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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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2019
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| Online Access: | http://hdl.handle.net/10356/77762 |
| _version_ | 1811688341084569600 |
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| author | Ho, Jian Wei |
| author2 | Soh Cheong Boon |
| author_facet | Soh Cheong Boon Ho, Jian Wei |
| author_sort | Ho, Jian Wei |
| collection | NTU |
| 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). |
| first_indexed | 2024-10-01T05:30:40Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/77762 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:30:40Z |
| publishDate | 2019 |
| record_format | dspace |
| spelling | ntu-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 |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering Ho, Jian Wei Optimal residential load scheduling scheme with price prediction |
| title | 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_short | Optimal residential load scheduling scheme with price prediction |
| title_sort | optimal residential load scheduling scheme with price prediction |
| topic | DRNTU::Engineering::Electrical and electronic engineering |
| url | http://hdl.handle.net/10356/77762 |
| work_keys_str_mv | AT hojianwei optimalresidentialloadschedulingschemewithpriceprediction |