Improvements in the Production, Monitoring, Management and Impact on the Grid of Photovoltaic Installations
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Editors
Dr. Isabel Santiago Chiquero
Dr. Isabel Santiago Chiquero
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Website
Guest Editor
Electronic and Computer Engineering Department, Electronic Technology Area, School of Engineering Sciences, University of Córdoba, Campus of Rabanales, Leonardo da Vinci Building, E-14071 Córdoba, Spain
Interests: photovoltaic energy; electricity demand modelling
Dr. Isabel María Moreno García
Dr. Isabel María Moreno García
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Website
Guest Editor
Electronic and Computer Engineering Department, Electronic Area, School of Engineering Sciences, University of Córdoba, Campus of Rabanales, Leonardo da Vinci Building, E-14071 Córdoba, Spain
Interests: photovoltaic energy; power quality
Dr. Rafael López Luque
Dr. Rafael López Luque
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Website
Guest Editor
Full professor of the University of Córdoba, Spain.
Applied Physics Department.
Campus of Rabanales, C2 Building, E-14071 Córdoba, Spain.
Interests: solar energy; sustainable buildings
Topical Collection Information
Dear Colleagues,
Photovoltaic (PV) systems, due to their technological development and the lower price of their components, have turned out to be one of the most competitive sources of energy, reaching important figures of installed power worldwide in the last few years. They are being considered as one of the renewable energy that will help in achieving the transition to the future energy system, providing the extra electricity generation that will be required for the electrification of mobility and helping to achieve the challenges of reducing the level of polluting emissions, to which most countries have committed themselves.
The full integration of this type of distributed renewable plant into the grid still faces many challenges. On the one hand, it is important to achieve an improvement in their production, technologically increasing the efficiencies of their components, and improving their operation and maintenance interventions. On the other hand, it is necessary to work on improving the prediction and manageability of their production, subject to the unforeseen weather conditions, by taking into account the installations both at the individual and at the aggregate level, if they operate in the same service area. Improving the coverage of the demand in self-consumption facilities through demand management techniques or by making use of storage systems is another of the challenges of this type of facility. It is also important to analyze and improve the impact of this type of installation on the supply network and on the quality of the network signal, the consequences of which have not yet been evaluated at a global level, in addition to studying the network’s hosting capacity.
For all these challenges, it is essential to be able to tackle the study of the installations and their operation, developing advanced monitoring systems, including synchronization systems for measurements, platforms for data processing, and information visualization, applying increasingly advanced techniques such as artificial intelligence as well as machine and deep learning, which help to extract the information that makes it possible to optimize the management, control, and intelligent programming of photovoltaic production.
This Special Issue is therefore dedicated to all the works that may represent an advance in any of the challenges proposed for improvement of the production of photovoltaic installations, their management, and their impact on the electricity grid. We look forward to receiving your contributions.
Dr. Isabel Santiago Chiquero
Dr. Isabel María Moreno García
Dr. Rafael López Luque
Guest Editors
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Keywords
- photovoltaic (PV) energy production
- efficiency improvement
- monitoring and communication in PV plants
- synchronized measures in PV plants
- operation and maintenance
- failure detection
- production predictability and dispatchability
- smoothing of production fluctuations
- energy storage
- self-consumption
- power quality and grid impact
- hosting capacity
Published Papers (21 papers)
Open AccessArticle
Energy Efficiency Improvement in Reconfigurable Photovoltaic Systems: An Evaluation of Team Systems
by
Roohollah Afzali and Guillermo Velasco-Quesada
Viewed by 421
Abstract
The main objective of this work is to evaluate the energy efficiency improvement obtained in grid-connected photovoltaic systems based on a dynamic reconfiguration strategy. The MIX and team reconfigurable photovoltaic system topologies have been considered since both minimize the operation of the inverters
[...] Read more.
The main objective of this work is to evaluate the energy efficiency improvement obtained in grid-connected photovoltaic systems based on a dynamic reconfiguration strategy. The MIX and team reconfigurable photovoltaic system topologies have been considered since both minimize the operation of the inverters in low-load conditions. A numerical method is used to analyze the energy flows within the photovoltaic system, with a specific focus on the plant-oriented configuration. In this work, MIX systems are only presented briefly, while team reconfigurable photovoltaic systems are analyzed in more detail. This is because team systems can be implemented using conventional commercial inverters, electromechanical switches to redirect power flows, and a simple digital controller (as based on the Arduino platforms). The energy supplied to the grid by two grid-connected photovoltaic systems will be evaluated: one based on a classic non-reconfigurable strategy and another based on the team strategy. The measurement of the energy generated by these two systems, tested under various irradiance levels (emulating different climatic conditions), shows that reconfigurable systems always exhibit greater energy efficiency. However, this energy improvement can only be considered substantial in certain situations.
