Design of a portal for time of use pricing in smart grid
The present world is changing and growing day by day. The growth is directly related to new technologies and infrastructures. These growing needs require high demand of energy. Henceforth the role of electricity is very crucial. Fossil fuels which provide us with electricity are depleting and new me...
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sg-ntu-dr.10356-601742023-07-07T17:31:51Z Design of a portal for time of use pricing in smart grid Jacob, Aleena So Ping Lam School of Electrical and Electronic Engineering DRNTU::Engineering The present world is changing and growing day by day. The growth is directly related to new technologies and infrastructures. These growing needs require high demand of energy. Henceforth the role of electricity is very crucial. Fossil fuels which provide us with electricity are depleting and new methods for electricity generation should be there. Along with new generation plans, appropriate conservation of electricity which reduces the wastage of electricity is important. In order to develop energy efficiency measures, understanding the customers and their consumption pattern is necessary. Demand response is an incentive which can regulate the electricity usage from demand side by manipulating behavior of people. Pay as you use policy. The initial step of the project was to understand the consumption behavior. Study was conducted by analyzing the use of electricity in NTU staff quarters for a span of 10 months. The accumulated data was synthesized using MATALB programing. Further survey was conducted to understand the lifestyle of the houses with different consumption pattern. Multivariate regression method was used to forecast the load for a household depending on occupancy pattern and appliance usage. Further time of use pricing algorithm was designed to implement the demand response. Time of pricing method was validated with the forecasted load profile for NTU. Bachelor of Engineering 2014-05-23T01:46:48Z 2014-05-23T01:46:48Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/60174 en Nanyang Technological University 54 p. application/pdf |
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The present world is changing and growing day by day. The growth is directly related to new technologies and infrastructures. These growing needs require high demand of energy. Henceforth the role of electricity is very crucial. Fossil fuels which provide us with electricity are depleting and new methods for electricity generation should be there. Along with new generation plans, appropriate conservation of electricity which reduces the wastage of electricity is important. In order to develop energy efficiency measures, understanding the customers and their consumption pattern is necessary. Demand response is an incentive which can regulate the electricity usage from demand side by manipulating behavior of people. Pay as you use policy. The initial step of the project was to understand the consumption behavior. Study was conducted by analyzing the use of electricity in NTU staff quarters for a span of 10 months. The accumulated data was synthesized using MATALB programing. Further survey was conducted to understand the lifestyle of the houses with different consumption pattern. Multivariate regression method was used to forecast the load for a household depending on occupancy pattern and appliance usage. Further time of use pricing algorithm was designed to implement the demand response. Time of pricing method was validated with the forecasted load profile for NTU. |
author2 |
So Ping Lam |
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So Ping Lam Jacob, Aleena |
format |
Final Year Project |
author |
Jacob, Aleena |
author_sort |
Jacob, Aleena |
title |
Design of a portal for time of use pricing in smart grid |
title_short |
Design of a portal for time of use pricing in smart grid |
title_full |
Design of a portal for time of use pricing in smart grid |
title_fullStr |
Design of a portal for time of use pricing in smart grid |
title_full_unstemmed |
Design of a portal for time of use pricing in smart grid |
title_sort |
design of a portal for time of use pricing in smart grid |
publishDate |
2014 |
url |
http://hdl.handle.net/10356/60174 |
_version_ |
1772828284468330496 |