Capacitor placement by variables' inclusion and interchange improved algorithm

Abstract

Summary Very diverse optimization methods have been used to determining the optimal capacitor placement in distribution systems. Most of these methods analyze the use of fixed capacitor banks on circuits with only one load state. Other contributions consider the compensation with capacitors switched at different load levels. Almost all previous works represent the load as constant power with respect to voltage variations. This work improves the variables' inclusion and interchange algorithm with a new voltage‐dependent model that considers the variation of active and reactive load with the increase of voltage due to the capacitor placement. The load model used in this work can represent the load by a generalized function of the voltage, in which the constant power load, the constant current load, or the constant impedance load are particular cases. This voltage‐dependent model is the fundamental novelty of the method. The presented algorithm maximizes the annual cost saving in a circuit with several load levels by determining the locations, sizes, and control in time of the needed fixed and switched capacitors. The optimization is constrained with the bounds of minimum and maximum voltages. The capacitor placement solutions proposed by the developed method for various examples of four known circuits are compared with several of the most recently published solutions for these examples. The comparison shows the effectiveness of this method. The solutions obtained for different models of loads show the importance of considering, in the optimization, the load dependence with voltage.

Active Power Loss Reduction for Radial Distribution Systems by Placing Capacitors and PV Systems with Geography Location Constraints

“…Deterministic methods Two-step method [11], 1999 Two-step method [12], 2008 Two-step method [13], 2013 Two-step method [14], 2015 MINPA [21], 2014 CPA [22], 2015 PLSF-AA [31], 2019 NFBHA [32] [23], 2014 BFOA [24], 2014 GSA [25], 2015 FPA [26], 2016 FPA [27], 2018 CSA [28], 2018 IMDE [29], 2016 MSA [30], 2018 IIA [33] In this paper, Stochastic Fractal Search Optimization Algorithm (SFSOA) [34] is proposed to solve the optimal location and size of capacitors in radial distribution networks. This method is a powerful meta-heuristic algorithm in terms of the accuracy of optimal values because it updates new solutions three times at each search iteration.…”

“…In recent years, many different algorithms have been applied for this consideration problem, including Mixed Integer Nonlinear Programming Algorithm (MINPA) [21], Combined Practical Algorithm (CPA) [22], Teaching-Learning Algorithm (TLA) [23], Bacterial Foraging Optimization Algorithm (BFOA) [24], Gravitational Search Algorithm (GSA) [25], Flower Pollination Algorithm (FPA) [26,27], Cuckoo Search Algorithm (CSA) [28], Intersect Mutation Differential Evolution (IMDE) [29], Moth Swarm Algorithm (MSA) [30], Power Loss Sensitivity Factor Based Analytical Approach (PLSF-AA) [31], Network Feature Based Heuristic Algorithm (NFBHA) [32] and Interchange Improved Algorithm (IIA) [33]. Among these methods, those that are not based-metaheuristic algorithms need the configuration features to select capacitor locations and compute the reactive power capacities.…”

“…Among these methods, those that are not based-metaheuristic algorithms need the configuration features to select capacitor locations and compute the reactive power capacities. Such methods include MINPA [21], CPA [22], PLSF-AA [31], NFBHA) [32] and IIA [33], but they are not capable of applying to all power systems, especially for complex systems with a high number of nodes and radial branches. In [21], the problem of capacitor placement in radial distribution networks was formulated as a nonlinear program and solved by a General Algebraic Modeling System (GAMS) software.…”

Loss cost reduction and power quality improvement with applying robust optimization algorithm for optimum energy storage system placement and capacitor bank allocation

“…Where (15) describes the limitation of reactive power injection by capacitor bank. The capacity of ESS is determined between maximum and minimum of that in (16).…”

A clustering‐based technoeconomic analysis for wind farm and shunt capacitor allocation in radial distribution systems

“…In that study, the optimization process is carried out by using a crow search algorithm. In Reference 21, the SCs' allocation problem in distribution networks is performed by using a variables' inclusion and interchange algorithm. The maximation of the annual cost's saving is the main objective behind the developed optimization problem.…”