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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| Format: | Final Year Project |
| Language: | English |
| Published: |
2019
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| Online Access: | http://hdl.handle.net/10356/77762 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | 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). |
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