• Energy Research

Energy efficiency and ratio performance are two key parameters for the analysis of the performance of photovoltaic (PV) modules. The present paper focusses on the assessment of the efficiency of four different photovoltaic module technologies based on energy efficiency and ratio performance. These PV modules were installed at the Applied Research Unit in Renewable Energy (URAER) in Algeria and were used to provide experimental data to help local and international economical actors with performance enhancement and optimal choice of different technologies subject to arid outdoor conditions. The modules studied in this paper are: two thin-film modules of copper indium selenide (CIS), hetero-junction with intrinsic thin-layer silicon (HIT) and two crystalline silicon modules (polycrystalline (poly-Si), monocrystalline (mono-Si)). These technologies were initially characterized using a DC regulator based on their measured I-V characteristics under the same outdoor climate conditions as the location where the monitoring of the electrical energy produced from each PV module was carried out. The DC regulator allows for extracting the maximum electrical power. At the same time, the measurements of the solar radiation and temperature were obtained from a pyranometer type Kipp & ZonenTM CMP21 and a Pt-100 temperature sensor (Kipp & Zonen, Delft, Netherlands). These measurements were performed from July 2020 to June 2021. In this work, the monthly average performance parameters such as energy efficiency are given and analyzed. The average efficiency of the modules over 12 months was evaluated at 4.74%, 7.65%, 9.13% and 10.27% for the HIT, CIS, mono-Si and poly-Si modules, respectively. The calculated percentage deviations in the efficiency of the modules were 8.49%, 18.88%, 19.74% and 23.57% for the HIT, CIS, mono-Si and poly-Si modules, respectively. The low variation in the efficiency of the HIT module can be attributed to the better operation of this module under arid outdoor conditions, which makes it a promising module for adaptation to the region concerned.

This paper describes an energy management strategy for a DC microgrid that utilizes a hybrid renewable energy system (HRES) composed of a photovoltaic (PV) module, a wind turbine based on a permanent magnetic synchronous generator (PMSG), and a battery energy storage system (BESS). The strategy is designed to provide a flexible and reliable system architecture that ensures continuous power supply to loads under all conditions. The control scheme is based on the generation of reference source currents and the management of power flux. To optimize the supply–demand balance and ensure optimal power sharing, the strategy employs artificial intelligence algorithms that use previous data, constantly updated forecasts (such as weather forecasts and local production data), and other factors to control all system components in an optimal manner. A double-input single-output DC–DC converter is used to extract the maximum power point tracking (MPPT) from each source. This allows the converter to still transfer power from one source to another even if one of the sources is unable to generate power. In this HRES configuration, all the sources are connected in parallel through the common DC–DC converter. The strategy also includes a long short-term memory (LSTM) network-based forecasting approach to predict the available energy production and the battery state of charge (SOC). The system is tested using Matlab/Simulink and validated experimentally in a laboratory setting.

Currently, for the determination of the suitable and optimal PV power plant according to the climate conditions of the concerned region, researchers focus on the estimation of certain performance factors, which are reported to be the key parameters for the analysis of the performances of grid-connected photovoltaic (PV) power systems. In this context, this paper focuses on on-site real-time analysis of the performance of three solar photovoltaic plants: Sidi-bel-Abbés (12 MWp), Laghouat (60 MWp), and Ghardaïa (1.1 MWp). These plants are located in different regions experiencing diverse climatic conditions in Algeria. The analysis was carried out by the standardized norms of IEC 61724, using monitoring data collected over one year. The photovoltaic power plants were evaluated in terms of performance factors, such as the reference yield (Yr), final yield (Yf), performance ratio (PR), and capacity factor (CF). On the other side, based on real data collected at the concerned sites, two linear functions depending on solar irradiance and the PV module temperature for each site are proposed for the evaluation of the generated alternative power output (PAC) for the three PV plants. The obtained results based on the study presented in this paper can help designers of PV power plants of different technologies and different climate conditions to precisely decide the convenient technology that allows the best production of the electrical energy for grid-tied PV systems. Furthermore, this study can contribute in giving a clear vision of the implementation of upcoming large-scale solar PV power plants in Algeria within the studied area and other areas.

Diesel engines (DEs) commonly power pumps used in agricultural and grassland irrigation. However, relying on unpredictable and costly fuel sources for DEs pose’s challenges related to availability, reliability, maintenance, and lifespan. Addressing these environmental concerns, this study introduces an emulation approach for photovoltaic (PV) water pumping (WP) systems. Emulation offers a promising alternative due to financial constraints, spatial limitations, and climate dependency in full-scale systems. The proposed setup includes three key elements: a PV system emulator employing back converter control to replicate PV panel characteristics, a boost converter with an MPPT algorithm for efficient power tracking across diverse conditions, and a motor pump (MP) emulator integrating an induction motor connected to a DC generator to simulate water pump behaviors. Precise induction motor control is achieved through a controlled inverter. This work innovatively combines PV and WP emulation while optimizing system dynamics, aiming to develop a comprehensive emulator and evaluate an enhanced control algorithm. An optimized scalar control strategy regulates the water MP, demonstrated through MATLAB/Simulink simulations that highlight superior performance and responsiveness to solar irradiation variations compared to conventional MPPT techniques. Experimental validation using the dSPACE control desk DS1104 confirms the emulator’s ability to faithfully reproduce genuine solar panel characteristics.

