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The work in this paper provides an approach to generate the optimal charge/discharge schedule for an EV plugged into a smart building. The building is assumed to be equipped with local solar generation and to be subjected to time-varying electricity pricing schemes such as time-of-use pricing (TOUP) or real-time pricing (RTP). Artificial neural networks (ANNs) are used to forecast the building's hourly...
This paper presents an optimization and control algorithm for residential temperature regulation. Concepts from system identification, model-predictive control, and genetic algorithms are evoked in the pursuit of an optimization methodology capable of achieving an acceptable compromise between comfort and cost in the presence of constant as well as time-varying electricity prices. Simulation results...
Electricity consumption in commercial and residential buildings account for around 70 percent of the total electricity consumption in the United States. Through advanced load identification and management technologies, electric energy consumption and carbon emissions in buildings can be reduced by providing fine management of energy usage in an efficient way. This paper gives a state-of-the-art review...
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