- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
Comparison of Different Electric Vehicle Integration Approaches in Presence of Photovoltaic and Superconducting Magnetic Energy Storage Systems
摘要： The impacts of electric vehicles on the electrical power network in the presence of renewable energy sources and energy storage systems is a field to be studied in depth. Especially because in recent years the installation of electric vehicles has increased considerably in order to reduce the emission of CO2 and fossil fuel consumption to reach environmental cleanliness. This paper presents a comparison between the different integration methods of electric vehicles subject to the availability of photovoltaic systems and superconducting magnetic energy storage systems. Moreover, it analyses and explains the issues of power loss, voltage fluctuation, load leveling and reactive power support in the different approaches. Besides that, this study explores the role of superconducting magnetic energy storage systems in different cases. A fuzzy logic control algorithm is proposed to estimate the charging and discharging process of superconducting magnetic energy storage systems and electric vehicles. In addition, a coordinated control system is proposed to manage the power between the photovoltaic system, the electric vehicles and superconducting magnetic energy storage system as well as boost the power system performance. A whole coordinated control system based on fuzzy logic control is proposed to make the power management of the grid, EVs, SMES, and PV in an all integration approach of electric vehicles to achieve the improvements in the power system performance and maintain the reliability and sustainability of the all system components. Finally, the data analysis of the simulation results, performed by the Matlab Simulink toolbox is presented in all cases to explain the performance of the superconducting magnetic energy storage system, the control system, power losses, voltage fluctuation and reactive power support.
关键词： Fuzzy Logic Controller (FLC),Photovoltaic system (PV),Coordinated Control,Electric Vehicles (EVs),Superconducting Magnetic Energy Storage (SMES),Different Integration Approach,Power loss and Voltage Control
更新于2025-09-23 15:19:57
-
[IEEE 2020 IEEE International Conference on Big Data and Smart Computing (BigComp) - Busan, Korea (South) (2020.2.19-2020.2.22)] 2020 IEEE International Conference on Big Data and Smart Computing (BigComp) - Normalized Residue Analysis for Deep Learning Based Probabilistic Forecasting of Photovoltaic Generations
摘要： In this study, probabilistic forecasting schemes of day-ahead photovoltaic (PV) generations are investigated with the auto-regressive recurrent neural network model named DeepAR, and are evaluated based on the normalized residues. For PV generations, probabilistic outcomes should be helpful for efficient grid managements to account uncertainties such as sudden changes in the local weather. The tightness of the prediction interval for local PV generations is investigated with DeepAR models with varying input data like the local weather forecasts of the day and historical records of the PV generations. For performance measure, normalized residue with the mean and standard deviation of the predicted traces is compared to the standard normal distribution. For evaluation, local PV generation data captured at Hadong, Korea is tested by the DeepAR models with optional input of local weather forecasts data. The evaluation results of the PV generation tests show that the local weather data provides extra tightness of the prediction interval with the normalized residues close to the standard normal distribution.
关键词： standard score,probabilistic forecasting,photovoltaic system
更新于2025-09-23 15:19:57
-
Robust Method for Diagnosis and Detection of Faults in??Photovoltaic Systems Using Artificial Neural Networks
摘要： During their operation, PV systems can be subject of various faults and anomalies that could lead to a reduction in the effectiveness and the profitability of the PV systems. These faults can crash, cause a fire or stop the whole system. The main objective of this work is to present a sophisticated method based on artificial neural networks ANN for diagnosing; detecting and precisely classifying the fault in the solar panels in order to avoid a fall in the production and performance of the photovoltaic system. The work established in this paper intends in first place to propose a method to detect possible various faults in PV module using the Multilayer Perceptron (MLP) ANN network. The developed artificial neural network requires a large database and periodic training to evaluate the output parameters with good accuracy. To evaluate the accuracy and the performance of the proposed approach, a comparison is carried out with the classic method (the method of thresholding). To test the effectiveness of the proposed approach in detecting and classifying different faults, an extensive simulation is carried out using Matlab SIMULINK.
