Bibliographic review of control systems for micro energy networks
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Published:
Nov 9, 2018
Keywords:
model predicitive control, energy management, micro-grids, cost function, hierarchical control
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Abstract
This article reviews the literature that focuses on determining the degree of importance of control systems for energy management in micro-networks. It describes the main reasons for the migration process from fossil fuel plants to industrial renewable energy plants, emphasizing some existing types of renewable energy. In addition, existing control techniques, including optimal and hierarchical control for micro-networks, are summarized. The leading technologies currently used to implement Model-Based Predictive Control (MPC) and Model-Based Predictive Economic Control (EMPC) are also outlined. In the latter, an analysis is made in economic terms as a function of cost.
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Bibliographic review of control systems for micro energy networks. (2018). MASKAY, 8(2), 60-66. https://doi.org/10.24133/maskay.v8i2.971
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How to Cite
Bibliographic review of control systems for micro energy networks. (2018). MASKAY, 8(2), 60-66. https://doi.org/10.24133/maskay.v8i2.971
References
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[2] J. Conti, P. Holtberg, J. Diefenderfer, A. LaRose, J. T. Turnure, and L. Westfall, International Energy Outlook 2016 With Projections to 2040, vol. 0484, no. May. 2016.
[3] L. G. G. Moncada, F. Asdrubali, and A. Rotili, “Influence of new fac tors on global energy prospects in the medium term: compar ison among the 2010, 2011 and 2012 editions of the IEA’s World Energy Outlook reports,” Econ. Policy Energy Environ., no. 3, pp. 67–89, 2013.
[4] A. Galkina, V. Kulagin, and I. Mironova, “Renewable Energy Sources : Global and Russian Outlook Up to 2040,” J. Technol. Innov. Renew. Energy, vol. 007, no. 499, pp. 185–194, 2014.
[5] P. H. Shaikh, N. B. M. Nor, P. Nallagownden, I. Elamvazuthi, and T. Ibrahim, “A review on optimized control systems for building energy and comfort management of smart sustainable buildings,” Renew. Sustain. Energy Rev., vol. 34, pp. 409–429, 2014.
[6] J. de Matos, F. e Silva, and L. Ribeiro, “Power Control in AC Isolated Microgrids with Renewable Energy Sources and Energy Storage Systems,” IEEE Trans. Ind. Electron., vol. 62, no. 6, pp. 1–1, 2014.
[7] C. Graves, S. D. Ebbesen, M. Mogensen, and K. S. Lackner, “Sustainable hydrocarbon fuels by recycling CO2and H2O with renewable or nuclear energy,” Renew. Sustain. Energy Rev., vol. 15, no. 1, pp. 1–23, 2011.
[8] A. Omri, N. Ben Mabrouk, and A. Sassi-Tmar, “Modeling the causal linkages between nuclear energy, renewable energy and economic growth in developed and developing countries,” Renew. Sustain. Energy Rev., vol. 42, pp. 1012–1022, 2015.
[9] P. G. Arul, V. K. Ramachandaramurthy, and R. K. Rajkumar, “Control strategies for a hybrid renewable energy system: A review,” Renew. Sustain. Energy Rev., vol. 42, pp. 597–608, 2015.
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[11] C. Diáz and D. Hernandez, “Smart Grid : Las TICs y la modernización de las redes de energía eléctrica – Estado del Arte,” Rev. Ssitemas y Telemat., vol. 9, pp. 53–81, 2011.
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[15] Y. L. Yin, Z. P. Song, Y. Li, R. Z. Wang, and X. Q. Zhai, “Experimental investigation of a mini-type solar absorption cooling system under different cooling modes,” Energy Build., vol. 47, pp. 131–138, 2012.
[16] H. F. Scherer, M. Pasamontes, J. L. Guzmán, J. D. Álvarez, E. Camponogara, and J. E. Normey-Rico, “Efficient building energy management using distributed model predictive control,” J. Process Control, vol. 24, no. 6, pp. 740–749, 2014.
[17] X. Wang, H. Teichgraeber, A. Palazoglu, and N. H. El-Farra, “An economic receding horizon optimization approach for energy management in the chlor-alkali process with hybrid renewable energy generation,” J. Process Control, vol. 24, no. 8, pp. 1318–1327, 2014.
[18] A. Parisio, E. Rikos, and L. Glielmo, “A Model Predictive Control Approach to Microgrid Operation Optimization,” IEEE Trans. Control Syst. Technol., vol. 22, no. 99, p. 1, 2014.
[19] G. Kyriakarakos, D. D. Piromalis, A. I. Dounis, K. G. Arvanitis, and G. Papadakis, “Intelligent demand side energy management system for autonomous polygeneration microgrids,” Appl. Energy, vol. 103, pp. 39–51, 2013.
[20] A. Parisio, E. Rikos, G. Tzamalis, and L. Glielmo, “Use of model predictive control for experimental microgrid optimization,” Appl. Energy, vol. 115, pp. 37–46, 2014.
[21] J. Patino, A. Marquez, and J. Espinosa, “An economic MPC approach for a micro grid energy management system,” in Transmission & Distribution Conference and Exposition - Latin America (PES T&D-LA), 2014 IEEE PES, 2014.
