A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Demand Response Implementation in an Optimization Based SCADA Model Under Real-Time Pricing Schemes
Advancement of renewable energy resources, development of smart grids, and the effectiveness of demand response programs, can be considered as solutions to deal with the rising of energy consumption. However, there is no benefit if the consumers do not have enough automation infrastructure to use the facilities. Since the entire kinds of buildings have a massive portion in electricity usage, equipping them with optimization-based systems can be very effective. For this purpose, this paper proposes an optimization-based model implemented in a Supervisory Control and Data Acquisition, and Multi Agent System. This optimization model is based on power reduction of air conditioners and lighting systems of an office building with respect to the price-based demand response programs, such as real-time pricing. The proposed system utilizes several agents associated with the different distributed based controller devices in order to perform decision making locally and communicate with other agents to fulfill the overall system’s goal. In the case study of the paper, the proposed system is used in order to show the cost reduction in the energy bill of the building, while it respects the user preferences and comfort level. ; The present work was done and funded in the scope of the following projects: H2020 DREAM-GO Project (Marie Sklodowska-Curie grant agreement No 641794); Project GREEDI (ANI|P2020 17822); and UID/EEA/00760/2013 funded by FEDER Funds through COMPETE program and by National Funds through FCT.
Demand Response Implementation in an Optimization Based SCADA Model Under Real-Time Pricing Schemes
Advancement of renewable energy resources, development of smart grids, and the effectiveness of demand response programs, can be considered as solutions to deal with the rising of energy consumption. However, there is no benefit if the consumers do not have enough automation infrastructure to use the facilities. Since the entire kinds of buildings have a massive portion in electricity usage, equipping them with optimization-based systems can be very effective. For this purpose, this paper proposes an optimization-based model implemented in a Supervisory Control and Data Acquisition, and Multi Agent System. This optimization model is based on power reduction of air conditioners and lighting systems of an office building with respect to the price-based demand response programs, such as real-time pricing. The proposed system utilizes several agents associated with the different distributed based controller devices in order to perform decision making locally and communicate with other agents to fulfill the overall system’s goal. In the case study of the paper, the proposed system is used in order to show the cost reduction in the energy bill of the building, while it respects the user preferences and comfort level. ; The present work was done and funded in the scope of the following projects: H2020 DREAM-GO Project (Marie Sklodowska-Curie grant agreement No 641794); Project GREEDI (ANI|P2020 17822); and UID/EEA/00760/2013 funded by FEDER Funds through COMPETE program and by National Funds through FCT.
Demand Response Implementation in an Optimization Based SCADA Model Under Real-Time Pricing Schemes
Mahsa Khorram (author) / Pedro Faria (author) / Omid Abrishambaf (author) / Zita Vale (author)
2019-01-09
Conference paper
Electronic Resource
English
DDC:
690
Demand Response Implementation in an Optimization Based SCADA Model Under Real-Time Pricing Schemes
| BASE | 2019
Demand response in electrical energy supply: an optimal real time pricing approach
| BASE | 2013
Optimization-Based Home Energy Management System Under Different Electricity Pricing Schemes
| BASE | 2018
Optimization-Based Home Energy Management System Under Different Electricity Pricing Schemes
| BASE | 2018
Demand response management by means of heat pumps controlled via real time pricing
| Online Contents | 2015