1. Model-Centric Smart Grid for Big Data
August 5, 2015
Robert Broadwater

2. 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
…..

3. 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”

4. 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

5. 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

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

7. 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

8. 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

9. 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

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

11. 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

12. “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

13. 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
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14. 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

15. 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

16. 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

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

18. 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

19. 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.