Ron Ambrosio Senior Technical Staff Member & Global Research Leader, Energy & Utilities Industry IBM TJ Watson Research Center, Yorktown Heights, NY

Transcription

1 IBM Research Enterprise Integration of Smart Grids: Stream and Event Computing Ron Ambrosio Senior Technical Staff Member & Global Research Leader, Energy & Utilities Industry IBM TJ Watson Research Center, Yorktown Heights, NY U.S. Dept. of Energy GridWise Architecture Council Member 2007 IBM Corporation

2 Utilities are Driving to more advanced T&D Monitoring & Control Intelligence Conventional Control Fully Integrated Intelligent Grid IBM Corporation

3 Five Layers of Grid Intelligence IBM Corporation

4 Busi ness Units Business Unit ID Central Stations Central Station ID Power Transformers Power Transformer ID Substation ID (FK) Hydran Units 1 Hydran Unit ID Power Transformer ID (FK) Substation to Transmissio n Lines Substation ID (FK) Transmission Line ID (FK) Segment ID (FK) P Sensor Readings Sensor ID (FK) Timestamp P Substations Substation ID Business Unit ID (FK) Central Stati on ID (FK) P Sensor Reading Value P Transmissi on Line Segment Transmission Line ID (FK) Segment ID IED Types IED Type 1 Weather Stations P W eather Station ID Substati on ID (FK) Sensors Sensor ID Sensor Type (FK) Substati on ID (FK) IED ID (FK) Hydran Unit ID (FK) W eather Station ID (FK) IEDs IED ID P P Substatio n ID (FK) IED Type (FK) Sensor Types Sensor Type Sensor Type Description UOM (FK) Transmi ssion Lines Transmission Line ID P IEDs to Ci rcuit Breakers IED ID (FK) Circuit Breaker ID (FK) P Ci rcuit Breakers Circuit Breaker ID Units of Measure UOM Five Major Components of an Utility Intelligent Network Information Presentation and Optimization Optimization 5 Information is presented to Users via customized portal dashboards for decision support Information available to Utility applications for automatic processing 5 Utility Applications External Applications Analytics Stack Portal/Dashboards Informed Decision Making Analytics Application Integration WAMS CIS OMS Planning Engineering ERP MWFM Doc. Mgt GIS EMS/DMS MDMS Historian Automation Information Information Operations Maintenance Finance Planning Engineering Customers Communication Infrastructure IP Enabled Digital Communications Network Data Sources Equipment Monitoring Automated Substations Digital Relays LAN Sensors Optimization IBM Corporation

5 IBM Research Need for an Interoperability Framework 2007 IBM Corporation

6 Interoperability Categories Organizational Informational Technical 8: Economic/Regulatory Policy 7: Business Objectives 6: Business Procedures 5: Business Context 4: Semantic Understanding 3: Syntactic Interoperability 2: Network Interoperability 1: Basic Connectivity Political and Economic Objectives as Embodied in Policy and Regulation Strategic and Tactical Objectives Shared between Businesses Alignment between Operational Business Processes and Procedures Awareness of the Business Knowledge Related to a Specific Interaction Understanding of the Concepts Contained in the Message Data Structures Understanding of Data Structure in Messages Exchanged between Systems Mechanism to Exchange Messages between Multiple Systems across a Variety of Networks Mechanism to Establish Physical and Logical Connections between Systems 7 May 07 GridWise Architecture Council 6

7 Interoperability Framework Interoperability Categories Cross-cutting Issues 8: Economic/Regulatory Policy Organizational Informational Technical 7: Business Objectives 6: Business Procedures 5: Business Context 4: Semantic Understanding 3: Syntactic Interoperability 2: Network Interoperability 1: Basic Connectivity Shared Meaning of Content Resource Identif fication Time Synch & Seq quencing Security & Priv vacy Logging & Audi iting Transaction & State Mgt System Prese ervation Performance/Reliabilit ty/scalability Discovery & Confi iguration System Evolu ution 7 May 07 GridWise Architecture Council 7

8 ISO/IEC JTC 1/SC 25/WG 1 Interoperability Framework ISO/IEC interoperability domain Sys. Mgmt. Interop Application Interop Application Syst. Mgmt. Application (7) Application Application Application Application Presentation (6) Presentation Presentation Session (5) RGIP RGIP Transport (4) Network (3) Data Link (2) Physical (1) La yer M g mt Network Data Link Physical RGIB Interoperable Residential Gateway Network Data Link Physical La yer M g mt Manufacturer-provided interworking Function System A connection (CEBus, Konnex, EchoNet, Echelon ) ISO/IEC gateway domain System B connection (CEBus, Konnex, EchoNet, Echelon ) 8 Ron Ambrosio