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Open AccessArticle
Novel Incremental Conductance Feedback Method with Integral Compensator for Maximum Power Point Tracking: A Comparison Using Hardware in the Loop
by
Sérgio André, Fernando Silva, Sónia Pinto and Pedro Miguens
Cited by 1 | Viewed by 1102
Abstract
Research on renewable energy sources and power electronic converters has been increasing due to environmental concerns. Many countries have established targets to decrease CO
2 emissions and boost the proportion of renewable energy, with solar power being a prominent area of investigation in
[...] Read more.
Research on renewable energy sources and power electronic converters has been increasing due to environmental concerns. Many countries have established targets to decrease CO
2 emissions and boost the proportion of renewable energy, with solar power being a prominent area of investigation in the recent literature. Techniques are being developed to optimize the energy recovered from PV cells and increase system efficiency, including modeling PV cells, the use of converter topologies to connect PV systems to high-power inverters, and the use of MPPT methods. Certain MPPT algorithms are intricate and demand high processing power. The literature describes several MPPT methods; however, the number of hardware resources required by MPPT algorithms is typically not disclosed. This work proposes a novel MPPT technique based on integral feedback conductance and incremental conductance error, considering the current dynamics of the boost converter. This MPPT algorithm is compared to the most widely used techniques in the literature and evaluates each method’s efficiency, performance, and computational needs using an HIL system. Comparisons are made with well-known MPPT algorithms, such as perturb and observe, incremental conductance, and newer techniques based on fuzzy logic and neural networks (NNs). As the NN that is most widely used in the literature depends on irradiation and temperature, an additional NN that is trained using the proposed method is also investigated.
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Open AccessFeature PaperArticle
Design and Development of a Relational Database Management System (RDBMS) with Open Source Tools for the Processing of Data Monitored in a Set of Photovoltaic (PV) Plants
by
David Trillo-Montero, Samuel Cosano-Lucena, Miguel Gonzalez-Redondo, Juan Jesus Luna-Rodriguez and Isabel Santiago
Cited by 3 | Viewed by 2342
Abstract
The objective of this work has been to implement an orderly, accessible, fast and space-saving storage system that allows the transfer to a Relational Database Management System (RDBMS) of all the data corresponding to the monitoring of a set of photovoltaic (PV) systems
[...] Read more.
The objective of this work has been to implement an orderly, accessible, fast and space-saving storage system that allows the transfer to a Relational Database Management System (RDBMS) of all the data corresponding to the monitoring of a set of photovoltaic (PV) systems whose behaviour is to be analysed. The RDBMS consists of a series of linked databases, enabling all PV system information to be stored, and it is scalable so it can be expanded depending on the number of installations to be studied. The data recorded in the plants are found in a large number of very disaggregated files, and with different measured parameters, different formats, nomenclatures, or units of measurement, so the developed system is responsible for homogenising all the information for storage. For this purpose, a procedure has been developed to carry out the automatic transfer of all the data recorded in their corresponding databases. In addition, in this work, a web application called
S·lar 2 has been developed to facilitate selective access to all the data once stored in the corresponding tables. This application, which is connected to the designed databases, allows the storage and management of the information coming from the PV plants, in order to determine, among other things, the operation mode of each of the components of these facilities. Using the data already organised, it has also been possible to establish a system for comparing the production of inverters within the same plant in order to have a tool that allows the quick and visual detection of possible deviations between them and thus detect malfunctions in any of the components. The whole procedure has been carried out using free software, such as Maria DB and Python.
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Open AccessArticle
Health Monitoring and Fault Detection in Photovoltaic Systems in Central Greece Using Artificial Neural Networks
by
Elias Roumpakias and Tassos Stamatelos
Cited by 3 | Viewed by 1748
Abstract
The operation and maintenance of a photovoltaic system is a challenging task that requires scientific soundness, and has significant economic impact. Faults in photovoltaic systems are a common phenomenon that demands fast diagnosis and repair. The effective and accurate diagnosis and categorization of
[...] Read more.
The operation and maintenance of a photovoltaic system is a challenging task that requires scientific soundness, and has significant economic impact. Faults in photovoltaic systems are a common phenomenon that demands fast diagnosis and repair. The effective and accurate diagnosis and categorization of faults is based on information received from the photovoltaic plant monitoring and energy management system. This paper presents the application of machine learning techniques in the processing of monitoring datasets of grid connected systems in order to diagnose faults. In particular, monitoring data from four photovoltaic parks located in Central Greece are analyzed. The existing data are divided for training and validation procedures. Different scenarios are examined first, in order to observe and quantify the behavior of artificial neural networks in already known faults. In this process, the faults are divided in three main categories. The system’s performance deviation against the prediction of the trained artificial neural network in each fault category is processed by health monitoring methodology in order to specify it quantitatively.
