Parameter Adjustment for the Droop Control Operating a Discharge PEC in PMG-Based WECSs With Generator-Charged Battery Units

ABSTRACT: 

Permanent magnet generator (PMG)-based wind energy conversion systems (WECSs) with battery units, have become a popular class of distributed generation units. These distributed generation units are typically operated using various types of controllers, including droop controllers. Existing droop controllers are designed to operate grid-side dc-ac power electronic converters (PEC) to ensure stable and reliable power production by a PMG-based WECS. The employment of battery storage units (to mitigate fluctuations in the power produced by a PMG-based WECS) introduces additional considerations for the design of droop controllers. Such considerations are due to the power available from battery units that is dependent on the state-of-charge (SOC). This paper proposes adjustments in the parameters (droop constants) of the droop control (operate the the discharge PEC) based on the SOC of the battery units. These adjustments are made to further support stable and reliable power delivery of the PMG-based WECS into the point-of-common-coupling (PCC). The proposed adjustments of droop constants are evaluated using a 7.5 kW grid-connected PMG-based WECS with 3.52 kW generator-charged battery storage units. Performance tests are carried out for step changes in the active and reactive power demands, changes in the wind speed, and grid-side disturbances. Test results show that the proposed correction of the droop constants is critical for maintaining a stable, effective, and accurate power delivery by the battery units, thus supporting the voltage/frequency stability at the PCC under different operating conditions.

 KEYWORDS:

1.      Permanent magnet generators

2.      Wind energy conversion systems

3.      Battery storage systems

       Droop control

 B   Distributed generation

SOFTWARE: MATLAB/SIMULINK

 SCHEMATIC DIAGRAM:

 

Figure 1. A Schematic Diagram For A Grid-Connected Pmg-Based Wecs With Generator-Charged Battery Units [2]. The Notation Mchb Denotes Modified Cascaded H-Bridge.

 

EXPECTED SIMULATION RESULTS:

 

Figure 2. Test Case 1: Changes In The Wind Speed And Power Delivery To The Grid: (A) The Wind Speed, (B) The Frequency As Measured At The Pcc, (C) The Voltage As Measured At The Pcc, (D) The Command And Actual Active And Reactive Powers Injected Into The Grid, (E) The Command And Actual Active And

Reactive Powers Delivered By The Gs-Pec, (F) The Command And Actual Active And Reactive Powers Delivered By The Ds-Pec, (G) The 3_ Currents Flowing From The Gs-Pec, (H) The 3_ Currents Flowing From The Ds-Pec, And (I) The Soc, Mp2, And Mq2.

 

Figure 3. Test Case 2: Voltage And Frequency Disturbance At The Pcc: (A) The Wind Speed, (B) The Frequency As Measured At The Pcc, (C) The Voltage As Measured At The Pcc, (D) The Command And Actual Active And Reactive Powers Injected Into The Grid, (E) The Command And Actual Active And Reactive Powers Delivered By The Gs-Pec, (F) The Command And Actual Active And Reactive Powers Delivered By The Ds-Pec, (G) The 3_ Currents Flowing From The Gs-Pec, (H) The 3_ Currents Flowing From The Ds-Pec, And (I) The Soc, Mp2, And Mq2.

CONCLUSION:

This paper has presented a method to adjust the constants of a droop controller operating a discharge PEC of battery units based on their SOC. The proposed adjustments in droop constants are developed for battery storage systems that are deployed in grid-connected PMG-based WECSs. Adjustments of droop constants are intended to ensure that the power delivered by a storage system is maintained close to its command as the SOC decreases. In addition, the correction of droop constants improves the ability of the PMG-based WECS and its battery storage system to meet their command power delivery, while ensuring the frequency and voltage stability at the PCC. The performance and responses of the pro- posed corrected droop constants have tested using a 7.5 kW grid-connected PMG-based WECS that has a 3.52 kW bat- tery storage system under different operating conditions. Test results for the PMG-based WECS with its battery storage system have shown an encouraging ability to adjust the power delivered by the grid-side and discharge PECs in response to changes in wind speed, power delivery to the grid, and grid-side disturbances. These abilities have been found insensitive to the wind speed, levels of power delivery to the grid, and/or nature of disturbances on the grid side. Such features of the droop control support its applicability.

