Grid-connected Photovoltaic Research Articles

Nonlinear control of grid-connected PV systems using active power filter with three-phase three-level NPC inverter

Grid-connected photovoltaic (PV) systems have become a significant area of interest for research scientists. Given this, this article presents a nonlinear control of grid-connected PV systems using active power filter (APF) with three-phase three-level neutral point clamped (NPC) inverter. The control objectives involve: (1) Forcing the PV output voltage to track a reference signal provided by the MPPT block in order to produce their maximum power, (2) Regulating the DC link voltage to satisfy a correct operation mode of the three-phase active power filter, and (3) Satisfying power factor correction (PFC) objective at the point of common coupling, PCC. Therefore, the suggested control strategy includes a cascade structure of two loops. The inner-loop regulator is designed using the sliding mode control technique and Lyapunov approaches to ensure the PFC objective by forcing the grid current to follow a given reference signal. The Outer-loop consists mainly of a proportional-integral (PI) regulator so that to regulate the output voltage. Further, the theory of instantaneous real power is used to calculate reference harmonics. The effectiveness of the proposed controller is demonstrated through simulation results using MATLAB/Simulink.

Assessing Techno-Economic Value of Battery Energy Storage with Grid-Connected Solar PV Compensation Schemes for Malaysian Commercial Prosumers

Assessing Techno-Economic Value of Battery Energy Storage with Grid-Connected Solar PV Compensation Schemes for Malaysian Commercial Prosumers

A Modified-Simplified MPPT Technique for Three-Phase Single-State Grid-Connected PV Systems

Nowadays, the single state inverter for the grid-connected photovoltaic (PV) systems is becoming more and more popular as they can reduce circuit complexity resulting in less power losses of the inverter. This paper focuses on the use of model predictive control (MPC) to control a 3-phase and 2-level single-state grid-connected inverter in order to regulate the PV maximum power point (MPP). The algorithm of MPC scheme was done to measure the simultaneous current signal including predicting the next sampling current flow. The reference current (Id*) was used to control the distribution of electrical power from the solar cell to the grid. To be able to control the maximum power point tracking (MPPT) when the sunlight suddenly changes, so that a developing MPPT based on estimation current perturbation and observation (ECP&O-MPPT) technique was used to control the reference current. This concept was experimented by using MATLAB/Simulink software package. The proposed technique was tested and compared with the old technique. The simulation results showed that the developed MPPT technique can track the MPP faster when the light changes rapidly under 1,000 W/m2, 25°C standard climatic conditions. The MPPT time was 0.015 s. The total harmonic distortion (THD) was 2.17% and the power factor was 1.

Transformerless Six-Switch (H6)-Based Single-Phase Inverter for Grid-Connected Photovoltaic System With Reduced Leakage Current

Due to the advancements of power electronic devices and photovoltaic (PV) power systems, there has been an increasing interest in transformerless grid-connected PV inverters, which offer lower cost, smaller volume, and higher efficiency than the one with the transformer. However, transformerless inverters with conventional topologies suffer from leakage current problem, which needs to be handled carefully. To overcome the conduction loss and leakage current problem associated with conventional transformerless inverters, a new transformerless H6 (six-switch-based) inverter topology is proposed in this article that can maintain constant common-mode (CM) voltage. At the same time, reduce or eliminate the leakage current problem. The proposed inverter topology is simulated using MATLAB/Simulink software to validate the proposed system's accuracy. The proposed topology's effectiveness is verified through the comparative results of CM voltage, CM leakage current, and conduction loss of the proposed topology with the conventional H6-I, H6-II, and H5 topologies. Finally, to validate the proposed topology, a laboratory prototype is also built and tested. The experimental results validate the theoretical analysis and simulation results.

Hybrid Deep Learning Model for Fault Detection and Classification of Grid-Connected Photovoltaic System