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Open AccessArticle
Machine Learning and Deep Learning Models Applied to Photovoltaic Production Forecasting
by
Moisés Cordeiro-Costas, Daniel Villanueva, Pablo Eguía-Oller and Enrique Granada-Álvarez
Cited by 13 | Viewed by 1880
Abstract
The increasing trend in energy demand is higher than the one from renewable generation, in the coming years. One of the greatest sources of consumption are buildings. The energy management of a building by means of the production of photovoltaic energy in situ
[...] Read more.
The increasing trend in energy demand is higher than the one from renewable generation, in the coming years. One of the greatest sources of consumption are buildings. The energy management of a building by means of the production of photovoltaic energy in situ is a common alternative to improve sustainability in this sector. An efficient trade-off of the photovoltaic source in the fields of Zero Energy Buildings (ZEB), nearly Zero Energy Buildings (nZEB) or MicroGrids (MG) requires an accurate forecast of photovoltaic production. These systems constantly generate data that are not used. Artificial Intelligence methods can take advantage of this missing information and provide accurate forecasts in real time. Thus, in this manuscript a comparative analysis is carried out to determine the most appropriate Artificial Intelligence methods to forecast photovoltaic production in buildings. On the one hand, the Machine Learning methods considered are Random Forest (RF), Extreme Gradient Boost (XGBoost), and Support Vector Regressor (SVR). On the other hand, Deep Learning techniques used are Standard Neural Network (SNN), Recurrent Neural Network (RNN), and Convolutional Neural Network (CNN). The models are checked with data from a real building. The models are validated using normalized Mean Bias Error (nMBE), normalized Root Mean Squared Error (nRMSE), and the coefficient of variation (R
2). Standard deviation is also used in conjunction with these metrics. The results show that the models forecast the test set with errors of less than 2.00% (nMBE) and 7.50% (nRMSE) in the case of considering nights, and 4.00% (nMBE) and 11.50% (nRMSE) if nights are not considered. In both situations, the R
2 is greater than 0.85 in all models.
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Open AccessArticle
Weather Files for the Calibration of Building Energy Models
by
Vicente Gutiérrez González, Germán Ramos Ruiz, Hu Du, Ana Sánchez-Ostiz and Carlos Fernández Bandera
Cited by 5 | Viewed by 1510
Abstract
In the fight against climate change, energy modeling is a key tool used to analyze the performance of proposed energy conservation measures for buildings. Studies on the integration of photovoltaic energy in buildings must use calibrated building energy models, as only with them
[...] Read more.
In the fight against climate change, energy modeling is a key tool used to analyze the performance of proposed energy conservation measures for buildings. Studies on the integration of photovoltaic energy in buildings must use calibrated building energy models, as only with them is the demand curve real, and the savings obtained at the self-consumption level, energy storage in the building, or feed into the grid are accurate. The adjustment process of a calibrated model depends on aspects inherent to the building properties (envelope parameters, internal loads, use schedules) as well as external to them (weather, ground properties, etc.). Naturally, the uncertainty of each is essential to obtaining good results. As for the meteorological data, it is preferable to use data from a weather station located in the building or its surroundings, although this is not always possible due to the cost of the initial investment and its maintenance. As a result, weather stations with public access to their data, such as those located at airports or specific locations in cities, are largely used to perform calibrations of building energy models, making it challenging to converge the simulated model with measured data. This research sheds light on how this obstacle can be overcome by using weather data provided by a third-party company, bridging the gap between reality and energy models. For this purpose, calibrations of the two buildings proposed in Annex 58 were performed with different weather configurations, using the mean absolute error (MAE) uncertainty index and Spearman’s rank correlation coefficient (rho) as comparative measures. An optimal and cost-effective solution was found as an alternative to an on-site weather station, based on the use of a single outdoor temperature sensor in combination with third-party weather data, achieving a robust and reliable building energy model.
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Open AccessArticle
Prediction of a Grid-Connected Photovoltaic Park’s Output with Artificial Neural Networks Trained by Actual Performance Data
by
Elias Roumpakias and Tassos Stamatelos
Cited by 15 | Viewed by 1792
Abstract
Increased penetration of grid-connected PV systems in modern electricity networks induces uncertainty factors to be considered from several different viewpoints, including the system’s protection and management. Accurate short-term prediction of a grid-connected PV park’s output is essential for optimal grid control and grid
[...] Read more.
Increased penetration of grid-connected PV systems in modern electricity networks induces uncertainty factors to be considered from several different viewpoints, including the system’s protection and management. Accurate short-term prediction of a grid-connected PV park’s output is essential for optimal grid control and grid resilience. Out of the numerous types of models employed to this end during the last decade, artificial neural networks, (ANNs) have proven capable of handling the uncertainty issues of solar radiation. Insolation and ambient, or panel temperature, are most commonly employed as the independent variables, and the system’s output power is successfully predicted within 3 to 5% error. In this paper, we apply a common type of ANN for the long-term prediction of a 100 kWp grid-connected PV park’s output, by exploiting experimental data from the last 8 years of operation. Solar radiation and backsheet temperature were utilized for the ANN training stage. The performance metrics of this model, along with a standard linear regression model, are compared against the actual performance data. The capabilities of the ANN model are exploited in the effort to decouple the fluctuating effect of PV panel soiling which interferes with the efficiency degradation process. The proposed methodology aimed to quantify degradation effects and is additionally employed as a fault diagnosis tool in long-term analysis.
