Connecting different renewable energy sources (RESs) to the electrical grids is presently being urged to fulfill the enormous need for electric power and to decrease traditional sources' ecological related issues, the so-called hybrid systems. Unfortunately, these hybrid systems suffer from the possible negative environmental impacts of the wind gusts in wind energy conversion systems (WECSs) that may degrade the overall system performance. Additionally, various severe faults may disconnect some RESs from the hybrid system, like three-phase faults. In this paper, the static synchronous compensator (STATCOM) is considered for both improving the performance of a hybrid system, contains WECS and photovoltaics (PVs) against wind gusts and maintaining the continuous operations of RESs during three-phase fault occur at the point of common coupling (PCC) between the RESs and the grid. The STATCOM is stimulated by two PI controllers regulating the reactive power flow between the STATCOM and the hybrid system at PCC and, consequently, regulating the voltage at PCC. A metaheuristic optimizer optimally schedules these two PI controllers based on whale optimization algorithm
Optimal power flow (OPF) is one of the most significant electric power network control and management issues. Adding unreliable and intermittent renewable energy sources to the electrical grid increase and complicates the OPF issue, which calls for using modern optimization techniques to solve this issue. This work presents the optimal location and size of some FACTS devices in a hybrid power system containing stochastic wind and traditional thermal power plants considering OPF. The FACTS devices used are thyristor-controlled series compensator (TCSC), thyristor-controlled phase shifter (TCPS), and static var compensator (SVC). This optimal location and size of FACTS devices was determined by introducing a multi-objective function containing reserve costs for overestimation and penalty costs for underestimating intermittent renewable sources besides active power losses. The uncertainty in the wind power output is predicted using Weibull probability density functions. This multi-objective function is optimized using a hybrid technique, gradient-based optimizer (GBO), and moth–flame optimization algorithm (MFO).
Wind Turbine Generator (WTG) has become one of the most popular renewable-based power generation that is broadly connected to electricity grids worldwide. Till the year 2019, the total WTGs installed worldwide reached about 650.8GW. The WTG is interfaced to the electricity grid through power electronic converters with a proper control algorithm to facilitate a smooth power delivery as well as maintaining the system voltage and frequency stability during wind intermittency. However, power grids are usually subjected to load expansion which affects the stiffness of the grid and hence its stability. A weak electricity grid exhibits voltage instability that may affect the performance of WTGs and in some cases may lead to serious damages to the wind turbines and the entire system. In this paper, superconducting magnetic energy storage (SMES) technology based on fuzzy logic controller is implemented to effectively resolve this issue and improve the overall performance of WTGs. Hysteresis current and fuzzy logic-based control system is proposed to control the energy exchange between the SMES coil and the investigated system. Results show the effectiveness of the SMES to improve the overall system performance and along with the fault ridethrough capability of the doubly-fed induction generator (DFIG).INDEX TERMS DFIG, SMES, Low voltage ride through, Wind energy, Weak grid.
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