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Smart Energy for a Sustainable Future. Experiences in Photovoltaic System Monitoring

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A topical collection in Sustainability (ISSN 2071-1050). This collection belongs to the section "Energy Sustainability".

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Prof. Dr. Catalina Rus-Casas

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Department of Electronic and Automatic Engineering, University of Jaen, 23071 Jaen, Spain
Interests: solar radiation; energy harvesting; photovoltaic systems; monitoring; performance analysis of photovoltaic generator; self-consumption; microgrids
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Topical Collection Information

Dear Colleagues,

Among the many challenges in science and engineering in recent decades, energy transition has been the most prominent. In this sense, European policies encourage sustainability, energy efficiency, and the implementation of renewable production in order to promote nearly zero energy buildings (NZEBs).

The increasing energy consumption throughout the world, as well as the environmental impact resulting from the use of fossil fuel-based energy have promoted the use of renewable energy sources, such as photovoltaic solar energy. Smart grids are considered as the solution to allow for the optimal management of photovoltaic generation. The control and management of smart grids is based mainly on updating energetic and economic parameters, such as the load consumption and the photovoltaic generation through smart connected devices, which provide real-time operation and energy measurements. The main characteristic of this type of energy is its unpredictibilty, as it depends on meteorological conditions. In this sense, monitoring the power generation of photovoltaic systems (PVS) in order to analyze its performance becomes crucial. In addition, monitoring allows for knowing if the system is failing, or the actual performance to deviate from the expected performance.

The main focus of this Topical Collection is to provide an up-to-date report on the state-of-the-art of all aspects of designing a monitoring system for a photovoltaic system.

The purpose of this Topical Collection is to compile a set of papers dealing with these wider aspects of innovative monitoring techniques, including remote sensing and the management of the relevant processes and numerical models, showing experiences and applying the lessons learned, and transferring technologies from other systems.

This Topical Collection will include studies for finding the reliable implementation of monitoring for performance analysis, finding anomalies from the data collected by sensors.

This Topical Collection invites scholars, researchers, engineers, and industry professionals to present their state-of-the-art research solutions and ideas toward significantly improving the field of smart energy. Priority will be given to papers that address novel approaches. The topics of interest include, but are not limited to, the following:

Monitoring: sensors, communications, and data analytics for photovoltaic systems
IoT solutions to monitoring
State-of-the-art reviews on monitoring PV systems and applications
Planning and operation of photovoltaic power systems
Monitoring, control, and management of PV systems
Machine learning, including deep learning, for detecting anomalies
Modeling of smart grids with photovoltaic power
Energy management and intelligent control for photovoltaic systems in the residential and industrial sector
Smart cities and energy planning
Net zero energy building
Energy efficiency
Energy performance
Energy storage.

Dr. Catalina Rus-Casas
Collection Editor

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Keywords

solar energy
photovoltaic systems (grid-connected, stand-alone, and self-consumption)
monitoring
smart meters
smart cities and planning
net zero energy building
energy efficiency
sustainable innovative technologies
energy performance
energy storage

Published Papers (12 papers)

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2022

Jump to: 2021, 2020

14 pages, 166910 KiB

Open AccessArticle

Performance Comparison between Fixed and Dual-Axis Sun-Tracking Photovoltaic Panels with an IoT Monitoring System in the Coastal Region of Ecuador

by Marcos A. Ponce-Jara, Carlos Velásquez-Figueroa, María Reyes-Mero and Catalina Rus-Casas

Sustainability 2022, 14(3), 1696; https://doi.org/10.3390/su14031696 - 01 Feb 2022

Cited by 9 | Viewed by 4883

Abstract

Solar photovoltaic (PV) energy systems are one of the most widely deployed renewable technologies in the world. The efficiency of solar panels has been studied during the last few decades, and, to date, it has not been possible to displace the production of energy using crystalline silicon wafer-based technology whose efficiency has reached values around 26.1%. Moreover, using solar tracking PV systems has become a feasible alternative to increase the electric output of PV silicon technologies instead of using the conventional fixed PV installation on a flat or sloping surface. The following study has compared fixed and dual-axis sun-tracking PV panels in order to quantify the enhancement associated with the amount of energy harvested when using dual-axis tracking PV systems in the city of Manta, located in a coastal region of Ecuador. In order to carry out this study, an IoT monitoring system based on Raspberry Pi3 and Arduino platforms was used. Measurements of solar radiation (W/m²), light intensity (Lux), temperature (°C), short-circuit current (A), and open-circuit voltage (V) were taken every minute for both systems. The results prove that the dual-axis tracking PV system produces, on average, 19.62% more energy than the static PV system. These results present an 8.62% energy increase with respect to a previous study carried out in an equatorial region with similar characteristics to those of the city of Manta, where a one-axis tracking PV system was used. Full article

