energies-logo

Journal Browser

Journal Browser

Special Issue "Selected Papers from SEEP2017: The 10th International Conference on Sustainable Energy and Environmental Protection"

A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: closed (4 December 2017).

Special Issue Editors

Emeritus Prof. Dr. Jurij Krope
E-Mail
Guest Editor
Faculty of Chemistry and Chemical Engineering, University of Maribor, Maribor, Slovenia
Interests: renewable energy sources; energy efficiency; energy management and policies; waste energy and management
Prof. Dr. Abdul-Ghani Olabi
grade E-Mail Website
Guest Editor
1. Department of Sustainable and Renewable Energy Engineering, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates
2. Mechanical Engineering and Design, School of Engineering and Applied Science, Aston University, Aston Triangle, Birmingham B4 7ET, UK
Interests: renewable energy; energy storage systems, sustainability; CAD and design; smart materials
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Darko Goričanec
E-Mail
Guest Editor
Faculty of Chemistry and Chemical Engineering, University of Maribor, Maribor, Slovenia
Interests: energy efficiency; modelling and simulations; environmental management and impact assessment; energy storage; waste energy and management; combined and hybrid energy systems

Special Issue Information

Dear Colleagues,

The demands for effective exploitation of energy, utilization of alternative energy sources, and the design of advanced energy systems are coming to the fore. In order to meet these demands in the best possible way, SEEP 2017 will take place, where we want to create an environment for exchanging information between researchers from universities and institutes, industrial experts, and PhD students. This will enable discussions regarding innovative solutions, successful practical applications, and different energy scenarios, which will be a significant contribution to sustainable energy development. SEEP 2017 is a conference for you to be informed and inspired regarding energy activities worldwide.

Emeritus Prof. Dr. Jurij Krope
Prof. Dr. Abdul Ghani Olabi
Prof. Dr. Darko Goričanec
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. 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

  • Renewable Energy Sources,
  • Energy Efficiency,
  • Bioenergy and Biofuels
  • Modelling and Simulations
  • Hydrogen and Fuel Cells
  • Environmental Management and Impact Assessment
  • Energy Storage
  • Energy Management and Policies,
  • Waste Energy and Management
  • Combined and Hybrid Energy Systems

Published Papers (3 papers)

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

Research

Article
A Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the Prediction of the Daily Direct Solar Radiation
Energies 2018, 11(3), 620; https://doi.org/10.3390/en11030620 - 10 Mar 2018
Cited by 113 | Viewed by 3945
Abstract
The solar photovoltaic (PV) energy has an important place among the renewable energy sources. Therefore, several researchers have been interested by its modelling and its prediction, in order to improve the management of the electrical systems which include PV arrays. Among the existing [...] Read more.
The solar photovoltaic (PV) energy has an important place among the renewable energy sources. Therefore, several researchers have been interested by its modelling and its prediction, in order to improve the management of the electrical systems which include PV arrays. Among the existing techniques, artificial neural networks have proved their performance in the prediction of the solar radiation. However, the existing neural network models don’t satisfy the requirements of certain specific situations such as the one analyzed in this paper. The aim of this research work is to supply, with electricity, a race sailboat using exclusively renewable sources. The developed solution predicts the direct solar radiation on a horizontal surface. For that, a Nonlinear Autoregressive Exogenous (NARX) neural network is used. All the specific conditions of the sailboat operation are taken into account. The results show that the best prediction performance is obtained when the training phase of the neural network is performed periodically. Full article
Show Figures

Graphical abstract

Article
Informatics Solution for Energy Efficiency Improvement and Consumption Management of Householders
Energies 2018, 11(1), 138; https://doi.org/10.3390/en11010138 - 05 Jan 2018
Cited by 10 | Viewed by 2048
Abstract
Although in 2012 the European Union (EU) has promoted energy efficiency in order to ensure a gradual 20% reduction of energy consumption by 2020, its targets related to energy efficiency have increased and extended to new time horizons. Therefore, in 2016, a new [...] Read more.
Although in 2012 the European Union (EU) has promoted energy efficiency in order to ensure a gradual 20% reduction of energy consumption by 2020, its targets related to energy efficiency have increased and extended to new time horizons. Therefore, in 2016, a new proposal for 2030 of energy efficiency target of 30% has been agreed. However, during the last years, even if the electricity consumption by households decreased in the EU-28, the largest expansion was recorded in Romania. Taking into account that the projected consumption peak is increasing and energy consumption management for residential activities is an important measure for energy efficiency improvement since its ratio from total consumption can be around 25–30%, in this paper, we propose an informatics solution that assists both electricity suppliers/grid operators and consumers. It includes three models for electricity consumption optimization, profiles, clustering and forecast. By this solution, the daily operation of appliances can be optimized and scheduled to minimize the consumption peak and reduce the stress on the grid. For optimization purpose, we propose three algorithms for shifting the operation of the programmable appliances from peak to off-peak hours. This approach enables the supplier to apply attractive time-of-use tariffs due to the fact that by flattening the consumption peak, it becomes more predictable, and thus improves the strategies on the electricity markets. According to the results of the optimization process, we compare the proposed algorithms emphasizing the benefits. For building consumption profiles, we develop a clustering algorithm based on self-organizing maps. By running the algorithm for three scenarios, well-delimited profiles are obtained. As for the consumption forecast, highly accurate feedforward artificial neural networks algorithm with backpropagation is implemented. Finally, we test these algorithms using several datasets showing their performance and integrate them into a web-service informatics solution as a prototype. Full article
Show Figures

Figure 1

Article
Energy Consumption Forecasting for University Sector Buildings
Energies 2017, 10(10), 1579; https://doi.org/10.3390/en10101579 - 12 Oct 2017
Cited by 42 | Viewed by 2751
Abstract
Reliable energy forecasting helps managers to prepare future budgets for their buildings. Therefore, a simple, easier, less time consuming and reliable forecasting model which could be used for different types of buildings is desired. In this paper, we have presented a forecasting model [...] Read more.
Reliable energy forecasting helps managers to prepare future budgets for their buildings. Therefore, a simple, easier, less time consuming and reliable forecasting model which could be used for different types of buildings is desired. In this paper, we have presented a forecasting model based on five years of real data sets for one dependent variable (the daily electricity consumption) and six explanatory variables (ambient temperature, solar radiation, relative humidity, wind speed, weekday index and building type). A single mathematical equation for forecasting daily electricity usage of university buildings has been developed using the Multiple Regression (MR) technique. Data of two such buildings, located at the Southwark Campus of London South Bank University in London, have been used for this study. The predicted test results of MR model are examined and judged against real electricity consumption data of both buildings for year 2011. The results demonstrate that out of six explanatory variables, three variables; surrounding temperature, weekday index and building type have significant influence on buildings energy consumption. The results of this model are associated with a Normalized Root Mean Square Error (NRMSE) of 12% for the administrative building and 13% for the academic building. Finally, some limitations of this study have also been discussed. Full article
Show Figures

Figure 1

Back to TopTop