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Most countries of the world have adopted renewable energy sources (RES) because of consistent policy and industry support. The use of these sources is expanding and will cover a larger part of the generation capacity in the future. Thus, power systems (PS) are experiencing the high scale RES integration. For a power system dominated by RES, the electrical grid characteristics, namely, the inertia constant (Hs) and the rate of change of frequency (ROCOF), should be evaluated. Furthermore, the requirements related to these characteristics should be specified in the grid code (GC) to reflect the actual needs of the transmission system operator (TSO) and to prepare the evolution of the RES penetration level. Due to the delay in specifying or updating these GC requirements, RES that are incorporating unsuitable functionalities for the future perspective, regarding fault-ride-through (FRT) and frequency support requirements, will remain operational by 2030; this will create additional constraints on the PS frequency stability after large-scale RES integration. In this paper, the impact assessment of deployed RES technologies on the Moroccan PS frequency stability is assessed by the year 2030, using MATLAB/Simulink environment. The main reason for focusing on the case study of Morocco is the country’s target of installing 52% of the energy supply from RES in the horizon of 2030.

The problem of state and parameter estimation in photovoltaic (PV) systems is addressed. The maximum power point tracking (MPPT) techniques and controllers design involve the PV generator (PVG) delivered voltage and current. However, in situations where PV arrays are located in a remote site from the control unit of the converter, so as to profit from good solar radiation, PVG voltage and current measurements become difficult. From other side, the use of long PV cable between the PVG and the converter would produce substantial voltage drops in the cable, which would consequently result in MPPT control inaccuracies if only voltage and current sensed in the converter input side of the cable are used instead. To avoid this problem, an adaptive Kalman–like observer for PV systems is designed, in this paper. Using only voltage and current measurements in the converter input, the observer performs online estimation of the PVG output voltage and current as well as of the cable resistance and inductance, regardless of these parameters uncertainties. The convergence of the system state and parameters is shown by simulation.

This work presents an adaptive observer-based control strategy for maximum power point tracking (MPPT) of uncertain photovoltaic (PV) systems. On the one hand, the PVG output voltage and/or current measurements are needed for MPPT techniques and controllers design and, on the other hand, the PV arrays have to be installed in a site that profits from good daily sunshine. This obviously leads to difficulty of PVG output current and voltage measurement if ever such a site is at great distance from the converter. Furthermore, the MPPT control accuracy could be significantly affected due to the cable parameters if only voltage and current measurements on the converter side of the cable are instead used. To overcome this issues, an adaptive extended Kalman–like observer providing estimates of PVG output current and voltage regardless of cable resistance and inductance deviations, is first designed. Afterwords, a backstepping controller is synthesized to ensure the MPPT objective. The designed adaptive observer-based MPPT control convergence is formally analyzed and its effectiveness in compensating for cable parameters uncertainties on the MPPT accuracy is validated through numerical simulations.

In this chapter, we show how the backstepping control design approach can be used to develop adaptive controllers for wind energy conversion systems (WECS). The focus is made on a WECS constituted of doubly fed induction generator (DFIG) and an AC/DC/AC converters association. The presented control strategy results in a multi-loop, nonlinear controller which is conceived to meet two control objectives: (i) speed reference optimization, in order to extract maximum wind energy despite the uncertainty and variations wind speed, and mechanical parameters; (ii) Power Factor Correction (PFC) to avoid net harmonic pollution. The entire nonlinear model is presented in the d-q framework and then based upon to design the multi-loop nonlinear controller using the adaptive backstepping design technique. A formal Lyapunov stability analysis is performed to prove the achievement of the control objectives. This theoretical result is confirmed by simulation with the MATLAB / Simulink software considering a 1.5 kW DFIG wind energy production system. The results of the simulation show that all control objectives (induction generator speed monitoring, stator flux, DC link voltage, and unit power factor control) are asymptotically achieved.

