Browsing by Author "Kenari, Meghdad Tourandaz"

Now showing 1 - 3 of 3

Probabilistic Approach To Assess and Minimize the Voltage Violation Risk in Active Distribution Networks
(Ieee, 2024) Kenari, Meghdad Tourandaz; Ozdemir, Aydogan; Heidari, Alireza
The increasing trend in using renewable energy resources in distribution systems has encouraged system operators to find the best methods to decrease the growing uncertainty's impact on system operation. A probabilistic approach based on the combination of Monte Carlo simulation and Particle Swarm Algorithm is proposed in this paper to reduce the risk of voltage magnitude violations. Also, a novel criterion is used to assess the risk of voltage magnitude violations in distribution system operation. This index is based on providing voltage samples using a probabilistic approach. Therefore, enhancing the confidence level of voltage risk is considered an objective function in finding the optimum location of energy storage systems. The proposed approach is applied to the IEEE 33-bus test system, and the results show that two ESS units installed at appropriate locations can solve all the voltage magnitude violation problems.
Citation - Scopus: 1
Probabilistic Assessment of Vehicle-to-Grid Power of Electric Vehicle Parking Lots: A New Comprehensive Approach
(IEEE-INST Electrical Electronics Engineers INC, 2025) Kenari, Meghdad Tourandaz; Ozdemir, Aydogan
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 influential 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.
Citation - WoS: 2
Citation - Scopus: 2
Simultaneous Impacts of Correlated Photovoltaic Systems and Fast Electric Vehicle Charging Stations on the Operation of Active Distribution Grids
(Elsevier, 2024) Kenari, Meghdad Tourandaz; Ozdemir, Aydogan
This paper presents two novel probabilistic models developed to account for the uncertainties of aggregated fast electric vehicle charging stations (FEVCSs) demand and correlated photovoltaic (PV) injections in active distribution network (ADN) analysis. Both models are more precise than the available ones. A probabilistic model based on the Beta distribution is used for solar radiance, while the shared random variables technique is proposed considering correlated solar radiation random variables. Furthermore, a probabilistic negative exponential load model is extended for modeling the FEVCSs based on the Weibull probability density function. Moreover, the proposed probabilistic load flow (PLF) model is solved using the combined cumulants and saddle-point approximation method. Numerical tests are provided and discussed by applying the IEEE 69-bus distribution system for different PV correlation coefficients and FEVCS load models. The results demonstrate how the uncertainty of PLF outputs is increased by integrating FEVCSs and correlated PV resources into the distribution network. In addition, simulation results validate that the cumulants-based methodology provides satisfactory accuracy with a low computational cost.