# A Comprehensive Review on a Virtual-Synchronous Generator: Topologies, Control Orders and Techniques, Energy Storages, and Applications

^{1}

^{2}

^{3}

^{4}

^{*}

## Abstract

**:**

## 1. Introduction

- Traditional power electronics control approaches of dc–ac converters have quick dynamics. However, the synchronous machine (SM) has slow dynamics and significant inertia. At a substantial distributed energy resources (DER) penetration, the grid’s equivalent rotational inertia will greatly decrease. The frequency stability will suffer as a result of this [5].
- The intermittent power supplied by DERs will be quickly provided to the grid using the fast-response feature of dc–ac converters. Instability in frequency, angle, and voltage will result from these interactions [16]. Similarly, large-size dc microgrids and parallel inverters are challenging to explore, particularly when the DERs and DC-ACconverters have comparable dynamics. DERs, on the other hand, are normally controlled by maximum power point tracking (MPPT) and hence are not dispatchable. As a result, these DC-ACconverters are unable to offer sufficient up-reserve to sustain grid frequency [16,17].

## 2. Current Virtual Inertia Topologies

#### 2.1. Topology Based on Synchronous Generator Model

#### 2.1.1. Synchronverters

#### 2.1.2. Kawasaki Heavy Industries (KHI)

#### 2.1.3. VISMA and IEPE Topologies

#### 2.2. A Swing Equation-Based Topology

#### 2.2.1. Ise Lab’s Topology

#### 2.2.2. Synchronous Power Controller (SPC)

#### 2.3. Inducverters

#### 2.4. Virtual Oscillator Control (VOC)

#### 2.5. Frequency–Power Response-Based Topologies

#### Virtual-Synchronous Generators (VSG)

#### 2.6. Droop-Based Approaches

## 3. Virtual-Synchronous Generator (VSG) Principles and Control Orders

#### 3.1. VSM Model with High Order

#### 3.2. Model of Low-Order VSM

## 4. VSG Operation Control

#### 4.1. Active and Reactive Power Controls

#### 4.2. Voltage and Frequency Control

## 5. Virtual Inertia (VI) Control Strategies

## 6. Energy Storage

## 7. Future Research Scope

## 8. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

## Abbreviations

AI | Artificial intelligence |

AVR | Automatic voltage regulator |

BESSs | Battery energy storage systems |

DER | Distributed energy resources |

DG | Distributed generation |

ESS | Energy storage system |

FM | Frequency modulation |

GDC | Generalized droop control |

HESS | Hybrid energy storage system |

IEPE | Institute of Electrical Power Engineering |

KHI | Kawasaki Heavy Industries |

MPC | Model predictive control |

MPPT | Maximum power point tracking |

PCC | Point of common coupling |

PLL | Phase-locked loop |

PV | Photovoltaics |

PWM | Pulse width modulation |

RES | Renewable energy sources |

ROCOF | Rate of change of frequency |

SG | Synchronous generator |

SM | Synchronous machine (SM) |

SOC | State of charge |

SPC | Synchronous power controller |

TSO | Transmission system operators |

VI | Virtual inertia |

VSG | Virtual-synchronous generator |

VSM | Virtual synchronous machine |

VSMG | VSM-based microgrid |

VOC | Virtual oscillator controller |

## References

- REN22, R. Global Status Report, 2022. 2022. Available online: https://www.ren21.net/ (accessed on 21 October 2022).
- Edrah, M.; Lo, K.L.; Anaya-Lara, O. Impacts of high penetration of DFIG wind turbines on rotor angle stability of power systems. IEEE Trans. Sustain. Energy
