Optimal Placement and Sizing of Shunt Capacitors in Radial Distribution System Using Polar Bear Optimization Algorithm

Compensating reactive power deficiency on power grids is a central concern in the distribution of energy management systems. Several approaches have been adopted over time to minimize the total real power loss and enhancing bus voltage profile. Shunt capacitor has been used from time immemorial for addressing issue of reactive power compensation at the distribution end of power systems, and the extent of benefits derivable from its usage depend solely on correct siting and sizing. To this effect, meta-heuristic algorithms are promising optimization tools for achieving these objectives. This paper, therefore, presents a comprehensive review of cuckoo search algorithm based on optimal siting and sizing of shunt capacitors in radial distribution systems. The suitability, in addition to strengths and weakness of each approaches reported in the reviewed articles have been painstakingly x-rayed. Based on the review, it was observed that a two-stage approach is always adopted in the compensation process: the pre-selection of potential or sensitive nodes and the optimal sizing of shunt capacitors needed for the compensation. For the pre-location, Voltage Stability Index and Loss Sensitivity Factor were found to be comparatively less complex and highly suitable techniques. Another cogent discovery from this review is that less attention has been drawn to the use of cuckoo search algorithm by Nigerian researchers. Therefore, regarding Nigerian electric grid system, the use of cuckoo search algorithm in reactive power support presents a research gap for further investigations.

This paper presents a novel method for the selection of appropriate location and calculation of the size of distributed generation (DG) and sizing of shunt capacitors in radial distribution systems. This methodology is based on wavelet neural network (WNN) which requires less computational burden compared to traditional ones. The proposed optimization technique takes into consideration minimizing the cost of peak power, reducing energy loss and improving voltage stability index. The proposed method of optimization is then compared with the golden section search (GSS), grid search (GS), and Acharya's heuristic method (AHM) on different IEEE radial buses, i.e. 12 bus, 12 bus with DG, 33 bus, 33 bus with DG. The results demonstrates that WNN provides more economical solution by reducing power losses, energy loss, total requiring capacitive compensation and presents a good improvement in nodes voltage. © 2014 IEEE.

Controlling active/reactive power in distribution systems has a great impact on its performance. The placement of distributed generators (DGs) and shunt capacitors (SCs) are the most popular mechanisms to improve the distribution system performance. In this line, this paper proposes an enhanced genetic algorithm (EGA) that combines the merits of genetic algorithm and local search to find the optimal placement and capacity of the simultaneous allocation of DGs/SCs in the radial systems. Incorporating local search scheme enhances the search space capability and increases the exploration rate for finding the global solution. The proposed procedure aims at minimizing both total real power losses and the total voltage deviation in order to enhance the distribution system performance. To prove the proposed algorithm ability and scalability, three standard test systems, IEEE 33 bus, 69 bus, and 119-bus test distribution networks, are considered. The simulation results show that the proposed EGA can efficiently search for the optimal solutions of the problem and outperforms the other existing algorithms in the literature. Moreover, an economic based cost analysis is provided for light, shoulder and heavy loading levels. It was proven, the proposed EGA leads to significant improvements in the technical and economic points of view.

In electrical distribution networks, capacitor banks are widely used to regulate reactive power and enhance power factor. The efficient placement of capacitor banks offers numerous advantages, including minimizing power losses, increasing overall cost savings, and enhancing voltage profiles across feeders. Numerous optimization algorithms have been applied to determine the optimal size and allocation of capacitor banks within distribution networks. This study proposes a solution to the Optimal Capacitor Placement and Sizing (OCPS) problem using the African Vulture Optimization Algorithm (AVOA) that mimics the natural foraging and navigational behavior of African vultures. Employing the AVOA algorithm identifies the most suitable buses for capacitor allocation and efficiently determines ideal locations and sizes for capacitor banks. The effectiveness of the proposed approach is validated on the IEEE-33 and IEEE-69 bus Radial Distribution Systems (RDS) and compared with other available optimization techniques. The results indicated that implementing AVOA leads to improved overall performance, leading to a reduction in total cost and loss, improved voltage profile, energy savings, and net savings in dollars per year. The annual net savings for IEEE-33 and IEEE-69 buses are 32.22% and 33.24%, respectively.

