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• W2886978314 abstract "According to importance of demand response programs in smart grids and microgrids, many efforts have been made to change the consumption patterns of the users, and the use of renewable resources has also increased. Significant part of energy consumption belongs to buildings such as residential, commercial, and office buildings. Many buildings are equipping with components that can be used for the participation in demand response programs. The SCADA system plays a key role in this context, which enables the building operator to have control and monitor the consumption and generation. This paper presents a real implementation of an optimization based SCADA system, which employs several controlling and monitoring methods in order to manage the consumption and generation of the building for decision support and participating in demand response events. Since the air conditioning devices are suitable controllable appliances for direct load control demand response, and lighting system as flexible loads for reduction and curtailment, they can play a key role in the scope of demand response programs. In this system, several real controller components manage the consumption of lighting system and air conditioning of the building based on an optimization model. In the case study of the paper, the SCADA system is considered as a player of an aggregation model, which is considered as demand response managing entity, and its performance during demand response events will be surveyed. The obtained results show that with adequate small reduction in the lighting system and air conditioning devices, the electricity customers are able to actively participate in the electricity markets using demand response programs and also for internal efficient use of electricity." @default.
• W2886978314 created "2018-08-22" @default.
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• W2886978314 date "2018-08-24" @default.
• W2886978314 modified "2023-09-30" @default.
• W2886978314 title "Office building participation in demand response programs supported by intelligent lighting management" @default.
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• W2886978314 doi "https://doi.org/10.1186/s42162-018-0008-4" @default.
• W2886978314 hasPublicationYear "2018" @default.
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