Enabling demand response potentials for resilient microgrid design

Document Type : Article

Authors

Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran.

Abstract

The future microgrids (MGs) hosting a great deal of uncertain and intermittent local renewable generations are envisioned to need for fast and flexible units in the generation side. Demand response, however, as a load shaping tool can alleviate the needs. This paper proposes a model to consider demand response potentials activated by time-varying prices in MG design studies. The model aims at maximizing MG owner’s profit while technical limits and constraints are adhered. The model also ensures that the designed MG is resilient against islanding events. To handle complexity of the model, Benders decomposition is used to decompose the model into a master problem and two types of sub-problems. The master problem optimizes binary variables indicating installing status of generating units and batteries. The first type of sub-problems optimizes continuous variables, and the second ensures the resilient operation of the MG against islanding events. In the model, the uncertainties associated with load and intermittent generation resources are captured via a scenario-based stochastic approach. The demand behavior in response to time-varying prices is modeled via price elasticity coefficients. The effectiveness of the proposed model is demonstrated through extensive numerical studies and sensitivity analyses.

Keywords


References:
1. "Critical infrastructure sectors", [Online]. Available: https://www.dhs.gov/cisa/critical-infrastructuresectors. 
2. National Academy of Sciences, Enhancing the Resilience of the Nation's Electricity System, Washington, DC, USA (2017).
3. Guttromson, R. and Watson, J. "Defining, measuring, and improving resilience of electric power systems", In Smart Grid Handbook, pp. 1-21, John Wiley & Sons, Ltd., Hoboken, New Jersey, USA (2016).
4. Field, C.B., Barros, V., Stocker, T.F., et al., IPCC (2012): Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation, Cambridge University Press, Cambridge, UK (2012).
5. Government Office of Science, Foresight Project of Reducing Risks of Future Disasters: Priorities for Decision Makers, Infrastructure and Resilience, London, UK (2012).
6. Khodai, A. "Guest editorial power grid resilience", IEEE Trans. Smart Grid, 7(6), pp. 2805-2806 (2016).
7. National Intelligence Council (NIC), Global Trends, Paradox of Progress, Washington, DC, USA (2017).
8. Governments of the United States and Canada, Joint United States-Canada Electric Grid Security and Resilience Strategy (2016).
9. Department of Energy, 2016-2020 Strategic Plan and Implementing Framework, Washington, DC, USA (2012).
10. Department of Energy, Los Alamos National Lab, Resilient Grid Operational Strategies, New Mexico, USA (2016).
11. Philips, J., Finster, M., and Pillon, J. "State energy resilience framework", REPORT ANL/GSS-16/4, Argonne National Lab., Chicago, Illinois, USA (Dec. 2016).
12. Potvin, J. and Short, T. "Distribution grid resiliency: overhead structures", REPORT 3002006780, EPRI, California, USA (2015).
13. Tripolitis, J., Martino S., and Rajagopalan, S.  Distribution grid resiliency: undergrounding", REPORT 3002006782, EPRI, California, USA (2015).
14. Department of Energy, Office of Energy Policy and Systems Analysis (EPSA), Resilience of the U.S. Electricity System: A Multi-Hazard Perspective, Washington, DC, USA (2016).
15. Anderson, J. and Deaver, B. "Distribution grid resiliency: modern grid technology", REPORT 3002006783, EPRI, California, USA (2015).
16. Clair, J. and Shahidehpour, M. "A functional microgrid for enhancing reliability, sustainability, and energy efficiency", Electric J., 25(8), pp. 21-28 (2012).
