Optimal Household Appliances Scheduling Under Day-Ahead Pricing and Load-Shaping Demand Response Strategies
By Nikolaos G. Paterakis, Ozan Erdinc, Anastasios G. Bakirtzis, João P. S. Catalão. IEEE Transactions on Industrial Informatics, 2015
397 citations recorded by the source corpus.
Subfields: Control and Systems Engineering, Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment
View Paper: https://www.semanticscholar.org/paper/d5cbaa4439b0473ef74671e059acc40d9084d778
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In Control and Systems Engineering
In Electrical and Electronic Engineering
In Renewable Energy, Sustainability and the Environment
Citations in the corpus
- Optimal residential community demand response scheduling in smart grid (2018, methodology): “…; min j ; t Air conditioning temperature state evolution is modeled with discrete time difference equation, which is commonly used in liter-atures [9,29] as follows: The internal temperature of air conditioner at hour t + 1 is described as a function of the internal temperature, ambient…”
- Demand Response for Home Energy Management Using Reinforcement Learning and Artificial Neural Network (2019, background): “Usually, the domestic electric appliances are separated into three main types based on their characteristics and priorities, including non-shiftable, shiftable and controllable loads [6], [24].”