Distributed Optimal Control for Distribution Systems with Microgrids
DOI:
https://doi.org/10.17533/udea.redin.20211164Keywords:
Microgrids, Optimal power flow, Distributed optimisation, Consensus innovationAbstract
The growing consumption of electricity as well as the progressive development of new technologies implies that the power system is increasingly automated with the purpose of having a more efficient and economical operation. This development drives the system to a Smart Grid, a large-scale cyber-physical network covering different energy generation technologies, storage and communications enabling real-time information exchange and control. In this work, we present an optimal distributed control based on the consensus+innovation technique, where each agent of the network obtains information from its neighbours. Simulations on a microgrid system based on an IEEE 14-Bus reference system demonstrate the effectiveness of the approach. Convergence is observed in the microgrid system under different scenarios in the physical and communications network.
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Robert Lasseter, Abbas Akhil, Chris Marnay, John Stephens, Jeff Dagle, Ross Guttromson, A Sakis Meliopoulous, Robert Yinger, and Joe Eto. Consortium for Electric Reliability Technology Solutions White Paper on Integration of Distributed Energy Resources The CERTS MicroGrid Concept. Program, Transmission Reliability Systems, Energy Program, Integration Interest, Public Commission, California Energy, (April):1–29, 2002.
R.H. Lasseter. MicroGrids. 2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309),1:305–308, 2002.
R. H. Lasseter. Microgrids and Distributed Generation. Journal of Energy Engineering, 133(3):144–149, 2007.
J. A Pec¸as Lopes, C. L. Moreira, and A. G. Madureira. Defining control strategies for microgrids islanded operation. IEEE Transactions on Power Systems, 21(2):916–924, 2006.
M. A. Mahmud, M. J. Hossain, H. R. Pota, and N. K. Roy. Ro bust Nonlinear distributed controller design for maintaining power balance in Islanded microgrids. IEEE Power and Energy Society General Meeting, 2014-Octob(October):893–903, 2014.
Edris Pouresmaeil, Oriol Gomis-Bellmunt, Daniel Montesinos Miracle, and Joan Bergas-Jan´e. Multilevel converters control for renewable energy integration to the power grid. Energy, 36(2):950–963, feb 2011.
Walid Saad, Zhu Han, and H Vincent Poor. Game-theoretic methods for the smart grid. IEEE Signal Processing Magazine, 29(September):86–105, 2012.
Ramon Zamora and Anurag K. Srivastava. Controls for microgrids with storage: Review, challenges, and research needs. Renewable and Sustainable Energy Reviews, 14(7):2009–2018, 2010.
P. Piagi and R.H. Lasseter. Autonomous control of microgrids. 2006 IEEE Power Engineering Society General Meeting, (June):8pp., 2006.
Nikos Hatziargyriou, Hiroshi Asano, Reza Iravani, and Chris Marnay. Microgrids: an overview of ongoing research, development, and demonstration projects. IEEE Power and Energy Magazine, (July 2007):78–94, 2007.
Jong Yul Kim, Jin Hong Jeon, Seul Ki Kim, Changhee Cho, June Ho Park, Hak Man Kim, and Kee Young Nam. Cooperative control strategy of energy storage system and microsources for stabilizing the microgrid during islanded operation. IEEE Transactions on Power Electronics, 25(12):3037–3048, 2010.
Yixin Zhu, Fang Zhuo, Feng Wang, Baoquan Liu, Ruifeng Gou, and Yangjie Zhao. A virtual impedance optimization method for reactive power sharing in networked microgrid. IEEE Transactions on Power Electronics, 31(4):2890–2904, 2016.
Tianguang Lv and Qian Ai. Interactive energy management of networked microgrids-based active distribution system considering large-scale integration of renewable energy resources. Applied Energy, 163:408–422, 2016.
Mosaddek Tushar and Chadi Assi. Optimal Energy Management and Marginal Cost Electricity Pricing in Microgrid Network. IEEE Transactions on Industrial Informatics, 3203(c):1–13, 2017.
