Capacitors In Distribution Network Research Articles

A flexible loss reduction formulation for simultaneous capacitor placement and network reconfiguration in distribution grids

Efficiently reducing power losses involves various strategies such as opening normally closed switches and closing normally open tie-lines in distribution feeders, and optimally placing shunt capacitors in distribution networks. In this process, the accurate modeling of the demand side is crucial in understanding the behavior of electricity consumers appropriately. It is important to note that loads are not constant; they vary with changes in voltage magnitude, which in turn depend on the type of consumer. Each load can be represented by its constant power, current, and impedance components. In this regard, establishing a clear relationship between these components and consumer types can significantly enhance the flexibility of the network switching or capacitor placement strategy. Therefore, this study aims to mathematically formulate the correlation between load components and consumer types, aiming at establishing an efficient reconfiguration and capacitor allocation formulations. This is achieved by transforming polynomial load formulations into quadratic ones, while establishing mathematical relationships between the quadratic and polynomial models for various load types. The accuracy and convergence time of the proposed model was tested through its application to 16- and 33-bus distribution networks, and the results have been compared with the nonlinear metaheuristic approach. The results demonstrated that the proposed framework can efficiently provide optimal solutions within a shorter computational time as compared to the nonlinear and metaheuristic approaches.

Optimal location determination for an EVPL and capacitors in distribution network considering power loss and voltage profile: SGOS2A technique

This paper proposes a hybrid optimization system depending on optimal location for electric vehicles parking lot (PL) and capacitors on distribution system to maintain voltage profile with electricity loss. The proposed system is the consolidation of Seagull optimization algorithm (SGO) and salp swarm algorithm (SSA). The migration and attacking behaviors of seagull is empowered through SSA method. By this manner, the proposed hybrid optimization scheme is known as SGOS2A method. Here, parking zone allocation with capacitor is considered to congestion management in conjunction through the compensation of reactive energy. So, one can optimally decide the size of automobile parking space, SGOS2A method is followed. Moreover, parking lot with capacitor allocation is considered to congestion control at the side of reactive power compensation. By this proper manipulate, the capacitors exact location, automobile parking space of electric vehicles on the grid, lessening of active with reactive power loss, voltage profile conversion is selected optimally. Besides, the proposed SGOS2A scheme is activated on MATLAB/Simulink site, then the efficiency is examined with different techniques. The mean, median and standard deviation of the proposed approach achieves 1.0593, 1.0915 and 0.1050.

Studi Rekonfigurasi Sistem Distribusi Pada Jaringan 20 kV Dengan Metode Simple Branch Exchange Pada Penyulang Cempaka

The increasing electric energy consumption must be balanced with good electricity network quality. To overcome this, we need a distribution network reconfiguration. Reconfiguration in power distribution network is done to improve power distribution network quality. Problem that exist in the radial distribution network is power losses. To minimize the power losses can be overcome by compensating capacitor. Done by determining the location of capacitors in distribution networks. With that the capacitor compensates the distribution network is more effective and efficient in distributing power. In this research discusses the network reconfiguration using simple branch exchange method to reduce power losses in radial distribution networks. The reconfiguration method was carried out with the help of the Electrical Transient Analysis Program (ETAP) 12.6.0 software and has been tested by PT REKAYASA INDUSTRI and PLN Area South Kalimantan on the 20 kV distribution system of Cempaka feeder, South Kalimantan. With this reconfiguration, the voltage drop that occurs on several buses, especially bus 37 and 44, has a voltage drop of up to 95.03% to 95.31% with an average drop voltage of 95.1%, which means the average voltage drop. each feeder is ableto send electricity to consumers properly.

Assessment for Voltage Violations considering Reactive Power Compensation Provided by Smart Inverters in Distribution Network

Due to the high proportion of renewable energies, traditional voltage regulation methods such as on-load tap changers (OLTCs) and switching capacitors (SCs) are currently facing the challenge of providing fast, step-less, and low-cost reactive power to reduce the increasing risks of voltage violations in distribution networks (DNs). To meet such increasing demand for voltage regulation, smart inverters, including photovoltaics (PVs) and electric vehicle (EV) chargers, stand out as a feasible approach for reactive power compensation. This paper aims to assess the voltage violation risks in DNs considering the reactive power response of smart inverters. Firstly, reactive power compensation models of PVs and EV chargers are investigated and voltage deviation indexes of the regulation results are proposed. Moreover, kernel density estimation (KDE) and slice sampling are adopted to provide the PV output and EV charging demand samples. Then, the risk assessment is carried out with a voltage regulation model utilizing OLTCs, SCs, and available smart inverters. Numerical studies demonstrate that the reactive power support from smart inverters can significantly mitigate the voltage violation risks and reduce the switching and cost of OLTCs and capacitors in DNs.