REFERENCES:

 

[1] IEEE Application Guide for IEEE Standard for Interconnecting Distributed Resources With Electric Power Systems, IEEE Standard 1547.2- 2008, 2008.

[2] S. A. Saleh and X. F. S. Onge, ``A new structure for PMG-based WECSs with battery storage systems,'' IEEE Access, vol. 8, pp. 190356_190366, 2020.

[3] S. Lakshminarayana, Y. Xu, H. V. Poor, and T. Q. S. Quek, ``Cooperation of storage operation in a power network with renewable generation,'' IEEE Trans. Smart Grid, vol. 7, no. 4, pp. 2108_2122, Jul. 2016.

[4] Y. Geng, L. Zhu, X. Song, K. Wang, and X. Li, ``A modi_ed droop control for grid-connected inverters with improved stability in the _uc- tuation of grid frequency and voltage magnitude,'' IEEE Access, vol. 7, pp. 75658_75669, 2019.

[5] M. Farhadi and O. Mohammed, ``Energy storage technologies for high- power applications,'' IEEE Trans. Ind. Appl., vol. 52, no. 3, pp. 1953_1961, Jun. 2016

Multi-Mode Operation and Control of a Z-Source Virtual Synchronous Generator in PV Systems

 ABSTRACT:

 

The increasing penetration of power electronics-based distributed energy resources (DERs) displacing conventional synchronous generators is rapidly changing the dynamics of large-scale power systems. As the result, the electric grid loses inertia, voltage support, and oscillation damping needed to provide ancillary services such as frequency and voltage regulation. This paper presents the multi-mode operation of a Z-source virtual synchronous generator (ZVSG). The converter is a Z-source inverter capable of emulating the virtual inertia to increase its stability margin and track its frequency. The added inertia will protect the system by improving the rate of change of frequency. This converter is also capable of operating under normal and grid fault conditions while providing needed grid ancillary services. In normal operation mode, the ZVSG is working in MPPT mode where the maximum power generated from the PV panels is fed into the grid. During grid faults, a low voltage ride through control method is implemented where the system provides reactive power to reestablish the grid voltage based on the grid codes and requirements. The proposed system operation is successfully validated experimentally in the OPAL-RT real-time simulator.

 

KEYWORDS:

1.      Impedance-source inverter

2.      Virtual synchronous generator

3.      Photovoltaic (PV) systems

4.      Low voltage ride through

SOFTWARE: MATLAB/SIMULINK

SCHEMATIC DIAGRAM:

Figure 1. Proposed ZVSG Converter Equipped With VSG And LVRT Control Algorithms.

 

EXPECTED SIMULATION RESULTS:

 

Figure 2. Rocof Curves With Different Amounts Of (A) Inertia (H) And (B) Damping Constant (Dp ).

Figure 3. Comparison In Zvsg Current Increase While (A) The Converter Is Directly Connected (100(Ma)_3:2_10000 D 3200a) And (B) A Pre-Synchronizing Control Method Is Hired To Decrease The Current Increment (200(Ma)_1_5000 D 1000a).

 

Figure 4. Multi-Mode Operation Of The Zvsg During (A) Normal Operation (C) Voltage Sage Occurrence At T1 And Switching To Lvrt Mode And (D) Returning To Normal Mode At T2.

