The paper presents the advanced control system of the wind energy conversion with a variable speed wind turbine. The considered system consists of a wind turbine with the permanent magnet synchronous generator (PMSG), machine side converter (MSC), grid side converter (GSC) and control circuits. The mathematical models of a wind turbine system, the PMSG generator and converters have been described. The control algorithms of the converter systems based on the methods of vector control have been applied. In the advanced control system of the machine side converter the optimal MPPT control method has been used. Additionally the pitch control scheme is included in order to achieve the limitation of maximum power and to prevent mechanical damage of the wind turbine. In the control system of the grid side converter the control of active and reactive power has been applied with the application of Voltage Oriented Control (VOC). The performance of the considered wind energy system has been studied by digital simulation. The results of simulation studies confirmed the good effectiveness of the considered wind turbine system and very good performance of the proposed methods of vector control and control systems.

This paper presents a comparative study between the conventional PI (Proportional Integral) and backstepping controllers applied to the DFIG (Doubly Fed Induction Generator) used in WECS (Wind Energy Conversion System). These two different control strategies proposed in this work are developed to control the active and reactive power of the DFIG on the one hand, and to maintain the DC-link voltage constant for the inverting function on the other hand. This is ensured by generating control signals for two power electronic converters, RSC (Rotor Side Converter) and GSC (Grid Side Converter). In order to optimise the power production in the WT (Wind Turbine), an MPPT (Maximum Power Point Tracking) algorithm is applied along with each control technique. To simulate the effectiveness of the proposed controllers, MATLAB/Simulink Software is used, and the obtained results are analysed and discussed to compare PI and backstepping controllers in terms of robustness against wind speed variations and tracking performance in dynamic and steady states.

A sliding mode controller for the photovoltaic pumping system has been proposed in this paper. This system is composed of a photovoltaic generator supplying a three-phase permanent magnet synchronous motor coupled to a centrifugal pump through a three-phase voltage inverter. The objective of this study is to minimise the number of regulators and apply the sliding mode control by exploiting the specification of the field oriented control scheme (FOC). The first regulator is used to force the photovoltaic generator to operate at the maximum power point, while the second is used to provide the field oriented control to improve the system performance.The whole system is analysed and its mathematical model is done. Matlab is used to validate the performance and robustness of the proposed control strategy.

The paper presents an induction generator connected to the power grid using the AC/DC/AC converter and LCL coupling filter. In the converter, both from the generator and the power grid side, three-level inverters were used. The algorithm realizing pulse width modulation (PWM) in inverters has been simplified to the maximum. Control of the induction generator was based on the indirect field oriented control (IFOC) method. At the same time, voltage control has been used for this solution. The MPPT algorithm has been extended to the variable pitch range of the wind turbine blades. The active voltage balancing circuit has been used in the inverter DC voltage circuit. Synchronization of control from the power grid side is ensured by the use of a PLL loop with the system of preliminary suppression of undesired harmonics (CDSC).

Wind and solar radiation are intermittent with stochastic fluctuations, which can influence the stability of operation of the hybrid system in the grid integrated mode of operation. In this research work, a smoothing control method for mitigating output power variations for a grid integrated wind/PV hybrid system using a battery and electric double layer capacitor (EDLC) is investigated. The power fluctuations of the hybrid system are absorbed by a battery and EDLC during wide variations in power generated from the solar and wind system, subsequently, the power supplied to the grid is smoothened. This makes higher penetration and incorporation of renewable energy resources to the utility system possible. The control strategy of the inverter is realized to inject the power to the utility system with the unity power factor and a constant DC bus voltage. Both photovoltaic (PV) and wind systems are controlled for extracting maximum output power. In order to observe the performance of the hybrid system under practical situations in smoothing the output power fluctuations, one-day practical site wind velocity and irradiation data are considered. The dynamic modeling and effectiveness of this control method

Photovoltaic (PV) cells are very costly because of the silicon element which is not cheaply available. Usually, PV cells are preferred to be used at maximum efficiency. Therefore, PV plants are emphasized to extract maximum power from PVcells. When inertia free PV plants are integrated into the grid in large numbers, the problem of maintaining system stability subjected to load perturbation is quite difficult. In response to this, a control topology is being an approach to make available the PV cells in maintaining system stability by utilizing the system frequency deviation as feedback to the controller. To implement this, the PVs are operated at Maximum Power Point Tracking (MPPT). This allows the PV to operate at Pseudo Maximum Power Point tracking (PMPPT) which makes it possible to run the PV with reserve power capacity without employing a battery for storage. The control strategy has been implemented over a two-stage power conversion model of the PV system. The simulation results showed that the proposed control PMPPT topology is effective in frequency regulation capability as compared to the MPPT technique.