[22] R. Halvgaard, L. Vandenberghe, N. K. Poulsen, H. Madsen, and J. B. Jørgensen, “Distributed Model Predictive Control for Smart Energy Systems,” IEEE Trans. Smart Grid, vol. 7, no. 3, pp. 1675 – 1682, 2016.
[23] W. Analytics, “atehnium analytics,” 2013. [Online]. Available at: http://www.weatheranalytics.com/.
[24] V. Chandan and A. G. Alleyne, “Decentralized predictive thermal control for buildings,” J. Process Control, vol. 24, no. 6, pp. 820–835, 2014.
[25] L. Lao, M. Ellis, and P. D. Christofides, “Economic model predictive control of parabolic PDE systems: Addressing state estimation and computational efficiency,” J. Process Control, vol. 24, no. 4, pp. 448–462, 2014.
[26] A. Ferramosca, D. Limon, and E. F. Camacho, “Economic MPC for a changing economic criterion for linear systems,” IEEE Trans. Automat. Contr., vol. 59, no. 10, pp. 2657–2667, 2014.
[27] M. Heidarinejad, J. Liu, and P. D. Christofides, “Economic Model Predictive Control ofNonlinear Process Systems Using LyapunovTechniques,” AIChE J., vol. 58, no. 3, pp. 855–870, 2012.
[28] J. Piccardo and A. Prieto, “Vehículo Eléctrico de Producción Nacional,” Universidad de Buenos Aires, 2012.
[29] J. Arango, F. Sierra, and V. Silva, “Análisis exploratorio de investigaciones sobre los motores de combustión interna que trabajan con biogás,” Tecnura, vol. 18, no. 39, pp. 152–164, 2014.
[30] C. Clastres, “Smart grids: Another step towards competition, energy security and climate change objectives,” Energy Policy, vol. 39, no. 9, pp. 5399–5408, 2011.
[31] J. Gao, Y. Xiao, J. Liu, W. Liang, and C. L. P. Chen, “A survey of communication/networking in Smart Grids,” Futur. Gener. Comput. Syst., vol. 28, no. 2, pp. 391–404, 2012.
[32] H. Lund, A. N. Andersen, P. A. Østergaard, B. V. Mathiesen, and D. Connolly, “From electricity smart grids to smart energy systems - A market operation based approach and understanding,” Energy, vol. 42, no. 1, pp. 96–102, 2012.
[33] J. Ma, S. J. Qin, and T. Salsbury, “Application of economic MPC to the energy and demand minimization of a commercial building,” J. Process Control, vol. 24, no. 8, pp. 1282–1291, 2014.
[34] R. Amrit, J. B. Rawlings, and D. Angeli, “Economic optimization using model predictive control with a terminal cost,” Annu. Rev. Control, vol. 35, no. 2, pp. 178–186, 2011.
[35] S. Lucia, J. A. E. Andersson, H. Brandt, M. Diehl, and S. Engell, “Handling uncertainty in economic nonlinear model predictive control: A comparative case study,” J. Process Control, vol. 24, no. 8, pp. 1247–1259, 2014.
[36] C. N. Papadimitriou, E. I. Zountouridou, and N. D. Hatziargyriou, “Review of hierarchical control in DC microgrids,” Electr. Power Syst. Res., vol. 122, pp. 159–167, 2015.
[37] N. Jain, J. P. Koeln, S. Sundaram, and A. G. Alleyne, “Partially decentralized control of large-scale variable-refrigerant-flow systems in buildings,” J. Process Control, vol. 24, no. 6, pp. 798–819, 2014.
[38] Y. Huang, J. Lu, C. Liu, X. Xu, W. Wang, and X. Zhou, “Comparative study of power forecasting methods for PV stations,” 2010 Int. Conf. Power Syst. Technol., pp. 1–6, 2010.
[39] Z. Váňa, J. Cigler, J. Široký, E. Žáčeková, and L. Ferkl, “Model-based energy efficient control applied to an office building,” J. Process Control, vol. 24, no. 6, pp. 790–797, 2014.
[40] Y. Zong, L. Mihet-Popa, D. Kullmann, A. Thavlov, O. Gehrke, and H. W. Bindner, “Model predictive controller for active demand side management with PV self-consumption in an intelligent building,” IEEE PES Innov. Smart Grid Technol. Conf. Eur., pp. 1–8, 2012.
[41] C. R. Touretzky and M. Baldea, “Nonlinear model reduction and model predictive control of residential buildings with energy recovery,” J. Process Control, vol. 24, no. 6, pp. 723–739, 2014.
[42] W. J. Cole, D. P. Morton, and T. F. Edgar, “Optimal electricity rate structures for peak demand reduction using economic model predictive control,” J. Process Control, vol. 24, no. 8, pp. 1311–1317, 2014.
[43] D. I. Mendoza-Serrano and D. J. Chmielewski, “Smart grid coordination in building HVAC systems: EMPC and the impact of forecasting,” J. Process Control, vol. 24, no. 8, pp. 1301–1310, 2014.