Introduction. In this paper, to maximize energy transmission in wind power system, various Maximum Power Point Tracking (MPPT) approaches are available. Among these techniques, we have proposed the one based on typical fuzzy logic. Despite the somewhat reduced performance of fuzzy MPPT. For a number of reasons, fuzzy MPPT can replace conventional optimization techniques. In practice, the effectiveness of conventional MPPT methods depends mainly on the accuracy of the information given and the wind speed or knowledge of the aerodynamic properties of the wind system. Novelty. Our new MPPT for monitoring the maximum power point has been proposed. We developed an algorithm to improve control performance and govern the stator’s developed active and reactive power using the typical fuzzy logic 2 and enable robust control of a grid-connected, doubly fed induction generator. Purpose. MPPT which implies the wind turbine’s rotating speed should be modified in real time to capture the most wind energy, is necessary to achieve high efficiency for wind energy conversion, according to the aerodynamic characteristics of the wind turbine. Methods. Developing a mathematical model for a wind energy production system is complex, can be strongly affected by wind variation and is a non-linear problem. Thanks to these characteristics, thus, the Lyapunov technique is combined with a sliding mode control to ensure overall asymptotic stability and robustness with regard to parametric fluctuations in order to accomplish this goal. We contrasted our fuzzy type-2 algorithm’s performance with that of the fuzzy type-1 and Perturbation & Observation (P&O) suggested in the literature. Practical value. The simulation results demonstrate that the control performance is satisfactory when using the fuzzy logic technique. From these results, it can be said for the optimization of energy conversion in wind systems, the fuzzy type-2 technique may offer a workable option. Since it presents a great possibility to avoid problems either technical or economics linked to conventional strategies.

This paper deals with multi-agent energy management and fault tolerant control of the micro-grid powered by wind farm based on two doubly fed induction generators. The stator flux orientation has used to eliminate the active and reactive power coupling. The proposed control scheme is based on two cascades closed loops. The inner controllers concern the rotor currents. The outer controllers have a parallel configuration with the stator voltage or the stator power control. Switching between these two controllers is realized by the synchronization mechanism. All controllers are designed with Lyapunov approach associated with sliding-mode control, this solution shows good robustness against parameter variations, measurement errors and faults. The global asymptotic stability of the overall system is proven. After that, a Multi-agent energy management was proposed and tested in order to satisfy some objectives and overcome some constraints. The advantages of the wind energy integration associated with multi-agent energy management are: production cost minimization, reduction of the carbon emissions, increasing the energy autonomy and he robustness against weather conditions and faults that may occur during operation. The results confirm the effectiveness of the proposed control.

The present paper exhibits a real time assessment of a robust Energy Management Strategy (EMS) for battery-super capacitor (SC) Hybrid Energy Storage System (HESS). The proposed algorithm, dedicated to an electric vehicular application, is based on a self-gain scheduled controller, which guarantees the H∞ performance for a class of linear parameter varying (LPV) systems. Assuming that the duty cycle of the involved DC-DC converters are considered as the variable parameters, that can be captured in real time, and forwarded to the controller to ensure both; the performance and robustness of the closed-loop system. The subsequent controller is therefore time-varying and it is automatically scheduled according to each parameter variation. This algorithm has been validated through experimental results provided by a tailor-made test bench including both the HESS and the vehicle traction emulation system. The experimental results demonstrate the overall stability of the system, where the proposed LPV supervisor successfully accomplishes a power frequency splitting in an adequate way, respecting the dynamic of the sources. The proposed solution provides significant performances for different speed levels.

In this paper, a robust current control of the hybrid renewable energy system (HRES), based on the PV-Wind system, is proposed. The HRES is connected to a multiport converter to synchronize the multi-source system with one DC-Bus. Due to their ability to integrate many renewable energy sources (RES) individually or simultaneously, multiport converters (MPC) are an innovative method suitable for renewable energy applications. Recently, many DC-DC converter designs and topologies have emerged to ensure the highest possible efficiency of hybrid RESs. The multiport converter is a typical coupling system with several modes of operation. Thus, the design of its controller become complicated. To stabilize the DC-Bus voltage, a battery has been added to the system. In this HRES configuration, all sources are connected in parallel via the multiport DC converter. We used the multiport DC converter to minimize the intermittent character of solar and wind and control the energy flow between the different power sources and the load, as well as to increase the performance of the system. The nonlinear robust control structure is based on Lyapunov approach to overcome the nonlinear model of the system to improve robustness and guarantees the asymptotic stability. The proposed control law is implemented and tested on dSPACE-DS1104. The results show the effectiveness and the feasibility of the proposed controller.

The overexploitation of non-renewable fossil resources has led to dangerous warming of our planet due to greenhouse gas emissions. The main reason for this problem is the increase in global energy demand. The rising prices of oil and gas have pushed governments around the world to turn to renewable energy, especially solar and wind power. For this reason, the present paper aimed to focus on photovoltaic and wind energy systems. However, exploitation of these two sources individually is not always easy because of their intermittent and irregular characters. Therefore, the obvious solution is the hybridisation of these two sources, which, when used alongside other systems such as batteries, increases the reliability, availability, and efficiency of these renewable sources. The main objective of this paper is to give an overview of different configurations of hybrid solar and wind energy conversion systems. First, the behaviour of each system, as well as their mathematical models, characteristics, and existing topologies, is presented. Then, the control strategies, optimal configurations, and sizing techniques, as well as different energy management strategies, of these hybrid PV–wind systems are presented.