Chapter 10 - Optimal Placement and Sizing of Shunt Capacitor Banks in the Presence of Harmonics

This paper presents a binary gravitational search algorithm (BGSA) is applied to solve the problem of optimal allotment of DG sets and Shunt capacitors in radial distribution systems. The problem is formulated as a nonlinear constrained single-objective optimization problem where the total line loss (TLL) and the total voltage deviations (TVD) are to be minimized separately by incorporating optimal placement of DG units and shunt capacitors with constraints which include limits on voltage, sizes of installed capacitors and DG. This BGSA is applied on the balanced IEEE 10 Bus distribution network and the results are compared with conventional binary particle swarm optimization.

This article presents a hybrid method based on analytical and metaheuristic optimization techniques for the optimal placement of distributed generations (DGs) and shunt capacitors (SCs) into radial distribution systems (RDSs) to minimize power loss. In the hybrid method, a meta-heuristic called the Salp Swarm Algorithm is utilized to determine the optimal locations of DGs and SCs, while an efficient analytical technique is applied to calculate the optimal sizes. To check the robustness of the proposed method, two standard IEEE systems are employed; IEEE 33-bus and 69-bus, and compared with existing optimization techniques. Also to confirm the ability of the proposed method on improving performance, it applied to an actual 94-bus Portuguese RDS. The obtained results show the feasibility of the proposed method in optimal allocating of the DG and SC into RDS.

Deploying shunt capacitor banks in distribution systems can effectively reduce the power loss and provide additional benefits for system operation. In practice, the power loss on distribution transformers can account for a considerable portion of the overall loss. This paper proposes a method for optimal placement of capacitor banks to the distribution transformers to reduce power loss. The capacitor bank locations are considered at the low-side of transformers. The net present value (NPV) criterion is adopted to evaluate the cost benefit of the capacitor installation project. First, an explicit formula for directly calculating the power loss of radial distribution systems is derived. Then, the optimal capacitor bank placement is formulated as a mixed-integer programming (MIP) model maximizing the NPV of the project subject to certain constraints. The model is suitable for being solved by commercial MIP packages, and the operational control of the capacitor banks to maximize the power loss reduction can be simply achieved by local automatic switching according to VAR measurements. The proposed method has been practically applied in the Macau distribution system, and the simulation results show that the proposed method is computationally efficient, and a considerable positive NPV can be obtained from the optimal capacitor bank placement.

This paper presents an efficient methodology for the optimal location and sizing of fixed and switched shunt capacitors in radial distribution systems using Genetic Algorithms. Unlike the conventional objective function, a new constraint objective cost function has been formulated to maximize the net annual savings by minimizing real power loss and optimizing the purchase cost of shunt capacitors while maintaining a better node voltage profile of the system. The application results of the proposed method are demonstrated and compared with other method available in literature. The suitability of the proposed method is tested on a large-scale distribution system. The effectiveness of the proposed algorithm is indicated by higher savings in energy loss, lower amounts of capacitive compensation, better allocation of fixed and switched shunt capacitor ratings and increased net annual savings.

In this paper we describe a new technique for placing fixed capacitors in radial distribution systems based on genetic algorithms (GA). Actually, current optimization models of capacitor placement only consider losses reduction and voltage profile simultaneously, but the compensation cost and the load changes are not taking into account as part of the objective function. Also, the result may be not the best choice because this is a very large optimization problem and there are too many combinations. We present here a general approach for the optimal solution of this problem considering all the parameters of the distribution system involved: capacitor cost, voltage, angle and load changes per hour. An exhaustive search through all possible solutions is needed. Therefore, GA is an ideal candidate to solve this situation. Working with this algorithm, a Microsoft Excel Program has been developed in order to answer the capacitor placement problem for any kind of radial distribution system. The test results are presented along with the discussion of the algorithm.

