access icon free Trans-oceanic remote power hardware-in-the-loop: multi-site hardware, integrated controller, and electric network co-simulation

Electric system operators are increasingly concerned with the potential system-wide impacts of the large-scale integration of distributed energy resources including voltage control, protection coordination, and equipment wear. This prompts a need for new simulation techniques that can simultaneously capture all the components of these large integrated smart grid systems. This study describes a novel platform that combines three emerging research areas: power systems co-simulation, power hardware in the loop (PHIL) simulation, and lab–lab links. The platform is distributed, real-time capable, allows for easy internet-based connection from geographically-dispersed participants, and is software platform agnostic. The authors demonstrate its utility by studying real-time PHIL co-simulation of coordinated solar photovoltaic (PV) firming control of two inverters connected in multiple electric distribution network models, prototypical of US and Australian systems. The novel trans-pacific closed-loop system simulation was conducted in real time using a power network simulator and physical PV/battery inverter at power at the National Renewable Energy Laboratory in Golden, CO, USA and a physical PV inverter at power at the Commonwealth Scientific and Industrial Research Organisation's Energy Centre in Newcastle, NSW, Australia. This capability enables smart grid researchers throughout the world to leverage their unique simulation capabilities for multi-site collaborations that can effectively simulate and validate emerging smart grid technology solutions.

Inspec keywords: power distribution protection; photovoltaic power systems; control engineering computing; smart power grids; invertors; power generation control; power generation protection; closed loop systems; voltage control; power distribution control; power system simulation; secondary cells

Other keywords: software platform agnostic; commonwealth scientific and industrial research organisation energy centre; coordinated solar photovoltaic firming control real-time PHIL cosimulation; Australian system; multisite collaborations; transoceanic remote power hardware-in-the-loop; distributed energy resource large-scale integration; Golden CO USA; geographically-dispersed participants; Newcastle NSW Australia; transpacific closed-loop system simulation; PHIL simulation; protection coordination; power system cosimulation; multiple electric distribution network models; lab–lab links; large integrated smart system; US systems; electric network cosimulation; National Renewable Energy Laboratory; internet-based connection; multisite hardware; integrated controller; physical PV-battery inverter; equipment wear; power network simulator; voltage control; PV firming control real-time PHIL co-simulation

Subjects: DC-AC power convertors (invertors); Control of electric power systems; Distribution networks; Control engineering computing; Voltage control; Power system protection; Solar power stations and photovoltaic power systems

