Browsing by Author "Ozdemir, A."

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Advanced Restoration Management Strategies in Smart Grids: the Role of Distributed Energy Resources and Load Priorities
(Elsevier Ltd, 2025) Ahmadi, B.; Ceylan, O.; Ozdemir, A.
Fast restoration following long outages is a challenge in the smart city management process. It is necessary to accurately characterize the real operating conditions of the system for optimal restoration. This study focuses on two key factors of a practical distribution system restoration. The first factor is cold load pickup (CLPU), which commonly occurs after an outage and is caused by thermostatically controlled loads. A time-dependent CLPU is modeled to accurately describe the restored load behaviors. The second factor is the effect of the distributed generators (DG), energy storage systems (ESSs), and load priority factors on the system's restoration process. To address this challenge, a robust optimization model is proposed that fully considers the effect of DG, and ESS units and uncertainty of CLPU. The proposed models are tested on the IEEE 33-node and 69-node test systems using the Advanced Grey Wolf Algorithm (AGWO). The simulation scenarios are designed to uncover optimal scheduling strategies for the restoration process corresponding to each Pareto solution of a previous study. The results are discussed for several distinct initial conditions. Moreover, a comparative evaluation is done, contrasting the outcomes achieved through the AGWO algorithm with those stemming from alternative heuristic methods. © 2025 The Authors
Citation - Scopus: 2
Energy Loss Minimization with Parallel Implementation of Marine Predators Algorithm
(Institute of Electrical and Electronics Engineers Inc., 2021) Ceylan, Oğuzhan; Ahmadi, B.; Ceylan, O.; Ozdemir, A.
Distribution network (DN) service continuity is one of the significant issues in today's power systems. This paper aims to put a strategy for supplying loads with less discontinuity and affordable energy-consuming. The energy loss in distribution grids causes many problems for the producer and consumer; hence, it needs to be improved to increase supply efficiency accordingly. For this aim a model aiming to minimize power losses by allocating and sizing distributed generators (DGs) is solved using recently developed Marine Predators Algorithm (MPA). Since the proposed method is a time-intensive process due to the vast computations, parallel computation is implemented into MPA to increase computation speed. The proposed formulation and parallel computation are tested for 69-bus radial distribution system. The results are discussed in terms of computational accuracy and solution efficiency. Moreover, the convergence characteristics of MPA are compared with some other heuristic methods. © 2021 Chamber of Turkish Electrical Engineers.
Probabilistic Assessment of Vehicle-To Power of Electric Vehicle Parking Lots: a New Comprehensive Approach
(Institute of Electrical and Electronics Engineers Inc., 2025) Tourandaz Kenari, M.; Ozdemir, A.
The increasing market share and parking occupancy of electric vehicles have increased the charging stations in parking lots (PLs) and motivated the research to provide proper management strategies. Although there have been several efforts to assess, schedule, and model the load of fast electric vehicle charging stations (FEVCSs), they are inappropriate for charging stations in EVPLs. This paper proposes a novel comprehensive probabilistic approach to calculate the parking lot power and energy for battery and hybrid electric vehicles. At first, a decision is made for the operation mode of an EV arriving at the PL, using an algorithm considering ten affective random variables. Then, the aggregated parking lot power and energy are determined using Monte Carlo simulations. Finally, the Gaussian Mixture Model is used to estimate the parameters of the output probability density functions, where the maximum likelihood estimation is employed to find model components. The proposed approach is applied to a sample parking lot, and its performance is demonstrated by comparing it to a base case study and one of the pioneering techniques introduced in the literature. Finally, a thorough sensitivity analysis is applied to assess the robustness of the outputs under different scenarios. The results demonstrate the superiority of the proposed method compared to the available studies. © 1967-2012 IEEE.