Creating virtual demand response assets using predictive modelling, with special application to Thailand
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Description
DuckDuck and and the Energy Research Insititute at Chulalongkorn University in Thailand are working with I-ON
(South Korea) to understand how Demand Response and distributed solar power can be combined to
contribute to the growth in solar production.
Under Demand Response schemes, electricity users (factories, offices, households etc.) are paid to temporarily
reduce their demand when the electricity grid is under strain. Solar power is intermittent (the sun shines when
it shines), but aggregated Demand Response can help balance out solar power's variability.
The consortium is using predictive algorithms to aggregate many small and inconsistent electrical loads into
large predictable loads which can be offered for demand response. This can then be assessed in trials, by
testing various demand response schemes.
| DUCKDUCK LTD | LEAD_ORG |
| UNISEARCH | PARTICIPANT_ORG |
| DUCKDUCK LTD | PARTICIPANT_ORG |
Subjects by relevance
- Solar energy
- Demand
- Smart grids
Extracted key phrases
- Virtual demand response asset
- Demand response scheme
- Predictive modelling
- Solar power
- Predictive algorithm
- Solar production
- Special application
- Energy Research Insititute
- Demand Response
- Inconsistent electrical load
- Large predictable load
- Thailand
- Electricity user
- Electricity grid
- Chulalongkorn University