 

CONCLUSION:

This paper studied the multi-mode operation of an impedance-source virtual synchronous generator which is comprised of a single-stage ZSI, equipped with VSG control algorithm and is capable of providing grid ancillary services. Since the PLL may fail to detect the correct angle in case of harmonic distorted voltage, a virtual flux orientation control method is hired which can select the correct angle to be fed to Park transformation. The operation of the system has been tested while transitioning from islanded to grid-connected mode where, to protect the system against inrush current while connecting to the grid, a pre-synchronizing control method is used to minimize the phase difference between grid and converter. In addition, a solution to survive the system against voltage faults is embedded in the system which can regulate the reactive power based on the grid codes. Hence, the control paradigm will switch from MPP generation to LVRT mode after detecting voltage sag in the system. In this method, the peak of the grid current is kept constant during LVRT operation mode and ensures over current protection limit is not violated then. The ZVSG has been implemented in the OPAL-RT real-time digital simulator and its validity have been verified by conducting several case studies. The proposed seamless control frame- work helps to smoothly switch between normal and faulty conditions.

REFERENCES:

 

[1] K. Jiang, H. Su, H. Lin, K. He, H. Zeng, and Y. Che, ``A practical secondary frequency control strategy for virtual synchronous generator,'' IEEE Trans. Smart Grid, vol. 11, no. 3, pp. 2734_2736, May 2020.

[2] K. Shi, W. Song, H. Ge, P. Xu, Y. Yang, and F. Blaabjerg, ``Transient analysis of microgrids with parallel synchronous generators and virtual synchronous generators,'' IEEE Trans. Energy Convers., vol. 35, no. 1, pp. 95_105, Mar. 2020.

[3] J. Chen and T. O'Donnell, ``Parameter constraints for virtual synchronous generator considering stability,'' IEEE Trans. Power Syst., vol. 34, no. 3, pp. 2479_2481, May 2019.

[4] H. Cheng, Z. Shuai, C. Shen, X. Liu, Z. Li, and Z. J. Shen, ``Transient angle stability of paralleled synchronous and virtual synchronous generators in islanded microgrids,'' IEEE Trans. Power Electron., vol. 35, no. 8, pp. 8751_8765, Aug. 2020.

[5] H. Nian and Y. Jiao, ``Improved virtual synchronous generator control of DFIG to ride-through symmetrical voltage fault,'' IEEE Trans. Energy Convers., vol. 35, no. 2, pp. 672_683, Jun. 2020.

Multifunctional Control of Wind-Turbine Based Nano-Grid Connected to a Distorted Utility-Grid

ABSTRACT:

 This paper proposes a multifunctional control strategy and associated control algorithms for distributed wind-turbine (WT) based nano-grids connected to a distorted utility-grid. The contribution is on a new strategy with innovative control algorithms to coordinate multiple converters for a multitasking operation of the nano-grids. The novelty is on a unique control design with feasibilities:maximizing the generated power from WT, maintaining power quality in both ac- and dc-sides under critical conditions of the power grid, and improving power quality against distortion from local nonlinear loads under a reduced switching frequency. A robust fast-dynamic predictive control method is developed for current controllers to fulfil the multifunction. Unconstrained deadbeat control inputs are derived in twofold targets: ensuring fast dynamic response and significantly reducing both the computation and switching frequency for finite predictive control. The control system is applied on a permanent-magnet synchronous generator (PMSG) WT-based nano-grid connected to a distorted utility-grid. An OPAL-RT-based real-time platform is used for comparative studies among the proportional integration (PI) control, finite predictive control (FS-MPC), and proposed control method. The performance verification exhibits the power quality improvement in both the nano- and utility-grids under critical conditions via high-performed regulation of currents, voltages, reactive power, and rotor speed of the PMSG-WT.

KEYWORDS:

1.      Deadbeat control

2.      Distortion

3.      Finite predictive control

4.      Harmonic

5.      Permanent magnet synchronous generator (PMSG)

6.      Wind energy conversion system

7.      Unbalanced and distorted grid

 

SOFTWARE: MATLAB/SIMULINK

SCHEMATIC DIAGRAM:

Fig. 1. A generic diagram of a WT-based nano-grid connected to a distribution grid.

