a b s t r a c tThe aim of this paper is to improve the reactive power compensation and active filtering capability of a Wind Energy Conversion System (WECS). The proposed algorithm is applied to a Doubly Fed Induction Generator (DFIG) with a stator directly connected to the grid and a rotor connected to the grid through a back-to-back AC-DC-AC PWM converter. The control strategy of the Rotor Side Converter (RSC) aims, at first, to extract a maximum of power under fluctuating wind speed. Then, depending on the rate power of the RSC, the power quality can be improved by compensating the reactive power and the grid harmonics current due to nonlinear loads. Hence, the RSC is controlled in order to manage the WECS function's priorities, between production of the maximum active power captured from the wind, and power quality improvement. The main goal of the proposed control strategy is to operate the RSC at its full capacity, without any over-rating, in terms of reactive power compensation and active filtering capability. Elsewhere, the Grid Side Converter (GSC) is controlled in such a way to guarantee a smooth DC voltage and ensure sinusoidal current in the grid side. Simulation results show that the wind turbine can operate at its optimum power point for a wide range of wind speed and power quality can be improved. It has been shown also that the proposed strategy allows an operating full capacity of the RSC in terms of reactive power compensation and active filtering.

No abstract

Abslracf -The aim of this paper is to present a novel design of a fuzzy-based self-tuning PI controller (FSTPIC) for speed regulation of an indirect field-oriented induction motor (IM). In this new approach, the fuzzy tuning of a conventionel PI controller gains is achieved through fuzzy rules deduced from many robustness simulation tests applied to several induction motors, for a variety of operating conditions such as response to step speed command from standstill, step load torque application and speed reversion, with nominal parameters and an ancreased and/or decreased rotor resistance, self inductance and inertia. Simulation results show that the proposed fuzzy self-tuning PI controller is better than the fixed gains one in terms of robustness and speed rise time, even under great variations of operating conditions and load disturbance.

Hybrid Renewable Energy Sources (HRES) integrated into a microgrid (MG) are a cost-effective and convenient solution to supply energy to off-grid and rural areas in developing countries. This research paper focuses on the optimization of an HRES connected to a stand-alone microgrid system consisting of photovoltaics (PV), wind turbines (WT), batteries (BT), diesel generators (DG), and inverters to meet the energy demand of fifteen residential housing units in the city of Djelfa, Algeria. In this context, the multiobjective salp swarm algorithm (MOSSA), which is among the latest nature-inspired metaheuristic algorithms recently introduced for hybrid microgrid system (HMS) optimization, has been proposed in this paper for solving the optimization of an isolated HRES. The proposed multiobjective optimization problem takes into account the cost of energy (COE) and loss of power supply probability (LPSP) as objective functions. The proposed approach is applied to determine three design variables, which are the nominal power of photovoltaic, the number of wind turbines, and the number of battery autonomy days considering higher reliability and minimum COE. In order to perform the optimum size of HMG, MOSSA is combined with a rule-based energy management strategy (EMS). The role of EMS is the coordination of the energy flow between different system components. The effectiveness of using MOSSA in addressing the optimization issue is investigated by comparing its performance with that of the multiobjective dragonfly algorithm (MODA), multiobjective grasshopper optimization algorithm (MOGOA), and multiobjective ant lion optimizer (MOALO). The MATLAB environment is used to simulate HMS. Simulation results confirm that MOSSA achieves the optimum system size as it contributed 0.255 USD/kW h of COE and LPSP of 27.079% compared to MODA, MOGOA, and MOALO. In addition, the optimization results obtained using the proposed method provided a set of design solutions for the HMS, which will help designers select the optimal solution for the HMS.

No abstract