Effective fault detection and classification play essential roles in reducing the hazards such as electric shocks and fire in photovoltaic (PV) systems. However, the issues of interest in fault detection and classification for PV systems remain an open-ended challenge due to manual and time-consuming processes that require the relevant domain knowledge and experience of fault diagnoses. This paper proposes a hybrid deep-learning (DL) model-based combined architectures as the novel DL approaches to achieve the real-time automatic fault detection and classification of a PV system. This research employed the wavelet packet transform (WPT) as a data preprocessing technique to handle the PV voltage signal collected and feeding them as the inputs for combined DL architectures that consist of the equilibrium optimizer algorithm (EOA) and long short-term memory (LSTM-SAE) approaches. The combined DL architectures are able to extract the fault features automatically from the preprocessed data without requiring any previous knowledge, therefore can override the traditional shortages of manual feature extraction and manual selection of optimal features from the extracted fault features. These desirable features are anticipated to speed up the fault detection and classification capability of the proposed DL model with higher accuracy. In order to determine the performance of the proposed fault model, we carried out a comprehensive evaluation study on a 250-kW grid-connected PV system. In this paper, symmetrical and asymmetrical faults have been studied involving all the phases and ground faults such as single phase to ground, phases to phase, phase to phase to ground, and three-phase to ground. The simulation results validate the efficacy of the proposed model in terms of computation time, accuracy of fault detection, and noise robustness. Comprehensive comparisons between the simulation results and previous studies demonstrate the multidisciplinary applications of the present study.

A Grid Frequency Support Control Strategy of the Three Phase Cascaded H-Bridge Based Photovoltaic Generation System

Due to advantages such as being clean and safe, photovoltaic (PV) generation has become an effective way to solve the energy crisis and environmental pollution problems. However, the PV inverter does not have inertia and damping characteristics. With the increased penetration of the PV generation into the power system, large-scale PV grid-connection has posed a great challenge to grid frequency stability. Cascaded H-bridge (CHB) inverter has become a promising candidate for the PV generation system by virtue of advantages such as modular structure and direct grid-connection without power frequency transformers. An inverter control strategy with grid frequency support function is proposed in this paper for the three phase CHB based PV generation system. With the PV string active power reserve, grid frequency dynamic characteristics are improved without energy storage devices. In order to solve the common module power unbalance problem for the CHB topology, the PV string output power is controlled to be balanced with the reserved power distribution control between PV strings proposed in this paper. The H-bridge inverter input power balance is maximized, and balanced three phase grid-connected current output is achieved. The over-modulation risk of H-bridge modules is reduced. At last, simulation models are built in Matlab/Simulink, and a 10kW experimental platform is also built. The effectiveness of the control strategy proposed is validated by simulation and experimental results.

Feasibility Study of the Technical and Economic Performance of Grid-Connected PV System for Selected Rooftops in UTHM

This paper presents the feasibility study of the technical and economic performances of grid-connected photovoltaic (PV) system for selected rooftops in Universiti Tun Hussein Onn Malaysia (UTHM). The analysis of the electricity consumption and electricity bill data of UTHM campus show that the monthly electricity usage in UTHM campus is very high and expensive. The main purpose of this project is to reduce the annual electricity consumption and electricity bill of UTHM with Net Energy Metering (NEM) scheme. Therefore, the grid-connected PV system has been proposed at Dewan Sultan Ibrahim (DSI), Tunku Tun Aminah Library (TTAL), Fakulti Kejuruteraan Awam dan Alam Bina (FKAAS) and F2 buildings UTHM by using three types of PV modules which are mono-crystalline silicon (Mono-Si), poly-crystalline silicon (Poly-Si) and Thin-film. These three PV modules were modeled, simulated and calculated using Helioscope software with the capacity of 2,166.40kWp, 2,046.20kWp and 1,845kWp respectively for the total rooftop area of 190,302.9 ft². The economic analysis was conducted on the chosen three installed PV modules using RETScreen software. As a result, the Mono-Si showed the best PV module that can produce 2,332,327.40 kWh of PV energy, 4.4% of CO₂ reduction, 9.3 years of payback period considering 21 years of the contractual period and profit of RM4,932,274.58 for 11.7 years after payback period. Moreover, the proposed installation of 2,166.40kWp (Mono-SI PV module) can reduce the annual electricity bill and CO2 emission of 3.6% (RM421,561.93) and 4.4% (1,851.40 tCO₂) compared to the system without PV system.

Validation of the procedure: Quantification of the degradation index of Photovoltaic Grid Connection Systems


 
 
 The results obtained from the validation of the procedure ‟Quantification of the degradation index of Photovoltaic Grid Connection Systems” are presented, using statistical parameters, which corroborate its accuracy, achieving a coefficient of determination of 0.9896, a percentage of the root of the mean square of the error RMSPE = 1.498% and a percentage of the mean absolute error MAPE = 1.15%, evidencing the precision of the procedure.
 