**2015**, 6, 759–766. [Google Scholar] [CrossRef] [Green Version] - Kahani, R.; Jamil, M.; Iqbal, M.T. Direct Model Reference Adaptive Control of a Boost Converter for Voltage Regulation in Microgrids. Energies
**2022**, 15, 5080. [Google Scholar] [CrossRef] - Fernández-Guillamón, A.; Gómez-Lázaro, E.; Muljadi, E.; Molina-García, Á. Power systems with high renewable energy sources: A review of inertia and frequency control strategies over time. Renew. Sustain. Energy Rev.
**2019**, 115, 109369. [Google Scholar] [CrossRef] [Green Version] - Chen, D.; Xu, Y.; Huang, A.Q. Integration of DC microgrids as virtual synchronous machines into the AC grid. IEEE Trans. Ind. Electron.
**2017**, 64, 7455–7466. [Google Scholar] [CrossRef] - Ratnam, K.S.; Palanisamy, K.; Yang, G. Future low-inertia power systems: Requirements, issues, and solutions-A review. Renew. Sustain. Energy Rev.
**2020**, 124, 109773. [Google Scholar] [CrossRef] - Hossain, M.A.; Pota, H.R.; Hossain, M.J.; Blaabjerg, F. Evolution of microgrids with converter-interfaced generations: Challenges and opportunities. Int. J. Electr. Power Energy Syst.
**2019**, 109, 160–186. [Google Scholar] [CrossRef] - Shah, R.; Mithulananthan, N.; Bansal, R.; Ramachandaramurthy, V. A review of key power system stability challenges for large-scale PV integration. Renew. Sustain. Energy Rev.
**2015**, 41, 1423–1436. [Google Scholar] [CrossRef] - Bajaj, M.; Singh, A.K. Grid integrated renewable DG systems: A review of power quality challenges and state-of-the-art mitigation techniques. Int. J. Energy Res.
**2020**, 44, 26–69. [Google Scholar] [CrossRef] - Yap, K.Y.; Sarimuthu, C.R.; Lim, J.M.-Y. Virtual inertia-based inverters for mitigating frequency instability in grid-connected renewable energy system: A review. Appl. Sci.
**2019**, 9, 5300. [Google Scholar] [CrossRef] [Green Version] - Hartmann, B.; Vokony, I.; Táczi, I. Effects of decreasing synchronous inertia on power system dynamics—Overview of recent experiences and marketisation of services. Int. Trans. Electr. Energy Syst.
**2019**, 29, e12128. [Google Scholar] [CrossRef] - Chown, G.; Wright, J.G.; Van Heerden, R.P.; Coker, M. System inertia and Rate of Change of Frequency (RoCoF) with increasing non-synchronous renewable energy penetration. In Proceedings of the 8th CIGRE Southern Africa Regional Conferenc, Cape Town, South Africa, 14-17 November 2017. [Google Scholar]
- Milano, F.; Dörfler, F.; Hug, G.; Hill, D.J.; Verbič, G. Foundations and challenges of low-inertia systems. In Proceedings of the 2018 Power Systems Computation Conference (PSCC), Dublin, Ireland, 11–15 June 2018; pp. 1–25. [Google Scholar]
- Mandal, R.; Chatterjee, K. Virtual inertia emulation and RoCoF control of a microgrid with high renewable power penetration. Electr. Power Syst. Res.
**2021**, 194, 107093. [Google Scholar] [CrossRef] - Modi, N.; Yan, R. Low inertia power systems: Frequency response challenges and a possible solution. In Proceedings of the 2016 Australasian Universities Power Engineering Conference (AUPEC), Brisbane, Australia, 25–28 September 2016; pp. 1–6. [Google Scholar]
- Rahman, M.S.; Oo, A. Distributed multi-agent based coordinated power management and control strategy for microgrids with distributed energy resources. Energy Convers. Manag.
**2017**, 139, 20–32. [Google Scholar] [CrossRef] - Rangu, S.K.; Lolla, P.R.; Dhenuvakonda, K.R.; Singh, A.R. Recent trends in power management strategies for optimal operation of distributed energy resources in microgrids: A comprehensive review. Int. J. Energy Res.
**2020**, 44, 9889–9911. [Google Scholar] [CrossRef] - Tamrakar, U.; Shrestha, D.; Maharjan, M.; Bhattarai, B.P.; Hansen, T.M.; Tonkoski, R. Virtual inertia: Current trends and future directions. Appl. Sci.
**2017**, 7, 654. [Google Scholar] [CrossRef] [Green Version] - Beck, H.-P.; Hesse, R. Virtual synchronous machine. In Proceedings of the 2007 9th International Conference on Electrical Power Quality and Utilisation, Barcelona, Spain, 9–11 October 2007; pp. 1–6. [Google Scholar]
- Rehman, H.U.; Yan, X.; Abdelbaky, M.A.; Jan, M.U.; Iqbal, S. An advanced virtual synchronous generator control technique for frequency regulation of grid-connected PV system. Int. J. Electr. Power Energy Syst.
