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Prediction of natural gas consumption of a town is very important for its logistics and district heating workflow. In this paper different empirical models are introduced for gas consumption prediction. The models are based on the characteristics of gas consumption data that was gathered in Ljubljana, Slovenia. Important observables were recognized from the data and the models were structured according...
In this study, the problems of modeling, energy dispatching and Photovoltaic (PV) array energy priorities for a grid connected residential house with PV array and battery storage using model predictive control (MPC) have been investigated. Artificial neural network (ANN) based global solar radiation forecast was used to plan in advance for periods of low sunshine. MPC was able to reduce electricity...
The spatial layout of an urban system has important effects on the indoor cooling load and outdoor thermal comfort especially for regions with extreme hot weather. These effects, however, are difficult to analyze in the presence of human adaptation to thermal stress. This paper presents an integrated model to analyze the effects of urban geometry on indoor cooling load and outdoor thermal comfort...
In this paper we present our developed and evaluated method for the dynamic mapping of the vertical characteristics inside a building. For achieving that, we extract data from smart-phone sensors and use those data for altitude estimation via the barometric formula. We introduce a novel approach for the extraction of reference pressure during the outdoor-to-indoor-transition of the user inside a building,...
This article deals with the identification of a dynamic building model from on-site input-output records. In practice, the solar gains, a key input, are often unobserved due to the cost of the associated sensor. We suggest here to replace this sensor by a cheap outdoor temperature sensor, exposed to the sun. Our assumption is that the temperature bias between this sensor and a second sheltered sensor...
Toward weather condition recognition, we emphasize the importance of regional cues in this paper and address a few important problems regarding appropriate representation, its differentiation among regions, and weather-condition feature construction. Our major contribution is, first, to construct a multi-class benchmark data set containing 65 000 images from six common categories for sunny, cloudy,...
Majority of energy consumption in Singapore buildings is due to air-conditioning, because of its hot and humid weather. Besides attaining a healthy indoor environment, a prior knowledge about the occupant's thermal comfort can be beneficial in reducing energy consumption, as it can save energy which is otherwise spent in extra cooling. This paper proposes a data-driven approach to predict individual...
In recent years, the research about energy waste and CO2 emission reduction has gained a strong momentum, also pushed by European and national funding initiatives. The main purpose of this large effort is to reduce the effects of greenhouse emission, climate change to head for a sustainable society. In this scenario, Information and Communication Technologies (ICT) play a key role. From one side,...
This paper introduces a deep-learning approach to photographic style transfer that handles a large variety of image content while faithfully transferring the reference style. Our approach builds upon the recent work on painterly transfer that separates style from the content of an image by considering different layers of a neural network. However, as is, this approach is not suitable for photorealistic...
In the current state of the art load management and demand response actions in smart buildings are often predetermined by a field engineer to a fixed set of (rule-based) options. This fixed set of options often neglects the cyber-physical nature of the building dynamics, thermostatic action and building automation system. In this work we will combine a rule-based load management program with a learning...
There is widespread consensus in the climate research community that households show different attitudes toward the broad spectrum of technologies and policy instruments implemented to reduce CO2 emissions. The aim of this paper is to investigate the monetary aspect of socio-economic acceptability of four sustainable green technologies development: green electricity, energy savings in residential...
HEART - an innovative EU H2020 funded project - recently took off with the goal of concretely tackling technical, economic and social aspects related to climate change and building energy consumptions.
Model predictive control is seen as one of the key future enabler in increasing energy efficiency in buildings. This paper presents a comparison of the performance of the control for different formulations of the objective function. This comparison is made in a simulation study on a single building using historical weather and power system data from Denmark. Trade-offs between energy consumption,...
To achieve climate and carbonization goals, electricity grid participants, such as buildings, must reduce their footprint trough renewable generation. Introducing storages can help buffering the fluctuating nature of renewable energy sources but only with future knowledge of consumption and generation, can batteries be scaled sensibly to economically viable options. An efficient energy management...
The rapid growth of urban housing density creates the problem of Urban Heat Island Effect. To reduce the heat impact and increase cooling insulation, most of the cities rely on greening project through landscape engineering. However, finding the space for the engineering in a highly-developed city is a significant challenge. Therefore, cities like New York, Hong Kong, and Singapore, with some of the...
The ventilation in buildings with its energy needs is becoming more and more important. A solar chimney for supporting of a natural ventilation can be an interesting way of an energy saving. Solar chimneys are still not fully recognized issue. Realizations are few and mainly they are in southern countries. This paper considers the potential of solar chimneys in Czech climate conditions during the...
This paper develops and utilizes an optimization based framework to investigate the maximal energy efficiency potentially attainable by HVAC system operation in a non-predictive context. Performance is evaluated relative to the existing state of the art set-point reset strategies. The expected efficiency increase driven by operation constraints relaxations is evaluated.
In this paper, the control objectives of future active distribution networks with high penetration of renewables and flexible loads are analyzed and reviewed. From a state of the art review, the important control objectives seen from the perspective of a distribution system operator are identified to be hosting capacity improvement, high reliable operation and cost effective network management. Based...
Buildings account for nearly 40% of the total energy consumption in the United States, about half of which is used by the HVAC (heating, ventilation, and air conditioning) system. Intelligent scheduling of building HVAC systems has the potential to significantly reduce the energy cost. However, the traditional rule-based and model-based strategies are often inefficient in practice, due to the complexity...
Industrial buildings are demonstrating increasing rates of energy consumption, with heating, ventilation, and air conditioning (HVAC) typically constituting over 50% of this consumption. However, these energy requirements are heavily influenced by weather conditions based on the season, the time of day, and different in-building activities. These activities take place in industrial setup over 24 h...
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