Abstract. Developing energy consumption models for smart buildings is important for studying demand response, home energy management, and distribution network simulation. In this work, we develop parsimo-nious Markovian models of smart buildings for different periods in a day for predicting electricity consumption. To develop these models, we collect two data sets with widely different load profiles over a period of seven months and one year, respectively. We validate the accuracy of our models for load prediction and compare our results with neural networks
Smart buildings seek to have a balance between energy consumption and occupant comfort. To make this...
AbstractThe nature of domestic electricity load is highly dependent on the demand of occupants. Dome...
Improving the management of electricity resources in residential buildings using intelligent control...
Abstract. Developing energy consumption models for smart buildings is important for studying demand ...
Short-term load forecasting ensures the efficient operation of power systems besides affording conti...
Modelling home energy consumption is necessary for study-ing demand-response, transformer sizing, an...
Time series load forecasting is an important aspect when it comes to energy management. This is an ...
The increasing levels of energy consumption worldwide is raising issues with respect to surpassing s...
Performance of smart grids and energy markets depends on the accuracy of forecasted power balances a...
The electrical power sector must undergo a thorough metamorphosis to achieve the ambitious targets i...
Internet of Things (IoT) is considered as one of the future disruptive technologies, which has the p...
In the last few years, the expanding energy utilization has imposed the formation of solutions for s...
A new method is presented, to derive an algorithm that provides a forecast of one day-ahead electric...
Electricity load forecasting is an important part of power system dispatching. Accurately forecastin...
Abstract The transformation of the energy system towards volatile renewable generation, increases th...
Smart buildings seek to have a balance between energy consumption and occupant comfort. To make this...
AbstractThe nature of domestic electricity load is highly dependent on the demand of occupants. Dome...
Improving the management of electricity resources in residential buildings using intelligent control...
Abstract. Developing energy consumption models for smart buildings is important for studying demand ...
Short-term load forecasting ensures the efficient operation of power systems besides affording conti...
Modelling home energy consumption is necessary for study-ing demand-response, transformer sizing, an...
Time series load forecasting is an important aspect when it comes to energy management. This is an ...
The increasing levels of energy consumption worldwide is raising issues with respect to surpassing s...
Performance of smart grids and energy markets depends on the accuracy of forecasted power balances a...
The electrical power sector must undergo a thorough metamorphosis to achieve the ambitious targets i...
Internet of Things (IoT) is considered as one of the future disruptive technologies, which has the p...
In the last few years, the expanding energy utilization has imposed the formation of solutions for s...
A new method is presented, to derive an algorithm that provides a forecast of one day-ahead electric...
Electricity load forecasting is an important part of power system dispatching. Accurately forecastin...
Abstract The transformation of the energy system towards volatile renewable generation, increases th...
Smart buildings seek to have a balance between energy consumption and occupant comfort. To make this...
AbstractThe nature of domestic electricity load is highly dependent on the demand of occupants. Dome...
Improving the management of electricity resources in residential buildings using intelligent control...