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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A2: Solar Energy and Photovoltaic Systems".

Deadline for manuscript submissions: closed (29 October 2024) | Viewed by 6935

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Special Issue Editors

Dr. Alessandro Ciocia

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Guest Editor

Department of Energy, Politecnico di Torino, 10129 Torino, Italy
Interests: photovoltaic and wind power systems; power systems analysis; measurements; distributed generation
Special Issues, Collections and Topics in MDPI journals

Dr. Antonio D'angola

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Guest Editor

SI-UniBas School of Engineering, University of Basilicata, via dell’Ateneo Lucano, 10, 85100 Potenza, Italy
Interests: renewable energy system modeling; PV and PVT power systems; applied energy; plasma physics; CFD and MHD modeling; thermal plasma systems; numerical methods
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is dedicated to photovoltaic (PV) solar energy. The reason for the current and future massive development of PV technology is the abundant amount of solar resource in the world. In particular, the solar energy received by the Earth in a year is more than 1000 times greater than the human energy consumption. Moreover, the increase in the efficiency of the PV modules and their price fall make PV one of the most installed technologies in recent years, with a new word capacity of more than 100 GW in 2020. Therefore, it is essential that the research world focuses its attention on the design, optimal operation, and maintenance of PV plants.

Contributions submitted to this Special Issue should deal with the following topics, as well as other potential topics that are not mentioned here:

Innovative design of PV components and systems (e.g., new maximum power point tracking logics);
Techniques for automatic fault detection (e.g., thermography and electroluminescence by drones, automatic scan of current–voltage curves);
Smart monitoring and maintenance of utility scale PV plants;
Techniques to increase local self-sufficiency and self-consumption by PV systems;
Methods to support the integration of a significant share of PV generation into the power grids (e.g., coupling with storage systems, active power curtailment, reactive power injection, remote/centralized control, grid reconfigurations);
Planning of utility scale PV generation at regional and national levels;
Forecasting of PV generation.
Modelling and simulation of photovoltaic energy conversion systems
Electrical and thermal modeling of a PV cell and of a module
Modelling, control, and simulation of integrated storage systems in photovoltaic plants

Dr. Alessandro Ciocia
Dr. Antonio D'angola
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

photovoltaic plants
self-sufficiency
storage systems
distributed generation
maintenance
forecasting

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Published Papers (6 papers)

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Research

25 pages, 7437 KiB

Open AccessArticle

Electrothermal Modeling of Photovoltaic Modules for the Detection of Hot-Spots Caused by Soiling

by Peter Winkel, Jakob Smretschnig, Stefan Wilbert, Marc Röger, Florian Sutter, Niklas Blum, José Antonio Carballo, Aránzazu Fernandez, Maria del Carmen Alonso-García, Jesus Polo and Robert Pitz-Paal

Energies 2024, 17(19), 4878; https://doi.org/10.3390/en17194878 - 28 Sep 2024

Viewed by 758

Abstract

Solar energy plays a major role in the transition to renewable energy. To ensure that large-scale photovoltaic (PV) power plants operate at their full potential, their monitoring is essential. It is common practice to utilize drones equipped with infrared thermography (IRT) cameras to detect defects in modules, as the latter can lead to deviating thermal behavior. However, IRT images can also show temperature hot-spots caused by inhomogeneous soiling on the module’s surface. Hence, the method does not differentiate between defective and soiled modules, which may cause false identification and economic and resource loss when replacing soiled but intact modules. To avoid this, we propose to detect spatially inhomogeneous soiling losses and model temperature variations explained by soiling. The spatially resolved soiling information can be obtained, for example, using aerial images captured with ordinary RGB cameras during drone flights. This paper presents an electrothermal model that translates the spatially resolved soiling losses of PV modules into temperature maps. By comparing such temperature maps with IRT images, it can be determined whether the module is soiled or defective. The proposed solution consists of an electrical model and a thermal model which influence each other. The electrical model of Bishop is used which is based on the single-diode model and replicates the power output or consumption of each cell, whereas the thermal model calculates the individual cell temperatures. Both models consider the given soiling and weather conditions. The developed model is capable of calculating the module temperature for a variety of different weather conditions. Furthermore, the model is capable of predicting which soiling pattern can cause critical hot-spots. Full article

(This article belongs to the Special Issue Advances in Photovoltaic Solar Energy II)

