Real-time household load priority scheduling algorithm based on prediction of renewable source availability
We propose a real-time household load priority scheduling algorithm based on renewable source availability prediction to maximize the benefits of renewable sources and minimize the total cost of energy consumption with consumers' comfort constraints. Home appliances are assigned dynamic priorit...
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| Veröffentlicht in: | IEEE transactions on consumer electronics Jg. 58; H. 2; S. 318 - 326 |
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| Hauptverfasser: | , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
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New York
IEEE
01.05.2012
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 0098-3063, 1558-4127 |
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| Abstract | We propose a real-time household load priority scheduling algorithm based on renewable source availability prediction to maximize the benefits of renewable sources and minimize the total cost of energy consumption with consumers' comfort constraints. Home appliances are assigned dynamic priority according to their different energy consumption modes and their corresponding status. Hour-byhour weather forecast is considered to predict the availability of the renewable sources. Based on the allocated priority, home appliances are scheduled according to the predicted output of renewable sources and the forecast electricity market price. In addition, to effectively schedule appliances according to the real-time output of renewable sources and the electricity market price changes, which generally deviate from the corresponding forecasting, an algorithm for realtime household load scheduling is proposed and its benefits on cost and energy efficiency are discussed as well. |
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| AbstractList | We propose a real-time household load priority scheduling algorithm based on renewable source availability prediction to maximize the benefits of renewable sources and minimize the total cost of energy consumption with consumers¿ comfort constraints. Home appliances are assigned dynamic priority according to their different energy consumption modes and their corresponding status. Hour-byhour weather forecast is considered to predict the availability of the renewable sources. Based on the allocated priority, home appliances are scheduled according to the predicted output of renewable sources and the forecast electricity market price. In addition, to effectively schedule appliances according to the real-time output of renewable sources and the electricity market price changes, which generally deviate from the corresponding forecasting, an algorithm for realtime household load scheduling is proposed and its benefits on cost and energy efficiency are discussed as well.¿ We propose a real-time household load priority scheduling algorithm based on renewable source availability prediction to maximize the benefits of renewable sources and minimize the total cost of energy consumption with consumers' comfort constraints. Home appliances are assigned dynamic priority according to their different energy consumption modes and their corresponding status. Hour-byhour weather forecast is considered to predict the availability of the renewable sources. Based on the allocated priority, home appliances are scheduled according to the predicted output of renewable sources and the forecast electricity market price. In addition, to effectively schedule appliances according to the real-time output of renewable sources and the electricity market price changes, which generally deviate from the corresponding forecasting, an algorithm for realtime household load scheduling is proposed and its benefits on cost and energy efficiency are discussed as well. |
| Author | Xin Liu Rui Kang Maier, M. Ivanescu, L. |
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| SubjectTerms | Algorithms Availability dynamic priority scheduling Electricity Electricity supply industry Energy consumption energy management Forecasting Households Markets Priorities Priority scheduling Real time Real time systems Refrigerators renewable sources Schedules Smart home |
| Title | Real-time household load priority scheduling algorithm based on prediction of renewable source availability |
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