Next Article in Journal
A Critical Analysis and Validation of the Accuracy of Wave Overtopping Prediction Formulae for OWECs
Next Article in Special Issue
A Nonlinear Autoregressive Exogenous (NARX) Neural Network Model for the Prediction of the Daily Direct Solar Radiation
Previous Article in Journal
Variance Characteristics of Tropical Radiosonde Winds Using a Vector-Tensor Method
Previous Article in Special Issue
Energy Consumption Forecasting for University Sector Buildings
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle
Energies 2018, 11(1), 138; doi:10.3390/en11010138

Informatics Solution for Energy Efficiency Improvement and Consumption Management of Householders

Department of Economic Informatics and Cybernetics, The Bucharest University of Economic Studies, Romana Square 6, Bucharest 010374, Romania
*
Author to whom correspondence should be addressed.
Received: 3 December 2017 / Revised: 22 December 2017 / Accepted: 1 January 2018 / Published: 5 January 2018
View Full-Text   |   Download PDF [6917 KB, uploaded 8 January 2018]   |  

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 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. View Full-Text
Keywords: consumption management; programmable appliances; informatics solution; optimization algorithms; load profile; forecast; web-services; prototype consumption management; programmable appliances; informatics solution; optimization algorithms; load profile; forecast; web-services; prototype
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Oprea, S.-V.; Bâra, A.; Reveiu, A. Informatics Solution for Energy Efficiency Improvement and Consumption Management of Householders. Energies 2018, 11, 138.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top