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23 pages, 2142 KiB

Open AccessArticle

Identifying Critical Failures in PV Systems Based on PV Inverters’ Monitoring Unit: A Techno-Economic Analysis

by Filipe Monteiro, Eduardo Sarquis and Paulo Branco

Energies 2024, 17(18), 4738; https://doi.org/10.3390/en17184738 - 23 Sep 2024

Viewed by 837

Abstract

Recent advancements in power electronics have significantly improved photovoltaic (PV) inverters by equipping them with sophisticated monitoring capabilities. These enhancements provide economic advantages by facilitating swift failure detection and lowering monitoring costs. Educating users on the economic repercussions of undetected failures in specific inverter monitoring systems is crucial. This paper introduces a novel metric, “Cost of Detection”, which assesses the financial impact of failures, considering the repair expenses and the “quality” of the monitoring system in place. The study analyzed fifteen inverter monitoring solutions, focusing on the variance in alerts generated by the manufacturers’ standard and extra monitoring features. Employing the Failure Mode and Effects Analysis (FMEA) method, alerts were prioritized based on their importance for two PV system scenarios: a low-power residential system (5 kWp) and a medium-power industrial/commercial system (100 kWp). Lisbon, Rome, and Berlin were chosen as the locations for these systems. The economic impact of system failures is evaluated annually for each capacity and city. Given the differing costs and annual yields, comparing their economic performance over time is essential. This comparison utilizes the Net Present Value (NPV), which estimates an investment’s worth by calculating the present value of all cash flows. The investment assessment includes only the costs of inverters and optimizers, excluding O&M expenses, licenses, and fees. Over five years, a higher NPV signifies a more economically advantageous solution. For residential systems, string inverters with optimizers have the highest NPV, surpassing those without optimizers by 17% across all three cities. The optimal monitoring solution in the industrial/commercial context was a string inverter with one optimizer for every two panels. Here, Rome emerged as the location with the most substantial NPV increase of 50%, followed by Berlin with 33% and Lisbon with 28%. Full article

(This article belongs to the Special Issue Advances in Photovoltaic Solar Energy II)

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29 pages, 4992 KiB

Open AccessArticle

Regressive and Spatio-Temporal Accessibility of Variability in Solar Energy on a Short Scale Measurement in the Southern and Mid Region of Mozambique

by Fernando Venâncio Mucomole, Carlos Augusto Santos Silva and Lourenço Lázaro Magaia

Energies 2024, 17(11), 2613; https://doi.org/10.3390/en17112613 - 29 May 2024

Viewed by 718

Abstract

Solar energy reaching a horizontal surface can possess fluctuations that impact electricity generation at a solar plant. Despite this, energy access remains inadequate, particularly in rural areas, with an estimated 82% deficiency. This drives us to assess the regressive and spatial-temporal accessibility of solar energy in the southern and mid regions of Mozambique. This evaluation aims to determine the actual availability of energy for electrification purposes. Data on global horizontal irradiation from approximately 8 stations across all provinces in the specified regions, collected between 2012 and 2014 at intervals of 1 and 10 min, were analyzed using regression and correlation methods along with a specialized algorithm for classifying days based on clear sky index terms. The statistical analysis identified days with significant potential for energy accessibility, exceeding 50% of the average. The findings suggest a correlation coefficient of approximately 0.30 for energy and non-linear regression with clear sky index coefficients around 0.80. The method employed demonstrated accuracy when compared to theoretical simulations of the clear sky index in the region, indicating its potential applicability in other regions of interest. Full article

(This article belongs to the Special Issue Advances in Photovoltaic Solar Energy II)

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30 pages, 17740 KiB

Open AccessArticle

Analysis of Different Scenarios to Include PV Rooftop Systems with Battery Energy Storage Systems in Olive Mills

by Jose Luis Sánchez-Jiménez, Francisco José Muñoz-Rodríguez, Gabino Jiménez-Castillo, Antonio Javier Martinez-Calahorro and Catalina Rus-Casas