 

Optimal sizing of grid-connected photovoltaic system for a large commercial load in Saudi Arabia

Energy mix optimization is considered an essential tool for assessing the efficacy of renewable energy system (RES). Countless approaches have been employed by grid planning engineers and scientists to optimally size grid-connected photovoltaic (PV) systems. Optimizing grid-connected PV systems is beneficial since it causes a reduction in the energy produced by the conventional power plants, and as a result, a reduction in the harmful emissions that are released as by-products. In this study, a large commercial load in the city of Makkah in Saudi Arabia is connected to an optimally designed grid-connected PV systems with the support of a battery storage system (BSS). First, using HOMER software, the system components are chosen by considering the electrical and economic variables. A comparative investigation is carried out for three configuration systems along with the detailed technical study for the proposed systems. Simulation results recommend utilizing a battery system and RES with a minimum cost of energy (COE) of $0.11. Using both HOMER and MATLAB, the PV, converter, and battery system optimal size are estimated by considering the net present cost (NPC), COE, excess electricity and energy savings, emissions, and renewable penetration ratio to find the most economical and environmental-friendly combination. The results show that 1.60 MW is the optimal capacity of each PV, converter, and battery BSS elements to achieve the minimum targeted emission and COE, which resulted in a reduction in the overall NPC of the scheme. When the optimal design is configurated, it is found that the unmet load is zero.

Acceptance Ratio Analysis in Grid-Connected Photovoltaic System: Is There Any Difference Between DC and AC?

The performance status of a grid-connected photovoltaic (GCPV) system is denoted by performance indices, namely performance ratio, capacity factor, and even through power acceptance ratio (AR), as documented in Malaysia Standard (MS) procedures for acceptance test of GCPV testing and commissioning (TNC). Even though AR analysis can be either on the DC or AC side, the MS TNC procedures implemented analysis on the AC side. Therefore, the question arises whether there is any significant difference when using AC AR analysis compared to DC AR analysis in evaluating the system performance. Thus, this paper evaluates the differences between applying DC AR analysis and AC AR analysis in accessing the performance of the ten kWp GCPV system in Malaysia. The AR analytical analysis employed the 2019 one-year historical data of solar irradiance, module temperature, DC power, and AC power. The results demonstrated that the monthly AC AR were consistently lower than DC AR with a percentage difference of approximately 3%. The percentage discrepancy was due to the variation of actual inverter efficiencies compared to the declared constant value by the manufacturer used in the AR prediction model. These findings have verified a significant difference between DC AR analysis and AC AR analysis. Most importantly, this study has highlighted the significance of AC AR analysis compared to DC AR analysis as a tool to evaluate GCPV system performance because AC AR has taken an additional factor into consideration, which is the inverter efficiency variation.

Photovoltaic Power Plant Collection and Connection to HVDC Grid with High Voltage DC/DC Converter

Photovoltaic (PV) power plant collection and connection to a high voltage direct current (HVDC) grid has many advantages. Compared with the traditional AC collection and grid-connection scheme, it can reduce the power conversion links and improve the system efficiency. As one of the most important devices in the application of a PV HVDC collection and grid-connection system, a high voltage, large capacity, high step-up ratio DC/DC converter is the critical technology. A DC/DC converter scheme based on a boost full bridge isolated power module cascaded in input parallel output series (IPOS) structure is proposed to meet the technical requirements of PV power conversion with high voltage, large capacity, and high step-up ratio. The operation mode of the power module is analyzed, the soft switching method is proposed, and the constraint to realize the soft switching of the power module is deduced. Aiming to resolve the problem of multi-module voltage and current equalization in a cascaded DC/DC converter, a distributed module equalization control strategy is proposed to realize the reliable operation of a power module and converter. A 5 kV/80 kW standard power module is developed, the DC/DC converter experimental platform is built, and the proposed system scheme and control strategy are verified by experiments. Based on a 14-power module input parallel output series connection, a ±30 kV/1 MW PV DC/DC converter is developed, a ±30 kV PV HVDC collection and grid-connection demonstration system is established, and the experimental test is completed to realize the stable operation of the system.

A robust model-free controller for a three-phase grid-connected photovoltaic system based on ultra-local model

In this paper, a robust model-free controller for a grid-connected photovoltaic (PV) system is designed. The system consists of a PV generator connected to a three-phase grid by a DC/AC converter. The control objectives of the overall system are to extract maximum power from the PV source, to control reactive power exchange and to improve the quality of the current injected into the grid. The model-free control technique is based on the use of an ultra-local model instead of the dynamic model of the overall system. The local model is continuously updated based on a numerical differentiator using only the input–output behavior of the controlled system. The model-free controller consists of a classical feedback controller and a compensator for the effects of internal parameter changes and external disturbances. Simulation results illustrate the efficiency of the controller for grid-connected PV systems.

