相关论文: Bayesian model of electrical heating disaggregatio…
Non-intrusive load monitoring (NILM) is a technique that uses a single sensor to measure the total power consumption of a building. Using an energy disaggregation method, the consumption of individual appliances can be estimated from the…
The housing structures have changed with urbanization and the growth due to the construction of high-rise buildings all around the world requires end-use appliance energy conservation and management in real-time. This shift also came along…
In recent years, many proposals have arisen from research on privacy in smart metering. In one of the considered approaches, referred to as anonymization, smart meters transmit fine-grained electricity consumption values in such a way that…
Earth, water, air, food, shelter and energy are essential factors required for human being to survive on the planet. Among this energy plays a key role in our day to day living including giving lighting, cooling and heating of shelter,…
Massive informations about individual (household, small and medium enterprise) consumption are now provided with new metering technologies and the smart grid. Two major exploitations of these data are load profiling and forecasting at…
In this paper, the process of forecasting household energy consumption is studied within the framework of the nonparametric Gaussian Process (GP), using multiple short time series data. As we begin to use smart meter data to paint a clearer…
Intensifying heatwaves driven by climate change are accelerating the adoption of mobile air conditioning (AC) systems. A rapid mass adoption of such AC systems could create additional stress on electricity grids and the power system. This…
Power outages caused by extreme weather events due to climate change have doubled in the United States in the last two decades. Outages pose severe health risks to over 4.4 million individuals dependent on in-home medical devices. Data on…
This paper introduces a novel Bayesian reverse unrestricted mixed-frequency model applied to a panel of nine European electricity markets. Our model analyzes the impact of daily fossil fuel prices and hourly renewable energy generation on…
The increased awareness regarding the impact of energy consumption on the environment has led to an increased focus on reducing energy consumption. Feedback on the appliance level energy consumption can help in reducing the energy demands…
Energy disaggregation techniques, which use smart meter data to infer appliance energy usage, can provide consumers and energy companies valuable insights into energy management. However, these techniques also present privacy risks, such as…
Energy disaggregation is the task of segregating the aggregate energy of the entire building (as logged by the smartmeter) into the energy consumed by individual appliances. This is a single channel (the only channel being the smart-meter)…
Residential homes constitute roughly one-fourth of the total energy usage worldwide. Providing appliance-level energy breakdown has been shown to induce positive behavioral changes that can reduce energy consumption by 15%. Existing…
This work presents ensemble forecasting of monthly electricity demand using pattern similarity-based forecasting methods (PSFMs). PSFMs applied in this study include $k$-nearest neighbor model, fuzzy neighborhood model, kernel regression…
The large-scale integration of flexible heating systems in the European electricity market leads to a substantial increase of transportation requirements and consecutively grid congestions in the continental transmission grid. Novel model…
The decarbonization of buildings requires the phase-out of fossil fuel heating systems. Heat pumps are considered a crucial technology to supply a substantial part of heating energy for buildings. Yet, their introduction is not without…
From both global and local perspectives, there are strong reasons to promote energy efficiency. These reasons have prompted leaders in the European Union (EU) and countries of the Middle East and North Africa (MENA) to adopt policies to…
With the development and introduction of smart metering, the energy information for costumers will change from infrequent manual meter readings to fine-grained energy consumption data. On the one hand these fine-grained measurements will…
Access to smart meter data is essential to rapid and successful transitions to electrified grids, underpinned by flexibility delivered by low carbon technologies, such as electric vehicles (EV) and heat pumps, and powered by renewable…
Energy disaggregation estimates appliance-by-appliance electricity consumption from a single meter that measures the whole home's electricity demand. Compared with intrusive load monitoring, NILM (Non-intrusive load monitoring) is low cost,…