Stand-alone Photovoltaic System Research Articles

MPP Tracking with a Modified Duty Cycle Sweeping (MDCS) Algorithm for Various Environmental Irradiance Conditions

In this paper, a photovoltaic (PV) system based on modified duty cycle sweeping (MDCS) has been proposed to achieve the maximum power point tracking (MPPT). The disadvantages of perturb and observe (P&O), such as diverging tracking directions and the inability to detect the global peak during partial shading (PS), are intended to be overcome by this method (PS). An intelligent double identification and tracking method consistently tracks the global peak under partial shading and the MPP under rapid irradiance fluctuations. Strict dynamic irradiance and partial shading tests are imposed in MATLAB/Simulink@ and simulated to validate the suggested concept. Additionally, a laboratory prototype MPPT standalone PV system supported by Texas Instruments’ Code Composer Studio is operated by a SEPIC converter in conjunction with the C2000 real-time microcontroller in order to conduct an experimental validation study. The effectiveness of the method is compared with the other well-known MPPT techniques, conventional P&O. The suggested method successfully follows the global peak under various patterns of partial shading as compared to the conventional algorithms. The algorithm’s efficiency has been preserved at around 95-100%.

Optimized ANN-fuzzy MPPT controller for a stand-alone PV system under fast-changing atmospheric conditions

Solar energy is one of the most promising renewable energy resources. Over the last few decades, photovoltaic (PV) systems have grown in popularity. Since the maximum power point (MPP) of a solar system changes with environmental circumstances, the maximum power point tracking (MPPT) technique is required to get the most power out of the solar system. Various MPPT techniques based on classical and artificial intelligence (AI) methodologies have been proposed in the literature so far. In this paper, we aim to provide a thorough comparative analysis of the most widely used MPPT algorithms based on AI. The MPPT techniques discussed are based on fuzzy logic (FL), artificial neural networks (ANN), and the suggested hybrid approach ANN-fuzzy. The designed MPPT controllers are evaluated in the same PV system, which consists of a PV module, a DC-DC boost converter, and a DC load, under the same weather profile. Using the MATLAB/Simulink simulation tool, the tracking accuracy, response time, overshoot, and steady-state ripple of each method are tested in different weather conditions. The simulation results show that the ANN-fuzzy proposed tactic outperforms both the FL and the ANN MPPT controllers in correctly and successfully tracking the maximum power under diverse atmospheric conditions.

Optimized ANN-fuzzy MPPT controller for a stand-alone PV system under fast-changing atmospheric conditions

Solar energy is one of the most promising renewable energy resources. Over the last few decades, photovoltaic (PV) systems have grown in popularity. Since the maximum power point (MPP) of a solar system changes with environmental circumstances, the maximum power point tracking (MPPT) technique is required to get the most power out of the solar system. Various MPPT techniques based on classical and artificial intelligence (AI) methodologies have been proposed in the literature so far. In this paper, we aim to provide a thorough comparative analysis of the most widely used MPPT algorithms based on AI. The MPPT techniques discussed are based on fuzzy logic (FL), artificial neural networks (ANN), and the suggested hybrid approach ANN-fuzzy. The designed MPPT controllers are evaluated in the same PV system, which consists of a PV module, a DC-DC boost converter, and a DC load, under the same weather profile. Using the MATLAB/Simulink simulation tool, the tracking accuracy, response time, overshoot, and steady-state ripple of each method are tested in different weather conditions. The simulation results show that the ANN-fuzzy proposed tactic outperforms both the FL and the ANN MPPT controllers in correctly and successfully tracking the maximum power under diverse atmospheric conditions.