17. Lasseter, R.H. "Smart distribution: Coupled microgrids", Pro. of the IEEE, 99(6), pp. 1074-1082 (2011).
18. Shahidehpour, M. "Role of smart microgrid in a perfect power system", 2010 IEEE Power and Energy Society General Meeting (2010).
19. Strbac, G., Hatziargyriou, N., Lopes, J.P., et al. "Microgrids", IEEE Power and Energy Mag., 13(4), pp. 35-43 (2015).
20. Aguero, J.R., Bahramirad, S., and Khodaei, A. "Building resilient integrated grids", Electrification Mag., 3(1), pp. 48-55 (2015).
21. Bahramirad, S., Reder, W., and Khodaei, A. "Reliability-constrained optimal sizing of energy storages", IEEE Trans. Smart Grid, 3(4), pp. 2056-2062 (2012).
22. Alsaidan, I., Khodaei, A., and Gao, W. "A comprehensive battery energy storage optimal sizing model for microgrid applications", IEEE Trans. Power Syst., 33(4), pp. 3968-3980 (2018).
23. Yuancheng, M. "Reliability and economy evaluation of microgrid based distribution network connection mode", 4th International Conf. on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), Shandong, China (2011).
24. Madathil, S.C., Yamangil, E., Nagarajan, H., et al. "Resilient off-grid microgrids: Capacity planning and N-1 security", IEEE Trans. Smart Grid, 9(6), pp. 6511-6521 (2018).
25. Billinton, R. "Maintaining supply reliability of small isolated power system using renewable energy", IEEE Proc. Generation, Transmission and Distribution, 148(6), pp. 530-534 (2001).
26. Arefifar, S.A. "Optimum microgrid design for enhancing reliability and supply-security", IEEE Trans. Smart Grid, 4(3), pp. 1567-1575 (2013).
27. Shahidehpour, M. and Khodaei, A. "Microgrid planning under uncertainty", IEEE Trans. Power Syst., 30(5), pp. 2417-2425 (2013).
28. Ranjbar, H. and Safdarian, A. "A robust model for daily operation of grid-connected microgrids during normal conditions", Sciantia Iranica J. (In Press). DOI:10.24200/sci.2019.50690.1819.
29. Zhang, J. and Zeng, B. "Integrated planning for transition to low-carbon distribution system with renewable energy generation and demand response", IEEE Trans. Smart Grid, 29(3), pp. 1153-1165 (2014).
30. Yang, X. "Microgrid's generation expansion planning considering carbon economy", 2012 Asia-Pacific Power and Energy Engineering Conf., Shanghai, China (2012).
31. Shahidehpour, M. and Khodaei, A. "Microgrid-based co-optimization of generation and transmission planning in power systems", IEEE Trans. Power Syst., 28(2), pp. 1582-1590 (2013).
32. Cheng, B. and Wang, Z. "Robust optimization based optimal DG placement in microgrids", IEEE Trans. Smart Grid, 5(5), pp. 2173-2182 (2014).
33. Khodaei, A. "Resiliency-oriented microgrid optimal scheduling", IEEE Trans. Smart Grid, 5(4), pp. 1584- 1591 (2014).
34. Khodaei, A. "Provisional microgrid planning", IEEE Trans. Smart Grid, 8(3), pp. 1584-1591 (2017).
35. Atia, R. and Yamada, N. "Sizing and analysis of renewable energy and battery systems in residential microgrids", IEEE Trans. Smart Grid, 7(3), pp. 1204- 1213 (2016).
36. Wu, T., Yang, Q., Bao, X., et al. "Coordinated energy dispatching in microgrid with wind power generation and plug-in electric vehicles", IEEE Trans. Smart Grid, 14(1), pp. 47-57 (2013).
37. Zhang, C., Xu, Y., Dong, Z.Y., et al. "Robust coordination of distributed generation and price-based demand response in microgrids", IEEE Trans. Smart Grid, 5(4), pp. 1608-1620 (2017).
38. Ahmad Bashir, A., Pourakbari-Kasmaei, M., Contreras, J., et al. "A novel energy scheduling framework for reliable and economic operation of islanded and grid-connected microgrids", Electric Power Systems Research J., 171, pp. 85-96 (2019).
39. Safdarian, A. "Integration of price-based demand response in Discos' short-term decision model", IEEE Trans. Smart Grid, 5(5), pp. 2235-2245 (2014).