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Highlights Coronavirus COVID-19 is spreading very fast in Brazil. Fast deployment of alcohol-based disinfectants is needed. Disinfectant from common ethanol of gas stations in Brazil.

Electric power systems have experienced large increases in the number of intelligent, connected and controllable devices being deployed, leading to a high degree of distributed intelligence at the grid-edge. These devices, both utility-owned and consumer-owned, include renewable generation, energy storage, remote switches, voltage regulators, and smart controllable loads. These new devices provide significant potential for increased operational flexibility that can be leveraged to achieve system reconfiguration, resiliency improvements, power quality improvements, and distribution system automation. However, two significant challenges must be addressed before these assets can be leveraged for operations: interoperability and system level validation prior to deployment. Because of the complexity of distributed control systems, and their interactions with legacy centralized controls, a purely simulations-based approach for predeployment validation is not sufficient. It requires hardware-inthe-loop (HIL) testing to emulate hardware devices and evaluate their performance. Additionally, securely integrating multiple test facilities at utility operators and vendors can enable the rapid scale-up of evaluation platforms and remove the need for multiple expensive standalone installations. Presented in this paper, is the development of a multi-site evaluation platform that employs Advanced Distribution Management Systems (ADMS), distributed control devices, real-time HIL assets, secure communication links, and protocol adapters. The testbed has been developed at three sites, with one site hosting the ADMS and the other two hosting HIL capabilities. This platform uses standardsbased approaches and open-source tools, and hence can serve as a template for other researchers and institutions to implement their multi-site evaluation frameworks for pre-deployment testing.

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