effective for future selection to improve large distribution networks by sizing and locating the capacitors optimally.

Mitigation of Power Losses and Enhancement in Voltage Profile by Optimal Placement of Capacitor Banks With Particle Swarm Optimization in Radial Distribution Networks

The prime purpose of placing a capacitor bank in a power system is to provide reactive power, reduce power losses, and enhances voltage profile. The main challenge is to determine the optimum capacitor position and size that reduces both system power losses and the overall cost of the system with rigid constraints. For this purpose, different optimization techniques are used, for example Particle Swarm Optimization (PSO) which converges the complex non-linear problem in a systematic and methodological way to find the best optimal solution. In this paper, the standard IEEE 33-bus and 69-bus systems are used to find the optimum location and size of the capacitors bank. These power networks are simulated in Siemens PSS®E software. For the optimum solution of capacitor banks, the PSO algorithm is used. The PSO fitness function is modelled in such a way which contains the high average bus voltage, the small size of capacitor banks, and low power losses. The fitness function used is a weighted type to reduce the computation time and multi-objective function complexity.

Adaptive Dead Time Compensation for Continuous Cross-Period Single Phase Shift Control of Dual Active Bridge Converters

The load transient response of a power converter is an important property, especially in a test equipment application. The dynamic behavior of a dual active bridge converter mainly depends on the switching frequency, the transformer leakage inductance, and the capacitor bank size. Using the Continuous Cross-Period Single Phase-Shift control, an excellent load transient response can be achieved without the need for expensive hardware components. However, in practical applications, the switch delay and the required inserted dead time distort the current waveform, increasing the electromagnetic noise. i

A Comparison of Metaheuristic Techniques for Solving Optimal Sitting and Sizing Problems of Capacitor Banks to Reduce the Power Loss in Radial Distribution System

The losses in the radial distribution system are inevitable which needs to be minimized for the proper transmission of power to the end customers. This problem can be solved by the allocation of capacitor banks at proper locations with appropriate sizing. These allocations need an efficient approach for the performance enhancement of RDS. In this paper, several metaheuristic techniques such as particle swarm optimization (PSO), Harmony search, Bat, Cuckoo, and Grey‐wolf (GW) algorithms are employed to find the size of capacitor banks. Loss sensitivity analysis is considered for the indication of candidate buses where a capacitor has to be installed to reduce the total system losses and ultimately increase efficiency. Cost‐effectiveness, power loss minimization, and voltage enhancement can be determined and compared for these 5 techniques and are implemented on the IEEE‐34 bus system to illustrate the efficacy of each of them. The results show the advantages and drawbacks of the techniques separately. The simulations are carried out in MATLAB.

Optimal Sizing and Placement of Capacitor Banks in Distribution Networks Using a Genetic Algorithm

Nowadays, response to electricity consumption growth is mainly supported by efficiency; therefore, this is the new main goal in the development of electric distribution networks, which must fully comply with the system’s constraints. In recent decades, the issue of independent reactive power services, including the optimal placement of capacitors in the grid due to the restructuring of the electricity industry and the creation of a competitive electricity market, has received attention from related companies. In this context, a genetic algorithm is proposed for optimal planning of capacitor banks. A case study derived from a real network, considering the application of suitable daily profiles for loads and generators, to obtain a better representation of the electrical conditions, is discussed in the present paper. The results confirmed that some placement solutions can be obtained with a good compromise between costs and benefits; the adopted benefits are energy losses and power factor infringements, taking into account the network technical limits. The feasibility and effectiveness of the proposed algorithm for optimal placement and sizing of capacitor banks in distribution systems, with the definition of a suitable control pattern, have been proved.

Locating and sizing of capacitor banks and multiple DGs in distribution system to improve reliability indexes and reduce loss using ABC algorithm

DG sources have been introduced as one of the most widely used and effective methods among various methods providing losses reduction in power systems. In this paper, the artificial bee colony algorithm has been employed with the aim of determining location and capacity of distributed generations (DGs) and capacitor banks (CBs) in distribution systems. The proposed objective function includes power losses and ENS reliability index, which is used by deploying weight coefficients as objective function in the algorithms. Accordingly, the standard 37-bus networks have been used for studies. The simulation results demonstrate that the artificial bee colony algorithm is more effective in all sections and has higher capability in reducing losses and improving reliability as well.

