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Dash, D.K.; Sadhu, P.K. Grid-Connected Active Power Filter. Encyclopedia. Available online: (accessed on 15 June 2024).
Dash DK, Sadhu PK. Grid-Connected Active Power Filter. Encyclopedia. Available at: Accessed June 15, 2024.
Dash, Dipak Kumar, Pradip Kumar Sadhu. "Grid-Connected Active Power Filter" Encyclopedia, (accessed June 15, 2024).
Dash, D.K., & Sadhu, P.K. (2023, May 22). Grid-Connected Active Power Filter. In Encyclopedia.
Dash, Dipak Kumar and Pradip Kumar Sadhu. "Grid-Connected Active Power Filter." Encyclopedia. Web. 22 May, 2023.
Grid-Connected Active Power Filter

Renewable energy sources such as photovoltaic (PV) and wind energies are integrated into the grid due to their low global emissions and higher power conversion efficiency techniques. Grid-connected inverters are the core components of distributed generation networks. However, several harmonic current and voltage variations affect the performance of circuits in grid-connected networks. These issues can be easily resolved using passive filters, static vector generators, and dynamic energy filters (APFs). 

APF inverter PV WECS power quality

1. Introduction

In contemporary developments, the demand for electricity from households to businesses is increasing swiftly, reducing energy supply and leading to network outages. To maximize energy production and efficiency and dependability have led to the implementation of distributed electricity [1][2], such as PV systems [3], optimization [4], energy storage [5], wind turbines [6][7], fuel cells [8], distributed power systems [9]. PV and wind energy are two of the most important renewable energy sources for reducing the demand on the national utility and the global environment.
However, the integration of PV and wind power into the grid generates a certain level of harmonic, heat, and other difficult problems in terms of quality and other energy issues. These issues have a negative effect on the variation of the current and voltage sine waves [10], leading to decreased system performance [11], transformer overheating, increased motor and cable malfunction, and increased power loss [12]. To make the solar grid system more reliable, necessary harmonic and energy reduction techniques must be implemented. Various solutions for power quality issues [13] have been proposed, including unbalanced power grids, load equilibrium, harmonic injection, unavoidable neutral current, reactive power load, and electrical device intervention. In grid-integrated applications, filters are commonly combined with a passive filter to combat serial harmonic systems.
However, passive filters are constrained by issues such as limited filters, certain load ranges, fixed compensation, large grid sizes, and negative grid and series impedances [14][15][16][17], which enable the passive components to degrade rapidly [18]. In examinations of interconnected devices such as wind turbines and inverters [19], advanced filtering technologies such as a static sync compensator, an active power filter (APF), a dynamic voltage meter, multistage inverters, and a consistent power quality control system will be discussed. The APF shunt is the most widespread and permissive method for this (SAPF). The basis of filter efficiency is the current filters, inverter parameters, and controller [20][21]. The APF is effectively regulated by p-theory, straightforward positive sequences, and synchro [22] detection. Currently, techniques for harmonic load detection are used to generate a reference signal. International standards such as IEEE-59 [23][24] and IEC a 61000-3-2 [25] impose constraints on the design and operation of electricity utility networks. In addition, the APF rating [26] is increasing in terms of demand for loads, power accumulation, and prices. For SAPF and PF customization, hybrid APF (HAPF) [27] is used. To eradicate low-order harmonics, the HAPF is powered by both SAPF [28] filters and PF for high-frequency harmonics [29]. APFs reduce load disturbances and increase compensation for harmonic voltage and current. The part of power filters based on power rating and faster response is depicted in Figure 1.
Figure 1. Subdivision of power filter based on power rating and speed of response.
However, a reduced transformer topology results in cleaner and more stable units, smaller volume capacities [30], lower costs [31], and more compact systems [32] than older topologies. Table 1 provides a fast comparison of the topologies of various grid-connected PV systems. The total cost of the device is weighed against three issues: a galvanic link [33], a fluctuation in the net voltage of the input pole to the ground [34], and safety, as well as transmission cost and system efficiency [35][36][37][38].
Table 1. Analysis of APFs in the grid-interconnected scheme.
The alternating current network power is utilized by electrical transmission systems and loads [39], whereas the direct current (DC) drives the green energy outgoing voltage. In both stand-alone and network-connected systems, an inverter is necessary to convert alternating current (AC) electricity into direct current (DC). It is utilized to generate an alternating current output with a sinusoidal waveform using the same collection of electronics, ranging from low power KW to high power MW [40][41]. Inverters are actively being designed and are extremely useful for large-scale wind and photovoltaic applications. Despite demand, most power-switching components, such as IGBTs and metal oxide field effect bipolar transistors, pose a significant challenge for converters (MOSFETs). Many pure SAPFs are minimized by using the higher power classification elements to improve the correction of the utility component and current harmonic compensations. As the system becomes more related to the grid, the increase in semiconductor switching components causes more switch losses, contributes to harmonic waveform power output voltage, lowers system efficiency [42], and defines system efficiency [43]. State-of-the-art solution in power electronics such as power semiconductors, circuit, sensor, and control circuit has recently been developed with reduced switch counting [44]. Although the reduction in components is essential in advancing energy problems, there is little literature regarding the reduction in APFs. The extensive research indicates progress in APF switching reduction and emphasis on grid-connected inverter cost, size, and weight loss. This document includes a comprehensive, systematic analysis of the literature by experts on reduction mechanisms and power transmission systems for grid-linked photovoltaic and wind energy systems. For PV APFs and WECS, some areas of research include module reduction, fewer inverters, and multispeed multifunctional inverters (ML-MFIs). In comparison to existing THD-based topologies, harmonic mitigation, active and reactive power adjustment, component speeds, and benefits, the new topology is more efficient and offers more advantages. Researchers are paying little attention to the study, which is being utilized to create and test more switching prevention approaches.