9 Scope and Definition of Interoperability Addresses the requirements of two communities: Product developers System integrators Product-level interoperability Focuses on syntactic issues data and protocol interfacing to specific products in a multi-system installation Application-level interoperability Focuses on semantic issues describing the application interactions between products in a multi-system installation 9 Ron Ambrosio

10 Approaches to Interoperability Adopt a single system as the agreed-upon universal standard Minimizes ability for product differentiation between manufacturers May not adequately address specific regional differences/requirements OR Develop system-to-system translations between all target systems Could easily degenerate into an n 2 translation situation Dependence on protocol translation can make the interoperability framework brittle very sensitive to minor changes in underlying systems OR Define a meta-framework to facilitate multi-system solutions without requiring specific system-to-system protocol translations Address unambiguous data mapping/translation Adopt an approach that is independent of the underlying protocols 10 Ron Ambrosio

11 Application-level Interoperability Basic approach is to describe the interaction between products in a multi-system installation Must capture enough information to enable an implementation of the interoperability framework to automatically determine which product parameters need to be transported across the interoperability event bus as a single unit i.e., to assemble the event message payloads dynamically This effectively breaks the tight association between individual product APIs and their associated protocol definitions for various product functions 11 Ron Ambrosio

12 IBM Research Cyber-Physical-Business Systems 2006 IBM Corporation

13 Making business processes responsive to disengaged EVENT data Transaction Choreography Process Choreography Internet with application and process servers ESB central transaction and database server 70 s - 80 s early 90 s Information and business process management - transactional - request / rsp ESB PDA data Events: Process & Data Choreography Sensors, RFID readers Control nets,actuators Information gathering and automation asynchronous disengaged data staged data filtering pruning to be augmented with events Application history, data warehouse IBM Corporation

14 Operational Integration Today Conventional Enterprise Computing Accounting Corporate Production Mgt Traditional operations integration (MES, ERP, Database, ) Conventional Operational Control SCADA Today s environment: Enterprise & embedded control domains are loosely coupled Different programming models Gateways Controller Fieldbus Device IBM Corporation

15 Create Business Value through Operational Integration Conventional Enterprise Computing Integrated Business Automation Corporate Accounting Sense and Respond Business Objects Production Mgt Closed-loop methods are emerging in the enterprise: Same Sense & Respond paradigm as embedded control systems Enables unified view of enterprise and operational processes: Common programming abstraction Shared or interoperable infrastructure IBM Corporation

16 Establish a Flexible Event-based Integration Model Conventional Enterprise Computing Integrated Business Automation Accounting Corporate Production Mgt Virtual sensors and actuators Creates a complete business automation architecture: Thin integration layer wraps underlying components Integrated event bus Virtual sensors & actuators present external interfaces via portals, web services, Physical sensors and actuators IBM Corporation

17 Cyber-Physical-Business Systems Overview Current sensor and actuator systems Future CPB systems Physical World Physical World Business Information System Business Information System Real-Time (Delay Sensitive Transactional Physical Systems (sensing) Physical Systems (actuation) Application Element Business system inputs/outputs D 1 D 2 end-to-end delay constraints IBM Corporation

18 Cyber-Physical-Business Systems Research Areas at IBM Event Driven Solutions SOA Tooling and methods Websphere Process and Application Servers WAS, WPS Complex Event processing Websphere Enterprise Services Bus (WESB) Event Processing Time-sensitive processing container Time-sensitive event processing RTJava Time-sensitive Event Communication Time Dependent SOA Tooling IBM Research Joint IBM Research and IBM Software Group IBM Corporation

19 IBM Research Cyber-Physical-Business Systems Internet-scale Control Systems (ics) prototype 2007 IBM Corporation

20 Building Blocks of the ics Programming Model Classical feedback control loop Abstraction of control elements Control Sensor Actuator Target IBM Corporation

21 XML Schema: Data Point, Type and Physical Unit Data type framework to map to computing space from business and operations domains Data types are extensible through XML schema to different industries and business domain Provide data type platform for Model Object Inputs/Outputs IBM Corporation