Stochastic Simultaneous Planning of Interruptible Loads, Renewable Generations and Capacitors in Distribution Network

Executing interruptible loads (ILs) can be significantly effective for optimal and secure operation of power systems. These ILs can aid the operators not only to increase the reliability of the power supply but also to reduce the procurement costs of the whole system. Therefore, determining the optimal location and capacity of ILs for a given incentive rate is of great interest to distribution companies. To do so, in this paper simultaneous allocation and sizing of ILs, wind turbines (WT), photovoltaic (PV) and capacitors have been done in the radial distribution network for different demand levels and subsequently the optimal value of compensation price for the ILs has been determined. Given the probabilistic nature of load, wind and solar generation as well as the price of energy at the pool, we have also proposed a stochastic model based on fuzzy decision making for modelling the technical constraints of the problem under uncertainty. The objective functions are technical constraint dissatisfaction, the total operating costs of the Distribution Company and CO2 emissions which are minimized by NSGA2. To model the uncertainties, a scenario-based method is used and then by using a scenario reduction method the number of scenarios is reduced to a certain number. The performance of the proposed method is assessed on the IEEE 33-node test feeder to verify the applicability and effectiveness of the method.

Optimal allocation of EV charging spots and capacitors in distribution network improving voltage and power loss by Quantum-Behaved and Gaussian Mutational Dragonfly Algorithm (QGDA)

In this paper, a new methodology for optimal planning of charging stations (CS) along with capacitors (CAP) using proposed technique is presented. In order to achieve a better balance between exploration and exploitation for dragonfly algorithm (DA), the quantum-behaved and Gaussian mutation strategies on the performance of DA is used. This is the novelty of our proposed work. Hence, it is named as quantum-behaved Gaussian mutational DA (QGDA). Here, parking lot and capacitor allocation is suggested for congestion management along with reactive power compensation. In order to optimally determine the parking lot size, QGDA is utilized. The effectiveness of the proposed technique is tested on adapted IEEE 34-bus distribution network. The result attained by QGDA technique is compared with existing techniques such as PSO and BBO. With PL, the proposed technique achieves the Ploss and Qloss of 25.61 kW and 25.99KVar. PL and C at same node, the proposed technique achieves the Ploss and Qloss of 31.09 kW and 32.88KVar. PL and C at different node, the proposed technique achieves the Ploss and Qloss of 25.09 kW and 26.98KVar. Furthermore, the proposed results show that an uneven EV charging scenario can cause significant voltage unbalance that goes beyond its allowed limit of 2%.

Placement of Distributed Generation and Shunt Capacitor in Distribution Network using Cuckoo Search Algorithm

This work aims at reduction in active and reactive power loss reduction in distribution networks as well as to improve the voltage stability of the networks. Optimum Distributed Generation (DG) placement and sizing is carried out in conjunction with shunt capacitor placement and sizing to determine the appropriate sizes of DG units and Capacitor banks to be placed in the networks so as not to violate certain constraints. The optimal sizes of the DG units and capacitor banks were obtained on application of a Cuckoo Search Optimization Algorithm while computations for Voltage stability was performed using the Voltage Stability Index (VSI). The obtained optimal sizes of DG units and Capacitors were individually and simultaneously placed on the distribution networks to ascertain the behaviour of the networks prior to and after their placements. The performance factors considered are power loss and voltage stability. A comparison of these performance factors under separate and simultaneous placement method was demonstrated using IEEE 33 and 69 test buses. Result show that power loss (active and reactive) reduced by 63.29% and 59.38% respectively for 33 bus system, with a 74.29% and 79.19% reduction on 69 bus system. Voltage stability also increased by 7.89% and 3.79% respectively for 33 and 69 bus system relative to values obtained for base case and separate DG and shunt capacitor placement.
 Keywords: Distributed generation, shunt capacitor, Cuckoo Search Algorithm (CSA), power loss and voltage stability.

