7,798 research outputs found

    DC Microgrids – Part I:A Review of Control Strategies and Stabilization Techniques

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    SMC framework in motion control systems

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    Design of a motion control system should take into account both the unconstrained motion performed without interaction with environment or other system, and the constrained motion where system is in contact with environment or has certain functional interaction with another system. In this paper control systems design approach, based on siding mode methods, that allows selection of control for generic tasks as trajectory and/or force tracking as well as for systems that require maintain some functional relation like bilateral or multilateral systems, establisment of virtual relation among mobile robots or control of haptic systems is presented. It is shown that all basic motion control problems - trajectory tracking, force control, hybrid position/force control scheme and the impedance control - can be treated in the same way while avoiding the structural change of the controller and guarantying stable behavior of the system In order to show applicability of the proposed techniques simulation and experimental results for high precision systems in microsystems assembly tasks and bilateral control systems are presente

    Priority-driven self-optimizing power control scheme for interlinking converters of hybrid AC/DC microgrid clusters in decentralized manner

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    Hybrid AC/DC microgrid clusters are key building blocks of smart grid to support sustainable and resilient urban power systems. In microgrid clusters, the subgrid load-priorities and power quality requirements for different areas vary significantly. To realize optimal power exchanges among microgrid clusters, this paper proposes a decentralized self-optimizing power control scheme for interlinking converters (ILC) of hybrid microgrid clusters. A priority-driven optimal power exchange model of ILCs is built considering the priorities and capacities in subgrids. The optimization objective is to minimize the total DC-voltage/AC-frequency state deviations of subgrids. To realize the decentralized power flow control, an optimal-oriented quasi-droop control strategy of ILCs is introduced to not only achieve a flexible self-optimizing power flow management, but also provide an ancillary function of voltage support. Consequently, as each of ILCs only monitors the local AC-side frequency and DC-side voltage signals, the whole optimal power control of the wide-area microgrid clusters is achieved in a decentralized manner without any communication link. Thus, the proposed control algorithm has the features of decreased cost, increased scalability, reduced geographic restrictions and high resilience in terms of communication faults. Finally, the proposed method is validated by case studies with four interconnected microgrids through hardware-in-loop tests

    Autonomous Demand Side Management of Electric Vehicles

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    There is an error in the table of content, where publication A and B have swiched places.Demand-side management approaches that exploit the temporal flexibility of electric vehicles have attracted much attention in recent years due to the increasing market penetration. These demand-side management measures contribute to alleviating the burden on the power system, especially in distribution grids where bottlenecks are more prevalent. Electric vehicles can be defined as an attractive asset for distribution system operators, which have the potential to provide grid services if properly managed. In this thesis, first, a systematic investigation is conducted for two typically employed demand-side management methods reported in the literature: A voltage droop control-based approach and a market-driven approach. Then a control scheme of decentralized autonomous demand side management for electric vehicle charging scheduling which relies on a unidirectionally communicated grid-induced signal is proposed. In all the topics considered, the implications on the distribution grid operation are evaluated using a set of time series load flow simulations performed for representative Austrian distribution grids. Droop control mechanisms are discussed for electric vehicle charging control which requires no communication. The method provides an economically viable solution at all penetrations if electric vehicles charge at low nominal power rates. However, with the current market trends in residential charging equipment especially in the European context where most of the charging equipment is designed for 11 kW charging, the technical feasibility of the method, in the long run, is debatable. As electricity demand strongly correlates with energy prices, a linear optimization algorithm is proposed to minimize charging costs, which uses next-day market prices as the grid-induced incentive function under the assumption of perfect user predictions. The constraints on the state of charge guarantee the energy required for driving is delivered without failure. An average energy cost saving of 30% is realized at all penetrations. Nevertheless, the avalanche effect due to simultaneous charging during low price periods introduces new power peaks exceeding those of uncontrolled charging. This obstructs the grid-friendly integration of electric vehicles.publishedVersio

    Review on Multi-Objective Control Strategies for Distributed Generation on Inverter-Based Microgrids

