Authors:
Simona-Vasilica Oprea
;
Adela Bâra
;
Cătălin Ceaparu
;
Anca Alexandra Ducman
;
Vlad Diaconița
and
Gabriela Dobrița Ene
Affiliation:
Department of Economic Informatics and Cybernetics, Bucharest University of Economic Studies, Romana Square 6, Bucharest 010374, Romania
Keyword(s):
Big Data Processing, Analytics, Load Flexibility, Market Value, Commercial Buildings.
Abstract:
The commercial buildings generate a significant volume of data that can be processed to assess the flexibility of the electricity consumption and their potential contribution to flatten the load curve or provide ancillary services. With the constant increase of the volatile output of the Renewable Energy Sources (RES) and numerous Electric Vehicles (EV), the flexibility potential of the commercial buildings has to be investigated to create smarter green cities. However, the volume of consumption data is significantly increasing when various activities are profiled, such as cooling, heating, fans, lights, equipment, etc. In this paper, we propose a big data processing framework or methodology to extract interesting insights from very large datasets and identify the flexibility of the commercial buildings (of several types from the United State of America – U.S.A.) and its market value in correlation with the Demand Response (DR) capabilities at the state and Independent System Operato
r (ISO) level. This is a theoretical approach combining several aspects, such as: large datasets processing techniques, DR programs, consumption data, flexibility potential estimation, scenarios and DR enabling technologies costs. Applying one of the DR programs, significant results in terms of savings are revealed from simulations.
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