Challenges and barriers to demand response deployment and evaluation
By Sheila Nolan, Mark J. O'Malley. 2015
276 citations recorded by the source corpus.
Subfields: Control and Systems Engineering, Electrical and Electronic Engineering
View Paper: https://www.semanticscholar.org/paper/1e04a73471cd7fcf2ce54ecdd392fe01d9382517
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Control and Systems Engineering
- Renzhi Lu
- Seung Ho Hong
- Federico E. Milano
- Pierluigi Mancarella
- Mengmeng Yu
- Parameswaran Kamalaruban
- A. Perera
In Electrical and Electronic Engineering
- Renzhi Lu
- Seung Ho Hong
- Federico E. Milano
- Pierluigi Mancarella
- Rafael Zárate-Miñano
- Mengmeng Yu
- Vijay Vittal
- G. Hou
Citations in the corpus
- The effect of time-of-use tariffs on the demand response flexibility of an all-electric smart-grid-ready dwelling (2016, background): “[7], the aggregation of few thousands of households represents a stable DR system resource.”
- A Dynamic pricing demand response algorithm for smart grid: Reinforcement learning approach (2018, background): “Owing to the modern advanced information and communication technologies in smart grid systems, demand response (DR) has become an effective method for improving grid reliability and reducing energy costs due to the ability to react quickly to supply-demand mismatches by adjusting flexible loads on t”
- Review and classification of barriers and enablers of demand response in the smart grid (2017, background): “Lack of market mechanisms, together with understanding of the potential value of DR, is further highlighted as a barrier to DR [17].”