**2021**, 125, 106440. [Google Scholar] [CrossRef] - Tamrakar, U.; Galipeau, D.; Tonkoski, R.; Tamrakar, I. Improving transient stability of photovoltaic-hydro microgrids using virtual synchronous machines. In Proceedings of the 2015 IEEE Eindhoven PowerTech, Eindhoven, The Netherlands, 29 June–2 July 2015; pp. 1–6. [Google Scholar]
- Serban, I.; Ion, C.P. Microgrid control based on a grid-forming inverter operating as virtual synchronous generator with enhanced dynamic response capability. Int. J. Electr. Power Energy Syst.
**2017**, 89, 94–105. [Google Scholar] [CrossRef] - Cheema, K.M. A comprehensive review of virtual synchronous generator. Int. J. Electr. Power Energy Syst.
**2020**, 120, 106006. [Google Scholar] [CrossRef] - Chen, M.; Zhou, D.; Blaabjerg, F. Modelling, implementation, and assessment of virtual synchronous generator in power systems. J. Mod. Power Syst. Clean Energy
**2020**, 8, 399–411. [Google Scholar] [CrossRef] - Dai, Y.; Zhang, L.; Chen, Q.; Zhou, K.; Hua, T. Multi-VSG-based frequency regulation for uninterruptible power AC micro-grid with distributed electric vehicles. Int. J. Electr. Power Energy Syst.
**2022**, 137, 107785. [Google Scholar] [CrossRef] - Zhong, Q.-C. Virtual Synchronous Machines: A unified interface for grid integration. IEEE Power Electron. Mag.
**2016**, 3, 18–27. [Google Scholar] [CrossRef] - Zhong, Q.-C.; Weiss, G. Synchronverters: Inverters that mimic synchronous generators. IEEE Trans. Ind. Electron.
**2010**, 58, 1259–1267. [Google Scholar] [CrossRef] - Hirase, Y.; Abe, K.; Sugimoto, K.; Shindo, Y. A grid-connected inverter with virtual synchronous generator model of algebraic type. Electr. Eng. Jpn.
**2013**, 184, 10–21. [Google Scholar] [CrossRef] - Ise, T.; Bevrani, H. Virtual synchronous generators and their applications in microgrids. In Integration of Distributed Energy Resources in Power Systems; Elsevier: Amsterdam, The Netherlands, 2016; pp. 282–294. [Google Scholar]
- Zhang, W.; Cantarellas, A.M.; Rocabert, J.; Luna, A.; Rodriguez, P. Synchronous power controller with flexible droop characteristics for renewable power generation systems. IEEE Trans. Sustain. Energy
**2016**, 7, 1572–1582. [Google Scholar] [CrossRef] - Tamrakar, U. Optimization-Based Fast-Frequency Support in Low Inertia Power Systems; South Dakota State University: Brookings, SD, USA, 2020. [Google Scholar]
- Sakimoto, K.; Miura, Y.; Ise, T. Stabilization of a power system with a distributed generator by a virtual synchronous generator function. In Proceedings of the 8th International Conference on Power Electronics-ECCE Asia, Jeju, Korea, 30 May–3 June 2011; pp. 1498–1505. [Google Scholar]
- Alipoor, J.; Miura, Y.; Ise, T. Power system stabilization using virtual synchronous generator with alternating moment of inertia. IEEE J. Emerg. Sel. Top. Power Electron.
**2014**, 3, 451–458. [Google Scholar] [CrossRef] - Tarrasó, A.; Verdugo, C.; Lai, N.B.; Candela, J.I.; Rodriguez, P. Synchronous power controller for distributed generation units. In Proceedings of the 2019 IEEE Energy Conversion Congress and Exposition (ECCE), Baltimore, MD, USA, 29 September–3 October 2019; pp. 4660–4664. [Google Scholar]
- Rakhshani, E.; Remon, D.; Cantarellas, A.; Garcia, J.M.; Rodriguez, P. Modeling and sensitivity analyses of VSP based virtual inertia controller in HVDC links of interconnected power systems. Electr. Power Syst. Res.
