In this paper we discuss the use of real-time Grid computing for the monitoring, control and simulation of renewable electricity generators and their associated electrical networks. We discuss briefly the architectural design of GRIDCC and how we have integrated a number of real (solar, CHP) and simulated conventional power generators into the GRIDCC environment. A local weather station has also been attached to an Instrument Manager to alert experts appropriately when the Solar Array is not generating. The customised remote control and monitoring environment (a virtual control room), distributed using a standard web server, is discussed

Frizziero, E

Hobson, PR

Huang, C

Irving, MR

Kalganova, T

Kyberd, P

Lelli, F

Petrucci, A

Pugliese, R

Taylor, GA

Taylor, R

English

Brunel University Research Archive

061215-032Grid Computing Technologies for RenewableElectricity Generator Monitoring and ControlP R Hobson, E Frizziero, Chenxi Huang, M R Irving, T Kalganova, P Kyberd, , F Lelli, A Petrucci,R Pugliese, G Taylor, R TaylorAbstract- In this paper we discuss the use of real-time Gridcomputing for the monitoring, control and simulation ofrenewable electricity generators and their associated electricalnetworks. We discuss briefly the architectural design of GRIDCCand how we have integrated a number of real (solar, CHP) andsimulated conventional power generators into the GRIDCCenvironment. A local weather station has also been attached to anInstrument Manager to alert experts appropriately when theSolar Array is not generating. The customised remote controland monitoring environment (a virtual control room), distributedusing a standard web server, is discussed.Index Terms- Distributed Computing, Electrical PowerGeneration, Grid Computing, Renewable EnergyI. INTRODUCTIONGrid computing has recently been developed primarily tosolve large-scale computational challenges in areas such asgenomics, biomedicine, particle physics and other scientificfields with similar large-scale computational challenges. TheEU funded GRIDCC project [1] is extending the concept ofthe Grid to encompass virtualized instrument resources and tocreate middleware which can provide Grids with a real-timequality of service.There are many application areas driving the developmentof a Grid that includes resources beyond the compute andstorage elements of currently deployed Grids. One prototypeapplication being developed in the GRIDCC project is controland monitoring ofrenewable electricity generation.In the coming decades a large number of offshore windpower generators will be connected to European transmissionsystems [2]. As these generators contribute larger amounts ofpower it will become necessary to monitor their performanceand control their operation with a much higher degree ofaccuracy, reliability and cooperation between transmissionManuscript received March 30, 2007. This work was supported in part bythe EC Framework Programme 6 Contract IST-5 11382.P R Hobson, Chenxi Huang, M R Irving, T Kalganova, P Kyberd, GTaylor, R Taylor are with the School of Engineering & Design, BrunelUniversity, Uxbridge UB8 3PH, UK (corresponding author P R Hobson:+44(0)1895266799; fax: +44(0)1895272391; e-mail:Peter.Hobson obrunel.ac.uk).E Frizziero, F Lelli and A Petrucci. are with INFN, Via Romea, 4,Legnaro, 1-35020, ItalyR Pugliese is with Sincrotrone Trieste S.C.p.A. di interesse nazionale,Strada Statale 14 km 163 in AREA Science Park, Basovizza, Trieste 1-34012,Italy1-4244-0635-8/07/$20.00 ©2007 IEEEsystem operators. The standard control technologies that arecurrently in use at transmission level are not easily scalable tothe very large numbers of off-shore wind power generatorswhich will be operating across Europe in the future. OpenSource Grid computing can provide a relatively inexpensivesolution, allowing the output of wind power generators to bemonitored and when appropriate controlled across largegeographical areas. An outline of the power systems Grid-computing platform that has been adopted for our research isillustrated in Figure 1.Power SystemsGrid-computing Other ParticipantsFig. 1. Overview of a power systems Grid Computing platform (from [3]).A Grid is scaleable - inherently it is designed to work aswell with 100,000 participants (nodes) as it is with 100. Thedistribution of computing resources requires additionalnetwork security, and it is important to note that this is alsoinherent to Grid computing, yet it can still provide a robustprovision of computational resources in terms of self-organisation and major fault tolerance [4]. Data can also bedistributed and replicated across a network of a virtualorganisation with specified levels of security.II. GRIDCCThe GRIDCC project has now demonstrated the extensionof existing computational grids to provide the ability to controland monitor collections of real