Enhancement Fault Ride-Through Capability of DFIG by Using Resistive and Inductive SFCLs

Abstract: The number of wind turbines connected to the grid is steadily increasing in recent years. This situation forced the revision of the electric utilities grid codes requirements, to remain connected during grid faults, i.e. to ride through the faults, especially for those with power electronic converters, such as DFIGs. In fault condition, the voltage at the Point of Common Coupling (PCC) drops immediately and The grid voltage dips imposed at the connection point of the DFIG to the grid induce large voltages in the rotor windings, resulting in high rotor current, which can damage the rotor-side converter and disconnect from grid. In this paper, resistive and inductive superconducting fault current limiter (SFCL) is used to improve the fault ride-through (FRT) of wind turbine generation system (WTGS). The WTGS is considered as a variable-speed system, equipped with a DFIG. The analytical and simulation studies of the resistive SFCL for improving FRT capability are presented and compared with the inductive SFCL. Key words: SFCL FRT Variable Speed Wind Turbine (VSWT) DFIG INTRODUCTION Fixed speed wind turbine (FSWT), Due to growing environmental concerns and demand induction generator (DFIG) for electricity, the capacity of electricity generation from VSWT based on permanent magnet synchronous renewable energy generation system (REGS) has generator (PMSG

Stochastic Security-constrained Unit Commitment Considering Electric Vehicles, Energy Storage Systems, and Flexible Loads with Renewable Energy Resources

In this paper, a new formulation for modeling the problem of stochastic security-constrained unit commitment along with optimal charging and discharging of large-scale electric vehicles, energy storage systems, and flexible loads with renewable energy resources is presented. The uncertainty of renewable energy resources is considered as a scenario-based model. In this paper, a multi-objective function which considers the reduction of operation cost, no-load and startup/shutdown costs, unserved load cost, load shifting, carbon emission, optimal charging and discharging of energy storage systems, and power curtailment of renewable energy resources is considered. The proposed formulation is a mixed-integer linear programming (MILP) model, of which the optimal global solution is guaranteed by commercial solvers. To validate the proposed formulation, several cases and networks are considered for analysis, and the results demonstrate the efficiency

Analysis and Designing of a Wireless Charging System for Electric Vehicles Using the Topology of Double Sided llC Compensator

The purpose of the present study is to simulate the equivalent circuit in the MATLAB software in order to implement the desired relationships for both continuous-conduction mode (CCM) and discontinuous-conduction mode (DCM) , and to obtain power and efficiency values at different frequencies. Then it is necessary to optimize the effective values on the power by Particle Swarm Optimization (PSO) algorithm. After optimization, the optimization and pre-optimization results should be compared and, if post-optimization results are not desirable, effective parameters should be reviewed before the optimization stage and the tunable parameters should be changed to achieve the desired results. This process will continue to obtain optimization results. The results show that the highest efficiency is 98% in DCM mode and is 95% in CCM mode. In both methods, we have achieved more favorable results than the baseline using the PSO method. However, DCM mode provides an improvement about 2.6% higher than CCM

Optimal Operation of Microgrids With Worst-Case Renewable Energy Outage: A Mixed-Integer Bi-Level Model

With the increasing penetration of renewable energy resources, such as wind and photovoltaic (PV) production, in future microgrids, challenges arise due to the potential interruption of these resources caused by changing weather conditions. In this paper, we propose a mixed-integer quadratic programming (MIQP) based bi-level model for the optimal operation of microgrids under worst-case (WC) scenarios of renewable energy resource outages. The upper-level problem formulates the minimization of energy loss and load shedding in a demand-side management (DSM) program, as well as optimal charging and discharging of electric vehicles (EVs) and energy storage systems (ESSs). The lower-level problem models the maximization of renewable energy curtailment to account for the worst-case realization of renewable resource outages. A decomposition and re-formulation method is adopted to solve the proposed bi-level optimization model, which includes binary variables in both levels. The proposed model and algorithm are implemented in the Julia programming language and solved with the Gurobi commercial solver. The model is analyzed using a 33-node microgrid under different cases to evaluate its performance, showcasing optimal microgrid operation results under worst-case renewable resource interruptions

A New Method for an Electric Vehicle Wireless Charging System Using LCC

Nowadays, there is a need for charging electric vehicles (EVs) wirelessly, since it provides a more convenient, reliable, and safer charging option for the EV customers. A wireless charging system using a double-sided LCC compensation topology is proven to be highly efficient; however, the large volume induced by the compensation coils is a drawback. Endocrine links are more useful in transmitting power wirelessly than other links. These links are used in the transmission of low and medium power. In this paper, by analyzing the equivalent circuit of a WPT power transmission system, the optimal value of the inductance was formulated to increase the yield. This can have other applications. In order to neutralize the reactive losses, the series resonance is used in both in primary and secondary sections, among which the lower quantities of series inductors were selected from the initial values to increase the efficiency and power. Furthermore, it is possible to optimize these values using suitable optimization methods. In this study, the PSO algorithm was used for this purpose

Smart distribution grid management during a worst-case scenario of renewable energy outage

Nowadays, due to the high penetration of renewable energy sources such as wind generation and PV in the distribution network and the possibility of their outage, the optimal operation of the distribution grid has faced challenges. In this paper, a bi-level model based on mixed integer quadratic programming (MIQP) is proposed for the optimal operation of smart distribution networks under the worst case of the outage of renewable energy resources. At the upper-level problem, minimization of the energy losses, energy purchase, and load shedding in the demand side management program is formulated, and at the lower-level problem, the maximization of output and curtailment of renewable energy resources is modeled. At the lower level, the worst-case realization of the renewable outage is derived and at the upper level, optimal operation of the distribution network is done under the worst-case realization of renewable resources. The reformulation method based on Karush–Kuhn–Tucker (KKT) conditions is considered to solve the proposed bi-level model, which is faster and less complicated than similar algorithms. The IEEE 33-bus distribution grid is considered for the analysis of the proposed model and method, which proves the accuracy and optimal performance of the proposed model and method. The findings indicate that, with the implementation of the suggested model, the smart distribution network successfully avoided load-shedding even when various renewable resources were disconnected. Also, the proposed model in operation under normal conditions has caused a 56% reduction in losses and a 53% reduction in energy purchases compared to the outage of 6 renewable units in the distribution network