Plug-and-play robust voltage control of DC microgrids

The purpose of this paper is to explore the applicability of linear time-invariant dynamical systems with polytopic uncertainty for modeling and control of islanded dc microgrids under plug-and-play (PnP) functionality of distributed generations (DGs). We develop a robust decentralized voltage control framework to ensure robust stability and reliable operation for islanded dc microgrids. The problem of voltage control of islanded dc microgrids with PnP operation of DGs is formulated as a convex optimization problem with structural constraints on some decision variables. The proposed control scheme offers several advantages including decentralized voltage control with no communication link, transient stability/performance, PnP capability, scalability of design, applicability to microgrids with general topology, and robustness to microgrid uncertainties. The effectiveness of the proposed control approach is evaluated through simulation studies carried out in MATLAB/SimPowerSystems Toolbox

Bidirectional vehicle-to-grid interface under a microgrid project

In the emergent deployment of smart grids, storage systems play an important role into assets utilization optimization, providing backup power and peak-shaving. This concept becomes more critical in the context of microgrids with a high penetration of renewable energy resources. Plug-in electric vehicles provide an enormous distributed storage capability, which favours the technical and economical exploitation of such systems. This paper presents a comprehensive implementation and control of a bidirectional power converter for vehicle-to-grid integration, based on a bidirectional DC/DC converter followed by a full bridge DC/AC converter.info:eu-repo/semantics/publishedVersio

