Optimal Placement of DG and Capacitor in Radial Distribution Systems Considering Load Variation

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.…”

“…These methods were run by setting population to 50 and the number of iterations to 100 excluding CSA without showing the number of iterations. The comparison between the Two-step method [13] and PLSF-AA [31] were not accomplished because these methods are not metaheuristic algorithms but are instead based on configuration of networks. In summary, SFSOA was more powerful than other ones in the case of three capacitors in terms of finding less power loss, using a smaller population and using a smaller number of iterations.…”

“…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.…”

“…However, its effectiveness is not persuasively demonstrated due to the lack of comparisons. Similarly, PLSF-AA [31] has used a power loss sensitivity factor to select the location of capacitors and reactive power flow in each branch to determine the capacity of reactive power sources at compensated nodes. In this group, implementing of methods is closely dependent on the configuration of consideration systems and becomes ineffective for a power system with more complex configuration.…”