Abstract
Accurate domestic (residential) load modelling is essential for load forecasting, simulation, planning and control of power distribution networks. This paper presents a novel method of modelling hourly domestic household's load demand taking account of the impact of microgrid. Wind and solar power generation are modeled in details and included in the load demand model. Meanwhile, multiple Gaussian distributions are used to reduce and simplify the data requirements for modelling. By discovering the relationship between domestic load profile characteristics and Gaussian distribution parameter, the model only requires very limited number of parameters to generate a household's hourly electricity load profile. The simplicity of this method made it possible to generate the hourly load profile without the detailed statistical data from the household required by other published methods. The models are therefore especially useful for the areas that smart meters are not yet deployed. Simulation results of an example domestic household show that the proposed method achieves a satisfying load modeling results.
Original language | English |
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Title of host publication | Proceeding: 2015 International Conference on Smart Grid and Clean Energy Technologies: ICSGCE 2015 |
Publisher | IEEE |
Pages | 180-186 |
Number of pages | 7 |
ISBN (Electronic) | 9781467387347 |
ISBN (Print) | 9781467387323 |
DOIs | |
Publication status | Published - 19 Apr 2016 |
Event | 2015 International Conference on Smart Grid and Clean Energy Technologies - Offenburg University of Applied Sciences, Offenburg, Germany Duration: 20 Oct 2015 → 23 Oct 2015 |
Conference
Conference | 2015 International Conference on Smart Grid and Clean Energy Technologies |
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Abbreviated title | ICSGCE 2015 |
Country/Territory | Germany |
City | Offenburg |
Period | 20/10/15 → 23/10/15 |
Keywords
- distribution systems
- Gaussian distribution
- household load demand
- load forecast
- microgrid
- power systems
ASJC Scopus subject areas
- Computer Networks and Communications
- Renewable Energy, Sustainability and the Environment
- Energy Engineering and Power Technology