Band 17, Heft 5 - Special Issue: Renewable Energy Systems, Guest Editors: Mohamed Becherif, Paul Lefley, Olivier Bethoux, Haitham Saad Mohamed Ramadan

This paper presents a robust controller for a variable speed wind turbine with a squirrel cage induction generator (SCIG). For variable speed wind energy conversion system, the maximum power point tracking (MPPT) is a very important requirement in order to maximize the efficiency. The system is nonlinear with parametric uncertainty and subject to large disturbances. A Takagi-Sugeno (TS) fuzzy logic is used to model the system dynamics. Based on the TS fuzzy model, a controller is developed for MPPT in the presence of disturbances and parametric uncertainties. The proposed technique ensures that the maximum power point (MPP) is determined, the generator speed is controlled and the closed loop system is stable. Robustness of the controller is tested via the variation of model’s parameters. Simulation studies clearly indicate the robustness and efficiency of the proposed control scheme compared to other techniques.

The design of power system stabilizer (PSS) is load-dependent and needs continuous adjustment at each operating condition. This paper aims at introducing a robust non-fragile PSS for interconnected power systems. The proposed controller has the capability of adaptively tuning online its rule-base through a variable-structure direct adaptive control algorithm in order to rigorously attain the desired objectives. The PSS controller acts on damping the electromechanical modes of oscillations not only through a wide range of operating conditions but also in presence of different disturbances. Using MATLAB TM -Simulink, simulation results significantly verify that the proposed controller provides favorable performance and efficiently contributes towards enhancing the system dynamic behavior when applied to the four machines two-area power system that mimics the typical system behavior in actual operation. The interaction between the variable-structure adaptive fuzzy-based power system stabilizer (VS-AFPSS) and the existed typical ones inside the interconnected power systems has been explicitly discussed. Compared to other conventional controllers, VS-AFPSS enables better damping characteristics to both local and inter-area oscillation modes considering different operating conditions and sever disturbances.

Integrating photovoltaic (PV) plants into electric power system exhibits challenges to power system dynamic performance. These challenges stem primarily from the natural characteristics of PV plants, which differ in some respects from the conventional plants. The most significant challenge is how to extract and regulate the maximum power from the sun. This paper presents the optimal design for the most commonly used Maximum Power Point Tracking (MPPT) techniques based on Proportional Integral tuned by Particle Swarm Optimization (PI-PSO). These suggested techniques are, (1) the incremental conductance, (2) perturb and observe, (3) fractional short circuit current and (4) fractional open circuit voltage techniques. This research work provides a comprehensive comparative study with the energy availability ratio from photovoltaic panels. The simulation results proved that the proposed controllers have an impressive tracking response. The system dynamic performance improved greatly using the proposed controllers.

The aim of this paper is to present a feasibility study of a grid connected photovoltaic (PV) and biomass Integrated renewable energy (IRE) system providing electricity to rural areas in the Beni Suef governorate, Egypt. The system load of the village is analyzed through the environmental and economic aspects. The model has been designed to provide an optimal system configuration based on daily data for energy availability and demands. A case study area, Monshaet Taher village (29° 1′ 17.0718”N, 30° 52′ 17.04”E) is identified for economic feasibility in this paper. HOMER optimization model plan imputed from total daily load demand, 2,340 kWh/day for current energy consuming of 223 households with Annual Average Insolation Incident on a Horizontal Surface of 5.79 (kWh/m 2 /day) and average biomass supplying 25 tons / day. It is found that a grid connected PV-biomass IRE system is an effective way of emissions reduction and it does not increase the investment of the energy system.

The power generated by solar photovoltaic (PV) module depends on the surrounding irradiance and temperature. This paper presents a hybrid Matlab™/Pspice™ simulation model of PV system, combined with Cadence software SLPS. The hybridization is performed in order to gain the advantages of both simulation tools such as accuracy and efficiency in both Pspice electronic circuit and Matlab™ mathematical modelling respectively. For this purpose, the PV panel and the boost converter are developed using Pspice™ and hybridized with the mathematical Matlab™ model of maximum power point method controller (MPPT) through SLPS. The main objective is verify the significance of using the proposed hybrid simulation techniques in comparing the different MPPT algorithms such as the perturbation and observation (P&O), incremental of conductance (Inc-Cond) and counter reaction voltage using pilot cell (Pilot-Cell). Various simulations are performed under different atmospheric conditions in order to evaluate the dynamic behaviour for the system under study in terms of stability, efficiency and rapidity.

In this paper Static Synchronous Compensator (STATCOM) is used for improving the performance of the power grid with wind turbine that drives synchronous generator. The main feature of the STATCOM is that it has the ability to absorb or inject rapidly reactive power to grid. Therefore the voltage regulation of the power grid with STATCOM device is achieved. STATCOM also improves the stability of the power system after occurring severe disturbance such as faults, or suddenly step change in wind speed. The proposed STATCOM controller is a Proportional-Integral (PI) controller tuned by Genetic Algorithm (GA). An experimental model was built in Helwan University to the proposed system. The system is tested at different operating conditions. The experimental results prove the effectiveness of the proposed STATCOM controller in damping the power system oscillations and restoring the power system voltage and stability.

