Optimal residential load scheduling scheme with price prediction

Electricity is generated and cannot be stored. Hence, its wholesale prices fluctuates daily and changes at various times of the day. In contrast to current normal flat rates, real-time electricity pricing (RTP) model may achieve environmental and economic advantages. By responding to pricing, consum...

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Main Author: Ho, Jian Wei
Other Authors: Soh Cheong Boon
Format: Final Year Project
Language:English
Published: 2019
Subjects:
Online Access:http://hdl.handle.net/10356/77762
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-777622023-07-07T16:30:17Z Optimal residential load scheduling scheme with price prediction Ho, Jian Wei Soh Cheong Boon School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Electricity is generated and cannot be stored. Hence, its wholesale prices fluctuates daily and changes at various times of the day. In contrast to current normal flat rates, real-time electricity pricing (RTP) model may achieve environmental and economic advantages. By responding to pricing, consumers will enjoy the benefits of a lower electricity bill. However, there are two big stumbling blocks that makes it challenging to enjoy the benefits of RTP tariffs. Recent research has shown that consumers’ knowledge about dealing with time-varying prices is limited. For example, information of electricity prices are readily available online but consumers rarely check because it is tough to monitor it hourly and react accordingly. There is also a lack of competent automation system of buildings. These problems can be eradicated by introducing an automatic and optimal residential energy consumption framework. It seeks to balance between reducing the operation latency for individual household appliances and lowering electricity bill in the presence of a RTP tariff coupled with inclining block rates (IBR). Bachelor of Engineering (Electrical and Electronic Engineering) 2019-06-06T03:52:39Z 2019-06-06T03:52:39Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/77762 en Nanyang Technological University 53 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Ho, Jian Wei
Optimal residential load scheduling scheme with price prediction
description Electricity is generated and cannot be stored. Hence, its wholesale prices fluctuates daily and changes at various times of the day. In contrast to current normal flat rates, real-time electricity pricing (RTP) model may achieve environmental and economic advantages. By responding to pricing, consumers will enjoy the benefits of a lower electricity bill. However, there are two big stumbling blocks that makes it challenging to enjoy the benefits of RTP tariffs. Recent research has shown that consumers’ knowledge about dealing with time-varying prices is limited. For example, information of electricity prices are readily available online but consumers rarely check because it is tough to monitor it hourly and react accordingly. There is also a lack of competent automation system of buildings. These problems can be eradicated by introducing an automatic and optimal residential energy consumption framework. It seeks to balance between reducing the operation latency for individual household appliances and lowering electricity bill in the presence of a RTP tariff coupled with inclining block rates (IBR).
author2 Soh Cheong Boon
author_facet Soh Cheong Boon
Ho, Jian Wei
format Final Year Project
author Ho, Jian Wei
author_sort Ho, Jian Wei
title Optimal residential load scheduling scheme with price prediction
title_short Optimal residential load scheduling scheme with price prediction
title_full Optimal residential load scheduling scheme with price prediction
title_fullStr Optimal residential load scheduling scheme with price prediction
title_full_unstemmed Optimal residential load scheduling scheme with price prediction
title_sort optimal residential load scheduling scheme with price prediction
publishDate 2019
url http://hdl.handle.net/10356/77762
_version_ 1772827063458201600