Connecting Distributed Pockets of EnergyFlexibility through Federated Computations:Limitations and Possibilities
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Javad Mohammadi, Jesse Thornburg
2020
Abstract
Electric grids are traditionally operated as multi-entity systems with each
entity managing a geographical region. Interest and demand for decarbonization
and energy democratization is resulting in growing penetration of controllable
energy resources. In turn, this process is increasing the number of grid
entities. The paradigm shift is also fueled by increased adoption of
intelligent sensors and actuators equipped with advanced processing and
computing capabilities. While collaboration among power grid entities (agents)
reduces energy cost and increases overall reliability, achieving effective
collaboration is challenging. The main challenges stem from the heterogeneity
of system agents and their collected information. Furthermore, the scale of
data collection is constantly increasing and many grid entities have strict
privacy requirements. Another challenge is the energy industry's common
practice of keeping data in silos. Federated computation is an approach well
suited to addressing these issues that are increasingly important for
multi-agent energy systems. Through federated computation, agents
collaboratively solve learning and optimization problems while respecting each
agent's privacy and overcoming barriers of cross-device and cross-organization
data isolation. In this paper, we first establish the need for federated
computations to achieve energy optimization goals of the future power grid. We
discuss practical challenges of performing multi-agent data processing in
general. Then we address challenges that arise specifically for orchestrating
operation of connected distributed energy resources in the Internet of Things.
We conclude this paper by presenting a novel federated computation framework
that addresses some of these issues, and we share examples of two initial field
test setups in research demonstrations and commercial building applications
with Grid Fruit LLC.
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