Special Issue "Selected Papers from the 20th IEEE International Conference on Environment and Electrical Engineering (EEEIC 2020) Special Session “Forecasting & Prognostic in Power Systems”"

A special issue of Forecasting (ISSN 2571-9394). This special issue belongs to the section "Power and Energy Forecasting".

Deadline for manuscript submissions: 30 June 2021.

Special Issue Editors

Prof. Dr. Sonia Leva
Website
Guest Editor
Department of Energy, Politecnico Di Milano, Via Lambruschini 4, Milano I-20156, Italy
Interests: energy forecasting; wind and solar energy systems; PV forecasting; renewable energy; multi-good microgrid; vehicle-to-grid
Special Issues and Collections in MDPI journals
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)
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

This special EEEIC session is about power forecasting and prognostic techniques in power systems. The main topics can be summarized as follows:

Energy Forecasting:

Forecasting of intermittent energy resources;

Wind and solar power forecasting;

Forecasting of demand (load) and price of electricity;

Load and generation forecasting in smart grid and microgrids;

Forecasting methods in energy planning models.

Forecasting of Remaining Useful Life:

Forecasting methods for reliability;

Maintenance and safety;

Smart device and prediction of system reliability;

Prognostics and system health management;

Predictive and prescriptive maintenance.

Prof. Dr. Sonia Leva
Prof. Francesco Grimaccia
Guest Editors

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. Forecasting is an international peer-reviewed open access quarterly 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 1000 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.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Open AccessArticle
Sun Position Identification in Sky Images for Nowcasting Application
Forecasting 2020, 2(4), 488-504; https://doi.org/10.3390/forecast2040026 - 16 Nov 2020
Abstract
Very-short-term photovoltaic power forecast, namely nowcasting, is gaining increasing attention to face grid stability issues and to optimize microgrid energy management systems in the presence of large penetration of renewable energy sources. In order to identify local phenomena as sharp ramps in photovoltaic [...] Read more.
Very-short-term photovoltaic power forecast, namely nowcasting, is gaining increasing attention to face grid stability issues and to optimize microgrid energy management systems in the presence of large penetration of renewable energy sources. In order to identify local phenomena as sharp ramps in photovoltaic production, whole sky images can be used effectively. The first step in the implementation of new and effective nowcasting algorithms is the identification of Sun positions. In this paper, three different techniques (solar angle-based, image processing-based, and neural network-based techniques) are proposed, described, and compared. These techniques are tested on real images obtained with a camera installed at SolarTechLab at Politecnico di Milano, Milan, Italy. Finally, the three techniques are compared by introducing some performance parameters aiming to evaluate of their reliability, accuracy, and computational effort. The neural network-based technique obtains the best performance: in fact, this method is able to identify accurately the Sun position and to estimate it when the Sun is covered by clouds. Full article
Show Figures

Figure 1

Back to TopTop