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Energies
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Stochastic Modeling of Wind Speed and Energy Production
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Stochastic Modeling of Wind Speed and Energy Production

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A3: Wind, Wave and Tidal Energy".

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 5586

Special Issue Editors

Prof. Dr. Filippo Petroni

E-Mail Website
Guest Editor
Department of Management, Università Politecnica delle Marche, 60121 Ancona, Italy
Interests: applied mathematics; stochastic models; financial mathematics; complex systems; languages; econophysics; renewable energies; semi-Markov processes
Prof. Dr. Guglielmo D'Amico

E-Mail Website
Guest Editor
Department of Economics, University “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy
Interests: stochastic modeling; Markov and semi-Markov processes; renewable energies; financial mathematics; inequality measures

Special Issue Information

Dear Colleagues,

I would like to extend a warm invitation to you all to submit a research paper to this Special Issue of Energies (ISSN 1996-1073; CODEN: ENERGA) on "Stochastic Modeling of Wind Speed and Energy Production". This is a topical issue dedicated to recent advances in this very broad field—the main criteria for paper acceptance being academic excellence, originality, and novelty of applications, methods, or fundamental findings. All types of research approaches are equally acceptable: experimental, theoretical, computational, and their mixtures. The papers can be of a fundamental or an applied nature, including industrial case studies. With such a wide scope, it is naturally very difficult to define a finite list of relevant disciplines. However, it is broadly anticipated that the authorship and ultimate readership would come from the fields of mathematics, economics, physics, energy, engineering, and all those disciplines interested not only in wind speed but in the broader subject of renewable energy. Cross-disciplinary research and development studies will also be most welcome.

Prof. Dr. Filippo Petroni
Prof. Dr. Guglielmo D'Amico
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 submissions that pass pre-check are 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 2600 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

  • stochastic modeling
  • wind speed
  • wind energy
  • renewable energy

Published Papers (2 papers)

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Research

25 pages, 4493 KiB  
Article
An Analysis of a Storage System for a Wind Farm with Ramp-Rate Limitation
by Guglielmo D’Amico, Filippo Petroni and Salvatore Vergine
Energies 2021, 14(13), 4066; https://doi.org/10.3390/en14134066 - 05 Jul 2021
Cited by 10 | Viewed by 2502
Abstract
This paper provides evidence on how the variability of the power produced by a wind farm and its revenue are affected by implementing a ramp-rate limitation strategy and by adding a storage device to the system. The wind farm receives penalties whenever the [...] Read more.
This paper provides evidence on how the variability of the power produced by a wind farm and its revenue are affected by implementing a ramp-rate limitation strategy and by adding a storage device to the system. The wind farm receives penalties whenever the ramp-rate limitations are not respected and may be supported by batteries to avoid this scenario. In this paper, we model the battery usage as a discrete time homogeneous Markov chain with rewards thanks to which it is possible to simulate the state of the charge of the battery and to calculate the amount of penalties suffered by the wind farm during any period. An application is performed considering the power produced by a hypothetical wind turbine located in Sardinia (Italy) using real wind speed data and electricity prices from a period of 10 years. We applied the concept of ramp-rate limitation on our hourly dataset, studying several limitation scenarios and battery capacities. Full article
(This article belongs to the Special Issue Stochastic Modeling of Wind Speed and Energy Production)
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Graphical abstract

16 pages, 1642 KiB  
Article
A Multivariate High-Order Markov Model for the Income Estimation of a Wind Farm
by Riccardo De Blasis, Giovanni Batista Masala and Filippo Petroni
Energies 2021, 14(2), 388; https://doi.org/10.3390/en14020388 - 12 Jan 2021
Cited by 4 | Viewed by 1781
Abstract
The energy produced by a wind farm in a given location and its associated income depends both on the wind characteristics in that location—i.e., speed and direction—and the dynamics of the electricity spot price. Because of the evidence of cross-correlations between wind speed, [...] Read more.
The energy produced by a wind farm in a given location and its associated income depends both on the wind characteristics in that location—i.e., speed and direction—and the dynamics of the electricity spot price. Because of the evidence of cross-correlations between wind speed, direction and price series and their lagged series, we aim to assess the income of a hypothetical wind farm located in central Italy when all interactions are considered. To model these cross and auto-correlations efficiently, we apply a high-order multivariate Markov model which includes dependencies from each time series and from a certain level of past values. Besides this, we used the Raftery Mixture Transition Distribution model (MTD) to reduce the number of parameters to get a more parsimonious model. Using data from the MERRA-2 project and from the electricity market in Italy, we estimate the model parameters and validate them through a Monte Carlo simulation. The results show that the simulated income faithfully reproduces the empirical income and that the multivariate model also closely reproduces the cross-correlations between the variables. Therefore, the model can be used to predict the income generated by a wind farm. Full article
(This article belongs to the Special Issue Stochastic Modeling of Wind Speed and Energy Production)
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