Power Loss Minimization and Voltage Stability Improvement in Electrical Distribution System via Network Reconfiguration and Distributed Generation Placement Using Novel Adaptive Shuffled Frogs Leaping Algorithm

Abstract

This paper proposes a novel adaptive optimization algorithm to solve the network reconfiguration and distributed generation (DG) placement problems with objective functions including power loss minimization and voltage stability index (VSI) improvement. The proposed technique called Adaptive Shuffled Frogs Leaping Algorithm (ASFLA) was performed for solving network reconfiguration and DG installation in IEEE 33-and 69-bus distribution systems with seven different scenarios. The performance of ASFLA was compared to that of other algorithms such as Fireworks Algorithm (FWA), Adaptive Cuckoo Search Algorithm (ACSA) and Shuffled Frogs Leaping Algorithm (SFLA). It was found that the power loss and VSI provided by ASFLA were better than those given by FWA, ACSA and SFLA in both 33-and 69-bus systems. The best solution of power loss reduction and VSI improvement of both 33-and 69-bus systems was achieved when the network reconfiguration with optimal sizing and the location DG were simultaneously implemented. From our analysis, it was indicated that the ASFLA could provide better solutions than other methods since the generating process, local and global searching of this algorithm were significantly improved from a conventional method. Hence, the ASFLA becomes another effective algorithm for solving network reconfiguration and DG placement problems in electrical distribution systems.

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“…This algorithm has advantage of combining the benefits of GA and PSO. SFLA are applied for finding optimal locations and sizes of DGs with minimisation of system loss and enhancement of voltage profile as the objective function . Taghikhani successfully applied SFLA to find optimal DG location and size in order to minimise line losses and improve system voltage profile…”

Optimal Estimation of Capacity and Location of Wind, Solar and Fuel Cell Sources in Distribution Systems Considering Load Changes by Lightning Search Algorithm

“…The ohmic losses of the lines can be calculated as equation (1). The loss function is the sum of the ohmic losses of all the lines [13][14]…”

“…In the above equation, Ri and Ii are the values of line resistance and current of the line i, respectively, N b is the number of lines in the feeder. The voltage deviation index is also calculated by equation (2) [13]. 24 Pr ofile t 1…”

“…Therefore, constraints should be considered to solve the optimization problem by algorithms. The most important limitations in locating and determining the capacity of DGs in the distribution feeder are[13]:The amount of active and reactive power produced and consumed should be equal after the installation of DGs in the feeder.…”

Reliability Enhancement and Loss Reduction in Radial Distribution System by Reconfiguration using BFA

“…In the literature, some researchers have considered reconfiguration and capacitor placement problems simultaneously. They have used methods such as branch exchange [7], ACSA [8], modified PSO [9 and 24], deterministic approach [10] etc to solve reconfiguration problem and methods like discrete optimization [11], harmony search algorithm [5], heuristic technique [12], Imperialist Competitive Algorithm [25] Adaptive Shuffled Frogs Leaping Algorithm [26] etc to determine the optimal location and amount of capacitances to be used.…”