**2016**, 141, 246–263. [Google Scholar] [CrossRef] - Zhang, W.; Remon, D.; Rodriguez, P. Frequency support characteristics of grid-interactive power converters based on the synchronous power controller. IET Renew. Power Gener.
**2017**, 11, 470–479. [Google Scholar] [CrossRef] [Green Version] - Zhang, W.; Remon, D.; Mir, A.; Luna, A.; Rocabert, J.; Candela, I.; Rodriguez, P. Comparison of different power loop controllers for synchronous power controlled grid-interactive converters. In Proceedings of the 2015 IEEE Energy Conversion Congress and Exposition (ECCE), Montreal, QC, Canada, 20–24 September 2015; pp. 3780–3787. [Google Scholar]
- Ashabani, M.; Freijedo, F.D.; Golestan, S.; Guerrero, J.M. Inducverters: PLL-less converters with auto-synchronization and emulated inertia capability. IEEE Trans. Smart Grid
**2015**, 7, 1660–1674. [Google Scholar] [CrossRef] [Green Version] - Hu, J.; Ma, H. Synchronization of the carrier wave of parallel three-phase inverters with virtual oscillator control. IEEE Trans. Power Electron.
**2016**, 32, 7998–8007. [Google Scholar] [CrossRef] - Padmawansa, N.U.; Arachchige, L.N.W. Improving Transient Stability of an Islanded Microgrid Using PV Based Virtual Synchronous Machines. In Proceedings of the 2020 Moratuwa Engineering Research Conference (MERCon), Moratuwa, Sri Lanka, 28–30 July 2020; pp. 543–548. [Google Scholar]
- Wang, R.; Chen, L.; Zheng, T.; Mei, S. VSG-based adaptive droop control for frequency and active power regulation in the MTDC system. CSEE J. Power Energy Syst.
**2017**, 3, 260–268. [Google Scholar] [CrossRef] - Alsiraji, H.A.; El-Shatshat, R. Comprehensive assessment of virtual synchronous machine based voltage source converter controllers. IET Gener. Transm. Distrib.
**2017**, 11, 1762–1769. [Google Scholar] [CrossRef] - Zheng, T.; Chen, L.; Guo, Y.; Mei, S. Comprehensive control strategy of virtual synchronous generator under unbalanced voltage conditions. IET Gener. Transm. Distrib.
**2018**, 12, 1621–1630. [Google Scholar] [CrossRef] - Chen, Y.; Hesse, R.; Turschner, D.; Beck, H.-P. Comparison of methods for implementing virtual synchronous machine on inverters. In Proceedings of the International Conference on Renewable Energies and Power Quality, Vigo, Spain, 27–29 July 2022; pp. 414–424. [Google Scholar]
- Cheema, K.M.; Mehmood, K. Improved virtual synchronous generator control to analyse and enhance the transient stability of microgrid. IET Renew. Power Gener.
**2020**, 14, 495–505. [Google Scholar] [CrossRef] - Li, J.; Wen, B.; Wang, H. Adaptive virtual inertia control strategy of VSG for micro-grid based on improved bang-bang control strategy. IEEE Access
**2019**, 7, 39509–39514. [Google Scholar] [CrossRef] - Li, P.; Hu, W.; Xu, X.; Huang, Q.; Liu, Z.; Chen, Z. A frequency control strategy of electric vehicles in microgrid using virtual synchronous generator control. Energy
**2019**, 189, 116389. [Google Scholar] [CrossRef] - Karimi, A.; Khayat, Y.; Naderi, M.; Dragičević, T.; Mirzaei, R.; Blaabjerg, F.; Bevrani, H. Inertia response improvement in AC microgrids: A fuzzy-based virtual synchronous generator control. IEEE Trans. Power Electron.
**2019**, 35, 4321–4331. [Google Scholar] [CrossRef] - Meng, X.; Liu, J.; Liu, Z. A generalized droop control for grid-supporting inverter based on comparison between traditional droop control and virtual synchronous generator control. IEEE Trans. Power Electron.
**2018**, 34, 5416–5438. [Google Scholar] [CrossRef] - Peng, Z.; Wang, J.; Bi, D.; Wen, Y.; Dai, Y.; Yin, X.; Shen, Z.J. Droop control strategy incorporating coupling compensation and virtual impedance for microgrid application. IEEE Trans. Energy Convers.
**2019**, 34, 277–291. [Google Scholar] [CrossRef] - Yu, Y.