2. Harmonics Mitigation and Distributed Device Generation

2.1. Grid-Synchronized APF-PV Based Inverter

The main goal of installing a PCC (point of common coupling) [45] is to improve the operation and efficiency of power delivery systems. In interactive PV grid topologies, it is common to pair a PV inverter with an SAPF (active power filter) [46] and a voltage and reactive control superstation in order to prevent the costs of the power circuit from rising too high. The PV inverter converts the electricity produced by the solar photovoltaic device into usable electricity, while also filtering the harmonics of the load current [47][48][49]. Integrating an APF into the grid-connected PV system enhances its performance, reliability, and reduces current harmonic distortions [50][51][52][53][54][55][56].
A recent evaluation places the ML-MFI (multispeed multifunctional inverter) at the top of the list of innovative power generation technologies that have been incorporated into the PV grid. PV and magnetic field induction are two of these devices. By using harmonic distortion measurements that are kept to a minimum while working at a high DC–rated voltage, the output waveform is clear and free of distortion. Multifunctional inverters must handle several issues, including grid power and imbalance harmonic mitigation, reactive energy compensation, PCC voltage [57][58], and the period between PV and power grids during APF operations.
Table 2 analyzes reactive power compensation in grid-integrated PV inverter setups and additional APF functions. In references [59][60], PWM (pulse-width modulation) space-vector twist-driven technology is used to build a three-level PV system with an SVSPWM (space-vector pulse-width modulation) for effective grid filtering [61], compensatory management, and power balancing [62].
Table 2. Parameters of reactive power compensation control impacted devices.
SAPF provides harmonic removal for the PV-harmonic network and a process for compensating for reactive energy to keep a constant voltage throughout the DC connection [63]. An acceptable statistical model is required to have controls that are more isolated from the variance of parameter values [64]. Energy storage devices such as batteries, super capacitors, and flywheels are made to handle the intermediate issues that arise in a solar photovoltaic system. Due to the inherent characteristics of photovoltaic systems, the rate of electricity generation can fluctuate, which can have a detrimental impact on the network’s effectiveness. Energy storage devices help maintain a constant voltage [65], lower voltage fluctuations [66], and improve solar panel efficiency [67]. The optimized PV grid system performance also leads to a reduction in harmonic content and better reactive potential control.