Improving the Sustainability of Self-Consumption with Cooperative DC Microgrids

[EN] The development of microgrids is of great interest to facilitate the integration of distributed generation in electricity networks, improving the sustainability of energy production. Microgrids in DC (DC-MG) provide advantages for the use of some types of renewable generation and energy storage systems, such as batteries. In this article, a possible practical implementation of an isolated DC-MG for residential use with a cooperative operation of the different nodes is proposed. The main criterion is to achieve a very simple design with only primary control in a residential area. This application achieves a simple system, with low implementation costs, in which each user has autonomy but benefits from the support of the other users connected to the microgrid, which improves its reliability. The description of the elements necessary to create this cooperative system is one of the contributions of the work. Another important contribution is the analysis of the operation of the microgrid as a whole, where each node can be, arbitrarily, a consumer or an energy generator. The proposed structures could promote the use of small distributed generation and energy storage systems as the basis for a new paradigm of a more sustainable electricity grid of the future.This work has been partially supported by funds for research support of the Universitat Politècnica de ValènciaRoldán-Porta, C.; Roldán-Blay, C.; Escrivá-Escrivá, G.; Quiles Cucarella, E. (2019). Improving the Sustainability of Self-Consumption with Cooperative DC Microgrids. Sustainability. 11(19):1-22. https://doi.org/10.3390/su11195472S1221119Justo, J. J., Mwasilu, F., Lee, J., & Jung, J.-W. (2013). AC-microgrids versus DC-microgrids with distributed energy resources: A review. Renewable and Sustainable Energy Reviews, 24, 387-405. doi:10.1016/j.rser.2013.03.067Farhangi, H. (2010). The path of the smart grid. 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IEEE Transactions on Power Delivery, 24(3), 1045-1053. doi:10.1109/tpwrd.2009.2016622Shuai, Z., Fang, J., Ning, F., & Shen, Z. J. (2018). Hierarchical structure and bus voltage control of DC microgrid. Renewable and Sustainable Energy Reviews, 82, 3670-3682. doi:10.1016/j.rser.2017.10.096Van den Broeck, G., Stuyts, J., & Driesen, J. (2018). A critical review of power quality standards and definitions applied to DC microgrids. Applied Energy, 229, 281-288. doi:10.1016/j.apenergy.2018.07.058Anand, S., Fernandes, B. G., & Guerrero, J. (2013). Distributed Control to Ensure Proportional Load Sharing and Improve Voltage Regulation in Low-Voltage DC Microgrids. IEEE Transactions on Power Electronics, 28(4), 1900-1913. doi:10.1109/tpel.2012.2215055Radwan, A. A. A., & Mohamed, Y. A.-R. I. (2012). Linear Active Stabilization of Converter-Dominated DC Microgrids. IEEE Transactions on Smart Grid, 3(1), 203-216. doi:10.1109/tsg.2011.2162430Che, Y., Zhou, J., Lin, T., Li, W., & Xu, J. (2018). A Simplified Control Method for Tie-Line Power of DC Micro-Grid. Energies, 11(4), 933. doi:10.3390/en11040933Huang, Y., Yang, L., Liu, S., & Wang, G. (2018). Cooperation between Two Micro-Grids Considering Power Exchange: An Optimal Sizing Approach Based on Collaborative Operation. Sustainability, 10(11), 4198. doi:10.3390/su10114198González, A., Riba, J.-R., & Rius, A. (2015). Optimal Sizing of a Hybrid Grid-Connected Photovoltaic–Wind–Biomass Power System. Sustainability, 7(9), 12787-12806. doi:10.3390/su70912787Maleki, A., Rosen, M., & Pourfayaz, F. (2017). Optimal Operation of a Grid-Connected Hybrid Renewable Energy System for Residential Applications. Sustainability, 9(8), 1314. doi:10.3390/su9081314Roldán-Blay, C., Escrivá-Escrivá, G., & Roldán-Porta, C. (2019). Improving the benefits of demand response participation in facilities with distributed energy resources. Energy, 169, 710-718. doi:10.1016/j.energy.2018.12.102Mao, M., Jin, P., Chang, L., & Xu, H. (2014). Economic Analysis and Optimal Design on Microgrids With SS-PVs for Industries. IEEE Transactions on Sustainable Energy, 5(4), 1328-1336. doi:10.1109/tste.2014.2327067Elrayyah, A., Cingoz, F., & Sozer, Y. (2015). Construction of Nonlinear Droop Relations to Optimize Islanded Microgrid Operation. IEEE Transactions on Industry Applications, 51(4), 3404-3413. doi:10.1109/tia.2014.2387484Meng, L., Shafiee, Q., Ferrari Trecate, G., Karimi, H., Fulwani, D., Lu, X., & Guerrero, J. M. (2017). Review on Control of DC Microgrids. IEEE Journal of Emerging and Selected Topics in Power Electronics, 1-1. doi:10.1109/jestpe.2017.2690219Huang, H.-H., Hsieh, C.-Y., Liao, J.-Y., & Chen, K.-H. (2011). Adaptive Droop Resistance Technique for Adaptive Voltage Positioning in Boost DC–DC Converters. IEEE Transactions on Power Electronics, 26(7), 1920-1932. doi:10.1109/tpel.2010.2095508Nasirian, V., Moayedi, S., Davoudi, A., & Lewis, F. L. (2015). Distributed Cooperative Control of DC Microgrids. IEEE Transactions on Power Electronics, 30(4), 2288-2303. doi:10.1109/tpel.2014.2324579Wang, P., Lu, X., Yang, X., Wang, W., & Xu, D. (2016). An Improved Distributed Secondary Control Method for DC Microgrids With Enhanced Dynamic Current Sharing Performance. IEEE Transactions on Power Electronics, 31(9), 6658-6673. doi:10.1109/tpel.2015.2499310Ma, J., Yuan, L., Zhao, Z., & He, F. (2017). Transmission Loss Optimization-Based Optimal Power Flow Strategy by Hierarchical Control for DC Microgrids. IEEE Transactions on Power Electronics, 32(3), 1952-1963. doi:10.1109/tpel.2016.2561301Ren, L., Qin, Y., Li, Y., Zhang, P., Wang, B., Luh, P. B., … Gong, T. (2018). Enabling resilient distributed power sharing in networked microgrids through software defined networking. Applied Energy, 210, 1251-1265. doi:10.1016/j.apenergy.2017.06.006Liang Che, & Shahidehpour, M. (2014). DC Microgrids: Economic Operation and Enhancement of Resilience by Hierarchical Control. IEEE Transactions on Smart Grid, 5(5), 2517-2526. doi:10.1109/tsg.2014.2344024Lasseter, R. H. (2011). Smart Distribution: Coupled Microgrids. Proceedings of the IEEE, 99(6), 1074-1082. doi:10.1109/jproc.2011.2114630Wang, H., & Huang, J. (2018). Incentivizing Energy Trading for Interconnected Microgrids. IEEE Transactions on Smart Grid, 9(4), 2647-2657. doi:10.1109/tsg.2016.2614988Wang, H., & Huang, J. (2016). Cooperative Planning of Renewable Generations for Interconnected Microgrids. IEEE Transactions on Smart Grid, 7(5), 2486-2496. doi:10.1109/tsg.2016.2552642Kasaei, M. J., Gandomkar, M., & Nikoukar, J. (2017). Optimal management of renewable energy sources by virtual power plant. Renewable Energy, 114, 1180-1188. doi:10.1016/j.renene.2017.08.010Gao, Y., Cheng, H., Zhu, J., Liang, H., & Li, P. (2016). The Optimal Dispatch of a Power System Containing Virtual Power Plants under Fog and Haze Weather. Sustainability, 8(1), 71. doi:10.3390/su8010071Khan, Z. A., & Jayaweera, D. (2017). 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Real-Time Coordination of Plug-In Electric Vehicle Charging in Smart Grids to Minimize Power Losses and Improve Voltage Profile. IEEE Transactions on Smart Grid, 2(3), 456-467. doi:10.1109/tsg.2011.2159816Olivares, D. E., Mehrizi-Sani, A., Etemadi, A. H., Canizares, C. A., Iravani, R., Kazerani, M., … Hatziargyriou, N. D. (2014). Trends in Microgrid Control. IEEE Transactions on Smart Grid, 5(4), 1905-1919. doi:10.1109/tsg.2013.229551