Maximum Power Point Tracking (MPPT) is now widely used method in increasing the photovoltaic (PV) efficiency. The conventional MPPT methods have many problems concerning the accuracy, flexibility and efficiency. The MPP depends on the PV temperature and solar irradiation that randomly varied. In this paper an artificial intelligence based controller is presented through implementing of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to obtain maximum power from PV. The ANFIS inputs are the temperature and cell current, and the output is optimal voltage at maximum power. During operation the trained ANFIS senses the PV current using suitable sensor and also senses the temperature to determine the optimal operating voltage that corresponds to the current at MPP. This voltage is used to control the boost converter duty cycle. The MATLAB simulation results shows the effectiveness of the ANFIS with sensing the PV current in obtaining the MPPT from the PV.

Large-scale integration of wind turbine generators (WTGs) may have significant impacts on power system operation with respect to system frequency and bus voltages. This paper studies the effect of Static Var Compensator (SVC) connected to wind energy conversion system (WECS) on voltage profile and the power generated from the induction generator (IG) in wind farm. Also paper presents, a dynamic reactive power compensation using Static Var Compensator (SVC) at the a point of interconnection of wind farm while static compensation (Fixed Capacitor Bank) is unable to prevent voltage collapse. Moreover, this paper shows that using advanced optimization techniques based on artificial intelligence (AI) such as Harmony Search Algorithm (HS) and Self-Adaptive Global Harmony Search Algorithm (SGHS) instead of a Conventional Control Method to tune the parameters of PI controller for SVC and pitch angle. Also paper illustrates that the performance of the system with controllers based on AI is improved under different operating conditions. MATLAB/Simulink based simulation is utilized to demonstrate the application of SVC in wind farm integration. It is also carried out to investigate the enhancement in performance of the WECS achieved with a PI Controller tuned by Harmony Search Algorithm as compared to a Conventional Control Method.

The present paper proposes a maximum power extraction control for a wind system consisting of a turbine, a permanent magnet synchronous generator, a rectifier, a load and one constant voltage source, which is used to form the DC bus. We propose a linear PI controller, based on passivity, whose stability is guaranteed under practically reasonable assumptions. PI structures are widely accepted in practice as they are easier to tune and simpler than other existing model-based methods. Real switching based simulations have been performed to assess the performance of the proposed controller.

This paper addresses the Energetic Macroscopic Representation EMR, the modelling and the control of photovoltaic panel PVP generation systems for simulation purposes. The model of the PVP considers the variations on irradiance and temperature. A maximum power point tracking MPPT algorithm is considered to control the power converter. A novel EMR is proposed to consider the dynamic model of the PVP with variations in the irradiance and the temperature. The EMR is evaluated through simulations of a PVP generation system.

This paper proposes a general model of five phase permanent magnet synchronous machine (PMSM) which is capable of representing the multiphase Inter Turn Short Circuit (ITSC) occurring in several phase simultaneously this model is based on a coupled magnetic circuit approach leading to a differential equations system goveming the induction machine behavior. The obtained time-differential state equations system is implemented under Matlab environment and numerically solved using the fourth order Rung-Kutta method with variable step time corrected at each rotor displacement through the electromagnetic torque. Also, Fast Fourier Transform and (FFT) analysis is performed to the phase current signal to detect the frequency spectrum, Power Spectral Density (PSD) is chosen as a classification method. Its efficiency depends on its ability to discriminate between various faults generating the same range of harmonics in the stator current spectrum and on its ability to evaluate the fault severity. So, in order to improve the efficiency of these diagnosis methods, one needs a relatively accurate model to simulate the five-phase PMSM in the case of inter-tum short circuit fault helping to predict performances andor to extract fault signature in the machine main quantities. Simulation work has been carried out using MATLAB to verify the performance of the proposed detection/diagnosis method.

One of the fundamental problems affects the performance of pumping stations is its relative high operational cost. As three-phase induction motors are the main prime mover of pumping stations and considered the most widely used electrical motors due to their reliability, ease of maintenance. However, its major problem is the low power factor which results in high electric energy consumption. Energy will be saved when power factor is improved. The main objective of this paper is studying the power factor improvement in El sadaa Pumping Station because of its low operating efficiency which goes from 20 % to 25 %and calculating penalty, ponus and savings in each cases. The correction is achieved by the addition of capacitor banks in parallel with the connected motor circuits and can be applied to the starter, applied at the switchboard or the distribution panel. A model of this station is created using Matlab TM Simulink. Then the determination of induction motor parameters is performed. The station model is discussed. From the simulation results, the power factor enhancement of the pumping station is highlighted.