Related papers: Forecasting Residential Heating and Electricity De…
Residential buildings account for a significant portion (35\%) of the total electricity consumption in the U.S. as of 2022. As more distributed energy resources are installed in buildings, their potential to provide flexibility to the grid…
This paper presents a Deep Learning (DL) framework for 48-hour forecasting of temperature, solar irradiance, and relative humidity to support Model Predictive Control (MPC) in smart HVAC systems. The approach employs a stacked Bidirectional…
The rising demand for electricity and its essential nature in today's world calls for intelligent home energy management (HEM) systems that can reduce energy usage. This involves scheduling of loads from peak hours of the day when energy…
In combating climate change, an effective demand-based energy supply operation of the district energy system (DES) for heating or cooling is indispensable. As a consequence, an accurate forecast of heat consumption on the consumer side…
Forecasting power consumptions of integrated electrical, heat or gas network systems is essential in order to operate more efficiently the whole energy network. Multi-energy systems are increasingly seen as a key component of future energy…
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…
In order to achieve the climate targets, electrification of individual mobility is essential. However, grid integration of electrical vehicles poses challenges for the electrical distribution network due to high charging power and…
Buildings sector is one of the major consumers of energy in the United States. The buildings HVAC (Heating, Ventilation, and Air Conditioning) systems, whose functionality is to maintain thermal comfort and indoor air quality (IAQ), account…
Both buyers and sellers face uncertainty in real estate transactions in about when to time a transaction and at what cost. Both buyers and sellers make decisions without knowing the present and future state of the large and dynamic real…
Home Energy Management Systems (HEMS) have emerged as a pivotal tool in the smart home ecosystem, aiming to enhance energy efficiency, reduce costs, and improve user comfort. By enabling intelligent control and optimization of household…
Residential consumers can use the demand response program (DRP) if they can utilize the home energy management system (HEMS), which reduces consumer costs by automatically adjusting air conditioning (AC) setpoints and shifting some…
It is crucial today that economies harness renewable energies and integrate them into the existing grid. Conventionally, energy has been generated based on forecasts of peak and low demands. Renewable energy can neither be produced on…
Building energy modeling is a key tool for optimizing the performance of building energy systems. Historically, a wide spectrum of methods has been explored -- ranging from conventional physics-based models to purely data-driven techniques.…
Advanced metering infrastructure systems record a high volume of residential load data, opening up an opportunity for utilities to understand consumer energy consumption behaviors. Existing studies have focused on load profiling and…
With the growth of smart building applications, occupancy information in residential buildings is becoming more and more significant. In the context of the smart buildings' paradigm, this kind of information is required for a wide range of…
This paper presents the building heating demand prediction model with occupancy profile and operational heating power level characteristics in short time horizon (a couple of days) using artificial neural network. In addition, novel pseudo…
We explore the application of kernel-based multi-task learning techniques to forecast the demand of electricity in multiple nodes of a distribution network. We show that recently developed output kernel learning techniques are particularly…
Buildings account for approximately 40% of global energy consumption, and with the growing share of intermittent renewable energy sources, enabling demand-side flexibility, particularly in heating, ventilation and air conditioning systems,…
Considering the interdependencies between water and electricity use is critical for ensuring conservation measures are successful in lowering the net water and electricity use in a city. This water-electricity demand nexus will become even…
With the growing number of forecasting techniques and the increasing significance of forecast-based operation - particularly in the rapidly evolving energy sector - selecting the most effective forecasting model has become a critical task.…