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Open AccessArticle
Current Sensorless MPPT Control for PV Systems Based on Robust Observer
by
David Cortes-Vega, Hussain Alazki and Jose Luis Rullan-Lara
Cited by 4 | Viewed by 1959
Abstract
Photovoltaic (PV) systems are among the most used alternatives for electrical power generation from renewable sources. To ensure that PV systems make the most of the available solar energy, maximum power point tracking (MPPT) schemes must be implemented, which usually require voltage and
[...] Read more.
Photovoltaic (PV) systems are among the most used alternatives for electrical power generation from renewable sources. To ensure that PV systems make the most of the available solar energy, maximum power point tracking (MPPT) schemes must be implemented, which usually require voltage and current sensors to track the PV power. This paper presents the design of a robust observer using the Attractive Ellipsoid Method to achieve a precise estimation of PV current under parametric uncertainty and output perturbations. The application of such an observer enables the PV generation system to operate in a current sensorless mode, which reduces the overall cost of the system and enhances its reliability. The convergence of the observer is guaranteed by solving an optimization problem which generates the optimal gains using Linear Matrix Inequalities (LMI). To prove the effectiveness of the proposed sensorless scheme, simulations are performed in Matlab under test profiles based on the EN50530 standard and parameter uncertainty conditions, obtaining an accurate estimation which is used for MPPT operation.
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Open AccessReview
A Note on Limits and Trends in PV Cells and Modules
by
Vitezslav Benda and Ladislava Cerna
Cited by 8 | Viewed by 2403
Abstract
The key components of photovoltaic (PV) systems are PV modules representing basic devices, which are able to operate in outdoor conditions for a long time. PV modules can be manufactured from different materials using different production technologies. The main criterion supporting or limiting
[...] Read more.
The key components of photovoltaic (PV) systems are PV modules representing basic devices, which are able to operate in outdoor conditions for a long time. PV modules can be manufactured from different materials using different production technologies. The main criterion supporting or limiting the successful placement of specific technologies on the market is the price of electricity produced by PV systems. The levelized cost of energy (LCOE) method considers investment costs, operating costs, and the total energy produced during a PV system’s service life. The influence of price, efficiency, and service life of PV modules on the LCOE (together with the availability of materials) sets limits for applicable technologies. Increasing the efficiency of the modules from 21% to 23% could lead to a reduction of the area-dependent part of the PV system costs by 8.7%. Extending the service life from 25 to 30 years could reduce the LCOE by about 10%. As shown in the work, wafer-based crystalline silicon technologies best meet these criteria due to their high efficiency, low costs, long service life, and the availability of materials at present. Technological innovations make it possible to increase the efficiency of the modules closer to the physical limits and to extend the service life of the modules.
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Open AccessArticle
Transient Differentiation Maximum Power Point Tracker (Td-MPPT) for Optimized Tracking under Very Fast-Changing Irradiance: A Theoretical Approach for Mobile PV Applications
by
Roberto I. Rico-Camacho, Luis J. Ricalde, Ali Bassam, Manuel I. Flota-Bañuelos and Alma Y. Alanis
Cited by 4 | Viewed by 1792
Abstract
This work presents an algorithm for Maximum Power Point Tracking (MPPT) that measures transitory states to prevent drift issues and that can reduce steady-state oscillations. The traditional MPPT algorithms can become confused under very fast-changing irradiance and perform tracking in the wrong direction.
[...] Read more.
This work presents an algorithm for Maximum Power Point Tracking (MPPT) that measures transitory states to prevent drift issues and that can reduce steady-state oscillations. The traditional MPPT algorithms can become confused under very fast-changing irradiance and perform tracking in the wrong direction. Errors occur because these algorithms operate under the assumption that power changes in the system are triggered exclusively due to perturbations introduced by them. However, the power increase triggered by irradiance changes could be more significant than those caused by the perturbation effect. The proposed method modifies the Perturb and Observe algorithm (P&O) with an additional measurement stage performed close to the maximum overshoot peak after the perturbation stage. By comparing power changes between three measurement points, the algorithm can accurately identify whether the perturbation was made in the correct direction or not. Furthermore, the algorithm can use additional information to determine if the operating point after the perturbation stage is beyond the maximum power point (MPP) and perturb in the opposite direction for the next iteration. Thus, the proposed algorithm shows reduced steady-state oscillations and improved tracking under fast irradiance changes compared to conventional P&O and P&O with power differences (dP-P&O). The design is validated via simulations using fast-changing irradiance tests based on the standard EN 50530 accelerated by a factor of 100×. The proposed algorithm achieved 99.74% of global efficiency versus 97.4% of the classical P&O and 99.54% of the dP-P&O under the tested conditions.