In this paper, a mine blast algorithm (MBA) is proposed for optimal allocations and sizing of capacitors in various distribution systems. First, the most candidate buses for installing capacitors are suggested using loss sensitivity factors (LSF). Then, the proposed MBA is employed to deduce the size of capacitors and their locations from the elected buses. The objective function is designed to reduce the total cost and, consequently, to increase the net saving per year. The proposed algorithm is tested on 10 and 85 bus radial distribution systems. The obtained results via the proposed algorithm are compared with others to highlight their benefits. Moreover, the results are introduced to verify the effectiveness of the suggested algorithm to minimize the losses and total cost and to enhance the voltage profile and net saving for various distribution systems and loading conditions.

Shunt capacitors installation in distribution systems requires optimal placement and sizing. More harmonics are being injected into distribution systems. Adding shunt capacitors may lead to high distortion levels. The capacitor placement and sizing problem is a nonlinear integer optimization problem, with locations and ratings of shunt capacitors being discrete values. The goal is to minimize the overall cost of the total real power loss and that of shunt capacitors while satisfying operating and power quality constraints. This paper proposes to solve the problem using particle swarm optimization (PSO). A discrete version of PSO is combined with a radial distribution power flow algorithm (RDPF) to form a hybrid PSO algorithm (HPSO). The former is employed as a global optimizer to find the global optimal solution, while the latter is used to calculate the objective function and to verify bus voltage limits. To include the presence of harmonics, the developed HPSO was integrated with a harmonic power flow algorithm (HPF). The proposed (HPSO-HPF)-based approach is tested on an IEEE 13-bus radial distribution system (13-Bus-RDS). The findings clearly demonstrate the necessity of including harmonics in optimal capacitor placement and sizing to avoid any possible problems associated with harmonics.

The electricity demand increment, fossil fuel depletion, and environmental degradation open the interest of power utilities to utilize the distributed generation (DG) and distributed-static compensator (DSTATCOM) in the distribution system. The optimal placement and sizing of these generations have positive benefits, whereas non-optimal placement and size may worsen the existing operational characteristics of the distribution system. Therefore, this article presents a new methodology for optimal placement and sizing of distributed generation and distributed-static compensator in a radial distribution system. Moreover, a short-term planning has been made for power loss reduction with existing and increased load growth using particle swarm optimization (PSO) algorithm. The performance of proposed methodology is tested using different case studies on standard IEEE 33 bus system (RDS). The measured results are also compared with other literature methods and it is revealed that the proposed method gives more significant results.

This article presents a simple method for investigating the problem of contemporaneously choosing optimal location and size of shunt capacitors in three-phase unbalanced radial distribution systems. The main objective function formulated consists of two terms: cost of energy loss and cost related to capacitor purchase and capacitor installation. The problem of choosing optimal locations and sizes for shunt capacitors in an unbalanced radial distribution system is addressed with the two algorithms in this article—one is for selecting the best locations of capacitor placement and candidate node identification algorithm; the second is for the sizing of capacitors, a variational technique algorithm according to available standard size of capacitors. The objective function used in this article is to maximize the net savings in the distribution system. This article presents the results of simulations for 25-bus and IEEE 37-bus unbalanced radial distribution systems.

Installation of capacitors in primary and secondary networks of distribution systems is one of the efficient methods for energy and peak load loss reduction. Also voltage profile in the feeder is improved and static voltage stability is enhanced. The main challenge is the determination of optimal location and size of fixed and switchable capacitors with respect to network configuration, distribution of load in the feeder, time variation of load and uncertainty in load forecasting or load allocation process. To solve this complex problem, an efficient method for simultaneous allocation of fixed and switchable capacitors in radial distribution systems is presented. Energy and peak load loss reduction, and capacitor cost are considered in the cost function. Time variation and uncertainty of load are also involved in problem formulation. Genetic algorithm with a new coding as two rows chromosomes is used for optimisation. Numerical studies show the effectiveness of the proposed procedure.