Development of a demand response management system for smart grids
The project on which this report is based on, is the Final Year Project of the author and it essentially includes a research on the Demand Response Management in smart grids and its aim is to develop and function a Demand Response (DR) software which both the Utility/DR aggregators and the consume...
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sg-ntu-dr.10356-680292023-07-07T15:55:23Z Development of a demand response management system for smart grids Payyada, Vishnu Prasad So Ping Lam School of Electrical and Electronic Engineering DRNTU::Engineering The project on which this report is based on, is the Final Year Project of the author and it essentially includes a research on the Demand Response Management in smart grids and its aim is to develop and function a Demand Response (DR) software which both the Utility/DR aggregators and the consumers can make use of to achieve their own goals. Utility/DR aggregators can make use of this software to key-in their details such as the tariff, incentives, and penalties and can trigger the different types of DR programs and then monitor the load shed by different consumers so that they can calculate the energy demand and then modify the supply accordingly. Consumers are encouraged to shed their lesser priority loads and change their consumption pattern in return for incentives which are calculated based on the DR program they had chosen and the amount of load they had shed. Different type of DR programs available in the market as well as the upcoming ones were studied. LabVIEW software is used to develop the Graphical User Interface (GUI) and the DR software. Along with the various DRs, optimization of the load pattern for the consumers and the integration of Photovoltaics (PVs) to the DR was also studied in detail and implemented in the software. Mainly three different type of consumers are chosen and they are Commercial, Industrial and Residential. They can choose to participate in the 5 DR programs implemented and the same time can opt for the optimization algorithm as well. For Residential consumers, an additional option of using PVs is also given to study the efficiency and economic feasibility of PVs. The simulated values here are all from the research, various scholarly articles, and weather forecasting of Singapore as well as Singapore’s energy market. Bachelor of Engineering 2016-05-24T03:33:34Z 2016-05-24T03:33:34Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/68029 en Nanyang Technological University 90 p. application/pdf |
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DRNTU::Engineering Payyada, Vishnu Prasad Development of a demand response management system for smart grids |
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The project on which this report is based on, is the Final Year Project of the author and it essentially includes
a research on the Demand Response Management in smart grids and its aim is to develop and function a
Demand Response (DR) software which both the Utility/DR aggregators and the consumers can make use
of to achieve their own goals. Utility/DR aggregators can make use of this software to key-in their details
such as the tariff, incentives, and penalties and can trigger the different types of DR programs and then
monitor the load shed by different consumers so that they can calculate the energy demand and then modify
the supply accordingly. Consumers are encouraged to shed their lesser priority loads and change their
consumption pattern in return for incentives which are calculated based on the DR program they had chosen
and the amount of load they had shed.
Different type of DR programs available in the market as well as the upcoming ones were studied. LabVIEW
software is used to develop the Graphical User Interface (GUI) and the DR software. Along with the various
DRs, optimization of the load pattern for the consumers and the integration of Photovoltaics (PVs) to the DR
was also studied in detail and implemented in the software.
Mainly three different type of consumers are chosen and they are Commercial, Industrial and Residential.
They can choose to participate in the 5 DR programs implemented and the same time can opt for the
optimization algorithm as well. For Residential consumers, an additional option of using PVs is also given
to study the efficiency and economic feasibility of PVs. The simulated values here are all from the research,
various scholarly articles, and weather forecasting of Singapore as well as Singapore’s energy market. |
author2 |
So Ping Lam |
author_facet |
So Ping Lam Payyada, Vishnu Prasad |
format |
Final Year Project |
author |
Payyada, Vishnu Prasad |
author_sort |
Payyada, Vishnu Prasad |
title |
Development of a demand response management system for smart grids |
title_short |
Development of a demand response management system for smart grids |
title_full |
Development of a demand response management system for smart grids |
title_fullStr |
Development of a demand response management system for smart grids |
title_full_unstemmed |
Development of a demand response management system for smart grids |
title_sort |
development of a demand response management system for smart grids |
publishDate |
2016 |
url |
http://hdl.handle.net/10356/68029 |
_version_ |
1772826307707535360 |