-j.; Cao, L.-k.; Zhao, X. A novel control strategy of virtual synchronous generator in island micro-grids. Syst. Sci. Control Eng.
**2018**, 6, 136–145. [Google Scholar] [CrossRef] [Green Version] - Kerdphol, T.; Watanabe, M.; Hongesombut, K.; Mitani, Y. Self-adaptive virtual inertia control-based fuzzy logic to improve frequency stability of microgrid with high renewable penetration. IEEE Access
**2019**, 7, 76071–76083. [Google Scholar] [CrossRef] - Ali, H.; Magdy, G.; Xu, D. A new optimal robust controller for frequency stability of interconnected hybrid microgrids considering non-inertia sources and uncertainties. Int. J. Electr. Power Energy Syst.
**2021**, 128, 106651. [Google Scholar] [CrossRef] - Skiparev, V.; Machlev, R.; Chowdhury, N.R.; Levron, Y.; Petlenkov, E.; Belikov, J. Virtual inertia control methods in islanded microgrids. Energies
**2021**, 14, 1562. [Google Scholar] [CrossRef] - Belila, A.; Amirat, Y.; Benbouzid, M.; Berkouk, E.M.; Yao, G. Virtual synchronous generators for voltage synchronization of a hybrid PV-diesel power system. Int. J. Electr. Power Energy Syst.
**2020**, 117, 105677. [Google Scholar] [CrossRef] - Long, B.; Liao, Y.; Chong, K.T.; Rodríguez, J.; Guerrero, J.M. MPC-controlled virtual synchronous generator to enhance frequency and voltage dynamic performance in islanded microgrids. IEEE Trans. Smart Grid
**2020**, 12, 953–964. [Google Scholar] [CrossRef] - Shi, K.; Ye, H.; Song, W.; Zhou, G. Virtual inertia control strategy in microgrid based on virtual synchronous generator technology. IEEE Access
**2018**, 6, 27949–27957. [Google Scholar] [CrossRef] - Zhao, H.; Yang, Q.; Zeng, H. Multi-loop virtual synchronous generator control of inverter-based DGs under microgrid dynamics. IET Gener. Transm. Distrib.
**2017**, 11, 795–803. [Google Scholar] [CrossRef] - Bose, U.; Chattopadhyay, S.K.; Chakraborty, C.; Pal, B. A novel method of frequency regulation in microgrid. IEEE Trans. Ind. Appl.
**2018**, 55, 111–121. [Google Scholar] [CrossRef] [Green Version] - Xu, T.; Jang, W.; Overbye, T. Commitment of fast-responding storage devices to mimic inertia for the enhancement of primary frequency response. IEEE Trans. Power Syst.
**2017**, 33, 1219–1230. [Google Scholar] [CrossRef] - Renjit, A.A.; Guo, F.; Sharma, R. An analytical framework to design a dynamic frequency control scheme for microgrids using energy storage. In Proceedings of the 2016 IEEE Applied Power Electronics Conference and Exposition (APEC), Long Beach, CA, USA, 20–24 March 2016; pp. 1682–1689. [Google Scholar]
- Kerdphol, T.; Rahman, F.S.; Mitani, Y.; Hongesombut, K.; Küfeoğlu, S. Virtual inertia control-based model predictive control for microgrid frequency stabilization considering high renewable energy integration. Sustainability
**2017**, 9, 773. [Google Scholar] [CrossRef] [Green Version] - Hu, W.; Wu, Z.; Dinavahi, V. Dynamic analysis and model order reduction of virtual synchronous machine based microgrid. IEEE Access
**2020**, 8, 106585–106600. [Google Scholar] [CrossRef] - Yan, W.; Cheng, L.; Yan, S.; Gao, W.; Gao, D.W. Enabling and evaluation of inertial control for PMSG-WTG using synchronverter with multiple virtual rotating masses in microgrid. IEEE Trans. Sustain. Energy
**2019**, 11, 1078–1088. [Google Scholar] [CrossRef] - Qu, S.; Wang, Z. Cooperative control strategy of virtual synchronous generator based on optimal damping ratio. IEEE Access
**2020**, 9, 709–719. [Google Scholar] [CrossRef] - Wang, F.; Zhang, L.; Feng, X.; Guo, H. An adaptive control strategy for virtual synchronous generator. IEEE Trans. Ind. Appl.