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Open AccessArticle
Analysis of Some Power Quality Parameters at the Points of Common Coupling of Photovoltaic Plants Based on Data Measured by Inverters
by
Isabel Santiago, Javier García-Quintero, Gonzalo Mengibar-Ariza, David Trillo-Montero, Rafael J. Real-Calvo and Miguel Gonzalez-Redondo
Cited by 3 | Viewed by 1991
Abstract
With the increasing implementation of renewable energies, the impact that this type of installation can have on the electricity supply grid is of great importance. In this context, the aim of this work is to analyse how the production and injection of electricity
[...] Read more.
With the increasing implementation of renewable energies, the impact that this type of installation can have on the electricity supply grid is of great importance. In this context, the aim of this work is to analyse how the production and injection of electricity generated by a series of small photovoltaic (PV) installations influence some parameters of the electricity grid in the low-voltage (LV) distribution networks to which they are connected, by analysing the basic data provided by the inverters of these installations. The presence of a slight rise in the grid voltage values in the Point of Common Coupling (PCC) as the production of the PV plants increases has been verified, with maximum slopes between 0.95 and 0.00027 V/kW, but which do not result in voltage values close to the limits set by the regulations. In addition to assessing this impact, the results obtained made it possible to determine the hosting capacity that the networks into which these installations inject their energy would have for this type of installation so as not to have a detrimental effect on the voltage values of the grid. The possible influence of the production of PV installations on the voltage imbalance between phases or on the frequency of the grid has also been analysed in this work. Although the values recorded by the inverters have limitations in their measurements that do not make them valid for assessing events such as the presence of harmonics or flickers, they do allow a first analysis to be made of the influence of PV plant production on some grid parameters, without the need to incorporate additional measurement systems in these renewable installations. However, it is important to be aware of the limitations of the measurements of this equipment and, as far as possible, to choose inverter models that carry out this type of measurement as completely as possible.
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Open AccessArticle
Efficient Reduction in the Annual Investment Costs in AC Distribution Networks via Optimal Integration of Solar PV Sources Using the Newton Metaheuristic Algorithm
by
Oscar Danilo Montoya, Luis Fernando Grisales-Noreña, Lázaro Alvarado-Barrios, Andres Arias-Londoño and Cesar Álvarez-Arroyo
Cited by 15 | Viewed by 1735
Abstract
This research addresses the problem of the optimal placement and sizing of (PV) sources in medium voltage distribution grids through the application of the recently developed Newton metaheuristic optimization algorithm (NMA). The studied problem is formulated through a mixed-integer nonlinear programming model where
[...] Read more.
This research addresses the problem of the optimal placement and sizing of (PV) sources in medium voltage distribution grids through the application of the recently developed Newton metaheuristic optimization algorithm (NMA). The studied problem is formulated through a mixed-integer nonlinear programming model where the binary variables regard the installation of a PV source in a particular node, and the continuous variables are associated with power generations as well as the voltage magnitudes and angles, among others. To improve the performance of the NMA, we propose the implementation of a discrete–continuous codification where the discrete component deals with the location problem and the continuous component works with the sizing problem of the PV sources. The main advantage of the NMA is that it works based on the first and second derivatives of the fitness function considering an evolution formula that contains its current solution
and the best current solution
, where the former one allows location exploitation and the latter allows the global exploration of the solution space. To evaluate the fitness function and its derivatives, the successive approximation power flow method was implemented, which became the proposed solution strategy in a master–slave optimizer, where the master stage is governed by the NMA and the slave stage corresponds to the power flow method. Numerical results in the IEEE 34- and IEEE 85-bus systems show the effectiveness of the proposed optimization approach to minimize the total annual operative costs of the network when compared to the classical Chu and Beasley genetic algorithm and the MINLP solvers available in the general algebraic modeling system with reductions of
and
for each test feeder with respect to the benchmark cases.
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Open AccessArticle
Cost-Benefit Analysis of Small-Scale Rooftop PV Systems: The Case of Dragotin, Croatia
by
Mladen Bošnjaković, Ante Čikić and Boris Zlatunić
Cited by 4 | Viewed by 2386
Abstract
A large drop in prices of photovoltaic (PV) equipment, an increase in electricity prices, and increasing environmental pressure to use renewable energy sources that pollute the environment significantly less than the use of fossil fuels have led to a large increase in installed
[...] Read more.