instruments withaccompanying supporting services such as a virtual controlroom (VCR) a workflow management system (WfMS), and ageneric Problem Solver running locally or globally. Some carehas been taken to build into the GRIDCC concept therequirements of real-time systems, where here real-timeimplies a defined response time for a process tostart/complete/return a status message etc. rather than anyparticular data rate. A critical element in achieving real-timeI061215-032response is the quality of service repository which can bequeried both by the Execution Service and from the VCR.Figure 2 shows the architecture of GRIDCC and figure 3shows the internal details of its new contribution to Gridcomputing; the instrument element (IE) [5].Fig. 2. Architecture of GRIDCC. The Execution Service controls theInstrument Element and existing Grid resources using a workflowmanagement system (WfMS) and agreement service (AgrS). The InstrumentElement is connected by instances of the Instrument Manager (IM) to realsensors and instruments.Resource Inf& Mon ProblemServce ervice SolverF ~~~~Daitahldr Instrument ElementData I Info FSMCollector Collector Hadler EngineCD 0)C D DC(J.(D.(J Real InstrumentsFig. 3. The internal details of the Instrument Element. The InstrumentManager handles the control, command and data for a specific instrument.The IE is a coherent collection of services allowing remoteconfiguration and control of a physical instrument andintegration with existing computational Grids. Inside the IE aset of Web Service interfaces called VIGS (Virtual InstrumentGrid Service) allows the user to remotely access the realinstrument, thus plugging the instrument itself in to the Grid.Additionally the Instrument Element can provide facilitiesfor interactive co-operation between computing Grid resourcesto applications that have real-time requirements or need fastinteraction with Compute Elements (CE) and StorageElements (SE).The Multipurpose Collaborative Environment (MCE) isWeb-based groupware which provides collaboration supporttools and the foundation to allow teams of people to controland manage Grid resources, including remote instrumentation.The MCE has been designed taking into account thefundamental needs of end-users and stakeholders of pilotapplications. In particular, a modular and layered architecturesupports the common requirements of a range of pilotapplictations. Following this philosophy, the MCE design anddevelopment has been divided into three parts:* a core system, providing fundamental architecture andservices ofthe entire system;* a set of general purpose plug-ins, aimed at supportingcommon groupware functionalities (e.g. chat, sharedcalendars, integration with videoconferencing systems), thatcan be activated/deactivated (or even substituted with otherones) in each specific VCR;* a set of application-specific plug-ins, supportingfunctionalities that are needed only for particular applications(e.g. the control of a particular instrument).The MCE is a Web portal providing access to the typicalfunctionalities of a scientific groupware through a Web-browser. Among the suitable portal frameworks available,GridSphere [6] offered a complete set of features (e.g. portaland user administration functionalities, JSR 168 standardcompliance, support for the integration of Grid components)for the goals ofthe GRIDCC project.III. DEMONSTRATOR FOR ELECTRICAL GENERATORMONITORING & CONTROLAt Brunel University there exist a number of smallrenewable energy generators, currently two 500Wphotovoltaic (PV) arrays and a 150 kW combined heat &power (CUP) of which 80 kW is electrical. A small (few kW)wind turbine is envisaged and we have a local weather stationfor environmental monitoring. In addition to the realgenerators we have sophisticated computer models [7] ofelectrical generators which we can run on Grid cluster workernodes in order to evaluate the scalability of the GRIDCCcontrol and monitoring system to potentially thousands ofgenerator instances.Currently we have customized Instrument Managers for thethree classes of power generator and the weather station. Eachof the generators has a different interface to the InstrumentElement via individual Instrument Managers. The generatorshave finite state machines (FSM Engine in Figure 3) to enablethem to be control from the VCR (see figure 4) or the WfMS.2061215-032Multipurpose Collaborative Environmenta Vrtuial Control Room over the WebbFig. 