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    [EN] Microgrids have emerged as a solution to address new challenges in power systems with the integration of distributed energy resources (DER). Inverter-based microgrids (IBMG) need to implement proper control systems to avoid stability and reliability issues. Thus, several researchers have introduced multi-objective control strategies for distributed generation on IBMG. This paper presents a review of the different approaches that have been proposed by several authors of multi-objective control. This work describes the main features of the inverter as a key component of microgrids. Details related to accomplishing efficient generation from a control systems' view have been observed. This study addresses the potential of multi-objective control to overcome conflicting objectives with balanced results. Finally, this paper shows future trends in control objectives and discussion of the different multi-objective approaches.Gonzales-Zurita, Ó.; Clairand, J.; Peñalvo-López, E.; Escrivá-Escrivá, G. (2020). Review on Multi-Objective Control Strategies for Distributed Generation on Inverter-Based Microgrids. Energies. 13(13):1-29. https://doi.org/10.3390/en13133483S1291313Ross, M., Abbey, C., Bouffard, F., & Joos, G. (2015). Multiobjective Optimization Dispatch for Microgrids With a High Penetration of Renewable Generation. IEEE Transactions on Sustainable Energy, 6(4), 1306-1314. doi:10.1109/tste.2015.2428676Murty, V. V. S. N., & Kumar, A. (2020). Multi-objective energy management in microgrids with hybrid energy sources and battery energy storage systems. Protection and Control of Modern Power Systems, 5(1). doi:10.1186/s41601-019-0147-zKatircioğlu, S., Abasiz, T., Sezer, S., & Katırcıoglu, S. (2019). 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Nonisolated High Gain DC–DC Converter for DC Microgrids. IEEE Transactions on Industrial Electronics, 65(2), 1205-1212. doi:10.1109/tie.2017.2733463Yin, C., Wu, H., Locment, F., & Sechilariu, M. (2017). Energy management of DC microgrid based on photovoltaic combined with diesel generator and supercapacitor. Energy Conversion and Management, 132, 14-27. doi:10.1016/j.enconman.2016.11.018Chen, D., Xu, Y., & Huang, A. Q. (2017). Integration of DC Microgrids as Virtual Synchronous Machines Into the AC Grid. IEEE Transactions on Industrial Electronics, 64(9), 7455-7466. doi:10.1109/tie.2017.2674621Abhinav, S., Schizas, I. D., Ferrese, F., & Davoudi, A. (2017). Optimization-Based AC Microgrid Synchronization. IEEE Transactions on Industrial Informatics, 13(5), 2339-2349. doi:10.1109/tii.2017.2702623Liu, Z., Su, M., Sun, Y., Li, L., Han, H., Zhang, X., & Zheng, M. (2019). Optimal criterion and global/sub-optimal control schemes of decentralized economical dispatch for AC microgrid. International Journal of Electrical Power & Energy Systems, 104, 38-42. doi:10.1016/j.ijepes.2018.06.045Khatibzadeh, A., Besmi, M., Mahabadi, A., & Reza Haghifam, M. (2017). Multi-Agent-Based Controller for Voltage Enhancement in AC/DC Hybrid Microgrid Using Energy Storages. Energies, 10(2), 169. doi:10.3390/en10020169Asghar, F., Talha, M., & Kim, S. (2017). Robust Frequency and Voltage Stability Control Strategy for Standalone AC/DC Hybrid Microgrid. Energies, 10(6), 760. doi:10.3390/en10060760Lotfi, H., & Khodaei, A. (2017). Hybrid AC/DC microgrid planning. Energy, 118, 37-46. doi:10.1016/j.energy.2016.12.015Kerdphol, T., Rahman, F., & Mitani, Y. (2018). Virtual Inertia Control Application to Enhance Frequency Stability of Interconnected Power Systems with High Renewable Energy Penetration. Energies, 11(4), 981. doi:10.3390/en11040981Rodrigues, Y. R., Zambroni de Souza, A. C., & Ribeiro, P. F. (2018). An inclusive methodology for Plug-in electrical vehicle operation with G2V and V2G in smart microgrid environments. International Journal of Electrical Power & Energy Systems, 102, 312-323. doi:10.1016/j.ijepes.2018.04.037Ghosh, S., & Chattopadhyay, S. (2020). Three-Loop-Based Universal Control Architecture for Decentralized Operation of Multiple Inverters in an Autonomous Grid-Interactive Microgrid. IEEE Transactions on Industry Applications, 56(2), 1966-1979. doi:10.1109/tia.2020.2964746Mohapatra, S. R., & Agarwal, V. (2020). Model Predictive Control for Flexible Reduction of Active Power Oscillation in Grid-Tied Multilevel Inverters Under Unbalanced and Distorted Microgrid Conditions. IEEE Transactions on Industry Applications, 56(2), 1107-1115. doi:10.1109/tia.2019.2957480Ziouani, I., Boukhetala, D., Darcherif, A.