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2021

Jump to: 2022, 2020

14 pages, 3209 KiB

Open AccessFeature PaperArticle

A Machine Learning and Internet of Things-Based Online Fault Diagnosis Method for Photovoltaic Arrays

by Adel Mellit, Omar Herrak, Catalina Rus Casas and Alessandro Massi Pavan

Sustainability 2021, 13(23), 13203; https://doi.org/10.3390/su132313203 - 29 Nov 2021

Cited by 9 | Viewed by 2037

Abstract

In this paper, a novel fault detection and classification method for photovoltaic (PV) arrays is introduced. The method has been developed using a dataset of voltage and current measurements (I–V curves) which were collected from a small-scale PV system at the RELab, the University of Jijel (Algeria). Two different machine learning-based algorithms have been used in order to detect and classify the faults. An Internet of Things-based application has been used in order to send data to the cloud, while the machine learning codes have been run on a Raspberry Pi 4. A webpage which shows the results and informs the user about the state of the PV array has also been developed. The results show the ability and the feasibility of the developed method, which detects and classifies a number of faults and anomalies (e.g., the accumulation of dust on the PV module surface, permanent shading, the disconnection of a PV module, and the presence of a short-circuited bypass diode in a PV module) with a pretty good accuracy (98% for detection and 96% classification). Full article

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22 pages, 2314 KiB

Open AccessArticle

Control-Oriented Model of Photovoltaic Systems Based on a Dual Active Bridge Converter

by Diego Alejandro Herrera-Jaramillo, Elkin Edilberto Henao-Bravo, Daniel González Montoya, Carlos Andrés Ramos-Paja and Andrés Julián Saavedra-Montes

Sustainability 2021, 13(14), 7689; https://doi.org/10.3390/su13147689 - 09 Jul 2021

Cited by 6 | Viewed by 2210

Abstract

Solar energy is a source of sustainable energy and its optimal use depends on the efficiency and reliability of PV systems. Dual active bridge converters are a solution to interface PV modules with the grid or high voltage requirement applications due to the high voltage-conversion-ratio and high efficiency provided by such a converter. The three main contributions of this work are: an extensive mathematical model of a DAB converter connected to a PV module including protection diodes, which is intended to design non-linear controllers, an explicit linearized version of the model, which is oriented to design traditional control systems; and a detailed and replicable application example of the model focused on maximizing the power extraction from a PV system. The modeling approach starts with the differential equations of the PV system; however, only the fundamental and average components of each signal is used to represent it. The control-oriented model is validated using a detailed circuital simulation. First, through the comparison of frequency and time diagrams of the proposed model and a detailed one; and then, through the simulation of the PV system in a realistic application case. PV voltage regulation and maximum power extraction are confirmed in simulation results. Full article

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27 pages, 13629 KiB

Open AccessArticle

An Efficient Neural Network-Based Method for Diagnosing Faults of PV Array

by Selma Tchoketch Kebir, Nawal Cheggaga, Adrian Ilinca and Sabri Boulouma

Sustainability 2021, 13(11), 6194; https://doi.org/10.3390/su13116194 - 31 May 2021

Cited by 11 | Viewed by 1987

Abstract

This paper presents an efficient neural network-based method for fault diagnosis in photovoltaic arrays. The proposed method was elaborated on three main steps: the data-feeding step, the fault-modeling step, and the decision step. The first step consists of feeding the real meteorological and electrical data to the neural networks, namely solar irradiance, panel temperature, photovoltaic-current, and photovoltaic-voltage. The second step consists of modeling a healthy mode of operation and five additional faulty operational modes; the modeling process is carried out using two networks of artificial neural networks. From this step, six classes are obtained, where each class corresponds to a predefined model, namely, the faultless scenario and five faulty scenarios. The third step involves the diagnosis decision about the system’s state. Based on the results from the above step, two probabilistic neural networks will classify each generated data according to the six classes. The obtained results show that the developed method can effectively detect different types of faults and classify them. Besides, this method still achieves high performances even in the presence of noises. It provides a diagnosis even in the presence of data injected at reduced real-time, which proves its robustness. Full article

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21 pages, 4443 KiB

Open AccessEditor’s ChoiceArticle

How the SP System May Promote Sustainability in Energy Consumption in IT Systems

by J. Gerard Wolff

Sustainability 2021, 13(8), 4565; https://doi.org/10.3390/su13084565 - 20 Apr 2021

