• Energy Research

The purpose of this work is to investigate the effect of environmental variables on the electric energy expenditure of a typical surface warship. Studies with similar objectives are much more frequent for merchant ships, but warship operations have peculiarities that will be emphasised. In particular, they spend large fractions of their life cycle at port, during which the vessel remains active. First, a discussion of the embarked systems is presented, pointing out the importance of auxiliary systems and, in particular, heating, ventilation and air conditioning. Quantitative estimates of the energy consumption of those systems are provided. Then, using data taken during real operations of a frigate of the Spanish Navy, correlations are computed between power consumption and different environmental variables. As a novelty, the analysis is carried out separating the different modes of operation of the ship. This leads to interesting conclusions, including a considerable positive correlation between seawater temperature and fuel consumption when the vessel is in port. The effect of a moored ship on the surrounding seawater temperature is studied by a numerical computation. The results suggest that the position of sea chests may be consequential for energy efficiency.

We present a statistical analysis of correlations between carbon dioxide concentration and energy consumption in workplaces, with the goal of enabling its eventual programming in energy platforms In Cloud for improving management and enhancing automation and control in the service sector industry. A low-cost system is used to measure and transmit the data of buildings and the information can be analyzed by any remote device. The study includes data measured during one year in two offices located at Sada (A Coruña, Spain) and Clayton (Panama). We present linear and nonlinear regression curves, show that there are significant positive correlations and discuss seasonal and climate-related aspects. We argue that this kind of analysis can provide useful information for the design and operation in the service industry, through web-based energy platforms for control and automation. Keywords: Industry 4.0, intelligent energy platforms, energy consumption, statistical analysis, automation of facilities, control of facilities.

Abstract We present a mathematical model to diagnose HVAC systems in buildings based upon the analysis of a small number of ambient state variables. In particular, the equations of the model accurately fit recorded data of temperature, relative humidity and carbon dioxide concentration in different workplaces. For validation, data were obtained under different conditions and with different sensors. In particular, we designed and fabricated a wireless sensor that measures and transmits data to a remote device and we also applied our model to data collected using a commercial sensor. For each case, information was obtained that could be used to understand and predict the evolution of ambient variables that impact thermal comfort and energy consumption in buildings. The tools presented here can thus be of great interest to achieve affordable, smart energy-efficient buildings, while adhering to environmental laws and comfort for work spaces.

In the present work, we analyze the influence of the designer’s choice of values for the human metabolic index (met) and insulation by clothing (clo) that can be selected within the ISO 7730 for the calculation of the energy demand of buildings. To this aim, we first numerically modeled, using TRNSYS, two buildings in different countries and climatologies. Then, we consistently validated our simulations by predicting indoor temperatures and comparing them with measured data. After that, the energy demand of both buildings was obtained. Subsequently, the variability of the set-point temperature concerning the choice of clo and met, within limits prescribed in ISO 7730, was analyzed using a Monte Carlo method. This variability of the interior comfort conditions has been finally used in the numerical model previously validated, to calculate the changes in the energy demand of the two buildings. Therefore, this work demonstrated that the diversity of possibilities offered by ISO 7730 for the choice of clo and met results, depending on the values chosen by the designer, in significant differences in indoor comfort conditions, leading to non-negligible changes in the calculations of energy consumption, especially in the case of big buildings.