A Two-Loop Hybrid Method for Optimal Placement and Scheduling of Switched Capacitors in Distribution Networks

This paper presents a method to find the optimal size and place of the switched capacitors using a hybrid optimization algorithm. The objective function includes the active and reactive power of power plants, the capital and maintenance costs of capacitor banks, and the cost of active and reactive power losses in distribution lines and transformers. The impact of the load model on the optimal sizing and placement of switched capacitors is studied using three different scenarios: In the first scenario, all loads are voltage-dependent; in the second scenario, only a portion of loads are voltage-dependent; in the third scenario, all loads are voltage-independent. The proposed hybrid algorithm incorporates an outer and two inner optimization layers. The outer layer is executed by a genetic algorithm (GA), while the inner layer is performed by a GA, an exchange market algorithm (EMA), or a particle swarm optimization (PSO). The performance of GA-GA, GA-EMA, and GA-PSO hybrid schemes are compared on an IEEE 33-bus test system. Moreover, IEEE 33-bus and 69-bus networks are used to verify the effectiveness of proposed hybrid scheme against the gravitational search algorithm (GSA), a combination of PSO and GSA (PSOGSA), cuckoo search algorithm (CSA), teaching learning-based optimization (TLBO), and flower pollination algorithm (FPA). The results highlight the advantage of the proposed hybrid optimization scheme over the other optimization algorithms.

Simultaneous optimal allocation and sizing of distributed generations and shunt capacitors in distribution networks using fuzzy GA methodology

This paper presents a combination of fuzzy and genetic algorithm (GA)-based methodology for simultaneous optimum allocation and sizing of distributed generations (DGs) and shunt capacitors (SCs) together in distribution systems. The objectives of reduction of active power and reactive power supply, reduction of real power loss and improvement of branch current capacity, voltage profile and voltage stability are considered. The combination of shunt capacitors with both unity power factor DGs and lagging power factor DGs also considered for analyzing the performance of the distribution systems. Simulation results are demonstrated to show the advantage of proposed fuzzy genetic algorithm-based technique over conventional multiobjective approach and loss sensitivity-based optimization techniques reported in the literature.

A novel multi-objective hybrid WIPSO-GSA algorithm-based optimal DG and capacitor planning for techno-economic benefits in radial distribution system

PurposeThis paper aims to optimally plan distributed generation (DG) and capacitor in distribution network by optimizing multiple conflicting operational objectives simultaneously so as to achieve enhanced operation of distribution system. The multi-objective optimization problem comprises three important objective functions such as minimization of total active power loss (Plosstotal), reduction of voltage deviation and balancing of current through feeder sections.Design/methodology/approachIn this study, a hybrid configuration of weight improved particle swarm optimization (WIPSO) and gravitational search algorithm (GSA) called hybrid WIPSO-GSA algorithm is proposed in multi-objective problem domain. To solve multi-objective optimization problem, the proposed hybrid WIPSO-GSA algorithm is integrated with two components. The first component is fixed-sized archive that is responsible for storing a set of non-dominated pareto optimal solutions and the second component is a leader selection strategy that helps to update and identify the best compromised solution from the archive.FindingsThe proposed methodology is tested on standard 33-bus and Indian 85-bus distribution systems. The results attained using proposed multi-objective hybrid WIPSO-GSA algorithm provides potential technical and economic benefits and its best compromised solution outperforms other commonly used multi-objective techniques, thereby making it highly suitable for solving multi-objective problems.Originality/valueA novel multi-objective hybrid WIPSO-GSA algorithm is proposed for optimal DG and capacitor planning in radial distribution network. The results demonstrate the usefulness of the proposed technique in improved distribution system planning and operation and also in achieving better optimized results than other existing multi-objective optimization techniques.

OPTIMASI REKONFIGURASI JARINGAN DISTRIBUSI RADIAL UNTUK MEMINIMALKAN RUGI JARINGAN MENGGUNAKAN METODE SIMPLE BRANCH EXCHANGE

The increasing electric energy consumption must be balanced with good electricity network quality. To overcome this, we need a distribution network reconfiguration. Reconfiguration in power distribution network is done to improve power distribution network quality. Problem that exist in the radial distribution network is power losses. To minimize the power losses can be overcome by compensating capacitor. Done by determining the location of capacitors in distribution networks. With that the capacitor compensates the distribution network is more effective and efficient in distributing power.
 In this research discusses the network reconfiguration using simple branch exchange method to reduce power losses in radial distribution networks . Plant that used in this final project is IEEE 33 bus feeders. Simple branch exchange method is a kind of heuristic method . It works by selecting the order of the loop is done for distribution networks reconfiguration. 
 Simulation results show that the use of a simple branch exchange method for reconfiguring network can reduce energy loss by 63,4677 kW. From the simulation results using the distribution system IEEE 33 bus feeders, showed that the decrease of energy losses from 202,6845 kW become 139,2168 kW.