An intelligent converter and controller for electric vehicle drives utilizing grid and stand-alone solar photovoltaic power generation systems

In this study, a battery energy management system for electric vehicle (EV) applications is proposed with a standalone photovoltaic (PV) source and controlled based on the availability of grid, PV source, load consumption, and energy stored in the battery. This paper proposes a single-ended primary-inductance converter (SEPIC) DC-DC converter for charging the battery through the utility and PV source that provides good load regulation. The bidirectional nature of the proposed DC-DC converter provides the charging and discharging of the EV battery in the succeeding modes of operation, i) grid-tied charging, ii) PV-tied charging, iii) discharging to the load in the absence of utility and PV source, and iv) regenerative braking. An improved perturb and observe-based maximum power point tracking (MPPT) algorithm is proposed to track the maximum power from the PV source. In addition, to handle the four modes of operation, a dedicated controller is also proposed. Firstly, the proposed system is validated using MATLAB/Simulink software by considering different operating conditions, and the performance is compared with the traditional MPPT algorithms. Finally, the effectiveness of the suggested system is validated through an experimental prototype. The result proved the superiority of the converter and controller over the traditional systems.<div align="center"> </div>

A Feasible MPPT Algorithm for the DC/DC Boost Converter

One of the most promising forms of renewable energy is solar energy. However, efficient exploitation of this energy form is a topic of great interest, especially in obtaining the maximum amount of power from the solar photovoltaic (PV) system under changing environmental conditions. To solve this problem, it is necessary to propose an optimal algorithm. Therefore, this paper presents a feasible maximum power point tracking (MPPT) technique for DC/DC boost converters applied in load-connected stand-alone PV systems to extract the maximum available power. This proposed method is based on the combination of the modified perturb and observe (P&O) and fractional open circuit voltage (FOCV) algorithms. The effectiveness of the proposed technique is verified via time-domain simulation of the load-connected stand-alone PV system using PSIM software. The simulation results show a tracking efficiency with an average value of 99.85%, 99.87%, and 99.96% for tracking the MPP under varying loads, irradiation, and simultaneously varying temperature, load, and irradiation, respectively. In addition, tracking time is always stable at 0.02 sec for changing weather conditions in the large range. Therefore, the results of the proposed method indicate advantages compared to the conventional method.

Modeling of a stand-alone solar photovoltaic water pumping system for irrigation

Solar photovoltaic water pumping systems have been research topics in recent decades. The purpose was to develop much more profitable and efficient systems to meet the needs of pumping water for livestock and irrigation. This paper describes the design of a stand-alone photovoltaic water pumping system. A Boost converter is used to apply the Maximum Power Point Tracking (MPPT) algorithm. Similarly, a three-phase voltage source converter (VSC) is used to supply the asynchronous motor. The installation must provide a continuous water flow during the irrigation interval. It has been verified that in adverse weather conditions (cloud transits or partly cloudy) it is necessary to incorporate a decentralized-hybrid energy storage system (based on batteries or ultracapacitors), or excessively oversize the standalone photovoltaic system, to supply the water pump. The model has been simulated in Matlab-Simulink. In this way, different simulations have been developed to verify the basic characteristics of the proposed system. The results of the simulated model and the conclusions obtained are also presented in this paper.

Effect of cloud transits in a stand-alone solar photovoltaic water pumping system

This paper discusses the effects of cloud transit on a stand-alone direct solar photovoltaic water pumping system for irrigation and farms. In this way, its impact is studied, applying a possible classification based on its incidence and effects on the system. For this, the information provided by the data loggers of different photovoltaic installations has been analyzed and in turn compared with the data obtained in the reference installation. In addition, the Matlab-Simulink simulation model used is described. Different simulations have been developed to verify the basic characteristics of the proposed system. In this way, it is possible to check the advantages and drawbacks of the direct water pumping in irrigation applications. At the same time, the system parameters can be easily modified to meet the requirements of different water flow capacities. Also, the water hammer effect and the cavitation phenomenon in the water pump are described. Finally, the simulation results obtained as well as their conclusions are presented.