W. A. Cronje, I. W. Hofsajer, M. Shuma-Iwisi, and J. I. Braid. Design considerations for rural modular microgrids. In 2012 IEEE International Energy Conference and Exhibition, ENERGYCON 2012, pages 743–748, 2012.
Luis I. Minchala-Avila, Luis E. Garza-Castañón, Adriana Vargas-Mart´ínez, and Youmin Zhang. A review of optimal control techniques applied to the energy management and control of microgrids. In Procedia Computer Science, volume 52, pages 780–787. Elsevier, 2015.
Morad Mohamed Abdelmageed Abdelaziz, Hany E. Farag, and Ehab F. El-Saadany. Optimum Reconfiguration of Droop-Controlled Islanded Microgrids. IEEE Transactions on Power Systems, 31(3):2144–2153, 2016.
Alessandra Parisio and Luigi Glielmo. Energy efficient microgrid management using Model Predictive Control. IEEE Conference on Decision and Control and European Control Conference, pages 5449–5454, 2011.
Julian Barreiro-Gomez, German Obando, and Nicanor Quijano. Distributed Population Dynamics: Optimization and Control Applications. IEEE Transactions on Systems, Man, and Cybernetics: Systems, pages 1–11, 2016.
Nicanor Quijano, Carlos Ocampo-Martinez, and Julian Barreiro-Gomez. Constrained Distributed Optimization Based on Population Dynamics. IEEE Conference on Decision and Control, 2014(1):4260–4265, 2014.
Aftab Ahmad Khan, Muhammad Naeem, Muhammad Iqbal, Saad Qaisar, and Alagan Anpalagan. A compendium of optimization objectives, constraints, tools and algorithms for energy management in microgrids. Renewable and Sustainable Energy Reviews, 58:1664–1683, 2016.
S. Kar, J. M. F. Moura, and K. Ramanan. Distributed parameter estimation in sensor networks: Nonlinear observation models and imperfect communication. IEEE Transactions on Information Theory, 58(6):3575–3605, 2012.
Amin Kargarian, Javad Mohammadi, Junyao Guo, Sambuddha Chakrabarti, Masoud Barati, Gabriela Hug, Soummya Kar, and Ross Baldick. Toward Distributed/Decentralized DC Optimal Power Flow Implementation in Future Electric Power Systems. IEEE Transactions on Smart Grid, 9(4):2574–2594, 2018.
Ali Abur and A. G. Exposito. Power System State Estimation: Theory and Implementation. 2004.
Lucio Florez and Alfonso Baron. Introducci´on al an´alisis de sistemas de potencia, volume I. 1993.
Daniel K. Molzahn, Florian D¨orfler, Henrik Sandberg, Steven H. Low, Sambuddha Chakrabarti, Ross Baldick, and Javad Lavaei. A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems. IEEE Transactions on Smart Grid, 8(6):2941–2962, 2017.
Saadat Hadi. Power System Analysis, volume 130. 1999.
Li Guo, Nan Wang, Hai Lu, Xialin Li, and Chengshan Wang. Multi-objective optimal planning of the stand-alone microgrid system based on different benefit subjects. Energy, 116, Part:353–363, 2016.
Evelyn Martin Landsdowne Beale. Introduction to optimization. 1988.
Gabriela Hug, Soummya Kar, and Chenye Wu. Consensus + Innovations Approach for Distributed Multiagent Coordination in a Microgrid. IEEE Transactions on Smart Grid, 6(4):1893–1903, 2015.
Javad Mohammadi, Soummya Kar, and Gabriela Hug. Distributed Approach for DC Optimal Power Flow Calculations. pages 1–11, 2014.
Soummya Kar and Jose´ M.F. Moura. Consensus + innovations distributed inference over networks: Cooperation and sensing in networked systems. IEEE Signal Processing Magazine, 30(3):99–109, 2013.
Soummya Kar, Jose´ M.F. Moura, and Kavita Ramanan. Distributed parameter estimation in sensor networks: Nonlinear observation models and imperfect communication, volume 58. 2012.
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