Cited by 2 | Viewed by 1448

Abstract

The SP System (SPS), referring to the SP Theory of Intelligence and its realisation as the SP Computer Model, has the potential to reduce demands for energy from IT, especially in AI applications and in the processing of big data, in addition to reductions in CO₂ emissions when the energy comes from the burning of fossil fuels. The biological foundations of the SPS suggest that with further development, the SPS may approach the extraordinarily low (20 W)energy demands of the human brain. Some of these savings may arise in the SPS because, like people, the SPS may learn usable knowledge from a single exposure or experience. As a comparison, deep neural networks (DNNs) need many repetitions, with much consumption of energy, for the learning of one concept. Another potential saving with the SPS is that like people, it can incorporate old learning in new. This contrasts with DNNs where new learning wipes out old learning (‘catastrophic forgetting’). Other ways in which the mature SPS is likely to prove relatively parsimonious in its demands for energy arise from the central role of information compression (IC) in the organisation and workings of the system: by making data smaller, there is less to process; because the efficiency of searching for matches between patterns can be improved by exploiting probabilities that arise from the intimate connection between IC and probabilities; and because, with SPS-derived ’Model-Based Codings’ of data, there can be substantial reductions in the demand for energy in transmitting data from one place to another. Full article

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22 pages, 2782 KiB

Open AccessArticle

A Comprehensive Approach to the Design of a Renewable Energy Microgrid for Rural Ethiopia: The Technical and Social Perspectives

by Stergios Emmanouil, Jason Philhower, Sophie Macdonald, Fahad Khan Khadim, Meijian Yang, Ezana Atsbeha, Himaja Nagireddy, Natalie Roach, Elizabeth Holzer and Emmanouil N. Anagnostou

Sustainability 2021, 13(7), 3974; https://doi.org/10.3390/su13073974 - 02 Apr 2021

Cited by 16 | Viewed by 4061

Abstract

In view of Ethiopia’s significant renewable energy (RE) potential and the dynamic interactions among the components of the Water–Energy–Food (WEF) Nexus, we attempted to incorporate solar and small-scale hydropower into the optimal design of an environmentally friendly microgrid with the primary goal of ensuring the sustainability of irrigation water pumping, while taking advantage of existing infrastructure in various small administrative units (kebele). Any additional generated energy would be made available to the community for other needs, such as lighting and cooking, to support health and food security and improve the general quality of life. The novelty of the study stems from the utilization of in situ social data, retrieved during fieldwork interviews conducted in the kebele of interest, to ascertain the actual needs and habits of the local people. Based on these combined efforts, we were able to formulate a realistic energy demand plan for climatic conditions typical of Sub-Saharan Africa agricultural communities and analyze four different scenarios of the microgrid’s potential functionality and capital cost, given different tolerance levels of scheduled outages. We demonstrated that the RE-based microgrid would be socially and environmentally beneficial and its capital cost sensitive to the incorporation of individual or communal machines and appliances. Ultimately, the social impact investigation revealed the design would be welcomed by the local community, whose members already implement tailor-made solutions to support their agricultural activities. Finally, we argue that extended educational programs and unambiguous policies should be in place before any implementation to ensure the venture’s sustainability and functionality. Full article

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19 pages, 5540 KiB

Open AccessArticle

Wind Coefficient Distribution of Arranged Ground Photovoltaic Panels

by Jangyoul You, Myungkwan Lim, Kipyo You and Changhee Lee

Sustainability 2021, 13(7), 3944; https://doi.org/10.3390/su13073944 - 02 Apr 2021

Cited by 7 | Viewed by 2230

Abstract

Solar panels installed on the ground receive wind loads. A wind experiment was conducted to evaluate the wind force coefficient acting on a single solar panel and solar panels arranged in an array. The surface roughness did not have a significant effect on the change in vertical force, which is the wind force coefficient acting on the vertical surface of a single solar panel. An examination of the change in wind direction angle showed that the largest vertical force coefficient was distributed in the 0° forward wind direction on the front of the solar panel, the 345° reverse wind direction on the rear side, and the 135° and 225° diagonal directions on the rear panel. Furthermore, an examination of the change in wind force coefficient according to the change in solar panel inclination angle (β) showed that the drag coefficient was the highest at the 40° inclination angle of the panel (β), followed by the 30° and 20° inclination angles. However, the lift coefficient and vertical force coefficient were not significantly affected by the inclination angle of the panel. The wind force coefficient of the panels arranged in an array was influenced by the wind direction angle and panel position. With the exclusion of the nearest row at a wind direction angle of 0°, all the panels in the array showed lower coefficients than those in the single-panel experiment. In the case of the panels placed inside, the wind speed was decreased by the surrounding panels. As a result, the wind force coefficient was lower than that of the single-panel experiment. This outcome is attributed to the small delamination at the end of the panels by the surrounding array of panels compared with that of the single-panel experiment. Full article