Robust MPPT Control of Stand-Alone Photovoltaic Systems via Adaptive Self-Adjusting Fractional Order PID Controller

The Photovoltaic (PV) system is an eco-friendly renewable energy system that is integrated with a DC-DC buck-boost converter to generate electrical energy as per the variations in solar irradiance and outdoor temperature. This article proposes a novel Adaptive Fractional Order PID (A-FOPID) compensator with self-adjusting fractional orders to extract maximum power from a stand-alone PV system as ambient conditions change. The reference voltage is generated using a feed-forward neural network. The conventional FOPID compensator, which operates on the output voltage error of the interleaved buck-boost converter, is employed as the baseline maximum-power-point-tracking (MPPT) controller. The baseline controller is retrofitted with an online state-error-driven adaptation law that dynamically modifies the fractional orders of the controller’s integral and differential operators. The adaptation law is formulated as a nonlinear hyperbolic scaling function of the system’s state error and error-derivative variables. This augmentation supplements the controller’s adaptability, enabling it to manipulate flexibly the tightness of the applied control effort as the operating conditions change. The efficacy of the proposed control law is analyzed by carrying out customized simulations in the MATLAB Simulink environment. The simulation results show that the proposed MPPT control scheme yields a mean improvement of 25.4% in tracking accuracy and 11.3% in transient response speed under varying environmental conditions.

Performance investigation of a concentrated photovoltaic-thermoelectric hybrid system for electricity and cooling production

To fully exploit inlet sunlight, a novel hybrid system comprising a concentrated photovoltaic cell, a thermoelectric generator, and a thermoelectric cooler is established. The thermoelectric generator generates electricity by thermally harnessing the solar spectrum energy unavailable to the concentrated photovoltaic cell and then drives the thermoelectric cooler to produce additional cooling. With full consideration of internal and external irreversibility, the numerical model of the hybrid system is developed, where comprehensive heat transfer equations are constructed by the effectiveness-number of transfer units method. Subsequently, the performance characteristics of the system are evaluated by energetic and exergetic analysis. Over the operating range of the thermoelectric unit, when the performance enhancement of the hybrid system is maximized, the associated power density, energy efficiency, and exergy efficiency are, respectively, 42.828 Wm-2, 0.0251, and 0.0255, which are improved by 3.53%, 3.72%, and 3.66% in comparison to the stand-alone concentrated photovoltaic system. Meanwhile, the exergy destruction rate density is reduced by 0.49%. Furthermore, comprehensive sensitivity analyses are undertaken to derive the effects of critical designing parameters and operating conditions on the overall performance. The obtained outcomes may contribute to the design and operation of such a cogeneration system.

A New Efficient Cuckoo Search MPPT Algorithm Based on a Super-Twisting Sliding Mode Controller for Partially Shaded Standalone Photovoltaic System

The impact of Partial Shading Conditions (PSCs) significantly influences the output of Photovoltaic Systems (PVSs). Under PSCs, the Power-Voltage (P-V) characteristic of the PVS unveils numerous power peaks, inclusive of local maxima and a global maximum. The latter represents the optimum power point. Traditional Maximum Power Point Tracking (MPPT) algorithms struggle to track the Global Maximum Power Point (GMPP). To address this, our study emphasizes the creation of a novel algorithm capable of identifying the GMPP. This approach combines the Cuckoo Search (CS) MPPT algorithm with an Integral Super-Twisting Sliding Mode Controller (STSMC) using their benefits to enhance the PVS performance under PSCs in terms of high efficiency, low power losses, and high-speed convergence towards the GMPP. The STSMC is a second-order Sliding Mode Control strategy that employs a continuous control action that attenuates the “chattering” phenomenon, caused when the first-order SMC technique is employed. Indeed, the proposed CS-STSMC-MPPT algorithm consists of two parts. The first one is based on the CS algorithm used for scanning the power-voltage curve to identify the GMPP, and subsequently generating the associated optimal voltage reference. The second part aims to track the voltage reference by manipulating the duty cycle of the boost converter. The proposed CS-STSMC-MPPT algorithm is featured by its strength against uncertainties and modeling errors. The obtained simulation results underline a high convergence speed and an excellent precision of the proposed method in identifying and tracking the GMPP with high efficiency under varying shading scenarios. For comparative purposes, this method is set against the hybrid CS-Proportional Integral Derivative, the conventional CS, the Particle Swarm Optimization, and the Perturb and Observe algorithms under different PSCs, including zero, weak, and severe shading. Simulation conducted in the Matlab/Simulink environment confirms the superior performance of the proposed CS-STSMC-MPPT algorithm in terms of precision, convergence speed, efficiency, and resilience.