**2018**, 54, 5124–5133. [Google Scholar] [CrossRef] - Rasool, A.; Yan, X.; Rasool, U.; Abbas, F.; Numan, M.; Rasool, H.; Jamil, M. Enhanced control strategies of VSG for EV charging station under a low inertia microgrid. IET Power Electron.
**2020**, 13, 2895–2904. [Google Scholar] [CrossRef] - Rasool, A.; Fahad, S.; Yan, X.; Rasool, H.; Jamil, M.; Padmanaban, S. Reactive Power Matching Through Virtual Variable Impedance for Parallel Virtual Synchronous Generator Control Scheme. IEEE Syst. J.
**2022**. [Google Scholar] [CrossRef] - Kerdphol, T.; Rahman, F.S.; Watanabe, M.; Mitani, Y.; Turschner, D.; Beck, H.-P. Enhanced virtual inertia control based on derivative technique to emulate simultaneous inertia and damping properties for microgrid frequency regulation. IEEE Access
**2019**, 7, 14422–14433. [Google Scholar] [CrossRef] - Abuagreb, M.; Allehyani, M.F.; Johnson, B.K. Overview of Virtual Synchronous Generators: Existing Projects, Challenges, and Future Trends. Electronics
**2022**, 11, 2843. [Google Scholar] [CrossRef] - Obaid, Z.A.; Cipcigan, L.; Muhssin, M.T.; Sami, S.S. Control of a population of battery energy storage systems for frequency response. Int. J. Electr. Power Energy Syst.
**2020**, 115, 105463. [Google Scholar] [CrossRef] - Fang, J.; Lin, P.; Li, H.; Yang, Y.; Tang, Y. An improved virtual inertia control for three-phase voltage source converters connected to a weak grid. IEEE Trans. Power Electron.
**2018**, 34, 8660–8670. [Google Scholar] [CrossRef] [Green Version] - Luo, X.; Wang, J.; Dooner, M.; Clarke, J. Overview of current development in electrical energy storage technologies and the application potential in power system operation. Appl. Energy
**2015**, 137, 511–536. [Google Scholar] [CrossRef] [Green Version] - Behi, B.; Baniasadi, A.; Arefi, A.; Gorjy, A.; Jennings, P.; Pivrikas, A. Cost–benefit analysis of a virtual power plant including solar PV, flow battery, heat pump, and demand management: A western australian case study. Energies
**2020**, 13, 2614. [Google Scholar] [CrossRef] - Mallemaci, V.; Mandrile, F.; Rubino, S.; Mazza, A.; Carpaneto, E.; Bojoi, R. A comprehensive comparison of Virtual Synchronous Generators with focus on virtual inertia and frequency regulation. Electr. Power Syst. Res.
**2021**, 201, 107516. [Google Scholar] [CrossRef] - Sang, W.; Guo, W.; Dai, S.; Tian, C.; Yu, S.; Teng, Y. Virtual Synchronous Generator, a Comprehensive Overview. Energies
**2022**, 15, 6148. [Google Scholar] [CrossRef] - Fang, J.; Tang, Y.; Li, H.; Li, X. A battery/ultracapacitor hybrid energy storage system for implementing the power management of virtual synchronous generators. IEEE Trans. Power Electron.
**2017**, 33, 2820–2824. [Google Scholar] [CrossRef] - Zhang, X.; Gao, Q.; Hu, Y.; Zhang, H.; Guo, Z. Active power reserve photovoltaic virtual synchronization control technology. Chin. J. Electr. Eng.
**2020**, 6, 1–6. [Google Scholar] [CrossRef] - Mercier, P.; Cherkaoui, R.; Oudalov, A. Optimizing a battery energy storage system for frequency control application in an isolated power system. IEEE Trans. Power Syst.
**2009**, 24, 1469–1477. [Google Scholar] [CrossRef] - Saleh, S.; Ahshan, R.; Al-Durra, A. Developing and Testing Model Predictive Control to Minimize Ground Potentials in Transformerless Interconnected Five-Level Power Electronic Converters. IEEE Trans. Ind. Appl.
**2021**, 57, 3500–3510. [Google Scholar] [CrossRef] - Saleh, S.; Ahshan, R. Resolution-level-controlled WM inverter for PMG-based wind energy conversion system. IEEE Trans. Ind. Appl.
**2012**, 48, 750–763. [Google Scholar] [CrossRef] - Ahshan, R. Pumped hydro storage for microgrid applications. In Recent Advances in Renewable Energy Technologies; Elsevier: Amsterdam, The Netherlands, 2022; pp. 323–354. [Google Scholar]