Design and simulation of a rooftop PV System in Taylor’s University Lakeside Campus

Solar photovoltaic (PV) system is proven to be a future-proof type of power generation for growing economies. There are almost zero pollutants released, low maintenance cost with high reliability as the lifespan of a solar PV stretches up to 30 years, a well-sought alternative form of sustainable energy. Moreover, the electricity consumption in Taylor’s University (TU), Malaysia is very high, as a consequence, a huge fraction of the fund is used to settle an RM450,000 electricity bill on average annually. In this paper, the study focused on how to reduce electricity consumption in TU by proposing a design of a comprehensive solar PV system. PVSYST and Sketchup software are used to design and analyze the PV system. In the present study, a Grid-Connected Photovoltaic (GCPV) mounted on the available roof space of TU is investigated. Also, a detailed economic analysis that includes the payback period and annual savings achieved through the proposed PV installation is analyzed. Annual savings of RM 267,621.00 can be made upon utilizing the proposed idea. Besides that, TU would be able to recover the initial investment cost in approximately 8 years of payback period, proving that the implementation of a 433kWp of solar PV unit is a smart option to address the sustainable energy goals.

Single-phase grid-connected PV system with golden section search-based MPPT algorithm

Maximum power point tracking (MPPT) is a technique employed for with variable-power sources, such as solar, wind, and ocean, to maximize energy extraction under all conditions. The commonly used perturb and observe (P&O) and incremental conductance (INC) methods have advantages such as ease of implementation, but they also have the challenge of selecting the most optimized perturbation step or increment size while considering the trade-off between convergence time and oscillation. To address these issues, an MPPT solution for grid-connected photovoltaic (PV) systems is proposed that combines the golden section search (GSS), P&O, and INC methods to simultaneously achieve faster convergence and smaller oscillation, converging to the MPP by repeatedly narrowing the width of the interval at the rate of the golden ratio. The proposed MPPT technique was applied to a PV system consisting of a PV array, boost chopper, and inverter. Simulation and experimental results verify the feasibility and effectiveness of the proposed MPPT technique, by which the system is able to locate the MPP in 36 ms and regain a drifting MPP in approximately 30 ms under transient performance. The overall MPPT efficiency is 98.99%.

Control of grid-connected residential solar-PV system using novel adaptive linear combiner filter for power quality improvement

ABSTRACT A grid-connected residential photovoltaic (PV) system has been proposed using novel adaptive linear combiner filter-based control for power quality (PQ) improvement. In the present work, novel adaptive linear combiner (ALC) filter-based control-based control has been proposed to generate reference current. MATLAB/Simulink software is used to develop the two-stage grid-connected residential PV. The proposed control is tested in MATLAB/Simulink2018(a) under nonlinear, linear load and variable input and validated experimentally on prototype hardware. The performance of the proposed ALC filter-based control has been analyzed and compared with that of conventional synchronous d-q control. It has been observed from results that THD in grid current using proposed control is 3.74% whereas using conventional d-q control THD is 4.75%. Proposed control provides more efficient performance by improving the PQ of the system by compensating the harmonics and reactive load demand. Harmonic distortion in the grid current is within the limits as per IEEE-1547. Furthermore, proposed control has better transient response viz. settling time, under shoot and overshoot in DC link voltage during grid connection of rooftop PV system and provides, reduced complexity due to absence of phase lock loop (PLL), thus less sampling time, better accuracy, ease of implementation, and adaptability.

Photovoltaic power prediction based on hybrid modeling of neural network and stochastic differential equation

With the increasing influence of new energy power system, the prediction of Photovoltaic (PV) output power becomes more and more important In this paper, it is the first time to put forward a hybrid modeling method combining long–short term memory recurrent neural network (LSTM) and stochastic differential equation (SDE). This method realizes the prediction of PV output power in different seasons and overcomes the uncertainty of PV power generation. Wavelet analysis and automatic encoder are used to decompose data and extract important features. According to the detailed signal sequence and the approximate signal sequence, the LSTM prediction model is established. Meanwhile, the mathematical model of SDE is established according to the detailed signal sequence. Finally, the output sequences of the two models are reconstructed by wavelet transform. This hybrid model can not only realize the point prediction of PV output power according to the predicted mean value, but also achieve the interval prediction under different confidence levels according to the randomness. In this paper, the proposed method is applied to predict the PV output power of CHINT photovoltaic power generation system with installed capacity of 10MW in different seasons, and the weather forecast data with errors of ±10%, ±20% and ±30% are used. Experimental results prove the effectiveness of the method. In the summer model considering forecast errors within ±20% of weather forecast data, the RMSEs of BP neural network, LSTM and convolutional neural network (CNN) are 5.9468, 5.6762 and 5.8004 respectively. However, the RMSE of the mean prediction with the confidence level of 90% under the proposed method is 4.4647. With this method, the results of interval prediction and point prediction of PV output power can provide better decision support for the stable and safe operation of PV grid connection. They have higher reference value for energy dispatching departments.