Solar Array Optimization Using Cryptographic Fibonacci Transformation for Global Power Enhancement and Ease of MPPT Controllers

The photovoltaic array reconfiguration approach is the most promising solution to enhance the global maximum power (GMP) and improve the array characteristics by mitigating the variation between distinct rows, thereby reducing the computational burden on maximum power point tracking systems. However, the majority of the existing reconfiguration approaches inherently have many drawbacks such as scalability issues, poor shade dispersion, distorted array characteristics, numerous power peaks, augmented mismatch, etc. In order to address these issues, this article proposes a novel integer‐based Fibonacci transform technique using the idea of image encryption for reconfiguration. The proposed strategy is tested for both symmetric and asymmetric photovoltaic (PV) arrays under 19 shading cases. Further, its performance is compared with the 23 existing techniques. Besides, a nonparametric Wilcoxon signed‐rank sum test with a significant difference (p‐value) of 0.05 is used to perform a pairwise unbiased comparison of all the techniques. Due to the discriminate shade dispersion through intelligent reconfiguration, the proposed strategy delivers consistently superior performance yielding the respective GMP enhancement of 34.43%, 12.5%, 5.06%, and 37.39%, 22.94%, 16.5% for 9 × 9, and 4 × 8 PV arrays under distinct cases. The proposed algorithm is further validated using the Levenberg–Marquardt neural network‐based MPPT controller for a 7 kWp standalone PV system.

Unified Environment for Real Time Control of Hybrid Energy System Using Digital Twin and IoT Approach.

Today, climate change combined with the energy crisis is accelerating the worldwide adoption of renewable energies through incentive policies. However, due to their intermittent and unpredictable behavior, renewable energy sources need EMS (energy management systems) as well as storage infrastructure. In addition, their complexity requires the implementation of software and hardware means for data acquisition and optimization. The technologies used in these systems are constantly evolving but their current maturity level already makes it possible to design innovative approaches and tools for the operation of renewable energy systems. This work focuses on the use of Internet of Things (IoT) and Digital Twin (DT) technologies for standalone photovoltaic systems. Based on Energetic Macroscopic Representation (EMR) formalism and the Digital Twin (DT) paradigm, we propose a framework to improve energy management in real time. In this article, the digital twin is defined as the combination of the physical system and its digital model, communicating data bi-directionally. Additionally, the digital replica and IoT devices are coupled via MATLAB Simulink as a unified software environment. Experimental tests are carried out to validate the efficiency of the digital twin developed for an autonomous photovoltaic system demonstrator.

Fuzzy logic control based maximum power point tracking technique in standalone photovoltaic system

This study describes the development of a smart technique for tracking the highest power point on a standalone photovoltaic (SAPV) system when temperature and irradiance conditions are changing using fuzzy logic control (FLC). The PV systems comprises of a PV array, a boost converter, a controller for tracking the maximum power point, and an inverter to power the AC loads. The FLC-based maximum power point tracking (MPPT) is proposed because the technique is not complex and does not need a deep comprehension of the particular model of the system. Furthermore, the technique is efficient and fast response in tracking maximum power (MP) from the PV array. The technique overcame the limitation of the conventional MPPT technique that resulted in slow tracking of the MP and was not accurate on the optimal position of the PV array output power. The SAPV system is integrated with the sealed lead acid (SLA) battery bank as an alternative power source and makes up for power shortages by supplying energy to the load without interruption during power shortages. A system for managing the battery has been included in the system to preserve the battery's longevity by controlling the battery's charging process. The PV system is able to supply single-phase output AC voltage of 230 Vrms and has low total harmonic distortion (THD) that is suitable for home appliances. The achieved simulation results demonstrate the effectiveness of the suggested fuzzy logic controller in tracking the MPP.

