Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon free Real-time optimal management of reverse power flow in integrated power and gas distribution grids under large renewable power penetration

© The Institution of Engineering and Technology
Received 25/09/2017, Accepted 18/02/2018, Revised 02/12/2017, Published 20/02/2018

Exponential penetration of renewable generation has led to the new issues in power distribution systems, such as reverse power flow in the feeders. In the case of sizable distributed generation during lower demand, the power tends to travel in the reverse direction. This, in turn, could cause serious operational issues such as voltage rise, extra heat in the transformers, and maloperation of protective devices. Newly emerging technologies for power-to-gas (PtG) conversion are now offering effective solutions to the problem. The proliferation of PtG facilities can lead to the deployment of integrated natural gas and power systems in the near future. PtG and gas-fired, i.e. gas-to-power (GtP), units can be utilised to address several issues in an integrated power and gas network. This study unveils the application of bi-directional energy converters within an integrated gas and power system for distribution system reverse power management (DSRPM). To that end, a new real-time algorithm is proposed for optimal joint scheduling of PtG and GtP units for DSRPM. A new index is also developed that would quantify the contribution of the PtG–GtP system to DSRPM. Numerical results using real-world data on a test system substantiate the effectiveness of the proposed algorithm.

Inspec keywords: load flow; distributed power generation; power generation scheduling; investment; power system management; optimisation; natural gas technology; power generation economics; power distribution economics; cost-benefit analysis; power grids; renewable energy sources; power convertors; steam power stations

Other keywords: reverse power flow real-time optimal management; RPFM; bidirectional energy converter; optimisation problem; large renewable power penetration; PtG-GtP unit optimal joint scheduling; power-to-gas conversion; PtG conversion; integrated power and gas distribution grids; return on investment; distributed generation; reverse direction; gas-fired units; power distribution systems; DSRPM; distribution system reverse power management; renewable generation exponential penetration

Subjects: Distributed power generation; Steam power stations and plants; Optimisation techniques; Power system management, operation and economics; Power convertors and power supplies to apparatus

