Journal
ELECTRIC POWER SYSTEMS RESEARCH
Volume 158, Issue -, Pages 26-36Publisher
ELSEVIER SCIENCE SA
DOI: 10.1016/j.epsr.2017.12.017
Keywords
Incentive base demand response; Elasticity; Appliance elasticity; Load disaggregation; Residential load modeling
Categories
Funding
- National Science Foundation (NSF) [CNS 1541117]
- Engineering Research Center Program of the NSF
- Department of Energy under NSF Award [EEC-1041877]
- CURENT Industry Partnership Program
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A key component to understanding demand response programs design is elasticity, which reflects customer reaction to economic offers. In this work, customer elasticity for Incentive Based Demand Response (IBDR) programs is estimated using data from two nation wide surveys and integrated with a detailed residential load model. In addition, incentive based elasticity is calculated at the individual appliance level since this is more effective for operations than at an aggregate value for a feeder. The concept of appliance base elasticity is derived from various contributions of each appliance in the aggregate load signal and the necessity of use for the customer. Results show that the needed customer incentive for certain loads, such as, lighting and washing is less than HVAC, but since the HVAC energy share in total load is much higher generally, it has greater elasticity. Considering the important role of HVAC in the aggregate load signal, the elasticity is studied in more detail using estimates of different thermostat settings. Analysis shows that elasticity of HVAC decreases while average power increases. To disaggregate the load signal for each appliance, a constrained non-negative matrix factorization (CNMF) method is proposed. In addition, this method is used to decompose the HVAC signal to identify different thermostat settings. (C) 2017 Published by Elsevier B.V.
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