Optimal Reactive Power Generation for Radial Distribution Systems Using a Highly Effective Proposed Algorithm

In this paper, a proposed modified stochastic fractal search algorithm (MSFS) is applied to find the most appropriate site and size of capacitor banks for distribution systems with 33, 69, and 85 buses. Two single-objective functions are considered to be reduction of power loss and reduction of total cost of energy loss and capacitor investment while satisfying limit of capacitors, limit of conductor, and power balance of the systems. MSFS was developed by performing three new mechanisms including new diffusion mechanism and two new update mechanisms on the conventional stochastic fractal search algorithm (SFS). As a result, MSFS can reduce 0.002%, 0.003%, and 0.18% of the total power loss from SFS for the three study systems. As compared to other methods, MSFS can reduce power loss from 0.07% to 3.98% for the first system, from 3.7% to 7.3% for the second system, and from 0.92% to 6.98% for the third system. For the reduction of total cost, the improvement level of the proposed method over SFS and two other methods is more significant. It is 0.03%, 1.22%, and 5.76% for the second system and 2.31%, 0.87%, and 3.77% for the third system. It is emphasized that the proposed method can find the global optimal solutions for all study cases while SFS was still implementing search process nearby or far away from the solutions. Furthermore, MSFS can converge to the best solutions much faster than these compared methods. Consequently, it can be concluded that the proposed method is very effective for finding the best location and size of added capacitors in distribution power systems.

Optimizing location and size of capacitors for power loss reduction in radial distribution networks

Power radial distribution systems are increasingly more and more important in transmitting the electric energy from power plants to customers. However, total loss in lines are very high. This issue can be solved by allocating capacitor banks. Determining the suitable allocation and optimal sizing of capacitor banks needs an efficient approach. In this study, the diffusion and update techniques-based algorithm (DUTA) is proposed for such reason. The efficiency of DUTA is inspected on two distribution systems consisting of 15-bus and 33-bus systems with different study cases. The solutions attained by DUTA are competed with recently published methods. As a consequence, the method is more effective than the other methods in terms of the quality of solution.

Optimal Allocation/Sizing of DGs/Capacitors in Reconfigured Radial Distribution System Using Quasi-Reflected Slime Mould Algorithm

Increased load demands worsen distribution system problems such as greater line losses, voltage deviation, and a plethora of other concerns. This current work presents an approach stressing simultaneous optimal allocation and sizing of capacitor banks and distributed generations, as well as optimal radial distribution system (RDS) reconfiguration, to address these difficulties. The above objectives are accomplished through the maiden application of the proposed quasi-reflection-based slime mould algorithm (QRSMA). The efficacy of QRSMA is established by testing it on different benchmark functions. A new modified backward forward load flow approach is also proposed and validated by comparing its results to those obtained using MATPOWER software for IEEE 69, 85, and 118 bus RDSs. The proposed load flow technique is independent of the sequential bus numbering scheme and may be applied to any RDS network topology. The proposed QRSMA is tested on 118 bus RDS and to prove its effectiveness; its results are compared to those of other studied algorithms. The study takes into account both fixed and variable loading scenarios. A cost-benefit analysis of the strategy is also performed in order to make the methodology more realistic.

Optimized Capacitor Placement Considering Load and Network Variability

This paper proposes a methodology for the optimized location and sizing of capacitor banks in distribution networks. The variabilities of system load and grid configuration are both considered. Cluster analysis on daily load curves is employed to model the load variability adequately, while changes in the grid configuration concern feeders’ reconfigurations associated with load transfers among them. Voltage profile improvement, energy loss reduction, and minimization of installation costs are pursued objectives, selected here for planning the investment in capacitor banks. The problem is combinatorial in nature and its solution using a genetic algorithm is proposed. Tests with a real distribution system are performed, exploring the knowledge about common network switching operations and employing system loading measurement data. The obtained results show the importance of adequately considering, during the planning phase, loading and topological conditions to which the distribution system will be submitted during operation.