**Figure 2.**Effect of inertia on frequency [6].

**Figure 3.**Concept of virtual inertia [18].

**Figure 5.**Synchronverter topology overall schematic showing the operating principle [18].

**Figure 6.**Power stage component of a synchronverter [26].

**Figure 7.**The components of a synchronverter: controller [26].

**Figure 8.**Simple structure of KHI topology [29].

**Figure 9.**Overall diagram of Ise Lab’s architecture [18].

**Figure 10.**Ise Lab’s topology: the governor model [18].

**Figure 11.**Synchronous power controller (SPC) control diagram [6].

**Figure 13.**Virtual-synchronous generator (VSG) topology [18].

**Figure 14.**VSYNCH’s virtual-synchronous generator block diagram [6].

**Figure 15.**Frequency droop control [18].

**Figure 17.**VSG classification according to model order [42].

Topologies | Type | Ref. | Features | Strength | Weaknesses | PLL |
---|---|---|---|---|---|---|

Synchronverters | Synchronous Generator Model-Based Topology | [6,23,26,27] | - Synchronverters may be used as grid-forming units without making substantial modifications to their operating structure.
- Frequency droop algorithm controls output power.
- Adjustable moment inertia and dampening.
- It is capable of simulating the precise dynamics of an SG.
| - There is no requirement for a frequency derivative.
- There is less noise in the system.
- Power sharing is scalable, and voltage phase and frequency are well-controlled.
- Particularly well-suited for inertia imitation from DGs that are not linked to the grid.
| - The numerical instability might be caused by the complexity of the differential equations involved.
- A voltage-source approach lacks intrinsic safety against strong grid transients.
- External protection systems are required.
| Required for initial synchronization |

Kawasaki Heavy Industries (KHI) | Synchronous Generator Model-Based Topology | [18,28,29] | - An equal governor and automated voltage regulator (AVR) model are used instead of a full dynamic model of the SG.
| - Highly efficient for asymmetrical loads and sharp changes in the utility grid.
| ||

VISMA and IEPE topologies | Synchronous Generator Model-Based Topology | [23,30,31] | - The VISMA approach uses d-q -based architecture to simulate the synchronous generator.
- IEPE uses the output current of a DG to provide a reference voltage for virtual machines.
| VISMA: - Accurate replication of SG dynamics.
- Automated power-sharing and syncing capabilities.
- Standalone and microgrid operation.
- Conceptually straightforward.
- Best-suited for islanded mode.
| VISMA: - Unstable due to the use of numerical data.
- Implementation of a PLL that is difficult.
- It is challenging to cope with transient currents in the synchronization period in a grid-connected case.
| Required for initial synchronization |

Ise Labs Topology | A Swing Equation-Based Topology | [18,32,33] | - To simulate inertia, this architecture solves the power–frequency swing equation per control cycle.
- It estimates the active output power of the inverter as well as the utility grid frequency.
- Imitates SG behavior.
- Designed for the self-contained functioning of isolated systems.
| - There is less noise in the system since the frequency derivative is not required to execute the control procedure.
| - Problems related to numerical instability.
- System oscillation might result from incorrect parameter tuning.
- As a result of the governor model’s delay, greater ROCOF and therefore larger frequency nadirs result.
| Required for initial synchronization |

Synchronous Power Controller (SPC) | A Swing Equation-Based Topology | [6,34,35,36,37] | - A cascaded control system is implemented using a virtual admittance, with an inner current and an outer voltage control loop.
| - A cascaded control system offers intrinsic over-current protection.
- Eliminates the discontinuities that occur while solving mathematical models, resulting in a system that is more resistant to numerical instabilities.
| - The nested loop structure makes setting the control system parameters more difficult.
| |

Inducverters | [6,38] | - Inducverter’s principle is established mostly on the induction machine inertial characteristics.
| - Offers the benefit of automatic synchronization without the need of a PLL.
- Able to share total system load.
| |||

Virtual Oscillator Control (VOC) | [18,39] | - Synchronizes DG units devoid of any kind of communication by implementing a non-linear oscillator inside the controller rather than simulating SG or induction generators.
| - This strategy is especially advantageous in a grid controlled by DGs.
- The controller is capable of maintaining synchronism and sharing the overall system load.
- Offers better voltage regulation.
| |||

VSYNC VSG Topology | Frequency–Power Response-Based | [6,18,40] | - It is established on the frequency measurement’s derivative.
- Simulates the inertial reaction to frequency variation.
- Uses virtual inertia in DG systems because it does not include all the SG’s precise equations.
| - The easiest method of simulating inertia is to use a frequency–power response-based architecture.
- Allows load sharing amongst parallel-connected devices.
- Inherent over-current protection.
- Quick reaction in tracking steady-state frequency.
| - A successful operation necessitates the use of a powerful and sophisticated PLL.
- Noise-sensitive, which might lead to unsteady functioning.
- In grid-connected mode.
- Reacts to changes in frequency rather than voltage.
- Execution time is lengthy.
- Under AC weak grids, a PLL has a negative impact on control performance.
| Needed |

Droop-Based Approaches | [18] | - For the autonomous functioning of standalone microgrid systems, frequency droop-based controllers have been established.
- Traditional droop control in SGs is similar to the concepts employed.
| - The delay created by the filters employed in these controllers for power measurements is mathematically comparable to virtual inertia.
- Traditional droop-based systems are known to have a delayed transient reaction.
| Needed |

**Table 2.**Islanded microgrids VI control approaches [54].

Control Type | Control Method | Advantage | Drawbacks | Complexity | Robustness |
---|---|---|---|---|---|

Classical | Robust H-infinity | - ▪ Robust frequency control.
- ▪ Strong overshoot minimization.
| - ▪ Notable rises when connection disruptions occur.
- ▪ Order reduction is required.
- ▪ Robustness is insufficient.
| Medium | High |

