Model-Centric Smart Grid for Big Data August 5, 2015 Robert Broadwater dew@edd-us.com

Utility Data Sets 1-Analysis models (load forecasting, transmission, radial distribution, heavily meshed network, power flow, fault, reliability, transient, outage management) 2-Substation models 3-GIS 4-Renewable generation 5-Device settings (control settings, protective devices) 6-Customer load (monthly, demand, AMI) 7-SCADA/EMS/PMU data 8-Outage data 9-As-Is Equipment List 10-Weather Data …..

Model-Centric Smart Grid The model-centric approach employs a holistic, construction detail, model of the physical system – “Integrated System Model (ISM)” All measurement data, including weather data, is related to the ISM Changes paradigm of “pushing data to algorithms” to “pushing algorithms to data”

ISM Features Model which includes everything needed for simulating scenarios that engineers, operators, and field personnel talk about Allows any data/measurement set to be attached Allows any calculation to be attached Different calculations may work together as a team Community maintained and shared model Emerging problem to solve – use ISM Move from “craftsman modeler” to “manufactured model” Proactive modeling with Circuit Server

Integrated System Model Merge different construction models together, relating all measurements “Aha” understanding Robert 1-Measurement sets (planning and real-time) – SCADA, customer load, load research statistics, outage data, weather including historical storm, lightning, EMS; 2-0.4% error in system loss calculations; 3-Failed SCADA measurement; 4-Winter peaking and not summer peaking; 5-Large new residential customers look like commercials in summer; 6-Checking crew operations; 7-Placed on Model Server, provides foundation for automating calculations Model for holistic solutions, not point or scenario based solutions

The Best Equivalent Is No Equivalent Every model simplification leads to elimination of scenarios

Model-Based Decisions Our ability to solve a problem depends upon the model we have to solve the problem Problem Domain Solution Domain Model Adding customer load measurements to the model with EMS or SCADA measurements Point solutions or scenario based solutions; Alphabet soup of systems with scattered data Makes it possible to find a solution that satisfies all scenarios

Finding Solutions for the Hard Problems Physical System Model Big Data Big Model Big Analysis Analysis extends beyond that which is possible with Data Analytics

Model-Centric Smart Grid Equation Performance Analysis + Economic Analysis + Lab Testing + Field Validation = Model-Centric Smart Grid Reliability, Efficiency, Capacity, Protection, Controllability Economic performance is not directly measureable, but can be estimated based upon the analysis of the physical performance

Silo’ed Organizations with Disjoint Models Suppose data sets contain terabytes? Age of the craftsman modeler

ISM “Living Model” Organization Eyes of all experts on the same model Moves modeling from “age of modeling craftsman” to “manufactured models” created and used by many Algorithms running on a “living model” can discover data and measurement inconsistencies Push algorithms to data

“Dependency Ordering” of Investments Incremental CBA Phase-Balance (no capacitors) Phase Balance for Time Varying Load Capacitor Design (capacitors on local control) Cap Design for Time Varying Load Auto Reconfiguration, Monte Carlo Efficiency policy goal Efficiency and energy reduction policy goals Reliability goal at least cost Base System (not optimized, some capacitors) Coordinated Control Distribution Automation (blue sky days) (storm conditions) “Dependency Ordering” of Investments

Big Analysis: Algorithms Working Together Power Flow Restoration Analysis Protection / Coordination Load Estimation Fault Analysis Customer Load Data Model Validation SCADA Measurements Monte Carlo Driven Reliability Analysis Contingency Analysis Outage Data © Copyright Electrical Distribution Design, Inc. 2015 Confidential

Graph Trace Analysis for the ISM Matrix Analysis with Edge- Node Graph Graph Trace Analysis with Edge-Edge Graph 2 1 5 4 2 3  Topology Iterators 1 2 3 Transform 5 4 Computer Processing Global View Local View Edges 1 2 3 4 5 Node s -1 Edge knows neighboring edges Topology continuously maintained Algorithms with topology iterators Write KVL and KCL directly Processing time required for configuration changes is independent of system size How can we perform analysis on the big model, especially when the big model is changing? As the size of the system grows, the matrix topology processing increases

Common Analysis Architecture Point Solution App 1 Creation of simplified models App 1 Model Core Models Interfaces? Topology Management SCADA Data Customer Load Data App 2 How about terabyte data sets App 2 Model Pushing measurement data

ISM Analysis Architecture Mass Storage Memory App 1 ISM edge-edge topology Customer Loads Topology iterators, sharing of results, measurements ISM SCADA Measurements Weather Measurements Discussing 3-phase versus 1-phase equivalent modeling. Why should not both App 1 and App 2 have structural information in the model? App 2 Interface provided by ISM to applications

ISM Model Management for Distributed Computation Environment Client: Fault Location Supports distributed computations ISM Model Server Model Queue Analysis Processes Client: Reconfiguration

Summary: Some Uses of ISM Effects on transmission system of high renewable penetration at distribution level Automated renewable generation screening analysis Weather dependent load forecast that takes into account renewable generation forecast Storm outage prediction with radar-weather data, … System reliability from analysis team of Monte Carlo, Power Flow, and Restoration Distribution solutions versus transmission solutions Time series driven, CBA of smart grid investments

Generic Programming Roots of GTA Algorithms that process objects in container, independent of object type Container with Iterators CS Algorithms Generic Programming Algorithms that process edges or components of graph Graph Trace Analysis Engineering Algorithms ISM with Topology Iterators Example algorithms: CS – sorting, engineering – flow simulation Generic analysis independent of system type - electric, gas, fluid, etc.