Energies 2024, 17(1), 144; https://doi.org/10.3390/en17010144 - 27 Dec 2023

Cited by 1 | Viewed by 1037

Abstract

The industrial sector is not the one with the highest energy consumption but, together with, it represents the most, together with the transport sector, the most polluting ones. Photovoltaic Rooftop systems and battery energy storage systems are very strong candidates to include renewable energy, allowing greater grid autonomy and greenhouse gas mitigation. Therefore, this paper aims to outline it will be provided a methodology based on monitored data to analyze the potential of photovoltaic Rooftops with battery energy storage systems regarding self-consumption and self-sufficiency indices in the industrial sector. Direct self-consumption and self-sufficiency indices, either with or without storage, will be analyzed. In addition, the iso self-consumption and iso self-sufficiency curves are used, which allow us to evaluate the matching between the generation and consumption profiles considering either direct self-consumption or the use of batteries. In this sense, a large, medium, and small olive mill were selected in order to cover the entire spectrum of these industries. Olive mills are suitable candidates for the incorporation of photovoltaic systems since generation profiles match the consumption profiles. However, the size of these systems is highly dependent on the period of consumption to be faced. Regarding batteries, both during the harvest and off-harvest periods, the impact on self-sufficiency becomes significant, reaching increases of up to 10%, depending on the battery capacity used. Full article

(This article belongs to the Special Issue Advances in Photovoltaic Solar Energy II)

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18 pages, 7049 KiB

Open AccessArticle

Revolutionizing Solar Power Forecasts by Correcting the Outputs of the WRF-SOLAR Model

by Cheng-Liang Huang, Yuan-Kang Wu, Chin-Cheng Tsai, Jing-Shan Hong and Yuan-Yao Li

Energies 2024, 17(1), 88; https://doi.org/10.3390/en17010088 - 22 Dec 2023

Viewed by 1060

Abstract

Climate change poses a significant threat to humanity. Achieving net-zero emissions is a key goal in many countries. Among various energy resources, solar power generation is one of the prominent renewable energy sources. Previous studies have demonstrated that post-processing techniques such as bias correction can enhance the accuracy of solar power forecasting based on numerical weather prediction (NWP) models. To improve the post-processing technique, this study proposes a new day-ahead forecasting framework that integrates weather research and forecasting solar (WRF-Solar) irradiances and the total solar power generation measurements for five cities in northern, central, and southern Taiwan. The WRF-Solar irradiances generated by the Taiwan Central Weather Bureau (CWB) were first subjected to bias correction using the decaying average (DA) method. Then, the effectiveness of this correction method was verified, which led to an improvement of 22% in the forecasting capability from the WRF-Solar model. Subsequently, the WRF-Solar irradiances after bias correction using the DA method were utilized as inputs into the transformer model to predict the day-ahead total solar power generation. The experimental results demonstrate that the application of bias-corrected WRF-Solar irradiances enhances the accuracy of day-ahead solar power forecasts by 15% compared with experiments conducted without bias correction. These findings highlight the necessity of correcting numerical weather predictions to improve the accuracy of solar power forecasts. Full article

(This article belongs to the Special Issue Advances in Photovoltaic Solar Energy II)

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22 pages, 4841 KiB

Open AccessArticle

Addressing Challenges in Delivering Sustainable Rural Water Provision Using Solar Water Pumping in Malawi: A Stakeholder Analysis

by Esther Phiri, Paul N. Rowley and Richard E. Blanchard

Energies 2023, 16(23), 7758; https://doi.org/10.3390/en16237758 - 24 Nov 2023

Cited by 1 | Viewed by 1406

Abstract

Despite the presence of relatively high insolation, solar photovoltaic water pumping (SWP) is rarely used for water provision in Malawi. Current methods of water abstraction are labour-intensive and have low discharge rates. A stakeholder analysis was carried out to evaluate the role, responsibilities, and challenges faced by individuals, communities, and organisations involved in developing SWP systems. Analysis of data collected via semi-structured interviews with stakeholders from government departments, public and private organisations, entrepreneurs, non-governmental organisations, and microfinance organisations shows that the national government should provide an enabling environment for other actors to deliver SWP projects. Further, this study reveals diverse interlinked challenges in delivering sustainable water and energy services related to policies, monitoring, coordination, financing, human resources, information and awareness, stakeholder malfeasance, political interference, and flawed community management. The impacts of these challenges result in inadequate water service provision resulting from access inequality, non-functionality, substandard installations, reliance on donations, substandard renewable energy products, and slow technology uptake. The results of this study imply that, given appropriate finance and management frameworks, effective coordination, enforcement of product and installation standards, and awareness and sensitisation of communities to SWP, significantly improved access to drinking and irrigation water for the rural population of Malawi and other countries in sub-Saharan Africa can be achieved. Full article

(This article belongs to the Special Issue Advances in Photovoltaic Solar Energy II)

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