 EXPECTED SIMULATION RESULTS:

 

 

Fig. 2. Rotor-speed dynamic tracking-performances of the WT for maximum power extraction under wind-speed turbulence (7%). (a) The conventional PI control (PI.), (b) The proposed multifunctional control with fast-dynamic response design (Pro.).

 

Fig. 3. Comparative speed and current regulation of the MSC control between the conventional FCS-MPC (Fcs.) – Left and proposed control method (Pro.) – Right, (a) Comparative dynamic performances under step-change of reference speed and current, (b) The current regulation and average switching frequency.

Fig. 4. Comparative switching behaviors in the MSC control, (a) The conventional FCS-MPC (Fcs.), (b) The proposed control method (Pro.).

Fig. 5. Comparative performances of the grid-injected current regulation in the grid-interface converter under critical disturbances from two-phase-to-ground fault at a medium voltage bus, (a) The PI control, (b) The Pro. control.

Fig. 6. Comparative performances from Matlab/Simulink on the grid-injected current regulation under critical disturbances in the grid-voltages (i.e., harmonics and unbalance), (a) The PI control, (b) The Pro. control.

Fig. 7. Verification results obtained from OPAL-RT-based real-time systems for the current regulation of Pro. under critical utility-grid conditions. (a) Two- phases-to-ground grid-fault (a and b), (b) Unbalanced and harmonic distortion in the utility-grid voltage.

Fig. 8. Power quality compensation of the multifunction control in the nano-grid for distorted local loads. (a) Unbalanced and harmonic compensation for the local load currents, (b) Improvement of grid-voltages and grid-injected currents in a long-feeder connected to the nano-grid, reactive power compensation for the local loads.

 CONCLUSION:

In this paper, a new multifunctional control strategy for WT-based nano-grids was proposed with an innovative direct control method for fast-dynamic response and reduced switching frequency. The approach in a context of a nano-grid enables multitasking operation by coordinating multiple converters in the nano-grid and efficiently utilizes the full-scaled capacity of the PMSG system. The new algorithm combines the fastest digital control (i.e., deadbeat laws) and finite set control to neglect the conventional exhaustive search, complicated prediction, and objective function evaluation while significantly reducing the average switching frequency. Fast-dynamic control components are embedded into conventional local controllers for multitasking operation. The coordination among converters in the nano-grid improves the performance of the WT-based nano-grid on optimal power tracking, voltage and current regulation, dc-voltage regulations, and power quality compensation in the utility-grid. This paper proves the benefits of a new approach by coordinating multiple converters in a broader context of nano-grids in multitasking operation where the rated power of converters can be efficiently exploited in comparison with the conventional grid-connected WT-systems. Comparative results demonstrate the efficacy of the proposed strategy and its potential to extensively apply to various applications in power electronics and power systems.

REFERENCES:

[1] V. Yaramasu and B. Wu, Model Predictive Control of Wind Energy Conversion Systems. IEEE Press, 2016.

[2] F. Blaabjerg and Z. Chen, POWER ELECTRONICS FOR MODERN WIND, vol. 1, no. 1. 2005.

[3] H. The N., A. S. Al-Sumaiti, V. P. Vu, A. Al-Durra, and T. D. Do, “Optimal power tracking of PMSG based wind energy conversion systems by constrained direct control with fast convergence rates,” Int. J. Electr. Power Energy Syst., 2020.

[4] A. Uehara et al., “A coordinated control method to smooth wind power fluctuations of a PMSG-Based WECS,” IEEE Trans. Energy Convers., 2011.

[5] V. Yaramasu, A. Dekka, M. J. Durán, S. Kouro, and B. Wu, “PMSG-based wind energy conversion systems: Survey on power converters and controls,” IET Electr. Power Appl., vol. 11, no. 6, pp. 956–968, 2017.