A large drop in prices of photovoltaic (PV) equipment, an increase in electricity prices, and increasing environmental pressure to use renewable energy sources that pollute the environment significantly less than the use of fossil fuels have led to a large increase in installed roof PV capacity in many parts of the world. In this context, this paper aims to analyze the cost-effectiveness of installing PV systems in the rural continental part of Croatia on existing family houses. A typical example is a house in Dragotin, Croatia with an annual consumption of 4211.70 kWh of electricity on which PV panels are placed facing south under the optimal slope. The calculation of the optimal size of a PV power plant with a capacity of 3.6 kW, without battery energy storage, was performed by the Homer program. The daily load curve was obtained by measuring the electricity consumption at the facility every hour during a characteristic day in the month of June. As most of the activities are related to electricity consumption, repeating during most days of the year, and taking into account seasonal activities, daily load curves were made for a characteristic day in each month of the year. Taking into account the insolation for the specified location, using the Internet platform Solargis Prospect, hourly data on the electricity production of selected PV modules for a characteristic day in each month were obtained. Based on the previous data, the electricity injected into the grid and taken from the grid was calculated. Taking into account the current tariffs for the sale and purchase of electricity, investment prices, and maintenance of equipment, the analysis shows that such a PV system can pay off in 10.5 years without government incentives.
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Open AccessArticle
Power Sharing Control in a Grid-Tied DC Microgrid: Controller Hardware in the Loop Validation
by
Víctor Samano-Ortega, Heriberto Rodriguez-Estrada, Elías Rodríguez-Segura, José Padilla-Medina, Juan Aguilera-Alvarez and Juan Martinez-Nolasco
Cited by 2 | Viewed by 1684
Abstract
This article presents the development of a low-cost control hardware in the loop platform for the validation and analysis of controllers used for the management of power sharing between the main grid and a DC microgrid. The platform is made up of two
[...] Read more.
This article presents the development of a low-cost control hardware in the loop platform for the validation and analysis of controllers used for the management of power sharing between the main grid and a DC microgrid. The platform is made up of two parts: a main grid interconnection system emulator (MGISE) and a controller under test (CUT). The MGISE operates on a 260 V DC bus and includes a 1000 W photovoltaic array, a DC variable load and a single H full bridge converter (HFBC). The CUT includes a phase locked loop and a main cascade control structure composed of two PI controllers. Both the MGISE and the CUT were embedded on an NI myRIO-1900 development board and programmed using LabVIEW virtual instrumentation software. These devices communicate with each other using analog signals representing the AC side current, the DC side voltage, and the HFBC control signal. The MGISE operates with an integration time of 6 µs and its performance is validated by comparing it with a simulation in PSIM. The integration time of the MGISE, the development boards used, as well as its programming environment, and the results obtained from the comparison with PSIM simulation, show that the proposed platform is useful for the validation of controllers for power sharing, with a simple implementation process compared to other hardware description methods and with a low-cost platform.
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Open AccessArticle
Monitoring of Energy Data with Seamless Temporal Accuracy Based on the Time-Sensitive Networking Standard and Enhanced µPMUs
by
Víctor Pallarés-López, Rafael Jesús Real-Calvo, Silvia del Rio Jiménez, Miguel González-Redondo, Isabel Moreno-García and Isabel Santiago
Cited by 2 | Viewed by 2117
Abstract
In the energy sector, distributed synchronism and a high degree of stability are necessary for all real-time monitoring and control systems. Instantaneous response to critical situations is essential for the integration of renewable energies. The most widely used standards for clock synchronisation, such
[...] Read more.
In the energy sector, distributed synchronism and a high degree of stability are necessary for all real-time monitoring and control systems. Instantaneous response to critical situations is essential for the integration of renewable energies. The most widely used standards for clock synchronisation, such as Network Time Protocol (NTP) and Precision Time Protocol (PTP), do not allow for achieving synchronised simultaneous sampling in distributed systems. In this work, a novel distributed synchronism system based on the Time-Sensitive Networking (TSN) standard has been validated for its integration in an architecture oriented towards the high-resolution digitisation of photovoltaic (PV) generation systems. This method guarantees a time stamping with an optimal resolution that allows for the analysis of the influence of fast-evolving atmospheric fluctuations in several plants located in the same geographical area. This paper proposes an enhanced micro-phasor measurement unit (µPMU) that acts as a phasor meter and TSN master controlling the monitoring system synchronism. With this technique, the synchronism would be extended to the remaining measurement systems that would be involved in the installation at distances greater than 100 m. Several analyses were carried out with an on-line topology of four acquisition systems capturing simultaneously. The influence of the Ethernet network and the transducers involved in the acquisition process were studied. Tests were performed with Ethernet cable lengths of 2, 10, 50, and 75 m. The results were validated with 24-bit Sigma-Delta converters and high-precision resistor networks specialised in high-voltage monitoring. It was observed that with an appropriate choice of sensors and TSN synchronism, phase errors of less than ±1 µs can be guaranteed by performing distributed captures up to 50 kS/s. Statistical analysis showed that uncertainties of less than ±100 ns were achieved with 16-bit Successive Approximation Register (SAR) converters at a moderate cost. Finally, the requirements of the IEEE C37.118.1-2011 standard for phasor measurement units (PMU) were also satisfied. This standard establishes an uncertainty of ±3.1 μs for 50 Hz systems. These results demonstrate the feasibility of implementing a simultaneous sampling system for distributed acquisition systems coordinated by a µPMU.