A photovoltaic system using supercapacitor energy storage for power equilibrium and voltage stability

<span lang="EN-US">In a photovoltaic system, a stable voltage and of tolerable power equilibrium is needed. Hence, a dedicated analog charge controller for a storage system which controls energy flow to impose power equilibrium, and therefore, voltage stability on the load is required. We demonstrate here our successful design considerations employing supercapacitors as main energy storage as well as a buffer in a standalone photovoltaic system, incorporating a dedicated supercapacitor charge controller for the first time. Firstly, we demonstrated a photovoltaic system employing supercapacitors as main energy storage as well as a buffer in a standalone photovoltaic system. Secondly, we design a constant voltage maximum power point tracker (MPPT) for peak power extraction from the photovoltaic generator. Thirdly, we incorporated a supercapacitor charge controller for power equilibrium and voltage stability through a dedicated analog charge controller in our design, the first of its kind. Fourthly, we analyzed the use of supercapacitor storage to mitigate disequilibrium between power supply and demands, which, in turn, causes overvoltage or under voltage across the load. Lastly, we then went ahead to demonstrate the control of the energy flow in the system so as to maintain rated voltage across a variant demand load.</span>

Towards rural net-zero energy buildings through integration of photovoltaic systems within bio-based earth houses: Case study in Eastern Morocco

Off-grid rural electrification programs involving renewable energy provide effective ways to boost the availability of power in remote areas. Herein, the combination of local bio-based building materials with appropriate sizing of a photovoltaic (PV) system to achieve energy-efficient rural housing in developing countries is investigated. The study focused on the fabrication and laboratory testing of a building material incorporating plant fibers, followed by a feasibility analysis of an integrated stand-alone PV system. EnergyPlus software was used to assess the energy-saving potential of bio-based building envelopes, and Homer Pro software was used for techno-economic optimization. Using a case-study building, various configurations were evaluated in terms of levelized energy cost and net present cost. According to the experimental results, the inclusion of 8 wt% Alfa fibers in earth blocks led to a noteworthy enhancement in the thermal resistance and time lag of the building envelope. Specifically, the improvement ranged from 0.549 to 1.125 m2K/W and from 18.5–h to 23.2–h, respectively, compared to using earth alone. This improvement resulted in a substantial decrease in the building's annual energy consumption, with a reduction of 24.3% for heating and 26.7% for cooling. Furthermore, the techno-economic analysis revealed that the electricity provided by a PV-battery hybrid system was 100% renewable and emission-free, with an energy cost of approximately $0.218/kWh and a present net cost of $11,560.21 These findings indicated that combining available solar energy with locally produced bio-based construction materials could be a viable approach for achieving carbon neutrality and building energy-efficient ulta-low-cost rural housing.

Optimal coordinated energy management strategy for standalone solar photovoltaic system with hybrid energy storage

Energy storage devices and renewable resources, especially rooftop photovoltaic (PV), are vital to the operation of standalone systems. In this study, an energy management strategy (EMS) for battery energy storage systems (BESS), PV, and supercapacitors (SC) is presented. The proposed control strategy is designed to optimize the BESS flow rate, discharge, and charge cycles of the energy system using the Meta-heuristic Jaya algorithm by properly coordinating SC and PV. SC is employed in HESS to fulfill the transient energy mismatches and reduce the transitory high charge/discharge current rate impacts on BESS using EMS. The proposed controller also has the benefit of keeping the battery's SoC within limitations for a long period. To extend the life of BESS, the EMS is aimed at minimizing deep charging and discharging by reducing PV generation, particularly under light load (no-load) situations and when battery and SC's SoC≥SoCmax or charging. Similarly, the optional load shedding is employed when battery and SC's SoC≤SoCmin to avoid deep discharge. The proposed EMS is validated in both simulation environment and hardware-prototype under different perturbations and operating conditions. The charge and discharge rate performance of BESS and SC under different charge and discharge time durations, i.e., 1 s, 2 s, and 3 s, were evaluated in both simulation and hardware, and compared to conventional charge and discharge methods for HESS, whose charge and discharge time durations are nearly 0.3 s to 0.4 s. As a result, battery stress is significantly reduced. Furthermore, the economic analysis of the complete system is carried out. In this, it is observed that standalone PV and HESS systems with the proposed EMS are cost-effective and economical compared with PV and BESS systems when operated for a long horizon beyond 6 years.