Modeling and Coordinated Control Design for Brushless Doubly-Fed Induction Generator-Based Wind Turbine to Withstand Grid Voltage Unbalance

ABSTRACT:

 

Grid codes require wind turbines to have capability to withstand a certain grid voltage unbalance without tripping. However, existing controls for brushless doubly-fed induction generator (BDFIG) based wind turbine under grid unbalance have many problems such as difficulty in realizing decoupling control, involvement with flux or current estimations, and complex control structure. Moreover, the existing studies only focused on the control of machine side converter (MSC), but the coordinated control between MSC and grid side converter (GSC) and the control objectives of overall BDFIG wind turbine system have not yet been addressed so far. To overcome these problems and improve the control capability, this paper proposes a coordinated control strategy by considering MSC and GSC together. First, the enhanced control objectives for overall BDFIG wind turbine system are determined. Second, the simple single current closed-loop controllers without involving with any flux or current estimations are designed for MSC and

GSC, respectively. Meanwhile, in current loops, all the disturbances and cross-coupling terms on dq axes are derived and used for feedforward control so as to achieve decoupling control and improve system dynamic response. Further, a fast sequence decomposition approach is employed to enhance the control characteristics of the whole system. Finally, the effectiveness of proposed control is validated through case studies for a 2 MW BDFIG based wind generation system. The results demonstrate that the proposed control can effectively achieve the control objectives of overall wind turbine system under grid voltage unbalance and provide excellent dynamic and stable performance.

 KEYWORDS:

1.      Brushless doubly-fed induction generator (BDFIG)

2.      Voltage unbalance

3.      Decoupling control

       Wind turbine

      Sequence decomposition

SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

Fig.1. configuration of BDFIG-based wind turbine system

 EXPECTED SIMULATION RESULTS:

 

 

Figure 2. Sequence Decomposition Results Of Grid Voltage With Notch Filter And Fast Decomposition Algorithm. (A) Grid Voltage Vgabc (P.U.). (B) Positive Sequence Component In __ Reference Frame (P.U.) (C) Negative Sequence Component In  Reference Frame (P.U.). (D) Positive Sequence Component In (Dq)C Reference Frame (P.U.). (E) Negative Sequence Component In (Dq)􀀀 Reference Frame (P.U.). (A) Decomposition Method With Notch Filter. (B) Fast Sequence Decomposition Algorithm

 

Figure 3. Waveforms With Elimination Of Torque Oscillations And Three Selectable Control Objectives Under 10% Grid Voltage Unbalance (!R D 0:7 P.U., " D 10%). (A) Total Output Current (P.U.). (B) Gsc D- Axis And Pw Q- Axis Currents (P.U.). (C) Gsc Q- Axis And Pw D-Axis Currents (P.U.). (D) Gsc Dc Axis And Qc Axis Currents (P.U.). (E)Total Output Active Power (P.U.). (F) Pw And Gsc Active Power (P.U.). (G) Total Output Reactive Power (P.U.). (H) Pw And Gsc Reactive Power (P.U.). (I) Electromagnetic Torque (P.U.). (J) Dc Link Voltage (P.U.).

Figure 4. Waveforms With Two Control Modes Under " D 10% Grid Voltage Unbalance (!R D 1:2 P.U.). (A) Total Output Current (P.U.). (B) Pw Voltage (P.U.). (C) Gsc Current (P.U.). (D) Cw Current (P.U.). (E) Total Output Active Power (P.U.). (F) Pw And Gsc Active Power (P.U.). (G) Total Output Reactive Power (P.U.). (H) Pw And Gsc Reactive Power (P.U.). (I) Bdfig Electromagnetic Torque (P.U.). (J) Dc Link Voltage (P.U.). (A) Control Mode 1. (B) Control Mode 2.

 

Figure 5. Waveforms With Variation Of Rotating Speed Under " D 10% Grid Voltage Unbalance. (A) Total Output Current (P.U.). (B) Cw Current (P.U.). (C) Total Output Active Power (P.U.). (D) Pw And Gsc Active Power (P.U.) (E) Total Output Reactive Power (P.U.). (F) Pw And Gsc Reactive Power (P.U.). (G) Mechanical Torque And Electromagnetic Torque (P.U.). (H) Rotor Rotating Speed (P.U.). (I) Dc Link Voltage (P.U.).