Optimum location and sizing of capacitor banks using VOLT VAR compensation in micro-grids

In this work, a mathematical model called optimization by swarm of particles (PSO), was implemented to optimally solve the location and sizing of capacitor banks in a micro-grid of electrical distribution. The proposed method is based on particle swarm optimization (PSO) and the solution will be obtained with dynamic programming, implementing an algorithm that will be developed entirely in MATLAB. The algorithm calculates the optimal solution satisfying the necessary requirements to guarantee the operation of the electrical system. As a case study, a model of a micro-grid which is typically of 5 bars will be used. However, the algorithm was implemented in a general way and it can respond correctly to multi-bar systems. As a final analysis we made a comparison of the system data without compensating and the compensated system data, highlighting an improvement in the voltage profiles, minimization of the losses in the lines, minimization of the total losses of the system, improvement of the power factor, decrement in the maximum voltage deviation and average voltage deviation, complying with a minimum possible cost restriction criterion.

Optimal Allocation of Capacitor Bank for Loss Minimization and Voltage Improvement Using Analytical Method

An electric distribution system plays an important role in achieving satisfactory power supply. The quality of power is measured by voltage stability and profile of voltage. The voltage profile is affected by the losses in distribution system. As the load is mostly inductive on the distribution system and requires large reactive power, most of the power quality problems can be resolved with requisite control of reactive power. Capacitors are often installed in distribution system for reactive power compensation. This paper presents two stage procedures to identify the location and size of capacitor bank. In the first stage, the load flow is carried out to find the losses of the system using sweep algorithm. In the next stage, different size of capacitors are initialized and placed in each possible candidate bus and again load flow for the system is carried out. The objective function of the cost incorporating capacitor cost and loss cost is formulated constrained with voltage limits. The capacitor with the minimum cost is selected as the optimized solution. The proposed procedure is applied to different standard test systems as 12-bus radial distribution systems. In addition, the proposed procedure is applied on a real distribution system, a section of Sallaghari Feeder of Thimi substation. The voltage drops and power loss before and after installing the capacitor were compared for the system under test in this work. The result showed better voltage profiles and power losses of the distribution system can be improved by using the proposed method and it can be a benefit to the distribution networks.

Optimal Capacitor Placement in Radial Distribution System Using Moth Flame Optimization Algorithm

The environment friendly designing and running of electricity distribution structures are becoming vaster with the conjunction of renewable electricity options into power distribution systems. This study presents Moth Flame Optimization (MFO) approach to minimize total losses kW and energy cost and maximize net savings with solving the voltage deviation problem through optimal site and size of capacitor banks in electrical radial distribution networks. Two various load profiles are utilized to take a look at the modified algorithm on IEEE 123-, and 13-bus check networks. The OpenDSS software is utilized to resolve the power flowing via MATLAB programming interface. The results obtained are compared with IEEE normal state and other two heuristic approaches in same study, namely, imperialist competitive algorithm and particle swarm optimization. The proposed algorithm is more effective to minimise the total power losses and total cost and maximise net savings and to enhance the voltage profile for various distribution systems.

Adaptive Robust Short-Term Planning of Electrical Distribution Systems Considering Siting and Sizing of Renewable Energy Based DG Units

Short-term planning is a decision-making process that aims at ensuring proper performance of electrical distribution systems (EDSs) within a short period of time. In recent years, this process has faced a significant challenge due to the integration of renewable energy based technologies. To handle such complicated planning problem most suitably, sophisticated algorithms are required. This paper proposes a mixed-integer linear programming model to find the optimal short-term plan of EDSs considering siting and sizing of capacitor banks and renewable energy sources, conductor replacement of overloaded circuits, and voltage regulators allocation. Besides considering the economic aspects, the environmental issues are also considered to promote a low carbon emission system. To address the uncertainties of electricity consumption and renewable energy output power, a two-stage robust optimization model is used, and to handle this model more efficiently, the column and constraint generation algorithm is applied. A 135-node distribution system is studied under different conditions to assess the performance of the proposed approach. Results show that the planning actions, for each case study, improve the efficiency of EDS and mitigate the pollutant emissions at the distribution level.