An overview of AC and DC microgrid energy management systems

In 2022, the global electricity consumption was 4,027 billion kWh, steadily increasing over the previous fifty years. Microgrids are required to integrate distributed energy sources (DES) into the utility power grid. They support renewable and nonrenewable distributed generation technologies and provide alternating current (AC) and direct current (DC) power through separate power connections. This paper presents a unified energy management system (EMS) paradigm with protection and control mechanisms, reactive power compensation, and frequency regulation for AC/DC microgrids. Microgrids link local loads to geographically dispersed power sources, allowing them to operate with or without the utility grid. Between 2021 and 2028, the expansion of the world's leading manufacturers will be driven by their commitment to technological advancements, infrastructure improvements, and a stable and secure global power supply. This article discusses iterative, linear, mixed integer linear, stochastic, and predictive microgrid EMS programming techniques. Iterative algorithms minimize the footprints of standalone systems, whereas linear programming optimizes energy management in freestanding hybrid systems with photovoltaic (PV). Mixed-integers linear programming (MILP) is useful for energy management modeling. Management of microgrid energy employs stochastic and robust optimization. Control and predictive modeling (MPC) generates energy management plans for microgrids. Future microgrids may use several AC/DC voltage standards to reduce power conversion stages and improve efficiency. Research into EMS interaction may be intriguing

Experimental Study of a Centralized Control Strategy of a DC Microgrid Working in Grid Connected Mode