The problem of state and parameter estimation in photovoltaic (PV) systems is considered. The system is composed of a photovoltaic generator (PVG) which supplies power, via a long PV cable, to a DC centrifugal pump driven by a DC-DC boost converter. The maximum power point tracking (MPPT) techniques and controllers are generally designed based on the PVG delivered voltage and/or current measurements. From other side, PV arrays should be established in a location that profits from good daily solar radiation. Such a location is, in numerous cases, remote from the converter, which obviously leads to difficulty of PVG voltage and current measurement. Besides, the use of a long PV cable may result in MPPT control inaccuracies due to voltage drops in the cable. For remedying these issues, an adaptive observer for PV systems is proposed, in this work. It accomplishes online estimation of PVG current and voltage as well as of the unknown resistance parameter of the cable. The designed adaptive observer convergence is theoretically proved and its performances are evaluated by simulation.

The purpose of this paper is to introduce the modelling and control strategy of the wind energy conversion system (WECS), based on double fed induction generator (DFIG) connected with AC/DC/AC converters. The proposed strategy involves a multi-loop non-linear controller, designed in order to obtain two main control objectives: speed reference optimization, designed to extract a maximum wind energy whatever the wind speed and power factor correction (PFC) requirement must be satisfactorily realized. The whole non-linear model is presented in d-q reference frame, within it the multi-loop non-linear controller is synthesized using the backstepping design technique. A formal analysis based on Lyapunov stability is carried out to exhibit the control system performances. The latter is validated through simulation using software Matlab/Simulink and studies on a 1.5 kw DFIG wind generation system. The simulation results show that the whole control objectives are asymptotically achieved.

The Low Voltage Ride Through (LVRT) is the most important requirement in the grid code regarding the connection of wind farms (WF), it requires that wind turbines (WT) must remain connected to the electrical grid during and after the normally cleared faults. This specification should reflect the true needs for system operation and must be updated depending on the renewable energy (RE) penetration level. The LVRT profile specified in the Moroccan grid code (GC) concerning the connection of WF to the 225KV and 60KV levels is evaluated, particularly after the large scale of RE penetration by 2030. In addition, some suggestions are proposed to update the GC to reflect the real needs of the electrical grid and to improve the stability of the electrical grid based on the critical analysis of the existing GC.

This paper presents an output feedback control of sensorless photovoltaic systems with maximum power point tracking (MPPT). The system consists of a Photovoltaic Generator (PVG) which supplies a DC centrifugal pump, via a DC/DC boost converter. This later being connected to the PVG by a long PV cable. Generally, PV systems are established near the control unit of the converter. The MPPT methods and control laws are based on the PVG voltage and current measurements. However, PV arrays must be located in a site that guarantees good solar radiation. In most cases, such a site is at great distance from the control unit. Thus, on the one hand, the PVG voltage and current measurements become difficult and, on the other hand, the PV cable parameters could significantly effect the MPPT control accuracy if only voltage and current measurements in the cable converter side are used. To overcome these issues, a state estimation for PV systems is considered in this paper. A high gain observer is designed on the basis of a PV system model that accounts for PV cable parameters. It provides estimates of PVG output voltage and current using only current and voltage measurements in the converter side of the cable. A backstepping controller is then synthesized with the view of ensuring the MPPT objective. The output feedback control convergence is formally analyzed and its performances are illustrated by simulation.

Morocco aims to obtain 52% of its energy supply from renewable sources by 2030. However, implementing these targets will require adequate electrical grid. In fact, the large scale renewable energies (RE) integration reduces system inertia, which counteract the frequency deviation, and then disturbs the system ability to regulate frequency in the event of sudden load or generation changes. It is because RE sources are in general loosely coupled to the grid, and their contribution to system inertia is negllgible. The objective of this paper is to analyze and quantify the dynamic stability of the Moroccan electrical grid concerning the inertial response after the large scale RE power penetration and to identify its impact on the control of the power system.

This paper presents a theoretical framework for adaptive control of a wind energy conversion system (WECS), involving a squirrel cage induction generator (SIG) connected with an AC/DC/AC IGBT-based PWM converter. A multi-loop nonlinear controller is designed to meet two main control objectives, i.e., (i) speed reference optimization in order to extract a maximum wind energy whatever the wind speed, and (ii) power factor correction (PFC) to avoid net harmonic pollution. These objectives must be achieved despite the mechanical parameters uncertainty. First, a nonlinear model of the whole controlled system is developed within the Park coordinates. Then, a multi-loop nonlinear controller is synthesized using the adaptive backstepping design. A formal analysis based on Lyapunov stability is carried out to describe the control system performances. In addition to closed-loop global asymptotic stability, it is proven that all control objectives (induction generator speed tracking, rotor flux regulation, DC link voltage regulation and unitary power factor) are asymptotically achieved.