Improving Reliability and Reducing Power Loss in Power Distribution Network by Determining Optimal Location and Size of Capacitor Banks

The use of capacitor banks in distribution system has many outstanding usages include improving the power factor of a system, voltage profile, and reliability besides the reducing of the power flow losses of the component’s reactive due to the compensation. These benefits depend greatly on how capacitors are placed in the distribution system. Hence, in order to achieve the high reliable construction, switching capacitor has been placed to improve the main challenges of the network designing (reliability and reduce power loss) in the radial distribution system. As regards, the importance of the reliability and power losses are ignored in the distribution networks; the aim of this paper is primarily to establish an objective function for the parallel optimization of these aforementioned parameters. In the simulation process, ten parameters have been compared, which are: System Average Interruption Frequent Index (SAIFI) and its cost, System Average Interruption Duration Index (SAIDI) and its cost, power loss and its cost, the installed capacity and it's cost and values of two objective functions. Honey-bee mating optimization (HBMO) algorithm has been used to solve this problem. Then, the developed technique has been used on the IEEE standard distribution network as a problem-solving system.

Improving Reliability and Reducing Power Loss in Power Distribution Network by Determining Optimal Location and Size of Capacitor Banks

Improving Reliability and Reducing Power Loss in Power Distribution Network by Determining Optimal Location and Size of Capacitor Banks

An analytical circuit based nonlinear thermal model for capacitor banks

The thermal couplings among capacitors in a bank could significantly alter the reliability performance compared to a single capacitor. The impact of thermal coupling is becoming stronger for high power density systems due to more stringent constraint in volume. Prior-art studies take into account the thermal coupling effects of a capacitor bank by either Finite Element Method (FEM) or experimental characterization, which are case dependent and time-consuming. This paper proposes a nonlinear mathematical model for capacitor banks based on physics of thermal conduction, convection, and radiation. A simplified version of the model is also obtained and represented by an RC circuit network, which enables computational-efficient thermal stress modeling. The proposed models are convenient to use to support model based sizing of capacitor banks and is scalable for multi-cell rectangle layout. A case study with experimental testing is discussed to verify the accuracy of the models.

Optimal Sizing and Placement of Capacitors in Radial Distribution Systems Based on Grey Wolf, Dragonfly and Moth–Flame Optimization Algorithms

The applications of grey wolf (GWO), dragonfly (DFO) and moth–flame (MFA) optimization techniques for optimum sitting of capacitors in various radial distribution systems (RDSs) are presented. The loss sensitivity factor is applied to determine the most candidate buses. Then, each optimization technique is utilized to find optimum placements and sizes of capacitors for determined Buses. In this study, 33-, 69- and 118-bus RDSs are considered for validating the effectiveness and efficiency of studied algorithms. The convergence performance is evaluated for tested RDSs using MATLAB/Simulink software. The obtained results confirm that GWO, DFO and MFA offer accurate convergence to the global minimum point of the objective function with high convergence speed. The ability of the studied techniques for enhancing voltage profiles with considered distribution systems is achieved. Finally, a comparison study between each studied technique with each other and with other techniques like PSO, fuzzy-GA, heuristic, DSA, TLBO, DA-PS, FPA and CSA has been carried out. The parameters of the comparison include: efficiency, execution time, the speed of convergence, minimizing total cost and increasing net savings. The results of comparison indicated that GWO-based algorithm has accurate convergence to optimal location and size of capacitor banks. In addition, it has the best performance in comparison with other techniques.

Optimal location and sizing of capacitor banks in distribution networks to reduce harmonic distortion and improve voltage profile using genetic algorithm

This paper considers the problem of determination of optimum locations and sizes of capacitor banks (CB) for reactive power compensation in distribution systems to reduce harmonic distortion and improve voltage profile. Genetic Algorithm (GA) was used for solving this non-linear multi-objective optimization problem with constraints. A detailed methodology was presented for solving the power flow problem at fundamental and higher harmonic frequencies of interest and models of network components in harmonic analysis. The proposed procedure was successfully tested on the standard IEEE 33-bus test system for three different objective functions. Calculations showed the efficiency of GA for solving this complex problem.