关键词： diagnosis,artificial neural networks,faults detection,photovoltaic system,method of thresholding
更新于2025-09-23 15:19:57
-
Reliability Analysis of Distributed Grid-connected Photovoltaic System Monitoring Network
摘要： A large amount of distributed grid-connected Photovoltaic systems have brought new challenges to the dispatching of power network. Real-time monitoring the PV system can efficiently help improve the ability of power network to accept and control the distributed PV systems, and thus mitigate the impulse on the power network imposed by the uncertainty of its power output. To study the reliability of distributed PV monitoring network, it is of great significance to look for a method to build a highly reliable monitoring system, analyze the weak links and key nodes of its monitoring performance in improving the performance of the monitoring network. Firstly a reliability model of PV system was constructed based on WSN technology. Then, in view of the dynamic characteristics of the network’s reliability, fault tree analysis was used to judge any possible reasons that cause the failure of the network and logical relationship between them. Finally, the reliability of the monitoring network was analyzed to figure out the weak links and key nodes. This paper provides guidance to build a stable and reliable monitoring network of a distributed PV system.
关键词： Monitoring Network,Fault Tree Analysis,Photovoltaic System,WSN,Reliability
更新于2025-09-23 15:19:57
-
Linear-Gompertz Model-Based Regression of Photovoltaic Power Generation by Satellite Imagery-Based Solar Irradiance
摘要： A simple yet accurate photovoltaic (PV) performance curve as a function of satellite-based solar irradiation is necessary to develop a PV power forecasting model that can cover all of South Korea, where more than 35,000 PV power plants are currently in operation. In order to express the nonlinear power output of the PV module with respect to the hourly global horizontal irradiance derived from satellite images, this study employed the Gompertz model, which is composed of three parameters and the sigmoid equation. The nonphysical behavior of the Gompertz model within the low solar irradiation range was corrected by combining a linear equation with the same gradient at the conjoint point. The overall ?tness of Linear-Gompertz regression to the 242 PV power plants representing the country was R2 = 0.85 and nRMSE = 0.09. The Gompertz model coe?cients showed normal distributions and equivariance of standard deviations of less than 15% by year and by season. Therefore, it can be conjectured that the Linear-Gompertz model represents the whole country’s PV system performance curve. In addition, the Gompertz coe?cient C, which controls the growth rate of the curve, showed a strong correlation with the capacity factor, such that the regression equation for the capacity factor could be derived as a function of the three Gompertz model coe?cients with a ?tness of R2 = 0.88.
关键词： photovoltaic system performance,Gompertz model,power output prediction,satellite-derived global horizontal irradiance,numerical analysis
更新于2025-09-23 15:19:57
-
Performance analysis of the Single-Phase Grid-Connected Inverter of a photovoltaic system in water and wind applications
摘要： Single-phase grid connected inverters are nowadays broadly developed and tested in various types of applications especially in photovoltaic systems. The main aim of the inverter control strategy is to extract the maximum energy from the PV system which corresponds to the maximum power at certain conditions. However, the MPPT methods are also important in other renewable energy conversion systems. This paper analyses the performance of a commercially available photovoltaic inverter in water and wind systems. Presented models are implemented in a laboratory test bench in the form of torque characteristics realised by an induction motor fed by the inverter with vector control. The parameters are scaled into relative variables to provide a proper performance comparison. Presented tests include step response to assess the performance of a system dynamic. The dynamic tests showed a fast response of the investigated systems. The MPPT tracking accuracy tested under realistic profiles is similar for both cases: 98% and 96% respectively for the wind and water systems. These results prove the satisfactory performance of the MPPT of the PV microinverter in these applications.
关键词： Single-phase grid-connected inverter,wind turbine,water turbine,MPPT,photovoltaic system
更新于2025-09-23 15:19:57
-
[IEEE 2019 International Conference on Power Electronics, Control and Automation (ICPECA) - New Delhi, India (2019.11.16-2019.11.17)] 2019 International Conference on Power Electronics, Control and Automation (ICPECA) - Fault Identification Algorithm for Grid Connected Photovoltaic Systems using Machine Learning Techniques
摘要： The motivation and background behind the fault detection for grid connected solar power plant is presented in this paper. The major issues encountered when integrating a PV system to the grid include multi-peak phenomenon due to partial shading, regulation of circulating currents, the impact of grid impedances on PV system stability, Fault Ride-Through (FRT) Capability, and anti-islanding detection. Hence, fault detection and condition monitoring system are necessary for smooth operation. In this paper, a fault classification technique for single-phase grid connected PV systems is developed. Wavelet Transform and Neural network approaches are used for developing the fault classification algorithm. The results depicted that the developed fault detection algorithm shows a significant improvement in the classification accuracy with 98.4%.
