Economic Scheduling of Microgrid Based on Energy Management and Demand Response
DOI:
https://doi.org/10.2478/ecce-2018-0012Keywords:
Augmented ɛ-constraint method, Economic and emission optimal scheduling, Demand response different programsAbstract
Currently, microgrids are regarded one of the main substations in distribution networks that generate electrical energy locally. The advantages of microgrids include easy management, optimization, and highly reliable supply. In this paper, the recommended model is based on economic and emission optimal scheduling in connection to the main grid mode; implementation model implies the short-term mode with optimal operation units and the use of real-time pricing (RTP) plan. In this study, a multi-objective function for operating costs and emission with the augmented ɛ-constraint method has been considered; fuzzy decision-making process has been employed to obtain the best solution. In addition, it has been considered that a microgrid has interruptible and shiftable loads that can participate in demand response programs. The presented results have been evaluated based on different demand response programs.References
H. Chamandoust, A. Hashemi, G. Derakhshan and B. Abdi, “Optimal Hybrid System Design Based on Renewable Energy Resources”, 2017 Smart Grid Conference (SGC), Dec. 2017. https://doi.org/10.1109/SGC.2017.8308878
O. Veligorskyi, O. Husev, V. Shevchenko, K. Tytelmaier, R. Yershov, R. Kosenko, and D. Vinnikov, “A Novel Hysteresis Power Point Optimizer for Distributed Solar Power Generation”, Electrical, Control and Communication Engineering, vol. 14, no. 1, pp. 12–22, 2018. https://doi.org/10.2478/ecce-2018-0002
L. Sigrist et al., “Island Power Systems”, CRC Press, 2016. https://doi.org/10.1201/9781315368740
H. Sun et al., “Smarter Energy: from Smart Metering to the Smart Grid”, IET Digital Library, 2016.
P. Jokar, N. Arianpoo, and V. C. M. Leung, “Electricity Theft Detection in AMI Using Customers’ Consumption Patterns”, IEEE Trans. on Smart Grid, vol. 7, no. 1, pp. 216–226, 2015. https://doi.org/10.1109/TSG.2015.2425222
S. Wang, Z. Li, L. Wu, M. Shahidehpour and Z. Li, “New metrics for assessing the reliability and economics of microgrids in distribution system”, IEEE Trans. Power Syst., vol. 28, no. 3, pp. 2852–2861, 2013. https://doi.org/10.1109/TPWRS.2013.2249539
C. Marnay, and G. Venkataramanan, “Microgrids in the evolving electricity generation and delivery infrastructure,” Conf. 2006 IEEE Power Engineering Society General Meeting, pp. 1–5, Jun. 2006. https://doi.org/10.1109/PES.2006.1709529
T. Logenthiran, D. Srinivasan and A. Khambadkone, “Multi-agent system for energy resource scheduling of integrated microgrids in a distributed system,” Electric Power Systems Research, vol. 81, no. 1, pp. 138–148, 2011. https://doi.org/10.1016/j.epsr.2010.07.019
A. K. Basu, S. Chowdhury and S. P. Chowdhury, “Impact of strategic deployment of CHP-based DERs on microgrid reliability,” IEEE Trans. on Power Delivery, vol. 25, no. 3, pp. 1697–1705, 2010. https://doi.org/10.1109/TPWRD.2010.2047121
C. Chen, et al., “Smart Energy Management System for Optimal Microgrid Economic Operation”. IET Renewable Power Generation, vol. 5, no. 3, pp. 258–267, 2011. https://doi.org/10.1049/iet-rpg.2010.0052
H. A. Aalami, M. Parsa Moghaddam and G. R. Yousefi, “Demand response modeling considering interruptible/curtailable loads and capacity market programs,” Applied Energy, vol. 87, no. 1, pp. 243–250, 2010. https://doi.org/10.1016/j.apenergy.2009.05.041
S. Sen, S. Chanda, S. Sengupta and A. De, “Demand response governed swarm intelligent grid scheduling framework for social welfare,” International Journal of Electrical Power & Energy Systems, vol. 78, pp. 783–792, 2016. https://doi.org/10.1016/j.ijepes.2015.12.013
F. Shariatzadeh, P. Mandal and A. K. Srivastava, “Demand response for sustainable energy systems: A review, application and implementation strategy,” Renewable and Sustainable Energy Reviews, vol. 45, pp. 343–350, 2015. https://doi.org/10.1016/j.rser.2015.01.062
S. Buryk, D. Mead, S. Mourato and J. Torriti, “Investigating preferences for dynamic electricity tariffs: The effect of environmental and system benefit disclosure,” Energy Policy, vol. 80, pp. 190–195, 2015. https://doi.org/10.1016/j.enpol.2015.01.030
M. Nazari-Heris, S. Abapour and B. Mohammadi-Ivatloo, “Optimal economic dispatch of FC-CHP based heat and power micro-grids”, Applied Thermal Engineering, vol. 114, pp. 756–769, 2017. https://doi.org/10.1016/j.applthermaleng.2016.12.016
G. Derakhshan, H. A. Shayanfar, and A. Kazemi, “The optimization of demand response programs in smart grids”, Energy Policy, vol. 94, no. 9, pp. 295–306, 2016. https://doi.org/10.1016/j.enpol.2016.04.009
G. R. Aghajani, H. A. Shayanfar, and H. Shayeghi, “Demand side management in a smart micro-grid in the presence of renewable generation and demand response”, Energy, vol. 126, pp. 622–637, 2017. https://doi.org/10.1016/j.energy.2017.03.051
G. S. Piperagkas, A. G. Anastasiadis, and N. D. Hatziargyriou, “Stochastic PSO-based heat and power dispatch under environmental constraints incorporating CHP and wind power units”, Electric Power Systems Research, vol. 81, no. 1, pp. 209–218, 2011. https://doi.org/10.1016/j.epsr.2010.08.009
L. Chunyang et al., “Economic scheduling model of microgrid considering the lifetime of batteries”, IET Generation, Transmission & Distribution. vol. 11, no. 3, 2017. https://doi.org/10.1049/iet-gtd.2016.0772
G. Cau, D. Cocco, M. Petrollese, S. K. Kaer, and C. Milan, “Energy management strategy based on short-term generation scheduling for a renewable microgrid using a hydrogen storage system”, Energy Conversion and Management, vol. 87, pp. 820–831, 2014. https://doi.org/10.1016/j.enconman.2014.07.078
G. Mavrotas, “Generation of efficient solutions in multiobjective mathematical programming problems using GAMS”. http://www.gams.com
G. Mavrotas, “Effective implementation of the e-constraint method in multiobjective mathematical programming problems”, Applied Mathematics and Computation, vol. 213, no. 2, pp. 455–465, 2009. https://doi.org/10.1016/j.amc.2009.03.037
R. Yu, W. Yang, and S. Rahardja, “A statistical demand-price model with its application in optimal real-time price,” IEEE Trans. Smart Grid, vol. 3, no. 4, pp. 1734–1742, 2012. https://doi.org/10.1109/TSG.2012.2217400
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