[EN] The results concerning the integration of a set of power management strategies and serial communications for the efficient coordination of the power converters composing an experimental DC microgrid is presented. The DC microgrid operates in grid connected mode by means of an interlinking converter. The overall control is carried out by means of a centralized microgrid controller implemented on a Texas Instruments TMS320F28335 DSP. The main objectives of the applied control strategies are to ensure the extract/inject power limits established by the grid operator as well as the renewable generation limits if it is required; to devise a realistic charging procedure of the energy storage batteries as a function of the microgrid status; to manage sudden changes of the available power from the photovoltaic energy sources, of the load power demand and of the power references established by the central controller; and to implement a load shedding functionality. The experimental results demonstrate that the proposed power management methodology allows the control of the power dispatch inside the DC microgrid properly.This work has been cofinanced by the Spanish Ministry of Economy and Competitiveness (MINECO) and by the European Regional Development Fund (ERDF) under Grant ENE2015-64087-C2-2.Salas-Puente, RA.; Marzal-Romeu, S.; González-Medina, R.; Figueres Amorós, E.; Garcerá, G. (2017). Experimental Study of a Centralized Control Strategy of a DC Microgrid Working in Grid Connected Mode. Energies. 10(10):1-25. https://doi.org/10.3390/en10101627S1251010Baek, J., Choi, W., & Chae, S. (2017). Distributed Control Strategy for Autonomous Operation of Hybrid AC/DC Microgrid. Energies, 10(3), 373. doi:10.3390/en10030373Patrao, I., Figueres, E., Garcerá, G., & González-Medina, R. (2015). Microgrid architectures for low voltage distributed generation. Renewable and Sustainable Energy Reviews, 43, 415-424. doi:10.1016/j.rser.2014.11.054Ma, T., Yahoui, H., Vu, H., Siauve, N., & Morel, H. (2017). A Control Strategy of DC Building Microgrid Connected to the Neighborhood and AC Power Network. Buildings, 7(4), 42. doi:10.3390/buildings7020042Lin, P., Wang, P., Xiao, J., Wang, J., Jin, C., & Tang, Y. (2018). An Integral Droop for Transient Power Allocation and Output Impedance Shaping of Hybrid Energy Storage System in DC Microgrid. IEEE Transactions on Power Electronics, 33(7), 6262-6277. doi:10.1109/tpel.2017.2741262Kakigano, H., Miura, Y., & Ise, T. (2010). Low-Voltage Bipolar-Type DC Microgrid for Super High Quality Distribution. IEEE Transactions on Power Electronics, 25(12), 3066-3075. doi:10.1109/tpel.2010.2077682Salomonsson, D., Soder, L., & Sannino, A. (2008). An Adaptive Control System for a DC Microgrid for Data Centers. IEEE Transactions on Industry Applications, 44(6), 1910-1917. doi:10.1109/tia.2008.2006398Xu, L., & Chen, D. (2011). Control and Operation of a DC Microgrid With Variable Generation and Energy Storage. IEEE Transactions on Power Delivery, 26(4), 2513-2522. doi:10.1109/tpwrd.2011.2158456Nejabatkhah, F., & Li, Y. W. (2015). Overview of Power Management Strategies of Hybrid AC/DC Microgrid. IEEE Transactions on Power Electronics, 30(12), 7072-7089. doi:10.1109/tpel.2014.2384999Lu, X., Guerrero, J. M., Sun, K., & Vasquez, J. C. (2014). An Improved Droop Control Method for DC Microgrids Based on Low Bandwidth Communication With DC Bus Voltage Restoration and Enhanced Current Sharing Accuracy. IEEE Transactions on Power Electronics, 29(4), 1800-1812. doi:10.1109/tpel.2013.2266419Chen, D., & Xu, L. (2012). Autonomous DC Voltage Control of a DC Microgrid With Multiple Slack Terminals. IEEE Transactions on Power Systems, 27(4), 1897-1905. doi:10.1109/tpwrs.2012.2189441Guerrero, J. M., Vasquez, J. C., Matas, J., de Vicuna, L. G., & Castilla, M. (2011). Hierarchical Control of Droop-Controlled AC and DC Microgrids—A General Approach Toward Standardization. IEEE Transactions on Industrial Electronics, 58(1), 158-172. doi:10.1109/tie.2010.2066534Vasquez, J., Guerrero, J., Miret, J., Castilla, M., & Garcia de Vicuna, L. (2010). Hierarchical Control of Intelligent Microgrids. IEEE Industrial Electronics Magazine, 4(4), 23-29. doi:10.1109/mie.2010.938720Unamuno, E., & Barrena, J. A. (2015). Hybrid ac/dc microgrids—Part II: Review and classification of control strategies. Renewable and Sustainable Energy Reviews, 52, 1123-1134. doi:10.1016/j.rser.2015.07.186Feng, X., Shekhar, A., Yang, F., E. Hebner, R., & Bauer, P. (2017). Comparison of Hierarchical Control and Distributed Control for Microgrid. Electric Power Components and Systems, 45(10), 1043-1056. doi:10.1080/15325008.2017.1318982Kaur, A., Kaushal, J., & Basak, P. (2016). A review on microgrid central controller. Renewable and Sustainable Energy Reviews, 55, 338-345. doi:10.1016/j.rser.2015.10.141Wu, D., Tang, F., Dragicevic, T., Guerrero, J. M., & Vasquez, J. C. (2015). Coordinated Control Based on Bus-Signaling and Virtual Inertia for Islanded DC Microgrids. IEEE Transactions on Smart Grid, 6(6), 2627-2638. doi:10.1109/tsg.2014.2387357Shi, D., Chen, X., Wang, Z., Zhang, X., Yu, Z., Wang, X., & Bian, D. (2018). A Distributed Cooperative Control Framework for Synchronized Reconnection of a Multi-Bus Microgrid. IEEE Transactions on Smart Grid, 9(6), 6646-6655. doi:10.1109/tsg.2017.2717806Dou, C., Zhang, Z., Yue, D., & Zheng, Y. (2017). MAS-Based Hierarchical Distributed Coordinate Control Strategy of Virtual Power Source Voltage in Low-Voltage Microgrid. IEEE Access, 5, 11381-11390. doi:10.1109/access.2017.2717493Bracale, A., Caramia, P., Carpinelli, G., Mancini, E., & Mottola, F. (2015). Optimal control strategy of a DC micro grid. International Journal of Electrical Power & Energy Systems, 67, 25-38. doi:10.1016/j.ijepes.2014.11.003Yue, J., Hu, Z., Li, C., Vasquez, J. C., & Guerrero, J. M. (2017). Economic Power Schedule and Transactive Energy through an Intelligent Centralized Energy Management System for a DC Residential Distribution System. Energies, 10(7), 916. doi:10.3390/en10070916Gao, L., Liu, Y., Ren, H., & Guerrero, J. (2017). A DC Microgrid Coordinated Control Strategy Based on Integrator Current-Sharing. Energies, 10(8), 1116. doi:10.3390/en10081116Operating Instructions Valve Regulated Stationary Lead-Acid Batterieshttp://www.hoppecke-us.com/tl_files/hoppecke/Documents/HO-US/Operating_Instructions_sealed_stationary_lead_acid_batteries_en1111.pdfTAB Batterieshttp://www.tabspain.com/wp-content/uploads/informacion-tecnica/renovables/curvas-y-tablas/din-41773-y-din-41774-para-baterias-pzs.pdfZhao, J., & Dörfler, F. (2015). Distributed control and optimization in DC microgrids. 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Mixed-integer-linear-programming-based energy management system for hybrid PV-wind-battery microgrids: Modeling, design, and experimental verification