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16 pages, 5146 KiB

Open AccessEditor’s ChoiceArticle

Analysis of PV Self-Consumption in Educational and Office Buildings in Spain

by Ángel José Ordóñez Mendieta and Esteban Sánchez Hernández

Sustainability 2021, 13(4), 1662; https://doi.org/10.3390/su13041662 - 04 Feb 2021

Cited by 8 | Viewed by 2177

Abstract

As grid parity is reached in many countries, photovoltaic self-consumption is raising great interest. Currently, there is a big number of new projects being developed in Spain thanks to the new regulation. From the experience of the monitoring of one full year of operation of a self-consumption PV plant in a university building, a regulatory, energy, and economic analysis is made for this type of building. It has been carried out by simulating the behavior of the building with installations within the range of PV powers allowed in the Spanish regulation. The analysis shows the good fitting between the new Royal Decree of Self-Consumption and the new Building Code. The economic analysis proves that the new simplified compensation method gives the best economic return for this use of the buildings when the PV production is matched with the consumption. The time of return of investment is between 8 and 9 years, and the levelized cost of electricity (LCOE) is into the range of the pool market price of electricity. These results show the profitability of PV self-consumption for this type of building. Full article

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16 pages, 3821 KiB

Open AccessArticle

Addressing Thermal Comfort in Regional Energy Poverty Assessment with Nussbaumer’s MEPI

by Tiare Robles-Bonilla and Karla G. Cedano

Sustainability 2021, 13(1), 352; https://doi.org/10.3390/su13010352 - 02 Jan 2021

Cited by 10 | Viewed by 2682

Abstract

Research on energy poverty (EP) started in the United Kingdom and other Western European countries in response to the Oil Crisis in 1973. In the last few years, the European community has made important breakthroughs on the topic, by establishing clear terminology as well as funding different multidisciplinary and intersectoral task groups that have EP understanding and alleviation as their goal. Several different methodologies have been developed to measure EP. For instance, the multidimensional energy poverty index (MEPI) by Nussbaumer et al. (2012) has been successfully used in Africa and in seven Latin American countries. Mexico does not have an official measure, indicator, or index on EP. However, a very important energy service has been overlooked: thermal comfort. In the present work, MEPI was understood as an energy services deprivation calculation, and thermal comfort was included. Understanding the regional nature of thermal comfort, we searched for weather-based regionalizations that could address a whole country diversity. We applied two regionalizations, one strongly related to political divisions (called climatic), and a another used for household design and construction standards (bioclimatic). The bioclimatic regionalization had a better fit when assessing energy services deprivation, since it addresses exclusively geographical and weather conditions, instead of the artificial political divisions. Having better ways to assess the level of EP in the local context is a key factor to develop effective public policies that might alleviate EP in a sustainable way. Full article

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2020

Jump to: 2022, 2021

28 pages, 4557 KiB

Open AccessArticle

Mathematical Model for Regular and Irregular PV Arrays with Improved Calculation Speed

by Luz Adriana Trejos-Grisales, Juan David Bastidas-Rodríguez and Carlos Andrés Ramos-Paja

Sustainability 2020, 12(24), 10684; https://doi.org/10.3390/su122410684 - 21 Dec 2020

Cited by 6 | Viewed by 2061

Abstract

Photovoltaic (PV) systems are usually developed by configuring the PV arrays with regular connection schemes, such as series-parallel, total cross-tied, bridge-linked, among others. Such a strategy is aimed at increasing the power that is generated by the PV system under partial shading conditions, since the power production changes depending on the connection scheme. Moreover, irregular and non-common connection schemes could provide higher power production for irregular (but realistic) shading conditions that aere caused by threes or other objects. However, there are few mathematical models that are able to predict the power production of different configurations and reproduce the behavior of both regular and irregular PV arrays. Those general array models are slow due to the large amount of computations that are needed to find the PV current for a given PV voltage. Therefore, this paper proposes a general mathematical model to predict the power production of regular and irregular PV arrays, which provides a faster calculation in comparison with the general models that were reported in the literature, but without reducing the prediction accuracy. The proposed modeling approach is based on detecting the inflection points that are caused by the bypass diodes activation, which enables to narrow the range in which the modules voltages are searched, thus reducing the calculation time. Therefore, this fast model is useful in designing the fixed connections of PV arrays that are subjected to shading conditions, in order to reconfigure the PV array in real-time, depending on the shading pattern, among other applications. The proposed solution is validated by comparing the results with another general model and with a circuital implementation of the PV system. Full article

