Energy - ASME JMD

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AUTOMATED DESIGN OF ENERGY EFFICIENT CONTROL STRATEGIES FOR BUILDING CLUSTERS USING REINFORCEMENT LEARNING 1/21/2019 Philip Odonkor; Kemper Lewis J. Mech. Des. 2018; 141(2):021704-021704-9. doi: 10.1115/1.4041629 From smartphones to electric cars, lithium-ion batteries allow us power our favorite devices. When used in our homes, they allow us to store cheap electricity for later use. These batteries, however, can be prohibitively expensive. But what if a single battery can intelligently be shared by multiple homes? In this paper, we demonstrate the feasibility of this idea by developing an algorithm to autonomously learn the consumption behaviors of multiple real-world homes. This insight is leveraged to produce use strategies, allowing multiple homes to simultaneously enjoy the benefits of a single battery system. Picture For the Full Paper please visit ASME's Digital Collection.

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AUTOMATED DESIGN OF ENERGY EFFICIENT CONTROL STRATEGIES FOR BUILDING CLUSTERS USING REINFORCEMENT LEARNING

From smartphones to electric cars, lithium-ion batteries allow us power our favorite devices. When used in our homes, they allow us to store cheap electricity for later use.

January 12, 2019