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Open AccessArticle
Simulation of Self-Consumption Photovoltaic Installations: Profitability Thresholds
by
Marta Varo-Martínez, Luis Manuel Fernández-Ahumada, Rafael López-Luque and José Ramírez-Faz
Cited by 4 | Viewed by 1593
Abstract
PV self-consumption can contribute positively to the spread of PV and, therefore, to the progress of renewable energies as a key element in a decarbonized energy model. However, the policies of each country regarding the promotion of this type of renewable technology is
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PV self-consumption can contribute positively to the spread of PV and, therefore, to the progress of renewable energies as a key element in a decarbonized energy model. However, the policies of each country regarding the promotion of this type of renewable technology is fundamental for their growth. Despite the high number of sunshine hours registered in Spain, self-consumption in this country has not been authorized until recently. In this new context, this work presents a systematic study of the profitability limits of a self-consumption PV installation under different conditions of installed peak power, orientation and inclination of the PV panels and level of obstruction of the installation. It was proved that, for the case of study (Córdoba, Spain), the maximum profitability was achieved for PV panels oriented to the south and with an inclination of 15° whereas the most unfavourable conditions are those of PV panels with an orientation and inclination of 180° and 90°, respectively. Furthermore, when the level of obstruction increases the maximum of the Net Present Value of self-consumptions PV installations decreases and this optimal value is achieved for installations with lower power. Finally, empirical adjustment equations have been developed to estimate the profitability parameters of self-consumptions PV installations as a function of their design variables.
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Open AccessArticle
Classification of Daily Irradiance Profiles and the Behaviour of Photovoltaic Plant Elements: The Effects of Cloud Enhancement
by
Isabel Santiago, Jorge Luis Esquivel-Martin, David Trillo-Montero, Rafael Jesús Real-Calvo and Víctor Pallarés-López
Cited by 6 | Viewed by 2728
Abstract
In this work, the automatic classification of daily irradiance profiles registered in a photovoltaic installation located in the south of Spain was carried out for a period of nine years, with a sampling frequency of 5 min, and the subsequent analysis of the
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In this work, the automatic classification of daily irradiance profiles registered in a photovoltaic installation located in the south of Spain was carried out for a period of nine years, with a sampling frequency of 5 min, and the subsequent analysis of the operation of the elements of the installation on each type of day was also performed. The classification was based on the total daily irradiance values and the fluctuations of this parameter throughout the day. The irradiance profiles were grouped into nine different categories using unsupervised machine learning algorithms for clustering, implemented in Python. It was found that the behaviour of the modules and the inverter of the installation was influenced by the type of day obtained, such that the latter worked with a better average efficiency on days with higher irradiance and lower fluctuations. However, the modules worked with better average efficiency on days with irradiance fluctuations than on clear sky days. This behaviour of the modules may be due to the presence, on days with passing clouds, of the phenomenon known as cloud enhancement, in which, due to reflections of radiation on the edges of the clouds, irradiance values can be higher at certain moments than those that occur on clear sky days, without passing clouds. This is due to the higher energy generated during these irradiance peaks and to the lower temperatures that the module reaches due to the shaded areas created by the clouds, resulting in a reduction in its temperature losses.
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Study of the Dependence of Solar Radiation Regarding Design Variables in Photovoltaic Solar Installations with Optimal Dual-Axis Tracking
by
Francisco Javier Gómez-Uceda, Isabel Maria Moreno-Garcia, Álvaro Perez-Castañeda and Luis Manuel Fernández-Ahumada
Cited by 3 | Viewed by 1764
Abstract
Solar tracking is an efficient strategy to increase the radiative capture of photovoltaic collectors. Within the multiple efforts made in recent decades to improve the production of these facilities, various works have studied solutions to optimize the number of rotation axes (single or
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Solar tracking is an efficient strategy to increase the radiative capture of photovoltaic collectors. Within the multiple efforts made in recent decades to improve the production of these facilities, various works have studied solutions to optimize the number of rotation axes (single or dual rotation axes), the degree of collector coverage, the distances between trackers, the geometric arrangement of trackers or the minimization of shading between collectors. However, although in this type of installation it is common to find collectors with geometric shapes other than rectangles, no studies on the influence of the shape of the collectors on the radiative incidence are found in the literature. In this connection, the present work systematically addresses the study of incident solar radiation in photovoltaic installations with dual-axis trackers with collectors of different geometric shapes. By means of the exhaustive study, the conclusion is drawn that, for dual-axis photovoltaic installations with an optimal tracking strategy, the main variables that influence the annual radiative incidence are the spacing between collectors, the coverage ratio (GCR), and the collector surface, while the type of arrangement of collectors and the shape of these do not show predictive values.
