Distributed Grid Intelligence

1. Distributed Grid Intelligence Dr. Bruce McMillin Missouri University of Science and Technology Wednesday June 1, 2011

2. Relationship to Strategic Plan System Demonstration: - Plug-In Hybrid Electric and Plug-In Electric Vehicles (PHEV/PEV) Distributed System Management Power Management and Economic Dispatch Enabling Technology: - Distributed Energy Storage Device (DESD) - Distributed Grid Intelligence (DGI) - Reliable and Secure Communications (RSC) • Configuration Management • State Collection • Fault Diagnosis Fundamental Technology: - System Theory Modeling and Control (SMC) - Advanced Storage (AS) Intelligent Fault Management Intelligent Energy Management Plug-In Hybrid Electric VehiclePlug-In Electric Vehicle IFM IEM PHEV/PEV IEM

3. Research Objectives • Objective: Perform the necessary research to develop software tools and platforms suitable for the implementation of intelligent, distributed, robust control functions for the FREEDM System. The control functions will be developed by SMC subthrust and other related subthrusts, and should achieve the functionality of IEM and IFM. • The long term research plan for DGI is to create a Distributed Grid Operating System that manages the energy resources of FREEDM. The research develops a resilient (secure, dependable, self-healing) and energy efficient management system for FREEDM

4. Research Roadmap • Year 1-4 • Distributed coordination of energy resources, based on algorithmic and economic optimization of resource allocation to and from each SST within the IEM; • Implementation of FREEDM first in a hybrid environment with distributed C++ code and PSCAD/RSCAD simulation, followed by distributed implementation of DGI in the green hub using networked computers in each SST interconnected by RSC. • Fault tolerance and configuration management of both DGI processes and interface to and from the IFM (at the FID level • Year 5-6 • Development of information security policies for FREEDM and implementation in a combined RSC/DGI environment, integrating messaging, code, and physical behavior • Correctness specification and formal verification of critical FREEDM functions and security using model checking techniques Grid Intelligence Software Module Broker Resource Manager, Coordinator/State Maintenance SST Standard Interface Plug and Play Device Standard Interface

5. Major Year 1-3 Accomplishments • DGI: Distributed Operating System for FREEDM • Scalable and Incremental Peer to Peer Functionality supporting plug-in Software Modules • Each Module has various communications requirements – most can be solved with datagram service • Broker Maintains System State • Active/Inactive SSTs • Load/Supply State of each SST • Active/Inactive Connections to other SSTs • Fault Tolerant Custom or Third Party Applications SCADA Outage Mgt System Resource Planning ISO-RTO Reporting AMR & AMI Energy Marketing Distributed Energy Resource Management Energy Management System Distribution Management System Asset & Facilities Management Engineering & Maintenance Security & High Fidelity Data Management GreenBusTM Internet-Scale Field Device Interface – DNP3.0 DESDs DRERs FIDs SSTs FIELD DEVICES

6. Major Year 1-3 Accomplishments DGI @ SST Software Modules • Power Management Algorithm • Fractional Knapsack from SMC, Year 2 – incremental bidding/migration • Balances the power on FREEDM to meet the net demand/supply through negotiation among peer SST nodes to control individual Power Electronics to add or subtract power to / from a shared power interconnection bus • Features • Inherently Fault-Tolerant (Omission Faults) • Reconfigurable & Scalable • Computes/Integrates with DD-LMP • Demo FAULT DETECTION DD-LMP CONSENSUS SYSTEM GROUP MANAGER STATE COLLECTION POWER MANAGEMENT Peer SST Peer SST

7. Major Year 1-3 Accomplishments DGI @ SST Software Modules • Group Management • Manages group membership of SST nodes by determining the neighbors/peers • Handles transient network partitions or failure of node(s) (through Reorganization) • Elects a leader of the group which has special group information to be used by other modules or a new node that joins the group • Features • Inherently Fault-Tolerant • Reconfigurable & Scalable • Manages system state for broker software modules • Demo (with power management) FAULT DETECTION DD-LMP CONSENSUS SYSTEM GROUP MANAGER STATE COLLECTION POWER MANAGEMENT Peer SST Peer SST Election between the leaders of subgroups to merge into a single group A new node forms a new group with itself as leader Leader node Failed node Member node New node Network partition due to failures leads to election within subgroups

8. Major Year 1-3 Accomplishments DGI @ SST Software Modules • State Collection • Fundamental Problem in Distributed Systems • Collect a causally consistent state of the SST nodes within a group • Chandy-Lamport Algorithm • Circulates a causal marker • Features • Collects the load state • Collects program variables for fault detection • Integrated for all message traffic within the broker FAULT DETECTION DD-LMP CONSENSUS SYSTEM GROUP MANAGER STATE COLLECTION POWER MANAGEMENT Peer SST Peer SST Inconsistent State Messages are recorded as received before they are sent (at SST 3) Consistent State Messages events are recorded in causal order SST 0 SST 1 SST 2 SST 3 DGI Progress

9. Major Year 1-3 Accomplishments DGI @ SST Software Modules • Development of D-LMP (from SMC, Year 3) • Experimentation with multiple power management algorithms (consensus from SMC Year 2,3) DD-LMP FAULT DETECTION CONSENSUS SYSTEM DD-LMP CONSENSUS SYSTEM GROUP MANAGER STATE COLLECTION POWER MANAGEMENT Peer SST Peer SST • Power System Simulation Environment with Distributed Systems Interface to Simulink and PSCAD/RSCAD (Year 3)

10. Major Challenges • The primary significant barrier in the development of DGI is bridging the Cyber/Physical/Network boundaries. Power system physics, network stability, and cyber correctness need to be represented on a common semantic basis to • create and validate the specification of salient control and resilience features of FREEDM, • verify the specification of FREEDM’s resilience against models of the implemented system, • provide test and validation of FREEDM’s operation, • assess the risks of and threats to FREEDM’s operation.

11. Response to 2010 SV: Actions Taken • SVT: The DGI and SMC subthrusts must work closely • Technical coordination among SMC, DGI, and Intelligent Energy Management (IEM) and Intelligent Fault Management (IFM) • Research within SMC and DGI cultivates multiple options • SMC, DGI and RSC involve three very different disciplines: power and control engineers, software engineers and communication and network engineers. • Develops significant cross-disciplinary experience • Possibility to consolidate SMC, DGI and RSC into one cluster and have a cluster leader with strong domain knowledge to coordinate and lead the activity. • DGI has emerged as the driving force drawing from SMC and RSC to create the operating system for IEM and IFM.

12. Related Posters • Y3.F.C1 Project Report – Distributed Control of FREEDM System • Broker Architecture • D-LMP and Consensus • Y3.F.C14 Project Report • Interacting control approach • REU Poster – Group Management System • Information Flow/Security • Demo of DGI Power Management and Reconfiguration

13. Year 4 and Beyond • The goal of the next few years is to integrate the DGI operating system with the IEM/IFM in the digital testbed using RSC as a delivery mechanism. • Develop lightweight RSC protocols integrated with DGI algorithms for efficiency, fault tolerance, and security • Interface with the IFM so that faults from the FID cause a reconfiguration of DGI, and faults detected by DGI are communicated to the FID. • Economic models of D-LMP become part of the software module plug-in of the DGI broker architecture as Distributed Distribution LMP (DD-LMP). • As the center moves forward, fault tolerance, correctness and security considerations are cross-cutting throughout DGI and RSC. • Ultimately, DGI will be deployed in the distributed green hub and digital testbedas their operating system.