Optimal economic-driven planning of multiple DG and capacitor in distribution network considering different compensation coefficients in feeder’s failure rate evaluation

The main aim of Distribution Companies (DISCOs) is to satisfy end user demand with quality and reliable supply of power at all possible locations in the distribution network. Since majority of loads connected to the distribution network are inductive in nature, there exists possibility of higher energy loss and lower reliability in the distribution feeder sections. In this study optimal planning of Distributed Generation (DG) and capacitor is investigated considering maximization of total cost benefit as main objective. Here, the cost benefit due to DG and capacitor installation is attained by minimizing energy purchased from the substation including energy loss and by reducing Expected Interruption Cost (ECOST) of the system. Moreover, a detailed analysis is carried out in the DG and capacitor planning problem considering different compensation coefficients in feeder’s failure rate evaluation so that the compensation coefficient resulting in enhanced net cost benefit is identified. Furthermore, a hybrid combination of Weight Improved Particle Swarm Optimization (WIPSO) and Gravitational Search Algorithm (GSA) called hybrid WIPSO-GSA algorithm is proposed to solve the optimal DG and capacitor planning problem in the distribution network. The proposed methodology is tested on standard 33-bus and Indian 85-bus distribution systems. The superiority of the proposed hybrid algorithm is also illustrated by comparing the results with other optimization techniques.

Gbest-Guided Artificial Bee Colony Optimization Algorithm-Based Optimal Incorporation of Shunt Capacitors in Distribution Networks under Load Growth

Abstract In this work, a new technique is introduced for optimal incorporation of shunt capacitors (SCs) in distribution networks. This technique has been compared to other sensitivity-based approaches such as loss sensitivity factor, index vector method, power loss index, and index of voltage stability. In the proposed technique, the optimal positions as well as the ratings of SCs are identified through an optimization algorithm. In sensitivity-based approaches, the positions of SCs are determined through a sensitivity approach and the optimal ratings of SCs are computed through an optimization algorithm. The main target of this study is to minimize the total annual cost and power loss of the network under load growth. This has been done through the population-based Gbest-guided artificial bee colony (GABC) optimization technique. Furthermore, the outcomes obtained through the GABC algorithm are compared to those from the iteration particle swarm optimization algorithm. The whole work along with the proposed methodology has been demonstrated on standard 34-bus and 118-bus distribution networks for SC placement. The results show that it reduces the total annual expense of the network to a great value. Consequently, it improves the total power loss reduction, enhances the voltage profile and power factor, and reduces the total voltage deviation. The obtained numerical outcomes through the proposed technique have been compared with the published literature outcomes to show the viability and superiority of the algorithm.

Gbest-guided artificial bee colony algorithm based simultaneous placement of distributed generation and shunt capacitor in distribution networks

This paper presents a combined placement of distributed generation (DG) and shunt capacitor in distribution network for the purpose of power loss reduction. The locations of DG and shunt capacitor are evaluated by using power loss index approach and index vector method, respectively. The population based Gbest-guided artificial bee colony meta-heuristic optimisation technique has been implemented to evaluate the optimum size of DG and shunt capacitor simultaneously. This methodology is being demonstrated on 33-bus and 85-bus distribution network. In addition to that, the two load scenarios are considered in this study. The technical analysis has been carried out for different combinations of DG and shunt capacitor. Comparison between various cases for power loss, minimum system voltage, voltage stability index and total voltage deviation are also mentioned in this paper. The numerical results obtained through proposed approach have been compared to the published research papers for showing its effectiveness.

A multiobjective approach for optimal placement and sizing of distributed generators and capacitors in distribution network

Both active and reactive power play important roles in power system transmission and distribution networks. While active power does the useful work, reactive power supports the voltage that necessitates control from system reliability aspect as deviation of voltage from nominal range may lead to inadvertent operation and premature failure of system components. Reactive power flow must also be controlled in the system to maximize the amount of real power that can be transferred across the power transmitting media. This paper proposes an approach to simultaneously minimize the real power loss and the net reactive power flow in the system when reinforced with distributed generators (DGs) and shunt capacitors (SCs). With the suggested method, the system performance, reliability and loading capacity can be increased by reduction of losses. A multiobjective evolutionary algorithm based on decomposition (MOEA/D) is adopted to select optimal sizes and locations of DGs and SCs in large scale distribution networks with objectives being minimizing system real and reactive power losses. MOEA/D is the process of decomposition of a multiobjective optimization problem into a number of scalar optimization subproblems and optimizing those concurrently. Case studies with standard IEEE 33-bus, 69-bus, 119-bus distribution networks and a practical 83-bus distribution network are performed. Output results of MOEA/D method are compared with similar past studies and notable improvement is observed.

