Short-term energy use prediction of solar-assisted water heating system: Application case of combined attention-based LSTM and time-series decomposition

Solar Energy ◽  
2020 ◽  
Vol 207 ◽  
pp. 626-639 ◽  
Author(s):  
Amirreza Heidari ◽  
Dolaana Khovalyg
Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3189
Author(s):  
Sukjoon Oh ◽  
Chul Kim ◽  
Joonghyeok Heo ◽  
Sung Lok Do ◽  
Kee Han Kim

Many smart apartments and renovated residential buildings have installed Smart Meters (SMs), which collect interval data to accelerate more efficient energy management in multi-family residential buildings. SMs are widely used for electricity, but many utility companies have been working on systems for natural gas and water monitoring to be included in SMs. In this study, we analyze heating energy use data obtained from SMs for short-term monitoring and annual predictions using change-point models for the coefficient checking method. It was found that 9-month periods were required to search the best short-term heating energy monitoring periods when non-weather-related and weather-related heating loads and heating change-point temperatures are considered. In addition, the 9-month to 11-month periods were needed for the analysis to apply to other case study residences in the same high-rise apartment. For the accurate annual heating prediction, 11-month periods were necessary. Finally, the results from the heating performance analysis of this study were compared with the cooling performance analysis from a previous study. This study found that the coefficient checking method is a simple and easy-to-interpret approach to analyze interval heating energy use in multi-family residential buildings. It was also found that the period of short-term energy monitoring should be carefully selected to effectively collect targeted heating and cooling data for an energy audit or annual prediction.


Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1569
Author(s):  
Santiago Moreno-Carbonell ◽  
Eugenio F. Sánchez-Úbeda ◽  
Antonio Muñoz

Temperature is widely known as one of the most important drivers to forecast electricity and gas variables, such as the load. Because of that reason, temperature forecasting is and has been for years of great interest for energy forecasters and several approaches and methods have been published. However, these methods usually do not consider temperature trend, which causes important error increases when dealing with medium- or long-term estimations. This paper presents several temperature forecasting methods based on time series decomposition and analyzes their results and the trends of 37 different European countries, proving their annual average temperature increase and their different behaviors regarding trend and seasonal components.


2016 ◽  
Vol 27 (2) ◽  
pp. 146-166 ◽  
Author(s):  
Stella Androulaki ◽  
Haris Doukas ◽  
Vangelis Marinakis ◽  
Leandro Madrazo ◽  
Nikoletta-Zabbeta Legaki

Purpose – The purpose of this paper is to identify the most appropriate multidisciplinary data sources related with energy optimization decision support as well as the related methodologies, tools and techniques for data capturing and processing for each of them. Design/methodology/approach – A review is conducted on the state-of-play of decision support systems for energy optimization, focussing on the municipal sector, followed by an identification of the most appropriate multidisciplinary data sources related with energy optimization decision support. An innovative methodology is outlined to integrate semantically modeled data from multiple sources, to assist city authorities in energy management. Findings – City authorities need to lead relevant actions toward energy-efficient neighborhoods. Although there are more and more energy and other related data available at the city level, there are no established methods and tools integrating and analyzing them in a smart way, with the purpose to support the decision-making process on energy use optimization. Originality/value – A novel multidimensional approach is proposed, using semantic technologies to integrate data from multiple sources, to assist city authorities to produce short-term energy plans in an integrated, transparent and comprehensive way.


Author(s):  
Pappu Kumar Singh ◽  
A. K. Mahapatra ◽  
U. Prasad

The efficient use of energy is the key to maintaining our world’s resources; indeed our future depends on it. Energy conservation can be achieved through increased efficient energy use, in connection with decreased energy consumption and reduced consumption from conventional energy sources. Energy conservation can result in increased financial capital, environmental quality, national security, personal security, and human comfort. Individuals and organizations that are direct consumers of energy choose to conserve energy to reduce energy costs and promote economic security. In view of the nation's energy security interests, it is important to be increasing alternative fuel capability throughout the fleet. The need to ensure the nation's long-term energy security is of such vital concern that it takes precedent over possible short-term convention energy sources consumption and environmental impacts.


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