Optimal capacitor allocations using evolutionary algorithms

Multi-objective Capacitor Allocations in Distribution Networks using Artificial Bee Colony Algorithm

“…The most likely buses for capacitor placements preidentified using both LSF 25, allows the proposed algorithm to select the optimal locations and amount of compensations required accordingly. The approach has selected 8 buses for OCA with the relevant amount of reactive compensation required per each location which is depicted in Table 7 for all the proposed load patterns / levels.…”

“…Many methods have been developed for reducing the network losses and improving the voltage profile in distribution systems: network reconfiguration and load balancing [4][5][6][7], high voltage distribution system [8], distributed generations [9][10][11][12] and shunt capacitor allocations [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31].…”

“…Recently and fortunately, many researchers have focused on various types of heuristic optimization techniques to solve the optimal capacitor allocation (OCA) problem such as heuristic strategies (HS) [13], genetic algorithms (GA) [14,15], tabu search [16], particle swarm optimization (PSO)-based algorithm [17], harmony search algorithm [18,19], an ant colony search [20,21], a fuzzy-GA [22], a bacterial foraging solution [23], an immune-based optimization technique [24], an integrated differential evolution and pattern search (DE-PS) [25], a big bang-big crunch optimization [26], plant growth simulation algorithm (PGSA) [27], an artificial bees colony (ABC)-based algorithm [28,29] and cuckoo-search algorithm (CSA) [30].…”

Novel Loss-Voltage Sensitivity Factor for Capacitor Placement in Radial Distribution System Using Analytical Approach

“…They are very effective and powerful in comparison with conventional methods in solving complex nonlinear constrained optimization problems. Authors [1], used Differential Evolution algorithm, Direct Search Algorithm [2], Artificial bee colony algorithm (ABC) [3], Flower Pollination Algorithm [4], Bacteria Foraging (BF) [5], Ant Colony Search Algorithm (ACO) [6], Cuckoo Search Algorithm (CSA) [7], Harmony Search (HS) [8], Plant Growth Simulation Algorithm (PGSA) [9], Teaching Learning Based Optimization (TLBO) [10], Firefly Algorithm (FA) [11], shark smell optimization algorithm [12], Particle Swarm Optimization (PSO) [13,14], Heuristic Algorithm [15], Fuzzy-GA method [16], Simulated Annealing (SA) [17], Genetic Algorithm (GA) [18], Nonlinear Programming [19]. Carpinelli et al [20] solved the problem of shunt capacitor placement and sizing by approximate power flow method.…”

A Novel Analytical Technique for Optimal Allocation of Capacitors in Radial Distribution Systems

“…The cost of real power losses and the cost of the capacitors were included in the objective function. Nonlinear programming [3], a genetic algorithm (GA) [4], simulated annealing (SA) [5], the cuckoo search algorithm [6], a heuristic algorithm [7], particle swarm optimization (PSO) [8][9], artificial bee colony (ABC) [10], the firefly algorithm (FA) [11], teaching-learning based optimization (TLBO) [12], the plant growth simulation algorithm (PGSA) [13], Harmony Search (HS) [14], the cuckoo search algorithm (CSA) [15], the ant colony search algorithm (ACO) [16], bacteria foraging (BF) [17], the flower pollination algorithm [18], the direct search algorithm [19], and the differential evolution algorithm [20] have been used to solve the optimal capacitor allocation problem. However, few authors have tested their algorithm on a real power distribution system.…”