-M., Amghar, B., & El Abbassi, I. (2018). Hierarchical control for flexible microgrid based on three-phase voltage source inverters operated in parallel. International Journal of Electrical Power & Energy Systems, 95, 188-201. doi:10.1016/j.ijepes.2017.08.027Golshannavaz, S., & Mortezapour, V. (2018). A generalized droop control approach for islanded DC microgrids hosting parallel-connected DERs. Sustainable Cities and Society, 36, 237-245. doi:10.1016/j.scs.2017.09.038Safa, A., Madjid Berkouk, E. L., Messlem, Y., & Gouichiche, A. (2018). A robust control algorithm for a multifunctional grid tied inverter to enhance the power quality of a microgrid under unbalanced conditions. International Journal of Electrical Power & Energy Systems, 100, 253-264. doi:10.1016/j.ijepes.2018.02.042Andishgar, M. H., Gholipour, E., & Hooshmand, R. (2017). An overview of control approaches of inverter-based microgrids in islanding mode of operation. Renewable and Sustainable Energy Reviews, 80, 1043-1060. doi:10.1016/j.rser.2017.05.267Li, Z., Zang, C., Zeng, P., Yu, H., Li, S., & Bian, J. (2017). Control of a Grid-Forming Inverter Based on Sliding-Mode and Mixed H2/H{H_2}/{H_\infty } Control. IEEE Transactions on Industrial Electronics, 64(5), 3862-3872. doi:10.1109/tie.2016.2636798Hossain, M. A., Pota, H. R., Squartini, S., & Abdou, A. F. (2019). Modified PSO algorithm for real-time energy management in grid-connected microgrids. Renewable Energy, 136, 746-757. doi:10.1016/j.renene.2019.01.005Shokoohi, S., Golshannavaz, S., Khezri, R., & Bevrani, H. (2018). Intelligent secondary control in smart microgrids: an on-line approach for islanded operations. Optimization and Engineering, 19(4), 917-936. doi:10.1007/s11081-018-9382-9Safari, A., Babaei, F., & Farrokhifar, M. (2019). A load frequency control using a PSO-based ANN for micro-grids in the presence of electric vehicles. International Journal of Ambient Energy, 42(6), 688-700. doi:10.1080/01430750.2018.1563811Miveh, M. R., Rahmat, M. F., Ghadimi, A. A., & Mustafa, M. W. (2016). Control techniques for three-phase four-leg voltage source inverters in autonomous microgrids: A review. Renewable and Sustainable Energy Reviews, 54, 1592-1610. doi:10.1016/j.rser.2015.10.079Rokrok, E., Shafie-khah, M., & Catalão, J. P. S. (2018). Review of primary voltage and frequency control methods for inverter-based islanded microgrids with distributed generation. Renewable and Sustainable Energy Reviews, 82, 3225-3235. doi:10.1016/j.rser.2017.10.022Bouzid, A. M., Guerrero, J. M., Cheriti, A., Bouhamida, M., Sicard, P., & Benghanem, M. (2015). A survey on control of electric power distributed generation systems for microgrid applications. Renewable and Sustainable Energy Reviews, 44, 751-766. doi:10.1016/j.rser.2015.01.016Vásquez, V., Ortega, L. M., Romero, D., Ortega, R., Carranza, O., & Rodríguez, J. J. (2017). Comparison of methods for controllers design of single phase inverter operating in island mode in a microgrid: Review. Renewable and Sustainable Energy Reviews, 76, 256-267. doi:10.1016/j.rser.2017.03.060Shen, X., Wang, H., Li, J., Su, Q., & Gao, L. (2019). Distributed Secondary Voltage Control of Islanded Microgrids Based on RBF-Neural-Network Sliding-Mode Technique. IEEE Access, 7, 65616-65623. doi:10.1109/access.2019.2915509Arbab-Zavar, B., Palacios-Garcia, E., Vasquez, J., & Guerrero, J. (2019). Smart Inverters for Microgrid Applications: A Review. Energies, 12(5), 840. doi:10.3390/en12050840Bullich-Massagué, E., Díaz-González, F., Aragüés-Peñalba, M., Girbau-Llistuella, F., Olivella-Rosell, P., & Sumper, A. (2018). Microgrid clustering architectures. Applied Energy, 212, 340-361. doi:10.1016/j.apenergy.2017.12.048Kerdphol, T., Rahman, F., Mitani, Y., Hongesombut, K., & Küfeoğlu, S. (2017). Virtual Inertia Control-Based Model Predictive Control for Microgrid Frequency Stabilization Considering High Renewable Energy Integration. Sustainability, 9(5), 773. doi:10.3390/su9050773Hajiakbari Fini, M., & Hamedani Golshan, M. E. (2018). Determining optimal virtual inertia and frequency control parameters to preserve the frequency stability in islanded microgrids with high penetration of renewables. Electric Power Systems Research, 154, 13-22. doi:10.1016/j.epsr.2017.08.007Jung, J., & Villaran, M. (2017). Optimal planning and design of hybrid renewable energy