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
Hauptverfasser: Xin Liu, Ivanescu, L., Rui Kang, Maier, M.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: 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.
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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