Capacitor placement in distribution systems for power loss reduction and voltage improvement: a new methodology

For compensating reactive power, shunt capacitors are often installed in electrical distribution networks. Consequently, in such systems, power loss reduces, voltage profile improves and feeder capacity releases. However, finding optimal size and location of capacitors in distribution networks is a complex combinatorial optimisation problem. In such problem, an objective function which is usually defined based on power losses and capacitor installation costs should be minimised subject to operational limitations. In this study, a newly developed metaheuristic technique, named crow search algorithm (CSA), is proposed for finding the optimal placement of the capacitors in a distribution network. CSA is a population-based technique inspired by the greedy behaviour of crows in finding better food sources. The main reasons of using CSA are its easy implementation, few parameters to adjust, fast convergence speed and high efficiency. In the case studies, simulated results indicate that the proposed CSA produces more accurate results than the other studied search methods.

Optimal capacitor placement in distribution networks regarding uncertainty in active power load and distributed generation units production

The paper proposes a new method for optimal allocation of shunt capacitors in distribution network with renewable distributed generation units such as wind turbines and/or solar power plants. The proposed method, based on application of the Monte Carlo simulation methods, respects the uncertainties associated with load demand and renewable sources power production. The optimisation problem is modelled by two criterion functions with the aim of improving voltage profile in a network by optimal selection of the locations and installed powers of the shunt capacitors. The suggested criterion functions have been optimised simultaneously by applying the non-dominated sorting genetic algorithm. On the basis of the measured data on wind speed and solar radiation, the method has been tested by the example of a real distribution network.

Simultaneous placement and sizing of DGs and shunt capacitors in distribution systems by using IMDE algorithm

This paper presents a new optimization algorithm, named intersect mutation differential evolution (IMDE) to optimally locate and to determine the size of DGs and capacitors in distribution networks simultaneously. The objective function is taken to minimize the power loss and loss expenses providing that the bus voltage and line current remain in their limits. Simulation results on IEEE 33-bus and 69-bus standard distribution systems show the efficiency and the superior performance of the proposed method when it is compared with other algorithms.

Optimal placement and sizing of distributed generators and shunt capacitors for power loss minimization in radial distribution networks using hybrid heuristic search optimization technique

Abstract This paper attempts to minimize power losses in radial distribution networks and facilitates an enhancement in bus voltage profile by determining optimal locations, optimally sized distributed generators and shunt capacitors by hybrid Harmony Search Algorithm approach. To overcome the drawback of premature and slow convergence of Harmony Search Algorithm (HSA) over multi model fitness landscape, the Particle Artificial Bee Colony algorithm (PABC) is utilized to enhance the harmony memory vector. In the first approach, the formulation echoes the determination of loss sensitivity factor to decide the sensitive nodes and thereafter decides on the optimal rating through the use of hybrid Algorithm. The second approach encircles the role of hybrid Algorithm to search for both the optimal candidate nodes and sizing of compensating devices by significant increase in loss reduction with the former approach. The procedure travels to examine the robustness of the proposed hybrid approach on 33 and 119 node test systems and the result outcomes are compared with the other techniques existing in the literature. The simulation results reveal the efficiency of the proposed hybrid algorithm in obtaining optimal solution for simultaneous placement of distributed generators and shunt capacitors in distribution networks.

Simultaneous placement of DG and capacitor in distribution network

In this study, the planning problem concerned with simultaneous placement of distribution generation (DG) and capacitor bank in the distribution network is investigated from a local distribution company's (DISCO's) viewpoint based on minimum total cost over the planning period and applying genetic algorithm (GA). The cost terms of the objective function include risk cost of load not supplied of the customers, cost of energy loss of the system, investment costs for purchasing the DGs and capacitor banks, and maintenance costs of the installed DGs and capacitor banks. Herein, the customers’ load types including residential, commercial, and industrial are modeled in the planning problem and load model-based power flow is applied instead of the conventional power flow. In addition, the failure rate of the distribution feeder is modeled respect with magnitude of the current flowing through the feeder applying several mathematical functions such as linear, power, exponential, and logarithmic. Moreover, in order to achieve realistic results, economic factors such as inflation and interest rates and technical factors including yearly load growth, hourly variations of the load, and daily variations of the load are taken into consideration in the planning problem.