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28 pages, 5573 KiB

Open AccessArticle

PV Monitoring System for a Water Pumping Scheme with a Lithium-Ion Battery Using Free Open-Source Software and IoT Technologies

by Francisco José Gimeno-Sales, Salvador Orts-Grau, Alejandro Escribá-Aparisi, Pablo González-Altozano, Ibán Balbastre-Peralta, Camilo Itzame Martínez-Márquez, María Gasque and Salvador Seguí-Chilet

Sustainability 2020, 12(24), 10651; https://doi.org/10.3390/su122410651 - 20 Dec 2020

Cited by 18 | Viewed by 4539

Abstract

The development of photovoltaic (PV) technology is now a reality. The inclusion of lithium-ion batteries in grid-connected PV systems is growing, and the sharp drop in prices for these batteries will enable their use in applications such as PV water pumping schemes (PVWPS). A technical solution for the monitoring and tracking of PV systems is shown in this work, and a novel quasi-real-time monitoring system for a PVWPS with a Li-ion battery is proposed in which open-source Internet of Things (IoT) tools are used. The purpose of the monitoring system is to provide a useful tool for the operation, management, and development of these facilities. The experimental facility used to test the monitoring system includes a 2.4 kW_pk photovoltaic field, a 3.6 kVA hybrid inverter, a 3.3 kWh/3 kW lithium-ion battery, a 2.2 kVA variable speed driver, and a 1.5 kW submersible pump. To address this study, data acquisition is performed using commercial hardware solutions that communicate using a Modbus-RTU protocol over an RS485 bus and open software. A Raspberry Pi is used in the data gateway stage, including a PM2 free open-source process manager to increase the robustness and reliability of the monitoring system. Data storage is performed in a server using InfluxDB for open-source database storage and Grafana as open-source data visualization software. Data processing is complemented with a configurable data exporter program that enables users to select and copy the data stored in InfluxDB. Excel or .csv files can be created that include the desired variables with a defined time interval and with the desired data granularity. Finally, the initial results of the monitoring system are presented, and the possible uses of the acquired data and potential users of the system are identified and described. Full article

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22 pages, 6881 KiB

Open AccessArticle

Integrating Transparent and Conventional Solar Cells TSC/SC

by Moh’d Al-Nimr, Abdallah Milhem, Basel Al-Bishawi and Khaleel Al Khasawneh

Sustainability 2020, 12(18), 7483; https://doi.org/10.3390/su12187483 - 11 Sep 2020

Cited by 2 | Viewed by 1958

Abstract

Conventional photovoltaic cells are able to convert the visible light spectrum of solar radiation into electricity; the unused wavelengths of the solar radiation spectrum are dissipated as heat in the system. On the other hand, certain types of transparent solar cells are able to utilize the rest of the solar radiation spectrum. The integration of transparent solar cells with conventional photovoltaic cells enables the system to absorb and utilize both wavelengths of the solar radiation spectrum. In this paper, two models for integrating transparent solar cells with conventional photovoltaic cells are proposed, simulated, and analyzed theoretically. ANSYS software was used to obtain the results for the proposed models. It is an initial theoretical study that shows some first results; it is almost a work in progress. The results showed that the highest efficiency was for the model that had two cooling spaces. The efficiency was increased as the ambient air temperature decreased and the mass flow rate increased. The percentage drop in photovoltaic (PV) cell efficiency decreased as the mass flow rate increased and the ambient temperature decreased, and it had the lowest value when air/water was used for cooling. The efficiency of the transparent solar cell (TSC) increased as the transparency decreased; in order to have higher efficiency, PV efficiency should be high, with low transparency. When added, the transparent solar cell was supposed to increase the harvested energy due to the utilization of the unconverted solar radiation, but it left two negative side effects. The first negative side effect was the reduction of the transmitted radiation to the conventional solar cell due to the transmissivity of the transparent cell. The second negative impact was the increase in the conventional cell temperature due to the additional thermal resistance, which reduced the effectiveness of cooling the cell from above. The proposed models were verified by comparing the results of the standalone PV that were available in the literature with the two models that are proposed in this paper. Full article

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Smart Energy for a Sustainable Future. Experiences in Photovoltaic System Monitoring

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Published Papers (12 papers)

2022

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2021

Jump to: 2022, 2020

2020

Jump to: 2022, 2021

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