 

CONCLUSION:

In this paper, the mathematical model of BDFIG based wind turbine system under grid voltage unbalance is derived in detail. Based on such model, a coordinated control strategy by considering MSC and GSC together is proposed. Compared to existing controls, proposed control for MSC is greatly simplified and more applicable and has much better parameter robustness due to adopting single current loop control structure without involving with PW flux, CW flux, and rotor current estimations. Meanwhile, in cur- rent loop, all the cross-coupling terms and disturbances are derived and used for feedforward control, thus decoupling controls for the d-axis and q-axis currents as well as the average PW active and reactive power can be achieved. On the other hand, GSC is used to realize coordinated control with MSC so as to achieve three selectable enhanced control objectives, i.e., eliminating unbalanced total output current, oscillations of the total output active or reactive power. Further, a fast sequence decomposition approach instead of notch filers and enhanced PLL for MSC and GSC are employed to improve the control characteristics of the whole system. The effectiveness of proposed control is verified by means of theoretical analysis and case studies. The results demonstrated that the proposed control can improve the capability of withstanding grid voltage unbalance significantly and provide excellent dynamic and stable performance.

REFERENCES:

 

[1] W. Xu, M. G. Hussien, Y. Liu, M. R. Islam, and S. M. Allam, ``Sensorless voltage control schemes for brushless doubly-fed induction generators in stand-alone and grid-connected applications,'' IEEE Trans. Energy Convers., vol. 35, no. 4, pp. 1781_1795, Dec. 2020.

[2] Z. Li, X. Wang, M. Kong, and X. Chen, ``Bidirectional harmonic current control of brushless doubly fed motor drive system based on a fractional unidirectional converter under a weak grid,'' IEEE Access, vol. 9, pp. 19926_19938, 2021.

[3] Y. Cheng, B. Yu, C. Kan, and X.Wang, ``Design and performance study of a brushless doubly fed generator based on differential modulation,'' IEEE Trans. Ind. Electron., vol. 67, no. 12, pp. 10024_10034, Dec. 2020.

[4] F. Zhang, S. Yu, Y. Wang, S. Jin, and M. G. Jovanovic, ``Design and performance comparisons of brushless doubly fed generators with different rotor structures,'' IEEE Trans. Ind. Electron., vol. 66, no. 1, pp. 631_640, Jan. 2019.

[5] I. A. Gowaid, A. S. Abdel-Khalik, A. M. Massoud, and S. Ahmed, ``Ride-through capability of grid-connected brushless cascade DFIG wind turbines in faulty grid conditions_A comparative study,'' IEEE Trans. Sustain. Energy, vol. 4, no. 4, pp. 1002_1015, Oct. 2013.

Inertia And Damping Analysis Of Grid-Tied Photovoltaic Power Generation System With Dc Voltage Droop Control

ABSTRACT:

Photovoltaic power generation relies on power electronics and therefore does not have natural inertia and damping characteristics. In order to make the capacitance of the medium time scale participate in the grid frequency response without adding additional equipment, this paper takes the grid-connected photovoltaic power generation system based on DC voltage droop control as the research object, and establishes the static synchronous generator (SSG) model of the system. The model is used to analyze the main parameters affecting the inertia, damping and synchronization characteristics of the system and their influence laws. The research results show that the energy storage effect of the capacitor on the medium time scale can also make the system exhibit certain inertia characteristics. From the point of view of control parameters, as the droop coefficient Dp decreases, the inertia characteristic exhibited by the system is stronger. The larger the DC voltage outer loop proportional coefficient Kp is, the stronger the damping effect of the system is. The larger the DC voltage outer loop integral coefficient Ki, the stronger the synchronization capability of the system. In addition, the MATLAB/Simulink simulation platform is used to verify the correctness of the theoretical analysis results.