22 ics Control-Process Elements I/O Event/Message Interface Function-Invocation Service Interface i1 i2 i3 i4 Input Data Points Input E/M Queue Timer Scheduler Inputs Description Table <<ics Control-Processing Element>> Model Object Model Processor Event Correlation FSM Configuration Properties, Parameters Model Algorithm Configuration Properties, Parameters Output E/M Queue Thread Pool Outputs Description Table Output Data Points o1 o2 I/O Event/Message Interface Function-Invocation Service Interface Control-Processing Elements (CPE) Three types: Sensor, Control and Actuator Model Object Each Model Object has following constructs: One or many Input Point (s) (for Control and Actuator): typed by ics XML Schema One or Many Output Point (s) (for Control and Sensor): typed by ics XML Schema Input and Output Event/Data Queue: Input/Output buffer Model Processor: internal event/processing control (event queue, correlation, execution threading of model-algorithm, publishing new events, etc..) Model Algorithm: processing function/logic of Model Object Timer (optional) Configuration Properties and Runtime Operation Parameters Each Model Object is fully described by ics Model XML Instance of ics Control-Processing Element is created by and deployed to ics Runtime Node IBM Corporation

23 ics Components IBM Corporation

24 Invensys Olympic Peninsula GridWise Demonstration $ IBM Market MW Mason 3 & Clallam PUDs n = 120, 0.8 MW DR Johnson Controls Event-based Internet communications Sequim Marine Sciences Lab, 0.3 MW DR 0.5 MW DG Port Angeles Water Supply District, 0.9 MW DR 24

25 Integration through Event-based Programming Utility Business Domain Retail Energy Market Customer Management Billing System Utility Operations Domain Base Supply Price/Capacity Distributed Generation Distributed Generation Distributed Control Generation Control Control DG DG Distribution Feeder DG DG Status/Capacity DG DG Customer Premises Home Home Energy Home Energy Mgt Energy Mgt Object Mgt Object Object Distributed Generation Distributed Generation Distributed Control Generation Control Control Virtual Virtual Thermostat Virtual Thermostat Thermostat Virtual Virtual Water Virtual Water Heater Water Heater Heater Virtual Virtual Electric Virtual Electric Meter Electric Meter Meter DG DG DG DG DG DG T-Stat T-Stat T-Stat T-Stat T-Stat T-Stat WH WH T-Stat T-Stat T-Stat WH Meter Meter Meter IBM Corporation

26 IBM Research System S 2007 IBM Corporation

27 IBM Research High Performance Stream Computing New Computing Paradigm Dense, distributed fabric of hundreds or thousands of individually unreliable stream processing components Components form a highly reliable, robust, highly scalable group for reliable decision making New Programming Model Continuous stream processing (not transactional, not store & process) Modules and system as a whole must dynamically adapt to content and resources Modules operate on partial and/or lossy representations of data stream New storage and file system architectures Structured, but not necessarily sequential, access High volume, temporal nature requires automated, policy-based aging New data management technology Query optimization focus moves from join reuse to complex dataflow management Declarative (query-like) language required for expressing operations Structured representations go beyond current limited treatment of time-series and rich media object stores IBM Corporation All Rights Reserved

28 IBM Research System S Stream Processing Model-driven analytic development Decompose applications into reusable, functional units of work Parsing, feature extraction, classification, correlation, aggregation, Simple Processing Element (PE) model Data object handler (invoked when data arrives) to process object Optional event handler to respond to adapt to system or application level change Declarative application composition Applications composed by identifying PEs and describe content of interest feedback SDO stream PE Reliable declaration of PE and dataflow properties enables Enforcement via generated container and services Automated / semi-automated assembly Ease of use, e.g., large applications (many PE s, numerous connections) Straight forward compositions Autonomic mechanisms for adaptive management of resources (CPU, bandwidth, storage) and assets (data, analytic) IBM Corporation All Rights Reserved

29 IBM Research System S Runtime Environment Analytics (PEs) developed and Applications composed by , VoIP, cell phone, image, video, TV/radio financial broadcast, web traffic, GPS data, chat, financial transaction data, satellite data, police scanners, badge swipes, Mission: Customers System: IBM, Customers Infrastructure developed by IBM Database/dat a warehouse Programming System S Develop processing elements Assemble into applications Deploy System S Runtime Stored models Underlying architecture and services Component interactions Details not needed by analytic and application developers System S Applications System S Infrastructure IBM Corporation All Rights Reserved

30 IBM Research Putting it all in the Context of a Smart Grid 2006 IBM Corporation

31 IBM Intelligent Utility Network Reference Architecture IBM Corporation

32 IBM Intelligent Utility Network Reference Architecture System S: platform for role-based analytics back-end Cyber-Physical-Business Systems ics IBM Corporation