Coefficient diagram method | - ▪ Robustness is high.
- ▪ Order reduction is not required.
| - ▪ Robustness is limited.
| Medium | High | |

Advanced algorithms | Fuzzy-logic-based controller | - ▪ Flexible reaction.
| - ▪ Manual optimization.
- ▪ Computing time is long.
- ▪ Fuzzy rules adaption limitations.
| High | High |

Reinforcement learning-based controller | - ▪ Rewarding system for learning.
- ▪ Efficient system feedback.
- ▪ Superior robustness.
| - ▪ There is a requirement for sample data.
- ▪ Particularly to the reward/penalty optimization.
| Very High | High | |

Hybrid algorithm | PI/PID and particle-swarm optimization | - ▪ Straightforward controller.
- ▪ Minimally complex numeric.
| - ▪ Global optimum solution convergence is not assured.
- ▪ Lack of robustness.
| Low | Low |

Model-predictive control | - ▪ Superior robustness.
- ▪ Rapid response based on prediction.
- ▪ Quick optimization.
| - ▪ Required dataset for prediction model.
- ▪ Complicated optimization.
| High | High |

Energy Storage Type | Efficiency (%) | Power Capability (MW) | Lifetime | Response Time | Charge Time |
---|---|---|---|---|---|

Lithium Batteries | 90–95 | 0.015–50 | 3–15 k times | <100 milliseconds | Hours |

Flywheels | 85–96 | 0.1–20 | >15 years | <2 milliseconds | Minutes |

Supercapacitors | 65–80 | 0.05–0.1 | 500 k times | <1 milliseconds | Seconds |

Superconducting magnetic | >95 | 1–10 | >30 years | <2 milliseconds | Seconds |

**Table 4.**Energy storage hybridization opportunities to mitigate various issues while deploying large-scale VSGs. X shows no opportunity, √ provides a significant potential, and * shows a possibility of hybridization.

Issues/Functionalities | Pumped Hydro-Storage—Alone | Pumped Hydro-Storage—Flywheel Energy Stoarge | Pumped Hydro-Stoarge—Battery | Pumped Hydro-Storage—Fuel Cell | Pumped Hydro-Storage—Superconducting Magnetic Energy Storage | Pumped Hydro-Storage—Supercapacitor |
---|---|---|---|---|---|---|

Power quality | X | √ | √ | * | √ | √ |

Energy management | √ | √ | √ | √ | √ | √ |

Intermittency mitigation | X | √ | √ | * | * | √ |

Back-up for renewable power integration | √ | √ | √ | √ | * | √ |

Back-up for emergency | X | √ | * | * | * | * |

Load following and ramping | X | * | √ | * | √ | * |

Time shifting | √ | √ | √ | √ | √ | √ |

Peak shaving | √ | √ | √ | √ | √ | √ |

Load leveling | √ | √ | √ | √ | √ | √ |

Seasonal energy storage | * | * | * | √ | * | * |

Low-voltage ride through | X | √ | √ | * | * | √ |

Black start | * | * | √ | √ | * | * |

Voltage control and regulation | X | * | √ | * | * | √ |

Grid fluctuation mitigation | X | √ | √ | * | √ | √ |

Spinning reserve | X | * | √ | * | * | X |

Uninterruptible power supply | X | √ | √ | * | * | √ |

Transmission system upgrade deferral | √ | √ | √ | √ | * | √ |

Standing reserve | * | * | √ | √ | * | * |

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Shadoul, M.; Ahshan, R.; AlAbri, R.S.; Al-Badi, A.; Albadi, M.; Jamil, M.
A Comprehensive Review on a Virtual-Synchronous Generator: Topologies, Control Orders and Techniques, Energy Storages, and Applications. *Energies* **2022**, *15*, 8406.
https://doi.org/10.3390/en15228406

**AMA Style**

Shadoul M, Ahshan R, AlAbri RS, Al-Badi A, Albadi M, Jamil M.
A Comprehensive Review on a Virtual-Synchronous Generator: Topologies, Control Orders and Techniques, Energy Storages, and Applications. *Energies*. 2022; 15(22):8406.
https://doi.org/10.3390/en15228406

**Chicago/Turabian Style**

Shadoul, Myada, Razzaqul Ahshan, Rashid S. AlAbri, Abdullah Al-Badi, Mohammed Albadi, and Mohsin Jamil.
2022. "A Comprehensive Review on a Virtual-Synchronous Generator: Topologies, Control Orders and Techniques, Energy Storages, and Applications" *Energies* 15, no. 22: 8406.
https://doi.org/10.3390/en15228406