References

    1. 1)
      • 5. Anderson, D., Zhao, C., Hauser, C., et al: ‘Power grid communications: integrated simulation for designing smart grid applications’ (Washington State University, 2011).
    2. 2)
      • 21. Palmintier, B., Lundstrom, B., Chakraborty, S., et al: ‘A power hardware-in-the-loop platform with remote distribution circuit cosimulation’, IEEE Trans. Ind. Electron., 2015, 62, (4), pp. 22362245.
    3. 3)
      • 16. Lauss, G., Faruque, M.O., Schoder, K., et al: ‘Characteristics and design of power hardware-in-the-loop simulations for electrical power systems’, IEEE Trans. Ind. Electron., 2016, 63, (1), pp. 406417.
    4. 4)
      • 19. Langston, J., Schoder, K., Steurer, M., et al: ‘Power hardware-in-the-loop testing of a 500 kW photovoltaic array inverter’. Proc. IECON 2012 – 38th Annual Conf. on IEEE Industrial Electronics Society, Montreal, QC, Canada, 2012, pp. 47974802.
    5. 5)
      • 30. ‘IEEE Std. 1547.7-2013: IEEE guide for conducting distribution impact studies for distributed resource interconnection’ (IEEE, 2013).
    6. 6)
      • 23. Bastos, J.L., Wu, J., Schulz, N., et al: ‘Distributed simulation using the virtual test bed and its real-time extension’. Proc. 2007 Summer Computer Simulation Conf., San Diego, CA, USA, 2007, pp. 757765.
    7. 7)
      • 6. Hopkinson, K., Wang, X., Giovanini, R., et al: ‘EPOCHS: a platform for agent-based electric power and communication simulation built from commercial off-the-shelf components’, IEEE Trans. Power Syst., 2006, 21, (2), pp. 548558.
    8. 8)
      • 4. Palmintier, B., Krishnamurthy, D., Top, P., et al: ‘Design of the HELICS high-performance transmission-distribution-communication-market co-simulation framework’. Proc. 2017 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, Pittsburgh, PA, 2017.
    9. 9)
      • 34. ‘BeagleBone Black’. Available at http://beagleboard.org/black.
    10. 10)
      • 10. Kelley, B.M., Top, P., Smith, S.G., et al: ‘A federated simulation toolkit for electric power grid and communication network co-simulation’. Proc. 2015 Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES), 2015, pp. 16.
    11. 11)
      • 31. Broderick, R.J., Quiroz, J.E., Reno, M.J., et al: ‘Time series power flow analysis for distribution connected PV generation’ (Sandia National Laboratories, 2013).
    12. 12)
      • 11. Palmintier, B., Hale, E., Hansen, T., et al: ‘IGMS: an integrated ISO-to-appliance scale grid modeling system’, IEEE Trans. Smart Grid, 2017, 8, (3), pp. 15251534.
    13. 13)
      • 27. EPRI: ‘Common functions for smart inverters, Version 3’ (EPRI, 2013).
    14. 14)
      • 36. Schneider, K.P., Chen, Y., Engle, D., et al: ‘Taxonomy of North American radial distribution feeders’. Proc. IEEE Power & Energy Society General Meeting 2009, Calgary, AB, 2009.
    15. 15)
      • 24. Stevic, M., Vogel, S., Monti, A., et al: ‘Feasibility of geographically distributed real-time simulation of HVDC system interconnected with AC networks’. Proc. 2015 IEEE PowerTech, Eindhoven, Netherlands, 2015, pp. 15.
    16. 16)
      • 1. Mets, K., Ojea, J.A., Develder, C.: ‘Combining power and communication network simulation for cost-effective smart grid analysis’, IEEE Commun. Surv. Tutor., 2014, 16, (3), pp. 17711796.
    17. 17)
      • 13. Palensky, P., Widl, E., Stifter, M., et al: ‘Modeling intelligent energy systems: co-simulation platform for validating flexible-demand EV charging management’, IEEE Trans. Smart Grid, 2013, 4, (4), pp. 19391947.
    18. 18)
      • 35. Schneider, K.P., Chen, Y., Chassin, D.P., et al: ‘Modern grid initiative distribution taxonomy final report’ (Pacific Northwest National Laboratory, 2008).
    19. 19)
      • 33. Google, Inc.: ‘Protocol buffers’. Available at https://developers.google.com/protocol-buffers/.
    20. 20)
      • 7. Georg, H., Müller, S.C., Dorsch, N., et al: ‘INSPIRE: integrated co-simulation of power and ICT systems for real-time evaluation’. Proc. 2013 IEEE Int. Conf. on Smart Grid Communications (SmartGridComm), Vancouver, Canada, 2013, pp. 576581.
    21. 21)