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksMicrogrids are energy systems that aggregate distributed energy resources, loads, and power electronics devices in a stable and balanced way. They rely on energy management systems to schedule optimally the distributed energy resources. Conventionally, many scheduling problems have been solved by using complex algorithms that, even so, do not consider the operation of the distributed energy resources. This paper presents the modeling and design of a modular energy management system and its integration to a grid-connected battery-based microgrid. The scheduling model is a power generation-side strategy, defined as a general mixed-integer linear programming by taking into account two stages for proper charging of the storage units. This model is considered as a deterministic problem that aims to minimize operating costs and promote self-consumption based on 24-hour ahead forecast data. The operation of the microgrid is complemented with a supervisory control stage that compensates any mismatch between the offline scheduling process and the real time microgrid operation. The proposal has been tested experimentally in a hybrid microgrid at the Microgrid Research Laboratory, Aalborg University.Peer ReviewedPostprint (author's final draft

A review of microgrid development in the United States – A decade of progress on policies, demonstrations, controls, and software tools

Microgrids have become increasingly popular in the United States. Supported by favorable federal and local policies, microgrid projects can provide greater energy stability and resilience within a project site or community. This paper reviews major federal, state, and utility-level policies driving microgrid development in the United States. Representative U.S. demonstration projects are selected and their technical characteristics and non-technical features are introduced. The paper discusses trends in the technology development of microgrid systems as well as microgrid control methods and interactions within the electricity market. Software tools for microgrid design, planning, and performance analysis are illustrated with each tool's core capability. Finally, the paper summarizes the successes and lessons learned during the recent expansion of the U.S. microgrid industry that may serve as a reference for other countries developing their own microgrid industries