4. The Instrument view presented to a remote user by the MCE. Here youcan see the links to the Weather Station, the two PV arrays (Sanyo and Sharp)and the CHP Generator.Figure 5 shows the monitoring of the electrical poweroutput of one of the PV arrays on a sunny day. The data isupdated every 5 seconds.Fig. 5. The monitored data from one of the PV arrays. The SolarIrradiance (W.m-2) is shown on the upper time chart and the simultaneouslymeasured instantaneous electrical power in watts is shown on the lower trace.The correlated drop at 15:58:56 UT+1 is clearly seen.The ability of a remote operator (or multiple remoteexperts) to see the dynamic behavior of any of the generatorsat any time is a principle goal of this project. A problem solverframework that can operate at the level of the InstrumentElement (see figure 3) is currently being implemented. Thisallows any appropriate problem solving system, for example aneural network or a decision tree, to be used to determineautomatically what the likely problem is when a generatorceases to behave normally (for example sudden loss ofpower). Local remedial action, for example a shutdown andrestart, could be taken or an appropriate message sent toremote experts. The collaborative features of the MCE, suchas the use of video conferencing facilities (provided by theVRVS tool [8, 9]) or email, chat window or Skype [10]telephone call also enhance the interaction between the controlcentre and the remote sites.IV. CONCLUSIONThis paper reports on work in progress with a pilotapplication using the GRIDCC middleware for the remotecontrol and monitoring of both real and simulated electricalpower generators. We have reported on the deployment of keyelements of the GRIDCC middleware, namely the InstrumentElement which virtualizes real instruments and sensors into aGrid computing resource analogous to a computationalWorker Node and the Multipurpose CollaborativeEnvironment which provides a customizable web portal basedon GridSphere from which individual instruments can bemonitored and controlled.We are now deploying other parts of the GRIDCCmiddleware, namely the Work-Flow Management System andthe Local Problem Solver to deal with use cases such as aPower Network Operator requesting an increase in powergeneration due to increased load demand. Providing a real-time quality-of-service is an important final stage ofimplementation in the demonstrator.We envisage the application to renewable electricitygenerator monitoring and control to be aimed primarily atsmall to medium scale systems where existing dedicatednetwork links and bespoke commercial software systems maybe too expensive compared to the use of the GRIDCC opensource middleware. Any existing local control system can bewrapped up by an Instrument Manager so that it can beoperated remotely by the a GRIDCC-based system. This isprecisely what we have done in the demonstrator describedabove with the commercial control and monitor systems thatwere provided for the Solar Arrays and the CHP.ACKNOWLEDGMENTThis abstract is submitted on behalf of the whole GRIDCCcollaboration.REFERENCES[1] GRIDCC EU ICT Project, 'Grid Enabled Remote Instrumentation withDistributed Control and Computation. Available htt:H wri[2] R. Pool, "Meet the New Super Power," IET Power Engineer, pp. 8-9,June/July. 2006.[3] G.A. Taylor et al, "Scalable Integration ofWind Power on TransmissionSystems using Grid Computing," in Sixth International Workshop onLarge-Scale Integration of Wind Power and Transmission NetworksforOffshore Wind Farms, Delft, 2006, pp. 26-28.[4] Foster, C. Kesselman and S. Tuecke, "The Anatomy of the Grid:Enabling Scalable Virtual Organisations" Int. Jnl. ofHigh PerformanceComputing Applications. vol. 15, 2001, pp. 200-2223061215-032 4[5] E Frizziero et al, "Instrument Element: A New Grid component thatEnables the Control of Remote Instrumentation," in Sixth IEEEInternational Symposium on Cluster Computing and the GridWorkshops (CCGRIDW'06), SIngapore, 2006, DOI Bookmark:[6] GridSphere Portal Framework Available[7] M.Rafian, M.J.H.Sterling and M.R.Irving, "Real Time Power SystemSimulation," Proc. IEE C 134, pp 206-223, 1987[8] D. Adamczyk, et al, "A Globally Distributed Real Time Infrastructurefor World Wide Collaborations," in Proceedings of Computingfor HighEnergy Physics (CHEP), Interlaken, 2004 Available[9] Virtual Room Videoconferencing System Available[10] skype Available hc

A Globally Distributed Real Time Infrastructure for World Wide Collaborations,&quot;

Grid Enabled Remote Instrumentation with Distributed Control and Computation. Available

Instrument Element: A New Grid component that Enables the Control of Remote Instrumentation,&quot;

M.J.H.Sterling and M.R.Irving, &quot;Real Time Power System Simulation,&quot;

Meet the New Super Power,&quot; IETPowerEngineer,

Scalable Integration ofWind Power on Transmission Systems using Grid Computing,&quot;

The Anatomy of the Grid: Enabling Scalable Virtual Organisations&quot;

Virtual Room Videoconferencing System Available

Grid computing technologies for renewable electricity generator monitoring and control

Grid computing technologies for renewable electricity generator monitoring and control

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