      • 12. Palensky, P., Widl, E., Elsheikh, A.: ‘Simulating cyber-physical energy systems: challenges, tools and methods’, IEEE Trans. Syst. Man Cybern. Syst., 2014, 44, (3), pp. 318326.
    22. 22)
      • 37. Cohen, M.A.: ‘GridLAB-D taxonomy feeder graphs’. Available at http://emac.berkeley.edu/gridlabd/taxonomy_graphs.
    23. 23)
      • 2. Li, W., Ferdowsi, M., Stevic, M., et al: ‘Cosimulation for smart grid communications’, IEEE Trans. Ind. Inf., 2014, 10, (4), pp. 23742384.
    24. 24)
      • 8. Anderson, K., Du, J., Narayan, A., et al: ‘GridSpice: a distributed simulation platform for the smart grid’, IEEE Trans. Ind. Inf., 2014, 10, (4), pp. 23542363.
    25. 25)
      • 9. Ciraci, S., Daily, J., Fuller, J., et al: ‘FNCS: a framework for power system and communication networks co-simulation’. Proc. of the Symp. on Theory of Modeling & Simulation - DEVS Integrative, San Diego, CA, USA, 2014, p. 36.
    26. 26)
      • 17. Lu, B., Wu, X., Figueroa, H., et al: ‘A low-cost real-time hardware-in-the-loop testing approach of power electronics controls’, IEEE Trans. Ind. Electron., 2007, 54, (2), pp. 919931.
    27. 27)
      • 29. Braslavsky, J.H., Ward, J.K., Collins, L.: ‘A stability vulnerability in the interaction between volt-VAR and volt-Watt response functions for smart inverters’. Proc. 2015 IEEE Conf. on Control Applications (CCA), Sydney, Australia, 2015, pp. 733738.
    28. 28)
      • 20. Palmintier, B., Giraldez, J.: ‘Feeder voltage regulation with high-penetration PV using advanced inverters and a distribution management system: a duke energy case study’ (National Renewable Energy Laboratory, 2016).
    29. 29)
      • 28. Collins, L., Ward, J.K.: ‘Real and reactive power control of distributed PV inverters for overvoltage prevention and increased renewable generation hosting capacity’, Renew. Energy, 2015, 81, pp. 464471.
    30. 30)
      • 38. Berry, A.M., Moore, T., Ward, J.K., et al: ‘National feeder taxonomy: describing a representative feeder set for Australian electricity distribution networks’ (CSIRO, 2013).
    31. 31)
      • 18. Benigni, A., Monti, A.: ‘A parallel approach to real-time simulation of power electronics systems’, IEEE Trans. Power Electron., 2015, 30, (9), pp. 51925206.
    32. 32)
      • 25. Stevic, M., Monti, A., Benigni, A.: ‘Development of a simulator-to-simulator interface for geographically distributed simulation of power systems in real time’. Proc. IECON 2015 – 41st Annual Conf. of the IEEE Industrial Electronics Society, Yokohama, Japan, 2015, pp. 50205025.
    33. 33)
      • 26. Williams, T., Fuller, J., Schneider, K., et al: ‘Examining system-wide impacts of solar PV control systems with a power hardware-in-the-loop platform’. IEEE 40th Proc. Photovoltaic Specialist Conf. (PVSC), 2014, Denver, CO, USA, 2014, pp. 20822087.
    34. 34)
      • 32. Chassin, D.P., Fuller, J.C., Djilali, N.: ‘GridLAB-D: an agent-based simulation framework for smart grids’, J. Appl. Math., 2014, 2014, pp. 112.
    35. 35)
      • 14. Ruth, M., Pratt, A., Lunacek, M., et al: ‘Effects of home energy management systems on distribution utilities and feeders under various market structures’. Proc. CIRED 23rd Int. Conf. and Exhibition on Electricity Distribution, Lyon, France, 2015.
    36. 36)
      • 22. Compere, M., Goodell, J., Simon, M., et al: ‘Robust control techniques enabling duty cycle experiments utilizing a 6-DOF crewstation motion base, a full scale combat hybrid electric power system, and long distance internet communications’. SAE Technical Paper 2006-01-3077, 2006.
    37. 37)
      • 15. Faruque, M.O., Strasser, T., Lauss, G., et al: ‘Real-time simulation technologies for power systems design, testing, and analysis’, IEEE Power Energy Technol. Syst. J., 2015, 2, (2), pp. 6373.
    38. 38)
      • 3. Lin, H., Veda, S.S., Shukla, S.S., et al: ‘GECO: global event-driven co-simulation framework for interconnected power system and communication network’, IEEE Trans. Smart Grid, 2012, 3, (3), pp. 14441456.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2016.1585
Loading

Related content

content/journals/10.1049/iet-gtd.2016.1585
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading