This article describes how a field oriented control can provide the same performance as it is achieved by a DC motor. However, this technique requires a mechanic sensor and is very sensitive to the variation of motor parameters which results in an undesirable coupling between the flux and the torque. To solve these problems, this paper proposes a global stability and robust nonlinear controller, applied to induction motor (IM), in order to achieve an exact decoupling between speed and flux for all motor operating conditions. The induction motor is coupled with a centrifugal hydraulic pump, powered by a photovoltaic array speeding system. The proposed system is designed for usage in rural areas or remote electricity needs in absence of the grid network. A nonlinear controller adjusts the motor speed reference to attain the maximum power point (MPPT). In presence of rotor and stator resistances and irradiation disturbance the results obtained by simulations confirm the effectiveness of the proposed method.

With a growing demand for more energy from subscribers, a traditional electric grid is unable to meet new challenges, in the remote areas remains the extension of the conventional electric network very hard to do make prohibitively expensive. Therefore, a new advanced generation of traditional electrical is inevitable and indispensable to move toward an efficient, economical, green, clean and self-correcting power system. The most well-known term used to define this next generation power system is Micro Grid (MG) based on renewable energy sources (RES). Since, the energy produced by RES are not constant at all times, a wide range of energy control techniques must be involved to provide a reliable power to consumers. To solve this problem in this paper we present a Fuzzy Logic Control of isolated Hybrid Systems (HRES) Including Renewable Energy in Micro-Grids to maintain a stability in voltage and frequency output especially in the standalone application. The considered HRES combine a wind turbine (WT) and photovoltaic (PV) panels as primary energy sources and an energy storage system (ESS) based on battery as a backup solution. Simulation results obtained from MATLAB/Simulink environment demonstrate the effectiveness of the proposed algorithm in decreasing the electricity bill of customer.

In this paper, a novel direct torque neuro-fuzzy control (DTCNF) scheme combining with space voltage modulation (SVM) technique of a three levels inverter is presented. Using neuro-fuzzy technique, the reference space voltage vector can be obtained dynamically in terms of torque error, stator flux error and the angle of stator flux. Compared with conventional direct torque control (C_DTC), in this new technique, the ripples of both torque and flux are reduced remarkable, and switching frequency is maintained constant. Simulation results verify the validity of the proposed method.

Due to the absence of energy transmission lines connected to the water pumping sites in remote areas, problems related to the electrical power outages and the environmental degradation caused by fossil fuel. For this one of the most conceived solutions is the photovoltaic water pumping technology which has the advantage of being sustainable and respectful of the environment to supply water to rural areas. To ensure the need of water, especially for domestic use and small communities, in this article, the photovoltaic energy system for autonomous water pumping using the induction motor was presented, particularly adapted to the isolated regions. Pumping system consists of four photovoltaic (PV) panels, boost converter, inverter, induction motor, centrifugal pump and a storage tank. In this study, the output power of a PV solar cell is fully used by proposing the P&O algorithm, where it is used to follow a maximum power point tracking (MPPT) technique. The recommended system is designed, modeled and simulated on the MATLAB/Simulink platform. The efficiency of the proposed algorithm is observed with variable solar sunshine.

The development of renewable energy contributes to the global objectives of reducing our greenhouse gas emissions, obtaining and increasing our energy efficiency. In the face of these changes, the electric-network must adapt, while maintaining a high level of reliability and a quality of energy production. To meet this objective, it is recommended to use highly developed electrical network by integrating renewable energy sources in order to adapt the energy consumption to their production, using electro-technical software information and telecommunications technologies. We are talking about intelligent grids (Smart Grid). The main objective of the work presented in this paper is the contribution to the study of intelligent network for efficient management of energy produced by several sources linked to the AC bus via the voltage inverters. Numerical simulations have been presented to validate the performance of the proposed active and reactive power controller (Droop Control).

This paper present a new advanced control algorithm based on continuous minimization of predicted tracking errors, to achieve torque, rotor speed and rotor flux amplitude tracking objectives. This algorithm called a new Adaptive Nonlinear Predictive Control to induction motor drive uses a combination of the adaptive observer for rotor flux and Cascaded Nonlinear Predictive Control technique. The variables to be controlled are the rotor speed and the rotor flux norm, required to implement the predictive control algorithm is estimated by flux observer. The parameters identified adaptively are stator and rotor resistance which vary with motor temperature using the adaptive rotor flux observer. A stability of the proposed adaptive flux observer will be proved by the Lyapunov's theorem. Simulations are carried out in order to show the effectiveness of the drive and the robustness to parameters variations.

It is now more then a choice to use small-distributed generators (DGs) based on renewable energy resources (RES) due to their benefits in minimizing environmental problems and simplifying power system planning and operation. The integration of DGs in the main grid or in forming a standalone microgrid (MG) is increasing day by day and became as an alternative solution to large conventional central power stations and as a key for the electrification of rural areas. This paper presents an overall comparison of controlling the MG system combining between different DGs in islanded mode. Energy management system (EMS) applied is mainly an essential task to maintain an ideal flow of energy in between generation and consumption, many are strategies to do so, the artificial intelligence (AI) (highlighted) is one of the most advantages methods to help sizing, optimizing, and power energy managing. To solve this problem in this paper we present a Fuzzy Logic Control of isolated MG in comparison with a classic PI control system to see the different influences in maintaining stability in voltage and frequency output especially in the standalone application. The considered HRES combines a wind turbine (WT) and photovoltaic (PV) and an energy storage system (ESS). Simulation results obtained from MATLAB/Simulink environment demonstrates the effectiveness of the proposed intelligent artificial algorithm.

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