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Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathematical models developed in scientific and engineering domains. As opposed to ...
IEEE2023
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Several distributed-optimization setups involve a group of agents coordinated by a central entity (coordinator), altogether operating in a collaborative framework. In such environments, it is often common that the agents solve proximal minimization problem ...
IEEE2018
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This paper presents an approach to provide demand response services with buildings. Each building receives a normalized signal that tells it to increase or decrease its power demand, and the building is free to implement any suitable strategy to follow the ...
2017
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The complexity and diversity of future energy systems will require co-simulation solutions that enable the integration of tools from multiple domains for research and development. We introduce an open-source framework, OpenBuildNet, for distributed co-simu ...
2016
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Ancillary services constitute the cornerstone of the power grid. They allow for an efficient system operation, provide resilience to uncertainties and establish safeguards against unprecedented events. Their importance is growing due to the rise of grid de ...
2015
Peak power consumption is a universal problem across energy control systems in electrical grids, buildings, and industrial automation where the uncoordinated operation of multiple controllers result in temporally correlated electricity demand surges (or pe ...