systems for microgrids. Renewable and Sustainable Energy Reviews, 75, 180-191. doi:10.1016/j.rser.2016.10.061Baharizadeh, M., Karshenas, H. R., & Guerrero, J. M. (2018). An improved power control strategy for hybrid AC-DC microgrids. International Journal of Electrical Power & Energy Systems, 95, 364-373. doi:10.1016/j.ijepes.2017.08.036Serban, I., & Ion, C. P. (2017). Microgrid control based on a grid-forming inverter operating as virtual synchronous generator with enhanced dynamic response capability. International Journal of Electrical Power & Energy Systems, 89, 94-105. doi:10.1016/j.ijepes.2017.01.009Tavakoli, M., Shokridehaki, F., Marzband, M., Godina, R., & Pouresmaeil, E. (2018). A two stage hierarchical control approach for the optimal energy management in commercial building microgrids based on local wind power and PEVs. Sustainable Cities and Society, 41, 332-340. doi:10.1016/j.scs.2018.05.035Cagnano, A., De Tuglie, E., & Cicognani, L. (2017). Prince — Electrical Energy Systems Lab. Electric Power Systems Research, 148, 10-17. doi:10.1016/j.epsr.2017.03.011Zhang, H., Meng, W., Qi, J., Wang, X., & Zheng, W. X. (2019). Distributed Load Sharing Under False Data Injection Attack in an Inverter-Based Microgrid. IEEE Transactions on Industrial Electronics, 66(2), 1543-1551. doi:10.1109/tie.2018.2793241Yang, L., Hu, Z., Xie, S., Kong, S., & Lin, W. (2019). Adjustable virtual inertia control of supercapacitors in PV-based AC microgrid cluster. Electric Power Systems Research, 173, 71-85. doi:10.1016/j.epsr.2019.04.011Rahman, F. S., Kerdphol, T., Watanabe, M., & Mitani, Y. (2019). Optimization of virtual inertia considering system frequency protection scheme. Electric Power Systems Research, 170, 294-302. doi:10.1016/j.epsr.2019.01.025Farrokhabadi, M., Canizares, C. A., Simpson-Porco, J. W., Nasr, E., Fan, L., Mendoza-Araya, P. A., … Reilly, J. (2020). Microgrid Stability Definitions, Analysis, and Examples. IEEE Transactions on Power Systems, 35(1), 13-29. doi:10.1109/tpwrs.2019.2925703Yoldaş, Y., Önen, A., Muyeen, S. M., Vasilakos, A. V., & Alan, İ. (2017). Enhancing smart grid with microgrids: Challenges and opportunities. Renewable and Sustainable Energy Reviews, 72, 205-214. doi:10.1016/j.rser.2017.01.064Rajesh, K. S., Dash, S. S., Rajagopal, R., & Sridhar, R. (2017). A review on control of ac microgrid. 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Overview of Current Microgrid Policies, Incentives and Barriers in the European Union, United States and China. Sustainability, 9(7), 1146. doi:10.3390/su9071146Cui, Y., Geng, Z., Zhu, Q., & Han, Y. (2017). Review: Multi-objective optimization methods and application in energy saving. Energy, 125, 681-704. doi:10.1016/j.energy.2017.02.174Yazdi, F., & Hosseinian, S. H. (2019). A novel «Smart Branch» for power quality improvement in microgrids. International Journal of Electrical Power & Energy Systems, 110, 161-170. doi:10.1016/j.ijepes.2019.02.026Bassey, O., Butler-Purry, K. L., & Chen, B. (2020). Dynamic Modeling of Sequential Service Restoration in Islanded Single Master Microgrids. IEEE Transactions on Power Systems, 35(1), 202-214. doi:10.1109/tpwrs.2019.2929268Chang, E.-C. (2018). Study and Application of Intelligent Sliding Mode Control for Voltage Source Inverters. Energies, 11(10), 2544. doi:10.3390/en11102544Das, D., Gurrala, G., & Shenoy, U. J. (2018). 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Energies, 11(10), 2590. doi:10.3390/en11102590California Carbon Market Watch: A Comprehensive Analysis of the Golden State’s Cap-and-Trade Program, Year One—2012–2013. 2014https://www.issuelab.org/resource/california-carbon-market-watch-a-comprehensive-analysis-of-the-golden-state-s-cap-and-trade-program-year-one-2012-2013.htmlExploring the Best Possible Trade-Off between Competing Objectives: Identifying the Pareto Fronthttps://pythonhealthcare.org/2018/09/27/93-exploring-the-best-possible-trade-off-between-competing-objectives-identifying-the-pTeekaraman, Y., Kuppusamy, R., & Nikolovski, S. (2019). Solution for Voltage and Frequency Regulation in Standalone Microgrid using Hybrid Multiobjective Symbiotic Organism Search Algorithm. Energies, 12(14), 2812. doi:10.3390/en12142812Zeng, Z., Li, H., Tang, S., Yang, H., & Zhao, R. (2016). Multi‐objective control of multi‐functional grid‐connected inverter for renewable energy integration and power quality service. 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