Browse > Article
http://dx.doi.org/10.12989/eri.2020.7.2.085

Microgrid energy scheduling with demand response  

Azimian, Mahdi (Department of Electrical and Computer Engineering, Kashan Branch, Islamic Azad University)
Amir, Vahid (Department of Electrical and Computer Engineering, Kashan Branch, Islamic Azad University)
Haddadipour, Shapour (Department of Electrical and Computer Engineering, Kashan Branch, Islamic Azad University)
Publication Information
Advances in Energy Research / v.7, no.2, 2020 , pp. 85-100 More about this Journal
Abstract
Distributed energy resources (DERs) are essential for coping with growing multiple energy demands. A microgrid (MG) is a small-scale version of the power system which makes possible the integration of DERs as well as achieving maximum demand-side management utilization. Hence, this study focuses on the analysis of optimal power dispatch considering economic aspects in a multi-carrier microgrid (MCMG) with price-responsive loads. This paper proposes a novel time-based demand-side management in order to reshape the load curve, as well as preventing the excessive use of energy in peak hours. In conventional studies, energy consumption is optimized from the perspective of each infrastructure user without considering the interactions. Here, the interaction of energy system infrastructures is considered in the presence of energy storage systems (ESSs), small-scale energy resources (SSERs), and responsive loads. Simulations are performed using GAMS (General Algebraic modeling system) to model MCMG, which are connected to the electricity, natural gas, and district heat networks for supplying multiple energy demands. Results show that the simultaneous operation of various energy carriers, as well as utilization of price-responsive loads, lead to better MCMG performance and decrease operating costs for smart distribution grids. This model is examined on a typical MCMG, and the effectiveness of the proposed model is proven.
Keywords
demand response; operation; microgrid; distributed energy resources;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Sheikhi, A., Rayati, M., Bahrami, S. and Ranjbar, A.M. (2015), "Integrated demand side management game in smart energy hubs", IEEE T. Smart Grid, 6(2), 675-683. https://doi.org/10.1109/TSG.2014.2377020.   DOI
2 Shilaja, C. and Ravi, K. (2016), "Optimal power flow considering intermittent wind power using particle swarm optimization", Int. J. Renew. Energy Res., 6(2), 504-509.
3 Sreejith, S., Indragandhi, V.I., Samiappan, D. and Muruganandam, M. (2016), "Security constraint unit commitment on combined solar thermal generating units using ABC algorithm", Int. J. Renew. Energy Res., 6(4), 1361-1372. https://doi.org/10.1234/ijrer.v6i4.4559.g6925.
4 Urooj, R. and Ahmad, S.S. (2017), "Assessment of electricity demand at domestic level in Balochistan, Pakistan", Adv. Energy Res., 5(1), 57-64. https://doi.org/10.12989/eri.2017.5.1.057.   DOI
5 Uy, L., Uy, P., Siy, J., Chiu, A.S.F. and Sy, C. (2018), "Target-oriented robust optimization of a microgrid system investment model", Front. Energy, 12(3), 440-455. https://doi.org/10.1007/s11708-018-0563-1.   DOI
6 Zakariazadeh, A., Jadid, S. and Siano, P. (2014), "Multi-objective scheduling of electric vehicles in smart distribution system", Energy Conversion Manage., 79, 43-53. https://doi.org/10.1016/j.enconman.2013.11.042.   DOI
7 Zhang, D., Liu, P., Ma, L., Li, Z. and Ni, W. (2012), "A multi-period modelling and optimization approach to the planning of China's power sector with consideration of carbon dioxide mitigation", Comput. Chem. Eng., 37, 227-247. https://doi.org/10.1016/j.compchemeng.2011.09.001.   DOI
8 Zhang, D., Ma, L., Liu, P., Zhang, L. and Li, Z. (2012), "A multi-period superstructure optimisation model for the optimal planning of China's power sector considering carbon dioxide mitigation. Discussion on China's carbon mitigation policy based on the model", Energy Policy, 41, 173-183. https://doi.org/10.1016/j.enpol.2011.10.031.   DOI
9 Manshadi, S.D. and Khodayar, M.E. (2015), "Resilient operation of multiple energy carrier microgrids", IEEE T. Smart Grid, 6(5), 2283-2292. https://doi.org/10.1109/TSG.2015.2397318.   DOI
10 Motevasel, M. and Seifi, A.R. (2014), "Expert energy management of a micro-grid considering wind energy uncertainty", Energy Conversion Manage., 83, 58-72. https://doi.org/10.1016/j.enconman.2014.03.022.   DOI
11 Nikmehr, N. and Najafi Ravadanegh, S. (2015), "Optimal power dispatch of multi-microgrids at future smart distribution grids", IEEE T. Smart Grid, 6(4), 1648-1657. https://doi.org/10.1109/TSG.2015.2396992.   DOI
12 Pazouki, S. and Haghifam, M.R. (2016), "Optimal planning and scheduling of energy hub in presence of wind, storage and demand response under uncertainty", Int. J. Electrical Power Energy Syst., 80, 219-239. https://doi.org/10.1016/j.ijepes.2016.01.044.   DOI
13 Sajjad, I.A., Chicco, G. and Napoli, R. (2015), "Probabilistic generation of time-coupled aggregate residential demand patterns", IET Gen. Transmiss. Distribution, 9(9), 789-797. https://doi.org/10.1049/iet-gtd.2014.0750.   DOI
14 Reddy, S.S., Park, J.Y. and Jung, C.M. (2016), "Optimal operation of microgrid using hybrid differential evolution and harmony search algorithm", Front. Energy, 10(3), 355-362. https://doi.org/10.1007/s11708-016-0414-x.   DOI
15 Ruiz Duarte, J.L. and Fan, N. (2019), "Operations of a microgrid with renewable energy integration and line switching", Energy Syst., 10(2), 247-272. https://doi.org/10.1007/s12667-018-0286-8.   DOI
16 Saito, N., Niimura, T., Koyanagi, K. and Yokoyama, R. (2009), "Trade-off analysis of autonomous microgrid sizing with PV, diesel, and battery storage", Proceedings of the 2009 IEEE Power and Energy Society General Meeting, Calgary, Alberta, Canada, July.