The influence of a DC-AC inverter used in a stand-alone vending machine equipped with photovoltaic panels

In this paper, we present an experimental model of a vending machine equipped with a stand-alone photovoltaic system and a DC-AC inverter used as the power supply for the refrigerator’s compressor. The harmonics generated by the inverter will be monitored using a power analyser and processed with a dedicated software. The acquired data is compared to the data obtained from data acquisition board specially built for the experimental model of the vending machine.

A Comparative Life Cycle Assessment and Costing of Lighting Systems for Environmental Design and Construction of Sustainable Roads

The management of the life cycle of the transport network is one of the main challenges of sustainable mobility. Roads and highways cause significant damage to the ecosystem. Specifically, lighting systems contribute to climate change, energy consumption, and human health effects. In this context, this work proposes the combination of life cycle assessment (LCA) with life cycle costing (LCC) to analyze the eco-efficiency of the life cycle of a road, including evaluation of the relative contribution of the lighting system to the total impact. Four scenarios were included in the model: (S1) high-pressure sodium lamps with ballast powered from the grid; (S2) halogen lamps powered from the grid; (S3) light-emitting diode lamps powered from the grid; and (S4) light-emitting diode lamps powered from a standalone photovoltaic system. The life cycle stages of raw material extraction, construction, use, maintenance, and end of road life were included in the analysis. The results show that scenarios S3 and S1 are the most eco-efficient relative to the less favorable S2 scenario (80% and 74% lower, respectively). Scenarios with the least environmental impact are the most economically viable.

Days of autonomy for optimal Battery Sizing in Stand-alone Photovoltaic Systems

The main purpose of our article is to optimize the battery sizing by identifying the most appropriate number of autonomy days. A case study has been established and simulated to define the optimal number. In the others current researches, only a small importance has been attributed to the battery autonomy. The objective is generally to ensure a continuous presence of energy especially for isolated systems while this is not always optimal nor economical and does not necessarily guarantee a safe supply. Nevertheless, an over dimensioning of the battery will lead to a consequent cost and a loss of energy. The results show that the number of days of autonomy must correspond to the minimum ratio linking the lack of energy to the surplus during a specific period.

A Novel MPPT Technique Based on Combination between the Incremental Conductance and Hysteresis Control Applied in a Standalone PV System

A new Maximum Power Point Tracking (MPPT) method, consisting in combining the Incremental Conductance (INC) algorithm with the Hysteresis control, was developed and applied to a standalone photovoltaic (PV) system to generate the maximum power of the PV array. The INC allows one to search for the Maximum Power Point (MPP). The hysteresis improves the accuracy of tracking the MPP very fast even after severe changes in weather conditions and has no oscillations around the MPP. The five-level S-Packed U Cells (SPUC5) inverter is used to transform the produced DC voltage to AC voltage; it generates five-level output voltage with a small number of switches and only DC source voltage. The capacitors of the SPUC5 are controlled by the Pulse Width Modulation (PWM) in order to balance their voltages. The proposed PV system was established and trained in the MATLAB/Simulink environment under various irradiation conditions. A comparison between different MPPT methods, INC-PWM and INC-PI, was investigated in order to examine the effectiveness of the developed MPPT technique in particular, and of all the PV system components. The results of the simulation validate the effectiveness of the suggested MPPT algorithm as well as the used SPUC5 inverter.