Development of The Novel Scheduling Network and Its Application to Smart Home Energy Management

Increasing flexibility of the building energy demand depends on multiple developments, including accurate forecasting and effective scheduling of the loads, incorporation of renewable energy sources such as solar and wind power, on-grid bidirectional connection, and suitable energy storage technologies into the building energy management system. Advanced control, optimization and forecasting approaches are necessary to operate these complex system seamlessly, decrease the cost of energy consumption, and minimize the carbon emission.

To this end, within this project, we plan perform the following tasks:

  1. Develop the methodology of the novel Scheduling Network
  2. Define the optimization problem for smart home energy management in hybrid system
  3. Find related datasets and create final dataset of smart home energy management system
  4. Implement “Scheduling Network” perform experiments, and
  5. Organize and plan the publication, and determine target venues.

Numer projektu: 

IITIS/BW/02/25

Termin: 

01/02/2025 to 01/05/2025

Typ projektu: 

Badania własne

Wykonawcy projektu: 

Kierownik zespołu / promotor: 

Historia zmian

Data aktualizacji: 18/02/2025 - 14:19; autor zmian: Katarzyna Chmelik (kchmelik@iitis.pl)

Increasing flexibility of the building energy demand depends on multiple developments, including accurate forecasting and effective scheduling of the loads, incorporation of renewable energy sources such as solar and wind power, on-grid bidirectional connection, and suitable energy storage technologies into the building energy management system. Advanced control, optimization and forecasting approaches are necessary to operate these complex system seamlessly, decrease the cost of energy consumption, and minimize the carbon emission.

To this end, within this project, we plan perform the following tasks:

  1. Develop the methodology of the novel Scheduling Network
  2. Define the optimization problem for smart home energy management in hybrid system
  3. Find related datasets and create final dataset of smart home energy management system
  4. Implement “Scheduling Network” perform experiments, and
  5. Organize and plan the publication, and determine target venues.