A Heuristic Methods-Based Power Distribution System Optimization Toolbox
Özlü İ.A. Baimakhanov O. Saukhimov A. Ceylan O.
January 2022MDPI
Algorithms
2022#15Issue 1
This paper proposes a toolbox for simulating the effective integration of renewable energy sources into distribution systems. The toolbox uses four heuristic methods: the particle swarm optimization (PSO) method, and three recently developed methods, namely Gray Wolf Optimization (GWO), Ant Lion Optimization (ALO), and Whale Optimization Algorithm (WOA), for the efficient operation of power distribution systems. The toolbox consists of two main functionalities. The first one allows the user to select the test system to be solved (33-, 69-, or 141-bus test systems), the locations of the distributed generators (DGs), and the voltage regulators. In addition, the user selects the daily active power output profiles of the DGs, and the tool solves the voltage deviation problem for the specified time of day. The second functionality involves the simulation of energy storage systems and provides the optimal daily power output of the resources. With this program, a graphical user interface (GUI) allows users to select the test system, the optimization method to be used, the number of DGs and locations, the locations and number of battery energy storage systems (BESSs), and the tap changer locations. With the simple user interface, the user can manage the distribution system simulation and see the results by making appropriate changes to the test systems.
Battery energy storage systems , Distributed generation , Distribution network , Optimization toolbox
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Management Information Systems Department, Kadir Has University, Istanbul, 34083, Turkey
Electrical Power Systems Department, Almaty University of Power Engineering & Telecommunications Named after G. Daukeyev, Almaty, 480013, Kazakhstan
Science & Innovations Department, Almaty University of Power Engineering & Telecommunications Named after G. Daukeyev, Almaty, 480013, Kazakhstan
Electrical and Electronics Engineering Department, Marmara University, Istanbul, 34854, Turkey
Management Information Systems Department
Electrical Power Systems Department
Science & Innovations Department
Electrical and Electronics Engineering Department
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