OPTIMAL CAPACITOR PLACEMENT, considering power system loss reduction, voltage profile improvement, line reactive power decrease and power factor correction, is of particular importance in power system planning and control. The distribution system operator calculates the OPTIMAL place, number and capacity of CAPACITORs based on two major purposes: active power loss reduction and return on investment maximization. In this paper, the optimization problem of various values of economic amount of reactive power is formulated, then after evaluation of objective function and implementation of optimization algorithm for each value, the optimum capacity of CAPACITORs and their arrangement in load nodes of power system are extracted. Also, using the proposed objective function, the threshold price of reactive power selling can be calculated, thus the investment of CAPACITOR installation will be beneficial for distribution system operator.

An iterative nonlinear algorithm is generated for OPTIMAL sizing and PLACEMENT of fixed and switched CAPACITOR banks on radial distribution lines in the presence of linear and nonlinear loads. The HARMFLOW algorithm and the Maximum Sensitivities Selection (MSS) method are used to solve the constrained optimization problem with discrete variables. To limit the burden of calculations and improve convergence, the problem is decomposed into two sub problems. Objective functions include minimum system losses and CAPACITOR cost while IEEE519 power quality limits are used as constraints. Results are presented and analyzed for the 18 bus IEEE distorted system. The advantage of the proposed algorithm compared to the previous work is the consideration of harmonic couplings and reactions of actual nonlinear loads of the distribution system.

The steady increase in energy demand results in under-voltage problems and an increase in the active power losses in electrical distribution networks. The OPTIMAL PLACEMENT of CAPACITOR banks in distribution systems is essential for enhancing the voltage profile and reducing power losses. This paper proposes a modified particle swarm optimization (PSO) algorithm using an adaptive inertia constant to expand the search space and determine the OPTIMAL locations and sizes of CAPACITOR banks. Two loss sensitivity indices (LSI) were applied to identify candidate buses. This methodology was applied to the IEEE 33-bus radial distribution system considering two scenarios: one with fixed CAPACITORs (Case 1) and the other with switched CAPACITORs (Case 2). The results demonstrate that the proposed algorithm effectively reduces system losses by 31.30% and 31.38% in Cases 1 and 2, respectively. In addition, in both cases, the voltage profiles were improved and maintained within allowable limits. Therefore, the proposed methodology is expected to work well in larger electrical distribution networks.

Meta-heuristics optimization methods are important techniques for OPTIMAL design of the engineering systems. Numerous Meta-heuristics methods, all inspired by different nature phenomena, have been introduced in the literature. A new modified version of Teaching-Learning-Based Optimization (TLBO) Algorithm is introduced in this paper. TLBO, as a parameter-free algorithm, is based on the learning procedure of students in a classroom. In the Conventional TLBO (CTLBO), the students enhance their grade in two phases known as teacher phase and student phase. In the former, the teacher tries to enhance the average of the class. In the latter, the students share their knowledge in the groups of two. In the proposed Modified TLBO (MTLBO), the students participate in the groups of several students and improve their knowledge based on the grade of these students. Participating in the meeting with more than two students increases the probability of enhancing the student marks. To testify the performance of the proposed algorithm, it is applied to the problem of OPTIMAL CAPACITOR PLACEMENT with the aim of annual net saving maximization and system stability enhancement. The test systems are 34-bus and 94-bus radial test systems. The comparison of the results with those from off-the-shelf algorithms clears the appropriate performance, fast convergence, and superiority of the proposed algorithm.

This paper describes an advantageous method for using the CAPACITOR banks in the distribution network, OPTIMALly. The aim is to determine the count, location and CAPACITOR values in order to minimize the annual cost resulting from energy losses and CAPACITOR bank’s installation cost. Besides, in the case of having nonlinear loads in the network, by installing CAPACITORs in appropriate locations, the possibility of occurring a resonance at harmonic frequencies originating from nonlinear loads, could be reduced. Therefore, in CAPACITOR PLACEMENT, power quality constraints, including the maximum harmonic deviation value, are taken into account. The case study is a nonlinear problem that a new algorithm based on the gravitational OPTIMAL detector and fuzzy system has been used to solve it. In comparison with other intelligent search methods, the proposed algorithm has appropriate precision and convergence rate. The proposed method has been performed on a 69-buss network and a part of the distribution network of city YAZD, and the results confirmed the performance and efficiency of the proposed algorithm.