17 Saldarriaga, C.A., Hincapie, R.A. and Salazar, H. (2013), "A holistic approach for planning natural gas and electricity distribution networks", IEEE T. Power Syst., 28(4), 4052-4063. https://doi.org/10.1109/TPWRS.2013.2268859.   DOI
18 Chen, C., Duan, S., Cai, T., Liu, B. and Hu, G. (2011), "Smart energy management system for optimal microgrid economic operation", IET Renew. Power Gen., 5(3), 258-267. https://doi.org/10.1049/iet-rpg.2010.0052   DOI
19 Fisher, M., Apt, J. and Sowell, F. (2018), "The economics of commercial demand response for spinning reserve", Energy Syst., 9(1), 3-23. https://doi.org/10.1007/s12667-017-0236-x.   DOI
20 Geidl, M. and Andersson, G. (2007), "Optimal power flow of multiple energy carriers", IEEE T. Power Syst., 22(1), 145-155. https://doi.org/10.1109/TPWRS.2006.888988.   DOI
21 Koutsopoulos, I. and Tassiulas, L. (2011), "Challenges in demand load control for the smart grid", IEEE Network, 25(5), 16-21. https://doi.org/10.1109/MNET.2011.6033031.   DOI
22 Heymann, B., Bonnans, J.F., Martinon, P., Silva, F.J., Lanas, F. and Jimenez-Estevez, G. (2018), "Continuous optimal control approaches to microgrid energy management", Energy Syst., 9(1), 59-77. https://doi.org/10.1007/s12667-016-0228-2.   DOI
23 Jin, M., Feng, W., Liu, P., Marnay, C. and Spanos, C. (2017), "MOD-DR: Microgrid optimal dispatch with demand response", Appl. Energy, 187, 758-776. https://doi.org/10.1016/j.apenergy.2016.11.093.   DOI
24 Joseph, A. and Shahidehpour, M. (2006), "Battery storage systems in electric power systems", Proceedings of the 2006 IEEE Power Engineering Society General Meeting, Montreal, Canada, June.
25 Krause, T., Andersson, G., Frohlich, K. and Vaccaro, A. (2011), "Multiple-energy carriers: Modeling of production, delivery, and consumption", Proc. IEEE, 99(1), 15-27. https://doi.org/10.1109/JPROC.2010.2083610.   DOI
26 Lotfi, H. and Khodaei, A. (2016), "An efficient preprocessing approach for uncertainty consideration in microgrids", Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference, Dallas, Texas, U.S.A., May.
27 Bahramirad, S., Reder, W. and Khodaei, A. (2012), "Reliability-constrained optimal sizing of energy storage system in a microgrid", IEEE T. Smart Grid, 3(4), 2056-2062. https://doi.org/10.1109/TSG.2012.2217991.   DOI
28 Adamek, F., Arnold, M. and Andersson, G. (2014), "On decisive storage parameters for minimizing energy supply costs in multi-carrier energy systems", IEEE T. Sustain. Energy, 5(1), 102-109. https://doi.org/10.1109/TSTE.2013.2267235.   DOI
29 Albadi, M.H. and El-Saadany, E.F. (2008), "A summary of demand response in electricity markets", Electric Power Syst. Res., 78(11), 1989-1996. https://doi.org/10.1016/j.epsr.2008.04.002.   DOI
30 Arun, S.L. and Selvan, M.P. (2019), "Smart residential energy management system for demand response in buildings with energy storage devices", Front. Energy, 13(4), 715-730. https://doi.org/10.1007/s11708-018-0538-2.   DOI
31 Bourbour, S. (2016), "Development of a Self-Healing strategy for future smart microgrids", Master Thesis, Murdoch University, Murdoch, Australia.
32 Cai, N., Nga, N.T.T. and Mitra, J. (2012), "Economic dispatch in microgrids using multi-agent system", Proceedings of the 2012 North American Power Symposium, Champaign, Illinois, U.S.A., September.
33 Zhang, Q., Mclellan, B.C., Tezuka, T. and Ishihara, K.N. (2012), "Economic and environmental analysis of power generation expansion in Japan considering Fukushima nuclear accident using a multi-objective optimization model", Energy, 44(1), 986-995. https://doi.org/10.1016/j.energy.2012.04.051.   DOI
34 Zheng, Q.P., Wang, J. and Liu, A.L. (2015), "Stochastic optimization for unit commitment - A review", IEEE T. Power Syst., 30(4), 1913-1924. https://doi.org/10.1109/TPWRS.2014.2355204.   DOI
35 Zhao, B., Zhang, X., Chen, J., Wang, C. and Guo, L. (2013), "Operation optimization of standalone microgrids considering lifetime characteristics of battery energy storage system", IEEE T. Sustain. Energy, 4(4), 934-943. https://doi.org/10.1109/TSTE.2013.2248400.   DOI
36 Zheng, Q.P., Rebennack, S., Iliadis, N.A. and Pardalos, P.M. (2010), Optimization Models in the Natural Gas Industry, in Handbook of Power Systems I, Springer, Berlin, Heidelberg, Germany, 121-148.