KEYWORDS:

1.      Grid-connected photovoltaic power generation system

2.      DC voltage droop control

3.      Inertia characteristic

4.      Damping effect

5.      Synchronization ability

 

SOFTWARE: MATLAB/SIMULINK

SCHEMATIC DIAGRAM:

 Figure 1. Grid-Connected Photovoltaic Power Generation System Based On Dc Voltage Droop Control.

 EXPECTED SIMULATION RESULTS

Figure 2. Influence Of Different Parameter Changes On System Inertia.

Figure 3. Influence Of Different Parameter Changes On System Inertia.

Figure 4. Influence Of Droop Coefficient Dp On Dc Voltage.

Figure 5. Influence Of Droop Coefficient Dp On System Power.

Figure 6. The Influence Of P Controller On Dc Voltage.

Figure 7. The Influence Of P Controller On System Power.

Figure 8. The Influence Of I Controller On Dc Voltage.

Figure 9. The Influence Of I Controller On System Power.

 CONCLUSION:

 This paper introduces a new GFC scheme for PV systems that do not employ real-time estimation of the MPP and make optimal use of the limited power reserves. By operating in full or limited grid-forming mode, the PV plant preserves its voltage source nature and manages to assist the grid during disturbances similarly or even better than synchronous machines. The modified current saturation scheme performs smoothly, without any need for fault detection or control switching.  Replacing SMs with PV GFC results in improved frequency profile during load disturbances due to faster response from the PV plant, and comparable terminal voltage profiles during faults despite the strict inverter over current limits. However, the PV GFC introduces another source of disturbances to the power system resulting from irradiance transients during cloud movement.

Inverters in GFL mode with ancillary services can support the grid during disturbances, but the contribution becomes limited as the system strength decreases. The GFC mode of inverter operation is the way forward for the renewables-rich and inverter-dominated power systems of the future.  Future work involves a complete investigation of the dynamic interactions between GFC and GFL inverters and the rest of the power system at various sizes and generation mixtures. Similarly, a methodology to determine the appropriate ratio of GFC and GFL resources would be very useful in converter-dominated power systems. Furthermore, the proposed method is designed for uniform illumination, which is the common assumption for utility-scale PV systems; an extension of the method to partial shading would improve its credibility and reliability at all possible conditions.

REFERENCES:

[1] F. Milano, F. Dörfler, G. Hug, D. J. Hill, and G. Verbič, "Foundations and challenges of low-inertia systems (Invited Paper)," Power Syst. Comp. Conf. (PSCC), Dublin, Ireland, 2018.

[2] C. Loutan, P. Klauer, S. Chowdhury, S. Hall, M. Morjaria, V. Chadliev, N. Milam, C. Milan, and V. Gevorgian, “Demonstration of essential reliability services by a 300-MW solar photovoltaic power plant,” National Renewable Energy Lab. (NREL), Golden, CO, United States, Rep. NREL/TP-5D00-67799, 2017.

[3] ENTSO-E, “Need for synthetic inertia (SI) for frequency regulation: ENTSO-E guidance document for national implementation for network codes on grid connection,” ENTSO-E, Brussels, Belgium, Tech. Guideline, Jan. 2018.

[4] J. C. Hernandez, P. G. Bueno, and F. Sanchez-Sutil, “Enhanced utility-scale photovoltaic units with frequency support functions and dynamic grid support for transmission systems,” IET Ren. Power Gen., vol. 11, no. 3, pp. 361-372, Jan. 2017.

[5] C. Guo, S. Yang, W. Liu, C. Zhao, and J. Hu, "Small-signal stability enhancement approach for VSC-HVDC system under weak AC grid conditions based on single-input single-output transfer function model," IEEE Trans. Power Del., to be published. DOI: 10.1109/TPWRD.2020.3006485.