关键词： Wavelet Transform,fault classification,fault diagnosis,Neural Network,Photovoltaic System
更新于2025-09-23 15:19:57
-
A novel adaptive command-filtered backstepping sliding mode control for PV grid-connected system with energy storage
摘要： In order to solve the problems of power fluctuation in the photovoltaic (PV) grid-connected system and the nonlinearity in the model of inverters, a projection-based adaptive backstepping sliding mode controller with command-filter is designed in the system to adjust the DC-link voltage and the AC side current in the PV grid-connected system. Firstly, the mathematical model of the inverter in PV system is established, then backstepping control method is applied to control it, and the command filter is added to the controller to eliminate the differential expansion of the backstepping controller. Furthermore, the adaptive law based on Lyapunov stability theory is designed to estimate the uncertain parameters in the grid-connected inverter. A projection algorithm is introduced into the adaptive controller due to the demand of guaranteeing the bounded estimated value. Additionally, a sliding mode controller is increased to improve its robustness in this system. Considering the influence of irradiation and temperature changes, a battery energy storage system (BESS) is applied on the DC side to suppress the fluctuation of the output power of the PV system. Finally, the simulation results demonstrate that the presented strategy can control precisely the grid-connected inverter.
关键词： Photovoltaic system,Battery energy storage,Projection adaptive,Sliding mode,Command-filtered backstepping
更新于2025-09-23 15:19:57
-
A High Performance Shade-Tolerant MPPT Based on Current-Mode Control
摘要： This paper proposes a high performance shade-tolerant maximum power point tracking (STMPPT) technique for DC-DC converter stage of photovoltaic (PV) applications. The average current-mode control (ACMC) is utilized to regulate the PV array current using two feedback control loops. The current-mode control is a superior scheme in control of DC-DC power electronic converters. The proposed STMPPT technique operates in two modes. The ACMC with the perturb and observe (P&O) MPPT algorithm functions in a local MPPT (LMPPT) mode under normal irradiance condition. When the PV array is likely to be partially shaded, a global MPPT (GMPPT) subroutine effectively scans the PV profile to optimize the PV system operation. This is achieved by implementing simple innovations to the ACMC-based P&O algorithm. The innovations benefit from useful observations of I-V characteristics. The idea behind using the I-V characteristics is to significantly reduce the search space, make the algorithm independent of shading conditions and PV array configuration, and inherently recognize the occurrence of partial shading conditions (PSCs). The proposed STMPPT technique enables very fast and reliable tracking of global maximum power point (GMPP). In addition, it can stably work under dynamic environmental change without losing correct sense of tracking direction. Its simplicity and independency would offer a viable solution for PV converter products. Simulation and experimental performance assessments are presented under different operating conditions that could happen in outdoor PV installations.
关键词： perturb and observe algorithm,partial shading condition,Photovoltaic system,current-mode control,shade-tolerant maximum power point tracking
更新于2025-09-19 17:15:36
-
A novel photovoltaic-pumped hydro storage microgrid applicable to rural areas
摘要： This paper proposes a novel photovoltaic-pumped hydro storage microgrid design, which is more cost-effective than photovoltaic-battery systems. Existing irrigation infrastructure is modified in order to store energy at a low cost. This energy storage system pumps water from the bottom of a water well to a reservoir at ground level to store surplus energy in the form of gravitational potential energy. This stored water can be released back to the well through a turbine to generate clean electricity when it is needed, or it can be used for irrigation. This microgrid needs a complex management system that takes into account energy generation, energy demand, water demand, energy tariff, and system losses to determine pump power, turbine flow rate, as well as irrigation times. The proposed energy management system considers the current and future state of the system and compares cost-saving and feed-in income for each decision by using two forecasting methods and a multi-level optimisation algorithm. The performance of the management system is experimentally verified on a real pump and turbine. The objective of this study is not only to manage pump power and turbine flow rate, but also to manage irrigation times and water volume. The results show that adding irrigation and water management assist the energy management system in using stored water more efficiently. As a result, electricity costs are reduced by more than 31% compared to existing management methods. The proposed system is simulated in MATLAB to calculate annual electricity costs. The payback period and lifetime benefit of the proposed storage are calculated to investigate the economic aspects of the system.
关键词： Pumped hydro storage system,Microgrid,Energy management system,Energy storage system,Solar photovoltaic system,Renewable energy
更新于2025-09-19 17:13:59