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This paper explores the impacts of decarbonisation of heat on demand and subsequently on the generation capacity required to secure against system adequacy standards. Gas demand is explored as a proxy variable for modelling the…
Decarbonizing the building stock in cold countries by replacing fossil fuel boilers with heat pumps is expected to drastically increase electricity demand. While heating flexibility could reduce the impact of additional demand from heat…
The rising availability of large volume data, along with increasing computing power, has enabled a wide application of statistical Machine Learning (ML) algorithms in the domains of Cyber-Physical Systems (CPS), Internet of Things (IoT) and…
We present a novel framework for high-resolution forecasting of residential heating demand and non-heating electricity demand using probabilistic deep learning models. Because our models are trained on electricity consumption from a…
Forecasting thermal load is a key component for the majority of optimization solutions for controlling district heating and cooling systems. Recent studies have analysed the results of a number of data-driven methods applied to thermal load…
As buildings become increasingly connected and sensor-rich, intelligent remote heating control is rapidly superseding conventional local heating control. Such control algorithms often aim at reducing energy consumption by minimizing…
The large scale deployment of Advanced Metering Infrastructure among residential energy customers has served as a boon for energy systems research relying on granular consumption data. Residential Demand Response aims to utilize the…
Heat, Ventilation and Air Conditioning (HVAC) systems play a critical role in maintaining a comfortable thermal environment and cost approximately 40% of primary energy usage in the building sector. For smart energy management in buildings,…
The evolution of the power grid towards the so-called Smart Grid, where information technologies help improve the efficiency of electricity production, distribution and consumption, allows to use the fine-grained control brought by the…
The increased integration of variable renewable generation into the power systems, along with the phase-out of fossil-based power stations, necessitate procuring more flexibility from the demand sectors. The electrification of the…
Scalable demand response of residential electric loads has been a timely research topic in recent years. The commercial coming of age or residential demand response requires a scalable control architecture that is both efficient and…
Before a building can participate in a demand response program, its facility managers must characterize the site's ability to reduce load. Today, this is often done through manual audit processes and prototypical control strategies. In this…
Despite various efforts, decarbonizing the heating sector remains a significant challenge. To tackle it by smart planning, the availability of highly resolved heating demand data is key. Several existing models provide heating demand only…
Grid-interactive building control is a challenging and important problem for reducing carbon emissions, increasing energy efficiency, and supporting the electric power grid. Currently researchers and practitioners are confronted with a…
The inter-temporal consumption flexibility of commercial buildings can be harnessed to improve the energy efficiency of buildings, or to provide ancillary service to the power grid. To do so, a predictive model of the building's thermal…
The increasing integration of renewable energy into the power grid has highlighted the critical importance of demand-side flexibility. Among flexible loads, heating, ventilation, and air-conditioning (HVAC) systems are particularly…
The fact that a proper HVAC control strategy can reduce the energy consumption of a building by up to 45% has driven significant research in demand-based HVAC control. This paper presents a novel framework for modeling and analysis of…
Energy saving and carbon emission reduction in buildings is one of the key measures in combating climate change. Heating, Ventilation, and Air Conditioning (HVAC) system account for the majority of the energy consumption in the built…
An optimized heat pump control for building heating was developed for minimizing CO2 emissions from related electrical power generation. The control is using weather and CO2 emission forecasts as input to a Model Predictive Control (MPC) -…
This paper illustrates the design and implementation of a smart home automation system for the conservation of energy and user control with the help of environmental sensors and Raspberry Pi 5. It monitors real-time conditions like motion,…