2.2. Wind Energy APF Grid-Interlinked

Recently, the use of renewable energy has risen in importance within the energy industry. With time, wind energy has improved in terms of legality, cost, and usability [68]. With no greenhouse gas emissions, a progressive, open, and scalable clean energy supply that guarantees that electricity demand is met and a more environmentally friendly energy distribution network, wind energy is also more affordable than fossil fuels and solar energy [69]. It is also more cost-effective than both of these sources of energy. However, achieving a power economy in grid-connected WECS is a challenging issue. The necessity for WECS installation with the main grid has an impact on reactive control, voltage spikes, switching, and flickering, as well as power and performance at the PCC during operations. Basic functions of variable speed in WECS include active regulation, reactive regulation, and the comparability of nonlinear and unbalanced loads. Nonlinear-control devices [70], which increase thermal efficiency while decreasing system efficiency, result in excessive tension, current, and WECS output degradation [71], as well as decreased WECS 4durability [72]. To accomplish even greater energy efficiency, WECS uses a network of harmonic reduction and reactive power compensation technologies [73]. When operating an APF to reduce existing harmonics, a WECS gives the PMSG for continuous wind speed [74]. An upstream modified modulation method based on various signal extraction techniques is used to control an APF device. To eliminate the harmonics and serve as APF in an island mode, a WECS [64] variable frequency-based technique is used that is even more sophisticated. WECS used electricity from APF in insulating mode by employing a fixed-rpm doubly fed induction generator (DFIG). To minimize conversion costs, the WECS approach employs a reduced-count topology [75]. The back-to-back converters in this area of voltage imbalance are split capacitors. In this configuration, there are issues with the separation between the grid and several PMSGs. It is necessary to add more DC connection condensers, increase the voltage significantly, and raise the semiconductor stress [76]. Reactive capacity monitoring and offsetting, a crucial component of the power supply system, are included in the networked WECS. To prevent losses in the transmission of reactive electricity to the power grid, it is essential to keep a constant voltage profile. The load tap changer transformer is one of the most crucial parts of the grid’s reactive energy compensation mechanism. Additionally, many WECS produce low volts and reactive power in a combined induction generator [77]. Solutions include STATCOM, SVC, on-load tap shifters (OLTCs), transformer condensers, PWM inverters, and condenser and inductor combinations [78]. DBR, OLTC, and manually switched condensing systems are some examples of technologies that are unable to overcome harmonics and voltage gaps. SVC, STATCOM, and DFIG systems have been added to fixed-speed wind turbines to increase their reactive output and dynamic stability [79]. By preserving the voltage equilibrium [76], these technologies enable grid-connected networks to use more wind energy. The WECS network is connected to the power-compensating systems. In Table 2 Reactive power compensation systems such as automatic voltage control (AVC), on-load tap changers (OLTC), dynamic voltage regulators (DERS), SBBR, STATCOM, static VAR controls (SVC), and thyristor-controlled sequencing (TCSC) are compared.