References

    1. 1)
      • 2. Alam, M.J.E., Muttaqi, K.M., Sutanto, D.: ‘Mitigation of rooftop solar PV impacts and evening peak support by managing available capacity of distributed energy storage systems’, IEEE Trans. Power Syst., 2013, 28, (4), pp. 3874–3884.
    2. 2)
      • 22. ANSI Std. C84.1: ‘American national standard for electric power systems and equipment–voltage ratings (60 Hertz)’, 2006.
    3. 3)
      • 14. Chen, S., Wei, Z., Sun, G., et al: ‘Multi–linear probabilistic energy flow analysis of integrated electrical and natural–gas systems’, IEEE Trans. Power Syst., 2017, 32, (3), pp. 1970–1979.
    4. 4)
      • 16. Baran, M.E., Wu, F.F.: ‘Network reconfiguration in distribution systems for loss reduction and load balancing’, IEEE Trans. Power Deliv., 1989, 4, (2), pp. 1401–1407.
    5. 5)
      • 23. Hydro Ottawa Annual Planning Report: ‘2014 system capacity plan’. Available at https://static.hydroottawa.com/documents/publications/planning/2%20-%20Capacity%20Planning%20-%202014.pdf.
    6. 6)
      • 4. Brusco, G., Burgio, A., Menniti, D., et al: ‘Energy management system for an energy district with demand response availability’, IEEE Trans. Smart Grid, 2014, 5, (5), pp. 2385–2393.
    7. 7)
      • 8. Camilo, F.M., Castro, R., Almeida, M.E., et al: ‘Self-consumption and storage as a way to facilitate the integration of renewable energy in low voltage distribution networks’, IET Gener. Transm. Distrib., 2016, 10, (7), pp. 1741–1748.
    8. 8)
      • 7. Tabari, M., Yazdani, A.: ‘An energy management strategy for a DC distribution system for power system integration of plug–in electric vehicles’, IEEE Trans. Smart Grid, 2016, 7, (2), pp. 659–668.
    9. 9)
      • 1. Hossain, M.I., Yan, R., Saha, T.S.: ‘Investigation of the interaction between step voltage regulators and large-scale photovoltaic systems regarding voltage regulation and unbalance’, IET Renew. Power Gener., 2016, 10, (3), pp. 299–309.
    10. 10)
      • 12. Clegg, S., Mancarella, P.: ‘Storing renewables in the gas network: modelling of power-to-gas seasonal storage flexibility in low-carbon power systems’, IET Gener. Transm. Distrib., 2016, 10, (3), pp. 566–575.
    11. 11)
      • 17. IESO Report: ‘Energy Storage’, IESO, Toronto, ON, Canada, 2016, pp. 1–60. Available at http://www.ieso.ca/-/media/files/ieso/document-library/energy-storage/ieso-energy-storage-report_march-2016.pdf.
    12. 12)
      • 15. He, C., Wu, L., Liu, T., et al: ‘Robust co-optimization scheduling of electricity and natural gas systems via ADMM’, IEEE Trans. Sustain. Energy, 2017, 8, (2), pp. 658–670.
    13. 13)
      • 9. Carne, G.D., Buticchi, G., Zou, Z.X., et al: ‘Reverse power flow control in a ST–fed distribution grid’, IEEE Trans. Smart Grid, 2017, PP, (99), pp. 1–9, DOI: 10.1109/TSG.2017.2651147.
    14. 14)
      • 5. Boemer, J.C., Rawn, B.G., Gibescu, M., et al: ‘Response of wind power park modules in distribution systems to transmission network faults during reverse power flows’, IET Renew. Power Gener., 2015, 9, (8), pp. 1033–1042.
    15. 15)
      • 11. Zeng, Q., Fang, J., Li, J., et al: ‘Steady-state analysis of the integrated natural gas and electric power system with bi–directional energy conversion’, Appl. Energy J., 2016, 184, (15), pp. 1483–1492.
    16. 16)
      • 18. Evangelopoulos, V.A., Georgilakis, P.S.: ‘Optimal distributed generation placement under uncertainties based on point estimate method embedded genetic algorithm’, IET Gener. Transm. Distrib., 2014, 8, (3), pp. 389–400.
    17. 17)
      • 19. Liu, H., Tang, C., Han, J., et al: ‘Probabilistic load flow analysis of active distribution network adopting improved sequence operation methodology’, IET Gener. Transm. Distrib., 2017, 11, (9), pp. 2147–2153.
    18. 18)
      • 6. Hashemi, S., Ostergaard, J.: —‘ Methods and strategies for overvoltage prevention in low voltage distribution systems with PV’, IET Renew. Power. Gener., 2016, 11, (2), pp. 205–214.
    19. 19)
      • 20. ‘The Ontario Independent Electricity System Operator (IESO)’. Available at http://www.ieso.ca/, accessed 9 September 2017.
    20. 20)
      • 21. The Department of Energy Hydrogen and Fuel Cells Program Plan: ‘An integrated strategic plan for the research, development, and demonstration of hydrogen and fuel cell technologies’. Available at https://energy.gov/sites/prod/files/2014/03/f12/program_plan2011.pdf.
    21. 21)
      • 13. Huang, J.H., Zhou, H.S., Wu, Q.H., et al: ‘Assessment of an integrated energy system embedded with power–to–gas plant’. Proc. IEEE Conf. Innovative Smart Grid Technologies – Asia, Australia, December 2016, pp. 196–201.
    22. 22)
      • 10. Jabr, R.A., Dzafic, I., Huseinagic, I.: ‘Real time optimal reconfiguration of multiphase active distribution networks’, IEEE Trans. Smart Grid, 2017, PP, (99), pp. 1–11, DOI: 10.1109/TSG.2017.2724766.
    23. 23)
      • 3. Ziadi, Z., Taira, S., Oshiro, M., et al: ‘Optimal power scheduling for smart grids considering controllable loads and high penetration of photovoltaic generation’, IEEE Trans. Smart Grid, 2014, 5, (5), pp. 2350–2359.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-gtd.2017.1513
Loading

Related content

content/journals/10.1049/iet-gtd.2017.1513
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
Print this page
This is a required field
Please enter a valid email address