Special Issue "Unmanned Aerial Vehicles for Energy Applications"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "Electric Vehicles".

Deadline for manuscript submissions: closed (30 April 2020).

Special Issue Editor

Prof. Dr. Francesco Grimaccia
Website
Guest Editor
Department of Energy, Politecnico Di Milano, Via Lambruschini 4, Milano I-20156, Italy
Interests: energy forecasting; PV forecasting; evolutionary computation; energy harvesting devices (EHDs); renewable systems; unmanned aerial vehicles (UAVs)
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Special Issue Information

Dear Colleagues,

Renewable energy sources’ contribution to power generation almost represents a valid alternative to limiting fossil fuel usage and pollution for the future. In the last two decades, many countries have widely invested in alternative energy sources to reduce emissions and politically promote so-called clean energy and we are facing a general transition scenario. Some countries, for example, have witnessed a too-rapid increase in their production rate from RES, especially solar and wind, with the complicity of a general market euphoria and, sometimes, generous public policies.

The quality of the installed components and subsystems has not always been guaranteed, especially because it was produced in a rapid time frame, and often with characteristics below the common standards, optimizing installation costs and underestimating a proper plant life cycle cost analysis. In some occasions, the race to install and meet public incentives has left many solar installations with a general lack of good maintenance strategies. In addition to this, advances in wind turbine blade design and materials and proper asset management actions often allow repowering strategies if advanced performance and control systems are available. Moreover, developing countries are implementing new energy plans for the next years to accelerate this energy transition towards more efficient systems.

Unmanned aerial vehicles (UAVs), also known as drones, have recently received much attention from the industry due to their ability to act as remote sensors for many applications, including 3D-mapping, construction monitoring, and data collection through heterogeneous sensors in general. A broad range of solutions are appearing in the market for different applications and services related to the acquisition of information, for example, in power plants, transmission lines, low-emission buildings or other energy systems and components.

Thus, to further spread the real opportunity offered by technologies and methods related to unmanned technologies in the energy sector, this Special Issue entitled “Unmanned Aerial Vehicles for Energy Applications” was proposed for the international journal Energies, which is an SSCI and SCIE journal (2015 IF = 2.072). This Special Issue mainly covers original research and studies related to the abovementioned topics, including but not limited to drone-based diagnosis methods, advanced O&M with unmanned technologies, predictive and reactive maintenance based on remote data, automatic inspection, and UAV-based control systems. Papers selected for this Special Issue are subject to a rigorous peer review procedure with the aim of rapid and wide dissemination of research results, developments, and applications.

I am writing to invite you to submit your original work to this Special Issue. The Special Issue welcomes contributions dealing with all facets of drones as mobile computing platforms in application in the energy sector, mainly related to renewable and traditional plants performance monitoring and control.

Prof. Dr. Grimaccia Francesco
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • UAV-based diagnosis, prognosis and forecasting methods for energy plant control
  • Predictive and reactive maintenance based on remote sensors
  • In-field diagnostic tools and algorithms
  • Components aging mechanisms and defect detection by UAVs
  • Reliability and effectiveness of novel algorithms based on multiple aerial sensors
  • UAV-based automatic inspection and control for energy systems
  • Advanced O&M with unmanned technologies
  • Energy assets’ management through UAVs

Published Papers (4 papers)

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Research

Open AccessArticle
A Computer Vision Line-Tracking Algorithm for Automatic UAV Photovoltaic Plants Monitoring Applications
Energies 2020, 13(4), 838; https://doi.org/10.3390/en13040838 - 14 Feb 2020
Cited by 4
Abstract
In this paper, the authors propose an UAV-based automatic inspection method for photovoltaic plants analyzing and testing a vision-based guidance method developed to this purpose. The maintenance of PV plants represents a key aspect for the profitability in energy production and autonomous inspection [...] Read more.
In this paper, the authors propose an UAV-based automatic inspection method for photovoltaic plants analyzing and testing a vision-based guidance method developed to this purpose. The maintenance of PV plants represents a key aspect for the profitability in energy production and autonomous inspection of such systems is a promising technology especially for large utility-scale plants where manned techniques have significant limitations in terms of time, cost and performance. In this light, an ad hoc flight control solution is investigated to exploit available UAV sensor data to enhance flight monitoring capability and correct GNSS position errors with respect to final target needs. The proposed algorithm has been tested in a simulated environment with a software-in-the loop (SITL) approach to show its effectiveness and final comparison with state of the art solutions. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles for Energy Applications)
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Open AccessArticle
Cooperative Transmission Tower Inspection with a Vehicle and a UAV in Urban Areas
Energies 2020, 13(2), 326; https://doi.org/10.3390/en13020326 - 09 Jan 2020
Cited by 3
Abstract
To reduce the workload of inspectors and improve the inspection efficiency of urban transmission towers, a new inspection method is proposed in this paper, in which an unmanned aerial vehicle (UAV) and vehicle cooperate with each other. We investigate the cooperative path planning [...] Read more.
To reduce the workload of inspectors and improve the inspection efficiency of urban transmission towers, a new inspection method is proposed in this paper, in which an unmanned aerial vehicle (UAV) and vehicle cooperate with each other. We investigate the cooperative path planning problem of a UAV and a vehicle for transmission tower inspection and develop a new 0–1 integer programming model to address the problem. An odd-even layered genetic algorithm (O-ELGA) is proposed to efficiently solve the model. Finally, the effectiveness of the algorithm is further verified by simulation experiments. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles for Energy Applications)
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Open AccessArticle
Advanced Asset Management Tools in Photovoltaic Plant Monitoring: UAV-Based Digital Mapping
Energies 2019, 12(24), 4736; https://doi.org/10.3390/en12244736 - 12 Dec 2019
Cited by 4
Abstract
Photovoltaic (PV) plant monitoring and maintenance has become an often critical activity: the high efficiency requirements of the new European policy have often been in contrast with the many low-quality plants installed in several countries over the past few years. In actual industrial [...] Read more.
Photovoltaic (PV) plant monitoring and maintenance has become an often critical activity: the high efficiency requirements of the new European policy have often been in contrast with the many low-quality plants installed in several countries over the past few years. In actual industrial practices, heterogeneous information is produced, and they are often managed in a fragmented way. Several software tools have been developed for obtaining reliable and valuable information from the PV plant’s raw data. With the aim of gathering and managing all these data in a more complex and integrated manner, an information managing system is proposed in this work—it is composed of a structured database, called the Photovoltaic Indexed Database, and a user interface, called the Digital Map, that allows for easy access and completion of the information present in the database. This information managment system and PV plant digitalization process is able to analyze and properly index the IR in the database, as well as the visual images obtained in photovoltaic plant monitoring. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles for Energy Applications)
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Open AccessArticle
Evaluating the Operational Potential of LRV Signatures Derived from UAV Imagery in Performance Evaluation of Cool Roofs
Energies 2019, 12(14), 2787; https://doi.org/10.3390/en12142787 - 19 Jul 2019
Cited by 1
Abstract
It is quite difficult to find studies regarding area-wide data from UAV (Unmanned Aerial Vehicle) remote sensing in evaluating the energy saving performance of a cool roof. Acknowledging these constraints, we investigated whether LRV (Light Reflectance Value) signatures derived from UAV imagery could [...] Read more.
It is quite difficult to find studies regarding area-wide data from UAV (Unmanned Aerial Vehicle) remote sensing in evaluating the energy saving performance of a cool roof. Acknowledging these constraints, we investigated whether LRV (Light Reflectance Value) signatures derived from UAV imagery could be used effectively as an indicator of area-wide heating and cooling load that distinctively appears according to rooftop color. The case study provides some quantitative tangible evidence for two distinct colors: A whitish color roof appears near the edge of the highest LRV (91.36) and with a low temperature (rooftop surface temperature: (38.03 °C), while a blackish color roof shows the lowest LRV (18.14) with a very high temperature (65.03 °C) where solar radiation is extensively absorbed. A strong negative association (Pearson correlation coefficient, r = −0.76) was observed between the LRV and surface temperature, implying that a higher LRV (e.g., a white color) plays a decisive role in lowering the surface temperature. This research can be used as a valuable reference introducing LRV in evaluating the thermal performance of rooftop color as rooftops satisfying the requirement of a cool roof (reflecting 75% or more of incoming solar energy) are identified based on area-wide objective evidence from UAV imagery. Full article
(This article belongs to the Special Issue Unmanned Aerial Vehicles for Energy Applications)
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