  1. Wu, G.; Ruan, X.; Ye, Z. Non-isolated high step-up DC–DC converters adopting switched-capacitor cell. IEEE Trans. Ind. Electron. 2015, 62, 383–393.
  2. Liang, T.-J.; Lee, J.-H.; Chen, S.-M.; Chen, J.-F.; Yang, L.-S. Novel isolated high-step-up DC–DC converter with voltage lift. IEEE Trans. Ind. Electron. 2013, 60, 1483–1491.
  3. Sitbon, M.; Schacham, S.; Suntio, T.; Kuperman, A. Improved adaptive input voltage control of a solar array interfacing current mode controlled boost power stage. Energy Convers. Manag. 2015, 98, 369–375.
  4. Lotfy, M.E.; Senjyu, T.; Farahat, M.A.; Abdel-Gawad, A.F.; Yona, A. Enhancement of a small power system performance using multi-objective optimization. IEEE Access 2017, 5, 6212–6224.
  5. Cumulative Development of Various Renewable Energy System/Devices in Country. Available online: (accessed on 30 April 2017).
  6. Pathan, N.T.; Adhau, S.P.; Adhau, P.G.; Sable, M. MPPT for grid connected hybrid wind driven PMSG-solar PV power generation system with single stage converter. J. Elect. Power Syst. Eng. 2017, 3, 41–59.
  7. Li, S.; Li, J. Output predictor-based active disturbance rejection control for a wind energy conversion system with PMSG. IEEE Access 2017, 5, 5205–5214.
  8. Fathabadi, H. Novel highly accurate universal maximum power point tracker for maximum power extraction from hybrid fuel cell/photovoltaic/wind power generation systems. Energy 2016, 116, 402–416.
  9. Fathabadi, H. Novel fast and high accuracy maximum power point tracking method for hybrid photovoltaic/fuel cell energy conversion systems. Renew. Energy 2017, 106, 232–242.
  10. Fathabadi, H. Novel high-efficient unified maximum power point tracking controller for hybrid fuel cell/wind systems. Appl. Energy 2016, 183, 1498–1510.
  11. Hong, C.M.; Chen, C.H. Intelligent control of a grid-connected wind-photovoltaic hybrid power systems. Int. J. Elect. Power Energy Syst. 2014, 55, 554–561.
  12. Baghdadi, F.; Mohammedi, K.; Diaf, S.; Behar, O. Feasibility study and energy conversion analysis of stand-alone hybrid renewable energy system. Energy Convers. Manag. 2015, 105, 471–479.
  13. Bhandari, B.; Poudel, S.R.; Lee, K.-T.; Ahn, S.-H. Mathematical modeling of hybrid renewable energy system: A review on small hydro- solar-wind power generation. Int. J. Precis. Eng. Manuf. Green Technol. 2014, 1, 157–173.
  14. Kwan, T.H.; Wu, X. Maximum power point tracking using a variable antecedent fuzzy logic controller. Sol. Energy 2016, 137, 189–200.
  15. Kabalci, E. Design and analysis of a hybrid renewable energy plant with solar and wind power. Energy Convers. Manag. 2013, 72, 51–59.
  16. Dihrab, S.S.; Sopian, K. Electricity generation of hybrid PV/wind systems in Iraq. Renew. Energy 2013, 35, 1303–1307.
  17. Kirubakaran, A.; Jain, S.; Nema, R.K. The PEM fuel cell system with DC/DC boost converter: Design, modeling and simulation. Int. J. Recent Trends Eng. 2009, 1, 157–161.
  18. Nejabatkhah, F.; Danyali, S.; Hosseini, S.H.; Sabahi, M.; Niapour, S.M. Modeling and control of a new three-input DC–DC boost converter for hybrid PV/FC/battery power system. IEEE Trans. Power Electron. 2012, 27, 2309–2324.
  19. Revathi, B.S.; Prabhakar, M. Non-isolated high gain DC-DC converter topologies for PV applications—A comprehensive review. Renew. Sustain. Energy Rev. 2016, 66, 920–933.
  20. Montuori, L.; Alcázar-Ortega, M.; Álvarez-Bel, C.; Domijan, A. Integration of renewable energy in microgrids coordinated with demand response resources: Economic evaluation of a biomass gasification plant by Homer Simulator. Appl. Energy 2014, 132, 15–22.
