Browsing by Author "Saukhimov, Almaz"

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Energy Loss Minimization by Using Single-Phase Bank Capacitors: Case Study of Mangystau MV Network
(Institute of Electrical and Electronics Engineers Inc., 2025) Bektimirov, Anur; Baimakhanov, Olzhas; Ceylan, Oguzhan; Saukhimov, Almaz
Citation - WoS: 7
Citation - Scopus: 12
A Heuristic Methods-Based Power Distribution System Optimization Toolbox
(Mdpi, 2022) Ozlue, Ismail Alperen; Baimakhanov, Olzhas; Saukhimov, Almaz; Ceylan, Oguzhan; Özlü, İsmail Alperen
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.
Citation - WoS: 3
Citation - Scopus: 7
Heuristic Optimization Approaches for Capacitor Sizing and Placement: a Case Study in Kazakhstan
(Mdpi, 2022) Baimakhanov, Olzhas; Senyuz, Hande; Saukhimov, Almaz; Ceylan, Oguzhan
Two methods for estimating the near-optimal positions and sizes of capacitors in radial distribution networks are presented. The first model assumes fixed-size capacitors, while the second model assumes controllable variable-size capacitors by changing the tap positions. In the second model, we limit the number of changes in capacitor size. In both approaches, the models consider many load scenarios and aim to obtain better voltage profiles by minimizing voltage deviations and active power losses. We use two recently developed heuristic algorithms called Salp Swarm Optimization algorithm (SSA) and Dragonfly algorithm (DA) to solve the proposed optimization models. We performed numerical simulations using data by modifying an actual distribution network in Almaty, Kazakhstan. To mimic various load scenarios, we start with the baseline load values and produce random variations. For the first model, the optimization algorithms identify the near-optimal positioning and sizes of fixed-size capacitors. Since the second model assumes variable-size capacitors, the algorithms also decide the tap positions for this case. Comparative analysis of the heuristic algorithms shows that the DA and SSA algorithms give similar results in solving the two optimization models: the former gives a slightly better voltage profile and lower active power losses.