Modeling of Inverter-Based Microgrid for Small-Signal and Large-Signal Stability Analysis

Integration of inverter-based resources (IBRs) such as solar photovoltaic, wind, and battery storage, is both a boon and a bane for electric power systems. On one hand, IBRs have helped in making electrical energy a clean (carbon-free) source of energy. On other hand, the dynamics of IBRs have changed the way power system studies have been carried out. With the advantages IBRs offer over conventional resources, it is assumed that a small distribution power system (microgrid) will have a 100% IBRs penetration in the future. Such a microgrid can operate in grid-connected mode or in an islanded mode. Both modes of operation bring challenges to system stability due to faster control dynamics of IBRs and can pose problems such as blackouts if the dynamics are not studied and mitigated properly. IBRs in a microgrid can operate in a grid-following (GFL) mode or grid-forming mode (GFM). We studied the effect of GFM inverters, GFL inverters, and elements of microgrid (such as lines, and transformers) on microgrid stability. We studied how solar radiation affects the bus voltage and how the inverter gains and line impedance can make a system unstable. Based on the study stable limits for a single inverter connected to a strong point of common coupling (PCC) were established. Since the study of a microgrid is still an evolving topic it has been observed that some elements such as a transformer are not modeled in detail for the stability study of the system. It was shown how detailed modeling of different transformer models will help in understanding the cause of high frequencies in the system following a disturbance. Droop type GFM inverters mimic the droop characteristics of the synchronous generator to control the frequency and voltage. Droop control is best suited for a power system where lines are highly inductive which is not the case for lines of a microgrid that are highly resistive. This results in a weak microgrid system. A modified primary control technique was developed for improving reactive power sharing between the inverters and thus making the microgrid system strong. Virtual Synchronous Generator (VSG) type of control of GFM inverters is another widely used control technique for GFM type of inverters. In an islanded microgrid GFM and GFL inverters work in parallel and interaction between these different types of inverter controls plays a huge role in system stability. Therefore, it is necessary to study the interactions of dynamics between GFM and GFL inverters to understand and define the stability limits of a microgrid system. We studied the inter-inverter dynamics in an islanded microgrid and demonstrated how in a deregulated market one inverter can aid another inverter to make the overall system more stable and reliable. A nonlinear study of inverters for large-signal stability was also performed for islanded microgrid system

Fusion of Model-free Reinforcement Learning with Microgrid Control: Review and Vision

Challenges and opportunities coexist in microgrids as a result of emerging large-scale distributed energy resources (DERs) and advanced control techniques. In this paper, a comprehensive review of microgrid control is presented with its fusion of model-free reinforcement learning (MFRL). A high-level research map of microgrid control is developed from six distinct perspectives, followed by bottom-level modularized control blocks illustrating the configurations of grid-following (GFL) and grid-forming (GFM) inverters. Then, mainstream MFRL algorithms are introduced with an explanation of how MFRL can be integrated into the existing control framework. Next, the application guideline of MFRL is summarized with a discussion of three fusing approaches, i.e., model identification and parameter tuning, supplementary signal generation, and controller substitution, with the existing control framework. Finally, the fundamental challenges associated with adopting MFRL in microgrid control and corresponding insights for addressing these concerns are fully discussed.Comment: 14 pages, 4 figures, published on IEEE Transaction on Smart Grid 2022 Nov 15. See: https://ieeexplore-ieee-org.utk.idm.oclc.org/stamp/stamp.jsp?arnumber=995140

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

[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). Volatility of the alternative energy input prices and spillover effects: a VAR [MA]-MGARCH in BEKK approach for the Turkish economy. Environmental Science and Pollution Research, 26(11), 10738-10745. doi:10.1007/s11356-019-04531-5Olivares, 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.2013.2295514Akinyele, D., Belikov, J., & Levron, Y. (2018). Challenges of Microgrids in Remote Communities: A STEEP Model Application. Energies, 11(2), 432. doi:10.3390/en11020432Benamar, A., Travaillé, P., Clairand, J.-M., & Escrivá-Escrivá, G. (2020). Non-Linear Control of a DC Microgrid for Electric Vehicle Charging Stations. International Journal on Advanced Science, Engineering and Information Technology, 10(2), 593. doi:10.18517/ijaseit.10.2.10815Lakshmi, M., & Hemamalini, S. (2018). 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. 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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. 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Renewable and Sustainable Energy Reviews, 71, 814-819. doi:10.1016/j.rser.2016.12.106Marzal, S., Salas, R., González-Medina, R., Garcerá, G., & Figueres, E. (2018). Current challenges and future trends in the field of communication architectures for microgrids. Renewable and Sustainable Energy Reviews, 82, 3610-3622. doi:10.1016/j.rser.2017.10.101Singh, A., & Suhag, S. (2018). Trends in Islanded Microgrid Frequency Regulation – A Review. Smart Science, 7(2), 91-115. doi:10.1080/23080477.2018.1540380Hou, X., Sun, Y., Lu, J., Zhang, X., Koh, L. H., Su, M., & Guerrero, J. M. (2018). Distributed Hierarchical Control of AC Microgrid Operating in Grid-Connected, Islanded and Their Transition Modes. IEEE Access, 6, 77388-77401. doi:10.1109/access.2018.2882678SHI, R., ZHANG, X., HU, C., XU, H., GU, J., & CAO, W. (2017). Self-tuning virtual synchronous generator control for improving frequency stability in autonomous photovoltaic-diesel microgrids. Journal of Modern Power Systems and Clean Energy, 6(3), 482-494. doi:10.1007/s40565-017-0347-3Toub, M., Bijaieh, M. M., Weaver, W. W., III, R. D. R., Maaroufi, M., & Aniba, G. (2019). Droop Control in DQ Coordinates for Fixed Frequency Inverter-Based AC Microgrids. Electronics, 8(10), 1168. doi:10.3390/electronics8101168Shuai, 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.2017.10.096Agundis-Tinajero, G., Segundo-Ramírez, J., Visairo-Cruz, N., Savaghebi, M., Guerrero, J. M., & Barocio, E. (2019). Power flow modeling of islanded AC microgrids with hierarchical control. International Journal of Electrical Power & Energy Systems, 105, 28-36. doi:10.1016/j.ijepes.2018.08.002Ali, A., Li, W., Hussain, R., He, X., Williams, B., & Memon, A. (2017). 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Microgrid, Its Control and Stability: The State of The Art

