Co-Optimization of Energy Losses and Transformer Operating Costs Based on Smart Charging Algorithm for Plug-in Electric Vehicle Parking Lots

The global transport sector has a significant share of greenhouse gas emissions. Thus, plug-in electric vehicles (PEVs) can play a vital role in the reduction of pollution. However, high penetration of PEVs can pose severe challenges to power systems, such as an increase in energy losses and a decrease in the transformers expected life. In this paper, a new day-ahead co-optimization algorithm is proposed to reduce the unwanted effects of PEVs on the power system. The aim of the proposed algorithm is minimizing the cost of energy losses as well as transformer operating cost by the management of active and reactive powers simultaneously. Moreover, the effect of harmonics, which are produced by the charger of PEVs, are considered in the proposed algorithm. Also, the transformer operating cost is obtained from a method that contains the purchase price, loading, and losses cost of the transformer. Another advantage of the proposed algorithm is that it can improve power quality parameters, e.g., voltage and power factor of the distribution network by managing the reactive power. Afterward, the proposed algorithm is applied to a real distribution network. The results show that the proposed algorithm optimizes the daily operating cost of the distribution network efficiently. Finally, the robustness of the proposed algorithm to the number and distribution of PEVs is verified by simulation results

A new DFT-based frequency estimation algorithm for protection devices under normal and fault conditions

Frequency is one of the essential parameters for monitoring, control, and protection in power systems. Some protection devices use frequency for deciding under various conditions of the power system. Therefore, it is important to estimate frequency rigorously and fast. In this paper, a DFT-based algorithm is introduced for frequency estimation in the presence of harmonics and decaying DC. Initially, According to the condition of the power system, the type of input signal (current or voltage) is determined. The current and voltage signals are the input to the proposed algorithm under fault and normal conditions, respectively. Based on the type of the input signal, the frequency estimation method (FEM) is selected and used. 2 FEMs are proposed to estimate the frequency based on solving a cubic equation. For both FEMs, an optimization-based filter is designed and applied to mitigate harmonics. The proposed algorithm is validated under various static and dynamic tests in MATLAB. The results show that the proposed algorithm is accurate and fast with a low computational burden