The problem of maximum power point tracking (MPPT) in photovoltaic (PV) arrays is addressed considering a PV system including a PV panel, a PWM DC/AC inverter connected to triphase grid. Interestingly, the proposed PV system features higher reliability and reduced cost as it involves no chopper and no radiation/temperature sensors, unlike standard systems. We seek the achievement of three control objectives: (i) the voltage reference must be designed so as to achieve maximum power point tracking (MPPT), (ii) the DC link voltage must be tightly regulated over a wide range voltage-reference variation, (iii) and the power factor correction (PFC) requirement must be satisfactorily realized. To meet these objectives, a multiloop controller is designed, using nonlinear design techniques, based on the nonlinear system model. Then, it is formally demonstrated that the proposed controller actually meets the desired control objectives.

Avoiding mechanical (speed, torque) sensors in electric motor control entails cost reduction and reliability improvement. Furthermore, sensorless controllers (also referred to output-feedback) are useful, even in the presence of mechanical sensors, to implement fault tolerant control strategies. In this paper, we deal with the problem of output-feedback control for induction motors. The solutions proposed so far have been developed based on the assumption that the machine magnetic circuit characteristic is linear. Ignoring magnetic saturation makes it not possible to meet optimal operation conditions in the presence of wide range speed and load torque variations. Presently, an output-feedback control strategy is developed on the basis of a motor model that accounts for magnetic saturation. The control strategy includes an optimal flux reference generator, designed in order to optimize energy consumption, and an output-feedback designed using the backstepping technique to meet tight speed regulation in the presence of wide range changes in speed reference and load torque. The controller sensorless feature is achieved using an adaptive observer providing the controller with online estimates of the mechanical variables. Adaptation is resorted to cope with the system parameter uncertainty. The controller performances are theoretically analyzed and illustrated by simulation.

The problem of maximum power point tracking (MPPT) in photovoltaic (PV) arrays is addressed considering a PV system including a PV panel, a PWM DC/AC inverter connected to single-phase grid. The maximum power point (MPPT) of PV generators varies with solar radiation and temperature. To reduce the PV system cost, the MPPT is presently achieved without chopper, resorting to solar radiation and temperature sensors. The proposed strategy involves a multi-loop controller designed to meet the three main control objectives i.e. (i) voltage reference generator designed to meet maximum power point tracking (MPPT) despite solar radiation, (ii) tight DC Link voltage regulation for a wide range of voltage-reference variation and (iii) power factor correction (PFC). It is formally shown that the developed strategy control actually meets the MPPT requirement.

This paper deals with the problem of controlling doubly-fed induction machines (DFIM). A nonlinear model of the whole controlled system, including the DFIM and the associated AC/DC rectifier and DC/AC inverter, is developed within the Park coordinates. A multi-loop nonlinear controller is developed, using the backstepping design technique. The controller is formally shown to meet its objectives i.e. accurate motor speed-reference tracking, tight regulation of the DC link voltage and power factor correction. The theoretical developments and results are validated by simulation on a representative nonlinear complex model.

The problem of maximum power point tracking (MPPT) in photovoltaic (PV) arrays is addressed considering a PV system including a PV panel, a PWM DC/AC inverter connected to single-phase grid. The maximum power point (MPP) of PV generators varies with solar radiation and temperature. To reduce the PV system cost, the MPPT is presently achieved without, chopper, resorting to solar radiation and temperature sensors. The proposed strategy involves a multi-loop nonlinear controller designed, using the backstepping design technique, to meet the three main control objectives i.e. (i) voltage reference generator designed to meet maximum power point tracking (MPPT), (ii) tight DC Link voltage regulation for a wide range voltage-reference variation and power factor correction (PFC) requirement must be satisfactorily realized. A formal analysis based on Lyapunov stability is developed to describe the control system performances. It is formally shown that the developed strategy control actually meets the MPPT requirement.