Some of the challenges facing the power industries globally include power quality and stability, diminishing fossil fuel, climate change amongst others. The use of distributed generators however is growing at a steady pace to address these challenges. When interconnected and integrated with storage devices and controllable load, these generators operate together in a grid, which has incidental stability and control issues. The focus of this paper, therefore, is on the review and discussion of the different control approaches and the hierarchical control on a microgrid, the current practice in the literature concerning stability and the control techniques deployed for microgrid control; the weakness and strength of the different control strategies were discussed in this work and some of the areas that require further research are highlighted

Microgrids

Microgrids are a growing segment of the energy industry, representing a paradigm shift from centralized structures toward more localized, autonomous, dynamic, and bi-directional energy networks, especially in cities and communities. The ability to isolate from the larger grid makes microgrids resilient, while their capability of forming scalable energy clusters permits the delivery of services that make the grid more sustainable and competitive. Through an optimal design and management process, microgrids could also provide efficient, low-cost, clean energy and help to improve the operation and stability of regional energy systems. This book covers these promising and dynamic areas of research and development and gathers contributions on different aspects of microgrids in an aim to impart higher degrees of sustainability and resilience to energy systems

Control and Stability of Residential Microgrid with Grid-Forming Prosumers

The rise of the prosumers (producers-consumers), residential customers equipped with behind-the-meter distributed energy resources (DER), such as battery storage and rooftop solar PV, offers an opportunity to use prosumer-owned DER innovatively. The thesis rests on the premise that prosumers equipped with grid-forming inverters can not only provide inertia to improve the frequency performance of the bulk grid but also support islanded operation of residential microgrids (low-voltage distribution feeder operated in an islanded mode), which can improve distribution grids’ resilience and reliability without purposely designing low-voltage (LV) distribution feeders as microgrids. Today, grid-following control is predominantly used to control prosumer DER, by which the prosumers behave as controlled current sources. These grid-following prosumers deliver active and reactive power by staying synchronized with the existing grid. However, they cannot operate if disconnected from the main grid due to the lack of voltage reference. This gives rise to the increasing interest in the use of grid-forming power converters, by which the prosumers behave as voltage sources. Grid-forming converters regulate their output voltage according to the reference of their own and exhibit load sharing with other prosumers even in islanded operation. Making use of grid-forming prosumers opens up opportunities to improve distribution grids’ resilience and enhance the genuine inertia of highly renewable-penetrated power systems. Firstly, electricity networks in many regional communities are prone to frequent power outages. Instead of purposely designing the community as a microgrid with dedicated grid-forming equipment, the LV feeder can be turned into a residential microgrid with multiple paralleled grid-forming prosumers. In this case, the LV feeder can operate in both grid-connected and islanded modes. Secondly, gridforming prosumers in the residential microgrid behave as voltage sources that respond naturally to the varying loads in the system. This is much like synchronous machines extracting kinetic energy from rotating masses. “Genuine” system inertia is thus enhanced, which is fundamentally different from the “emulated” inertia by fast frequency response (FFR) from grid-following converters. Against this backdrop, this thesis mainly focuses on two aspects. The first is the small-signal stability of such residential microgrids. In particular, the impact of the increasing number of grid-forming prosumers is studied based on the linearised model. The impact of the various dynamic response of primary sources is also investigated. The second is the control of the grid-forming prosumers aiming to provide sufficient inertia for the system. The control is focused on both the inverters and the DC-stage converters. Specifically, the thesis proposes an advanced controller for the DC-stage converters based on active disturbance rejection control (ADRC), which observes and rejects the “total disturbance” of the system, thereby enhancing the inertial response provided by prosumer DER. In addition, to make better use of the energy from prosumer-owned DER, an adaptive droop controller based on a piecewise power function is proposed, which ensures that residential ESS provide little power in the steady state while supplying sufficient power to cater for the demand variation during the transient state. Proposed strategies are verified by time-domain simulations