Towards a Distributed, Service-Oriented Control Infrastructure for Smart Grid

1. Towards a Distributed, Service-Oriented Control Infrastructure for Smart Grid ASU - Cyber Physical Systems Lab Professor G. Fainekos Presenter: RamtinRajiKermani Muhammad Umer Tariq1, Santiago Grijalva, Marilyn Wolf Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, USA.

2. Some Background … • What is Smart Grid? • A smart grid is a digitally enabled electrical grid that gathers, distributes, and acts on information about the behavior of all participants (suppliers and consumers) in order to improve the efficiency, importance, reliability, economics, and sustainability of electricity services. (Wikipedia)

3. Abstract • What is missing? • Smart Grid initiatives aim to overlay the existing power grid infrastructure with a communication and computation infrastructure to enable integration of renewable resources and increased efficiency and reliability of the electric power grid.

4. Abstract • Enable integration of renewable energy • Increased Efficiency • Reliability Communication Infrastructure Overlay Smart Grid Initiative Electric Power Grid + ComputationInfrastructure • How? • Substantial changes to Centralized Control Infrastructure • More Powerful Comm. and Comp. Infrastructure

5. In This Paper … • We describe: The elements required for implementation of a “Prosumer” based distributed control architecture for smart grid. • We propose: • A Hard Real Time enabled, Web Services based 1- Computing infrastructure 2- Distributed Control infrastructure For Development For Operation

6. In This Paper … • Main components of this computing infrastructure: • Generic Real Time API (Generic RT-API) • A Rule based Configurable API Translator • A Hard Real Time Web Services (HRT-WS) Engine • The ability to receive XML based configuration/control instructions remotely. • We have used LXRT/RTAI based Hard Real Time Linux environment.

7. In This Paper … • Keywords: • Smart Grid, • Cyber Physical Systems, • Power System Informatics • Hard Real-Time Systems • Web Services • Model Transformation

8. Introduction • Energy Management Systems (EMS) Traditionally, the control of the bulk electric power grid has been realized by Energy Management Systems (EMS) that allow control devices located at substations, generation units and loads to achieve safe and economical operation of the grid. • Main components of these EMS systems: • Supervisory Control and Data Acquisition (SCADA) • Computing Resources, • User Interface • Network Economic • Security Application Software • Distributed management System (DMS) • Increased automation level compared to EMS

9. Introduction • EMS and DMS  Based on Centralized Control • Limitations of Centralized Control: • Too much data is needed for operation • Communication bottlenecks • Intractable control & optimization problems • Exponential growth of EMS and DMS complexity • Vulnerability of energy control centers to security attacks • Also EMS/DMS: • Bad software stack • Introduction of More software for power applications  • Suitable software engineering techniques. •  Ensure the fulfillment of mission critical requirements

10. Introduction • Transition towards Distributed Control Architecture Needs: Appropriate Computing and Control infrastructure • Using Web Services and Service Oriented Architecture? smart grid applications would require enhancements to the current Web Services infrastructure, such as support for Timeliness Proposed Computing Structure in this paper: • Development Support • Run-time Support

11. Introduction • Contributions of this paper: • A Futuristic distributed control architecture for Smart Grid built on the concept of “Prosumer”. • A Hard Real Time-enabled, Web Services based Computing Infrastructure required to implement our proposed distributed control architecture • Implementation steps towards a lab prototype of the proposed computing infrastructure

12. Related Work • Smart grid Architecture • Some works support just one type of apps • Some don’t support a generic infrastructure • The Smart Grid initiative of the National Institute of Standards and Technology (NIST) is developing standards to ensure interoperability of the smart grid components

13. Related Work • Our Architecture represents an abstraction layer which hides the NIST Conceptual Reference Model and GWAC interoperability stack from smart grid applications and presents them with an interface which is more suitable to realizing flexible and reliable smart grid applications

14. Related Work NIST Conceptual Reference Model

15. Related Work • Service Oriented Architecture • Web Services has emerged as the most popular technology for developing SOA based solutions • SOA is not just a set of standards. It is a design philosophy which aims at developing systems that are loosely coupled, flexible, reusable and adaptable. Our proposed infrastructure moves the concepts of Web Services and SOA beyond the enterprise domain and applies them to the development of a smart grid control infrastructure.

16. Concept of “Prosumer” • Prosumer: Producer + Consumer • Prosumer may consist of a combination of: a) components: energy sources, loads, and storage, b) an electric grid, c) a grid control system, and d) a market • Any electric system can be represented as a prosumer, and all the power system control interactions can be modelled as interactions between prosumers

17. Proposed Control Architecture • Architecture level • 4 (hierarchical) Control Layers • Interactions are defined based on interfaces

18. Proposed Control Architecture • Prosumer Services and Interfaces • We use the concept of Prosumer and its associated control layers to propose a Web Services-based SOA control infrastructure for smart grid by standardizing a set of entity-centric web services.

19. Proposed Control Architecture

20. Proposed Control Architecture • The details of power system quantities like voltage, active power and reactive power are contained inside the messages used in the service definitions above. • For example, giveRealTimeStatusMsg of LCTRL service would include all the real time status values that are of interest to a service trying to control that particular device. Moreover, we propose to modify the traditional WSDL definition to associate a timing constraint with each of the operation

21. Proposed Control Architecture • Case Study: Residential Demand Response • Utility  U_PRSMR • Neighbourhood  N_PRSMR • Home  H_PRSMR How it works?

22. Proposed Control Architecture • Advantages: • Autonomous Local Control • Smaller Optimization Problems • Automated Configuration and Operation • Reliability and Certification • Flexibility for Market Innovations

23. IMPLEMENTATION REQUIREMENTS OF PROPOSEDDISTRIBUTED CONTROL ARCHITECTURE • Location of Computing resources • LCRTL  Devices • Prioritizing Applications • Supporting different data rates • Timelines • Model driven Development and operation

24. Proposed computing infrastructure • Hardware • Heterogeneous hardware (Servers to embedded) • Operating System • RTAI (Real-time Application Interface) (Kernel) • LXRT (Linux Real-time) (User Space) • Generic RT API and API translator • Generic Real-time API • Rule-based Configurable API translator • Middleware • Hard Real-Time Web Services (HRT-WS) Engine

25. Proposed computing infrastructure Program Structure using the Generic RT-API • Once we have a program in terms of our Generic RT-API, we can translate it to a particular RTOS platform using an API Translator

26. Proposed computing infrastructure

27. Proposed computing infrastructure

28. Proposed computing infrastructure

29. Steps towards Implementation • We propose to use model driven tools to transform model based simulations into actual machine readable configurations for the individual elements of computing platform proposed here, in an automated and reliable manner. • Analogy: Simulink model for Automotive industry  Executable Code generation

30. Steps towards Implementation

31. Conclusion and Future Work • The proposed hard real time enabled, Web Services based automatically configurable computing infrastructure can support and accelerate the application development for the Prosumer- driven, distributed smart grid control architecture. • The scope of the paper is at the architecture level which will open multiple opportunities for research in future.

32. How this paper could be useful in our Lab?

33. More Questions? ?