A novel mechanical analogy based battery model for SoC estimation using a multi-cell EKF

The future evolution of technological systems dedicated to improve energy efficiency will strongly depend on effective and reliable Energy Storage Systems, as key components for Smart Grids, microgrids and electric mobility. Besides possible improvements in chemical materials and cells design, the Battery Management System is the most important electronic device that improves the reliability of a battery pack. In fact, a precise State of Charge (SoC) estimation allows the energy flows controller to exploit better the full capacity of each cell. In this paper, we propose an alternative definition for the SoC, explaining the rationales by a mechanical analogy. We introduce a novel cell model, conceived as a series of three electric dipoles, together with a procedure for parameters estimation relying only on voltage measures and a given current profile. The three dipoles represent the quasi-stationary, the dynamics and the istantaneous components of voltage measures. An Extended Kalman Filer (EKF) is adopted as a nonlinear state estimator. Moreover, we propose a multi-cell EKF system based on a round-robin approach to allow the same processing block to keep track of many cells at the same time. Performance tests with a prototype battery pack composed by 18 A123 cells connected in series show encouraging results.Comment: 8 page, 12 figures, 1 tabl

The role of intelligent systems in delivering the smart grid

The development of "smart" or "intelligent" energy networks has been proposed by both EPRI's IntelliGrid initiative and the European SmartGrids Technology Platform as a key step in meeting our future energy needs. A central challenge in delivering the energy networks of the future is the judicious selection and development of an appropriate set of technologies and techniques which will form "a toolbox of proven technical solutions". This paper considers functionality required to deliver key parts of the Smart Grid vision of future energy networks. The role of intelligent systems in providing these networks with the requisite decision-making functionality is discussed. In addition to that functionality, the paper considers the role of intelligent systems, in particular multi-agent systems, in providing flexible and extensible architectures for deploying intelligence within the Smart Grid. Beyond exploiting intelligent systems as architectural elements of the Smart Grid, with the purpose of meeting a set of engineering requirements, the role of intelligent systems as a tool for understanding what those requirements are in the first instance, is also briefly discussed

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. Automatica, 61, 18-26. doi:10.1016/j.automatica.2015.07.015Eghtedarpour, N., & Farjah, E. (2014). Power Control and Management in a Hybrid AC/DC Microgrid. IEEE Transactions on Smart Grid, 5(3), 1494-1505. doi:10.1109/tsg.2013.2294275Installation, Commissioning and Operation Handbook for Gel-Vrla-Batterieshttp://www.sonnenschein.org/PDF%20files/GelHandbookPart2.pdfAlLee, G., & Tschudi, W. (2012). Edison Redux: 380 Vdc Brings Reliability and Efficiency to Sustainable Data Centers. IEEE Power and Energy Magazine, 10(6), 50-59. doi:10.1109/mpe.2012.2212607Aryani, D., & Song, H. (2016). Coordination Control Strategy for AC/DC Hybrid Microgrids in Stand-Alone Mode. Energies, 9(6), 469. doi:10.3390/en9060469Dragicevic, T., Guerrero, J. M., Vasquez, J. C., & Skrlec, D. (2014). Supervisory Control of an Adaptive-Droop Regulated DC Microgrid With Battery Management Capability. IEEE Transactions on Power Electronics, 29(2), 695-706. doi:10.1109/tpel.2013.2257857Tian, Y., Li, D., Tian, J., & Xia, B. (2017). State of charge estimation of lithium-ion batteries using an optimal adaptive gain nonlinear observer. Electrochimica Acta, 225, 225-234. doi:10.1016/j.electacta.2016.12.119Standard for Interconnecting Distributed Resources with Electric Power Systemshttp://fglongatt.org/OLD/Archivos/Archivos/SistGD/IEEE1547.pd

Massive MIMO is a Reality -- What is Next? Five Promising Research Directions for Antenna Arrays

Massive MIMO (multiple-input multiple-output) is no longer a "wild" or "promising" concept for future cellular networks - in 2018 it became a reality. Base stations (BSs) with 64 fully digital transceiver chains were commercially deployed in several countries, the key ingredients of Massive MIMO have made it into the 5G standard, the signal processing methods required to achieve unprecedented spectral efficiency have been developed, and the limitation due to pilot contamination has been resolved. Even the development of fully digital Massive MIMO arrays for mmWave frequencies - once viewed prohibitively complicated and costly - is well underway. In a few years, Massive MIMO with fully digital transceivers will be a mainstream feature at both sub-6 GHz and mmWave frequencies. In this paper, we explain how the first chapter of the Massive MIMO research saga has come to an end, while the story has just begun. The coming wide-scale deployment of BSs with massive antenna arrays opens the door to a brand new world where spatial processing capabilities are omnipresent. In addition to mobile broadband services, the antennas can be used for other communication applications, such as low-power machine-type or ultra-reliable communications, as well as non-communication applications such as radar, sensing and positioning. We outline five new Massive MIMO related research directions: Extremely large aperture arrays, Holographic Massive MIMO, Six-dimensional positioning, Large-scale MIMO radar, and Intelligent Massive MIMO.Comment: 20 pages, 9 figures, submitted to Digital Signal Processin

Micro-to-macro: astrodynamics at extremes of lengths-scale

This paper investigates astrodynamics at extremes of length-scale, ranging from swarms of future `smart dust' devices to the capture and utilisation of small near Earth asteroids. At the smallest length-scales families of orbits are found which balance the energy gain from solar radiation pressure with energy dissipation due to air drag. This results in long orbit lifetimes for high area-to-mass ratio `smart dust' devices. High area-to-mass hybrid spacecraft, using both solar sail and electric propulsion, are then considered to enable `pole-sitter' orbits providing a polar-stationary vantage point for Earth observation. These spacecraft are also considered to enable displaced geostationary orbits. Finally, the potential material resource available from captured near Earth asteroids is considered which can underpin future large-scale space engineering ventures. The use of such material for geo-engineering is investigated using a cloud of unprocessed dust in the vicinity of the Earth-Sun $L_1$ point to fractionally reduce solar insolation