A Novel Intelligent control of a Unified Power Quality Conditioner (UPQC) coupled with Photovoltaic (PV) system is proposed in this work. The utilization of a Re-lift Luo converter in conjunction with a Cascaded Artificial Neural Network (ANN) Maximum Power Point Tracking (MPPT) method facilitates the optimization of power extraction from PV sources. UPQC is made up of a series and shunt Active Power Filter (APF), where the former compensates source side voltage quality issues and the latter compensates the load side current quality issues. The PV along with a series and shunt APFs of the UPQC are linked to a common dc-bus and for regulating a dc-bus voltage a fuzzy tuned Adaptive PI controller is employed. Moreover, a harmonics free reference current is generated with the aid of CNN assisted dq theory in case of the shunt APF. The results obtained from MATLAB simulation.

The presented distributed photovoltaic system is made of divided into individual modules photovoltaic panel, consisting of several photovoltaic cells properly connected and coupling them with low-power DC / DC converters. The essence of the research is to increase the reliability of the system and the resultant efficiency of the entire system, so that it is possible to convert solar radiation energy into electricity with the greatest efficiency. The article focuses on the presentation of the implementation and tests of the overriding control algorithm, the task of which is to provide full functionality for a distributed photovoltaic system. The control is designed to minimize the negative effects of shadows on the operation of the photovoltaic system and conduct self-diagnostics. The conclusion for the carried out work is the formulation of hardware and interface requirements for the further development of the project.

The wind energy conversion systems (WECS) suffer from an intermittent nature of source (wind) and the resulting disparity between power generation and electricity demand. Thus, WECS are required to be operated at maximum power point (MPP). This research paper addresses a sophisticated MPP tracking (MPPT) strategy to ensure optimum (maximum) power out of the WECS despite environmental (wind) variations. This study considers a WECS (fixed pitch, 3KW, variable speed) coupled with a permanent magnet synchronous generator (PMSG) and proposes three sliding mode control (SMC) based MPPT schemes, a conventional first order SMC (FOSMC), an integral back-stepping-based SMC (IBSMC) and a super-twisting reachability-based SMC, for maximizing the power output. However, the efficacy of MPPT/control schemes rely on availability of system parameters especially, uncertain/nonlinear dynamics and aerodynamic terms, which are not commonly accessible in practice. As a remedy, an off-line artificial function-fitting neural network (ANN) based on Levenberg-Marquardt algorithm is employed to enhance the performance and robustness of MPPT/control scheme by effectively imitating the uncertain/nonlinear drift terms in the control input pathways. Furthermore, the speed and missing derivative of a generator shaft are determined using a high-gain observer (HGO). Finally, a comparison is made among the stated strategies subjected to stochastic and deterministic wind speed profiles. Extensive MATLAB/Simulink simulations assess the effectiveness of the suggested approaches.

Research related to photovoltaic panels comprises different topics starting with modelling solar cells, finding new maximum power point tracking (MPPT) algorithms, testing existing ones or designing of DC/DC converters for MPPT systems and microgrids that incorporate photovoltaic energy sources. In each of the examples above a deep knowledge of photovoltaic panels is required, as well as a reliable measurement system that can deliver continuous, stable light with enough power to meet standard test conditions (STC) and that can ensure repeatable results. Therefore this paper presents a low-cost solar simulator with a microcontroller-based measurement system, that can be used for various measurements of low-power photovoltaic panels.

Many parts of remote locations in the world are not electrified even in this Advanced Technology Era. To provide electricity in such remote places renewable hybrid energy systems are very much suitable. In this paper PV/Wind/Battery Hybrid Power System (HPS) is considered to provide an economical and sustainable power to a remote load. HPS can supply the maximum power to the load at a particular operating point which is generally called as Maximum Power Point (MPP). Fuzzy Logic based MPPT (FLMPPT) control method has been implemented for both Solar and Wind Power Systems. FLMPPT control technique is implemented to generate the optimal reference voltage for the first stage of DC-DC Boost converter in both the PV and Wind energy system. The HPS is tested with variable solar irradiation, temperature, and wind speed. The FLMPPT method is compared with P&O MPPT method. The proposed method provides a good maximum power operation of the hybrid system at all operating conditions. In order to combine both sources, the DC bus voltage is made constant by employing PI Controllers for the second stage of DC-DC Buck-Boost converter in both Solar and Wind Power Systems. Battery Bank is used to store excess power from Renewable Energy Sources (RES) and to provide continuous power to load when the RES power is less than load power. A SPWM inverter is designed to convert DC power into AC to supply three phase load. An LC filter is also used at the output of inverter to get sinusoidal current from the PWM inverter. The entire system was modeled and simulated in Matlab/Simulink Environment. The results presented show the validation of the HPS design.