  21. Zhao, B.; Zhang, X.; Li, P.; Wang, K.; Xue, M.; Wang, C. Optimal sizing, operating strategy and operational experience of a stand-alone microgrid on Dongfushan Island. Appl. Energy Jan. 2014, 113, 1656–1666.
  22. Kuhn, V.; Klemeš, J.; Bulatov, I. MicroCHP: Overview of selected technologies, products and field test results. Appl. Therm. Eng. 2008, 28, 2039–2048.
  23. Patel, N.; Gupta, N.; Babu, B.C. Design, Development, and Implementation of Grid-Connected Solar Photovoltaic Power Conversion System. Energy Sources Part A Recovery Util. Environ. Eff. 2019, 43, 1–20.
  24. Ranaboldo, M.; Lega, B.D.; Ferrenbach, D.V.; Ferrer-Martí, L.; Moreno, R.P.; GarcíaVilloria, A. Renewable energy projects to electrify rural communities in Cape Verde. Appl. Energy 2014, 118, 280–291.
  25. Ma, T.; Yang, H.; Lu, L. A feasibility study of a stand-alone hybrid solar–wind– battery system for a remote island. Appl. Energy 2014, 121, 149–158.
  26. Deshmukh, M.K.; Deshmukh, S.S. Modeling of hybrid renewable energy systems. Renew. Sustain. Energy Rev. 2008, 12, 235–249.
  27. Natarajan, K.; Sankaramoorthy, M.; Rajkumar, A.; Shamshabad, T.; Kandlakoya, T. Controlling the Power Loss in Radial Distribution Network by Optimally Placing UPQC through Reconfiguration Using Evolutionary Algorithms. Int. J. Pure Appl. Math. 2018, 118, 161–179.
  28. Calise, F.; Cipollina, A.; Dentice d’Accadia, M.; Piacentino, A. A novel renewable poly generation system for a small Mediterranean volcanic island for the combined production of energy and water: Dynamic simulation and economic assessment. Appl. Energy 2014, 135, 675–693.
  29. Chen, H.-C. Optimum capacity determination of stand-alone hybrid generation system considering cost and reliability. Appl. Energy 2013, 103, 155–164.
  30. Perera, A.T.D.; Attalage, R.A.; Perera, K.K.C.K.; Dassanayake, V.P.C. A hybrid tool to combine multi-objective optimization and multi-criterion decision making in designing standalone hybrid energy systems. Appl. Energy 2013, 107, 412–425.
  31. Perera, A.T.D.; Attalage, R.A.; Perera, K.K.C.K.; Dassanayake, V.P.C. Designing standalone hybrid energy systems minimizing initial investment, life cycle cost and pollutant emission. Energy 2013, 54, 220–230.
  32. Bhandari, B.; Lee, K.-T.; Lee, C.S.; Song, C.-K.; Maskey, R.K.; Ahn, S.-H. A novel off-grid hybrid power system comprised of solar photovoltaic, wind, and hydro energy sources. Appl. Energy 2014, 133, 236–242.
  33. Esmaeili, M.; Shayeghi, H.; Valipour, K.; Safari, A.; Sedaghati, F. Power quality improvement of multimicrogrid using improved custom power device called as distributed power condition controller. Int. Trans. Electr. Energy Syst. 2020, 30, e12259.
  34. Bekele, G.; Tadesse, G. Feasibility study of small Hydro/PV/Wind hybrid system for off-grid rural electrification in Ethiopia. Appl. Energy 2012, 97, 5–15.
  35. Bekele, G.; Palm, B. Feasibility study for a standalone solar–wind-based hybrid energy system for application in Ethiopia. Appl. Energy 2010, 87, 487–495.
  36. Rehman, S.; Mahbub Alam, M.; Meyer, J.P.; Al-Hadhrami, L.M. Feasibility study of a wind–pv–diesel hybrid power system for a village. Renew. Energy 2012, 38, 258–268.
  37. Fadaee, M.; Radzi, M.A.M. Multi-objective optimization of a stand-alone hybrid renewable energy system by using evolutionary algorithms: A review. Renew. Sustain. Energy Rev. 2012, 16, 3364–3369.
  38. Abbes, D.; Martinez, A.; Champenois, G. Life cycle cost, embodied energy and loss of power supply probability for the optimal design of hybrid power systems. Math. Comput. Simul. 2014, 98, 46–62.
  39. Hu, Y.; Solana, P. