Ad-hoc der machine data aggregation for co-simulation, deep learning and fault-tolerant power systems

A method for managing a plurality of distributed energy resources (DERs) at a cloud-based node, comprising:

• generating, based on a desired system-level analysis, a data collection protocol for implementation at the plurality of DERs;
• transmitting, via a peer-to-peer network, the data collection protocol to the DERs via a set of edge nodes, the set of edge nodes comprising at least one super edge node and a plurality of private-device edge nodes in communication with the super edge node;
• receiving, based on the data collection protocol, data related to the plurality of DERs from edge nodes in the set of edge nodes;
• and
• generating a system recommendation based on the received data by processing the data with a machine trained network, the machine trained network having been trained with a combination of real-time data and simulation data.

A method for managing a plurality of distributed energy resources (DERs) at an edge computing device, comprising:

• identifying a set of one or more private-device edge nodes capable of receiving data from one or more DERs and transmitting data received from a DER to the edge computing device;
• registering the identified private-device edge nodes for inclusion in a peer-to-peer network;
• transmitting, to each of the registered private-device edge nodes in a peer-to-peer network, a data collection protocol for the DERs to implement;
• and
• receiving, based on the data collection protocol, data relating to the plurality of DERs from the identified private-device edge nodes through the peer-to-peer network.