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Thermal Effects on Photovoltaic Array Performance: Experimentation, Modeling, and Simulation
by
Levon Ghabuzyan, Kevin Pan, Arianna Fatahi, Jim Kuo and Christopher Baldus-Jeursen
Cited by 17 | Viewed by 3246
Abstract
The performance of photovoltaic (PV) arrays are affected by the operating temperature, which is influenced by thermal losses to the ambient environment. The factors affecting thermal losses include wind speed, wind direction, and ambient temperature. The purpose of this work is to analyze
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The performance of photovoltaic (PV) arrays are affected by the operating temperature, which is influenced by thermal losses to the ambient environment. The factors affecting thermal losses include wind speed, wind direction, and ambient temperature. The purpose of this work is to analyze how the aforementioned factors affect array efficiency, temperature, and heat transfer coefficient/thermal loss factor. Data on ambient and array temperatures, wind speed and direction, solar irradiance, and electrical output were collected from a PV array mounted on a CanmetENERGY facility in Varennes, Canada, and analyzed. The results were compared with computational fluid dynamics (CFD) simulations and existing results from PVsyst. The findings can be summarized into three points. First, ambient temperature and wind speed are important factors in determining PV performance, while wind direction seems to play a minor role. Second, CFD simulations found that temperature variation on the PV array surface is greater at lower wind speeds, and decreases at higher wind speeds. Lastly, an empirical correlation of heat transfer coefficient/thermal loss factor has been developed.
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Game Approach to HDR-TS-PV Hybrid Power System Dispatching
by
Yang Si, Laijun Chen, Xuelin Zhang, Xiaotao Chen, Tianwen Zheng and Shengwei Mei
Cited by 6 | Viewed by 1664
Abstract
Hot dry rock (
HDR) power stations have the potential to serve as an energy storage system for large-scale photovoltaic (
PV) plants. For flexible operation, thermal storage (
TS) power stations are required to coordinate with
HDR power stations.
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Hot dry rock (
HDR) power stations have the potential to serve as an energy storage system for large-scale photovoltaic (
PV) plants. For flexible operation, thermal storage (
TS) power stations are required to coordinate with
HDR power stations. In this study, a hybrid power system is constructed by combining the
HDR,
TS, and
PV plants. Game theory is then introduced into the optimal dispatch of the hybrid power system. Considering
HDR,
TS, and
PV as players, non-cooperative and cooperative game dispatching models are established and verified by a case in the Gonghe basin of Qinghai. Finally, the stability of the coalitions and the rationality of allocation of the hybrid power system is verified, and the sensitivity of critical parameters is analyzed. The results demonstrate that the overall payoff of the hybrid power system is increased by 10.15%. The payoff of the
HDR power station is increased by 16.5%. The
TS power station has obtained 50% of the total extra profits. The
PV plant reduces the impact on the grid to obtain the priority of grid connection. Based on these results, a theoretical basis can be provided for developing generation systems based on the
HDR resources in the Gonghe Basin.
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Open AccessFeature PaperArticle
Analysis of the Influence of Terrain Orientation on the Design of PV Facilities with Single-Axis Trackers
by
Francisco J. Gómez-Uceda, Isabel M. Moreno-Garcia, José M. Jiménez-Martínez, Rafael López-Luque and Luis M. Fernández-Ahumada
Cited by 7 | Viewed by 2690
Abstract
This paper investigates how to optimally orient the photovoltaic solar trackers of an axis parallel to the terrain, applying the sky model of Hay–Davies. This problem has been widely studied. However, the number of studies that consider the orientation (inclination and azimuth of
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This paper investigates how to optimally orient the photovoltaic solar trackers of an axis parallel to the terrain, applying the sky model of Hay–Davies. This problem has been widely studied. However, the number of studies that consider the orientation (inclination and azimuth of the terrain) is very limited. This paper provides an examination of incident solar irradiance that can be extended to terrain with variable orientation and in consideration of different azimuths of the axis of rotation. Furthermore, a case study of the south of Spain is provided, considering different inclination and orientation terrain values. The results obtained in this study indicate, as a novelty, that for lands that are not south facing, the rotation axis azimuth of solar trackers should be different from zero and adjusted to the same direction as the land azimuth in order to maximize energy production. Annual energy production is sensitive to changes in the rotation axis azimuths of solar trackers (an influence of around 3% of annual energy production).
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Planned Papers
The below list represents only planned manuscripts. Some of these
manuscripts have not been received by the Editorial Office yet. Papers
submitted to MDPI journals are subject to peer-review.
1. Gómez-Uceda, FJ; Moreno-García, I; Jiménez-Martínez, JM; Fernández-Ahumada, LM
Title: Analysis of models for optimisation in one axis tracker PV facilities
2. Marta Varo-Martínez, Luis M. Fernández-Ahumada, Jose C. Ramírez-Faz and Rafael López-Luque
Title: Simulation of Self-Consumption Photovoltaic Installations: Profitability Thresholds