Research on the Calculation Method of Distributed Photovoltaic Access Capacity Considering Harmonic Characteristics

To raise the maximum access ability of the maximal distributed photovoltaic system, based on the metering terminal of plant and station system for many years, a nonparametric estimation method based on kernel density is proposed to calculate harmonic probability distribution, this paper proposes the calculation method of superposition index and simultaneous coefficient suitable for distributed photovoltaic grid-connection, and puts forward the capacity calculation method considering harmonic constraints. An example shows that the proposed method can increase the maximum admittance capacity by at least 15% compared with the traditional method under the condition that the harmonic emission level does not exceed the threshold value of national standard, and realize the safe, stable and economic operation.

The influence of shifting the electric bus charging routine on the techno-economic performance of a solar-powered bus depot

Electric buses consume a considerable amount of energy during charging, which inevitably increases the maximum demand (MD) on a system. We have therefore developed a model to investigate the techno-economic feasibility of solar energy for an electric bus depot. The influence of the bus charging routine (BCR) on the techno-economic performance of solar PV systems was investigated. After applying the BCR, results from simulation software provided the optimal hybrid grid-connected PV (GCPV) system of 850 kWp capacity. The cost of energy (COE) and net present cost (NPC) for this system are 0.434 MYR/kWh and 13.3 million MYR, respectively, notably lower than the existing conventional grid system (0.48 MYR/kWh and 14.7 million MYR, respectively). This optimised system significantly reduces the MD by 450 kW and CO2 emission by ∼38% per year. The configuration based on 850 kWp was designed and sized using design software to deliver 3.19 kWh/kWp of energy per day, and to provide a performance ratio (PR) of 82%. Overall, the GCPV system with the BCR is the most feasible option in techno-economic terms, which can reduce the operational cost and carbon emissions in order to develop sustainable transport throughout the region and beyond.

Assessment of Power Quality for Large Scale Utility Grid-Connected Solar Power Plant Integrated System

This paper introduces the simulation and analysis of a three-phase large-scale grid-connected solar Photovoltaic (PV) system in order to assess the effect of integrated PV grid-connected mode on the power quality of the utility grid. The study takes into account the effect of solar system power variation as well as the PV inverter's introduction of penetrating harmonics into the system. The simulation of the system is done in MATLAB software using the SIMULINK environment and is tested by the Pysyst program. Where it is done in real-time with an actual case study on a 1620-kW PV array connected to an 11-kV grid via a three-level Voltage Source Converter (VSC). The technical data was recorded, and the system's power quality was examined. The grid-connected PV system's Performance Ratio (PR) is assessed to determine the PV system's reliability and grid connectivity.

A cartographic approach coupled with optimized sizing and management of an on-grid hybrid PV-solar-battery-group based on the state of the sky: An african case study

A novel optimized sizing and management strategy of a grid-connected hybrid photovoltaic (PV)-solar-battery-group system were proposed for the electrification of residential consumers in Northwest Africa (a case of Mauritania), and the influence of the state of the sky (clear, moderately overcast, and overcast) was analyzed according to the load flowing (LF) and the cycle charging (CC) strategies. In order to mitigate the pressure on the national grid, consolidate the consumer autonomy, minimize the cost of medium- and long-term consumption bills, and CO2-related emissions, a cartographic approach was conducted as the first attempt to map the electricity consumption potential for buildings in the city of Nouakchott (Mauritania) using a geo-referenced database. ArcGIS®, HOMER Pro®, and MATLAB® softwares were used for the establishment of the load profile, optimized sizing of the PV-batteries-group-grid system, and calculation of the lightness index, respectively. The LF strategy provided the best monitoring of the load throughout the day by minimizing the generator uptime. The techno-economic analysis revealed the values of cost of energy (COE) and net present cost (NPC) as follows: COE = $0.0549/kWh and NPC = $24,796 for the LF PV-batteries-grid strategy, COE = 0.0646 $/kWh and NPC = $23,380 for the CC PV-batteries-grid strategy, and COE = $0.17/kWh and NPC = $23,262 for the case of the grid on its own.