Optimal determination of island boundaries besides the optimal placement of D-STATCOM devices and DG units

Abstract

Abstract:In this study, integration of three important concepts of distributed generation, D-FACTS devices, and microgrids are evaluated. The performance of a microgrid is dependent on its location, capacity, and placement of DG units and D-FACTS devices. In this paper a new method is proposed to simultaneously determine the optimal number, location, and capacity of DG units and D-STATCOM devices and optimal boundaries of electrical islands in the independent mode of microgrids. The main objective is to minimize the economic costs. The optimal locations of DG units and D-STATCOM devices should be determined to maximize the DG capacities with minimum loss in the best voltage profile and in the grid-connected mode of microgrids. Moreover, this locating besides simultaneous determination of island boundaries makes it possible to supply the maximum load in the islanded mode operation. To meet the mentioned goals, the PSO algorithm and MATLAB software are used. Analyzing the obtained results shows that the proposed method has suitable capability in optimal operation and cost management of distribution network planning.

Optimizing the hybrid PVDG and DSTATCOM integration in electrical distribution systems based on a modified homonuclear molecules optimization algorithm

“…These algorithms include applying the Cuckoo Search Algorithm (CSA) to minimize active power loss [3], using Particle Swarm Optimization (PSO) to optimize the function of operating and losses cost while integrating the DG and DSTATCOM units [4], utilizing Adaptive PSO (APSO) to minimize the power loss index while considering the load ratio for different time intervals in Northern Cyprus power feeders [5], using the Grey Wolf Optimizer (GWO) algorithm to minimize power losses at different load levels [6], applying the Improved Crow Search Algorithm (ICSA) to enhance bus voltage, minimize line losses, increase economic benefits, and mitigate emissions [7], using the Arithmetic Optimization Algorithm (AOA) to optimize a multi‐objective functions that includes the Active Power Loss (APL), the Voltage Stability Index (VSI), the Fast Voltage Stability Index (FVSI), the Line Stability Factor (LPQ), and the Power‐Voltage Stability Index (PVSI) [8], applying the Ant Lion optimization (ALO) algorithm to optimize active/reactive power losses and a new voltage stability index [9], utilizing Modified PSO algorithms to maximize the active power loss level (APLL) in the electrical distribution system [10], using the Whale Optimization Algorithm (WOA) to optimize active/reactive power losses in the Iranian distribution system [11], using the Fuzzy‐Lightning Search Algorithm (FLSA) to reduce power loss by solving the optimal placement problem of PVDG and DSTATCOM devices in the distribution system [12], and applying the Bat Algorithm (BA) to improve the voltage stability index with a variation of load levels [13].…”

Simultaneous allocation of photovoltaic DG and DSTATCOM for techno‐economic and environmental benefits in electrical distribution systems at different loading conditions using novel hybrid optimization algorithms

“…In 2016, applied Bacterial Foraging Optimization Algorithm (BFOA) to minimize the APL, voltage profile index and operational cost, 8 and hybrid Fuzzy and Expanded Invasive Weed Optimization (Fuzzy‐ExIWO) algorithm with the optimal tuning of nonlinear PID controller for the DSTATCOM 9 . In 2017, applied Cuckoo Search Algorithm (CSA) for minimizing the APL, 10 Lightning Search Algorithm (LSA) to multi‐objective optimization based on APL ratio, the Total Voltage Deviation (TVV), and the Voltage Stability Index (VSI) with considering the load variation, 11 Particle Swarm Optimization (PSO) algorithm to determine the optimal any number of various DG units and DSTATCOMs based operation and losses costs, 12 and Maximum voltage stability margin by Honey Bees Mating Optimization (HBMO) algorithm 13 …”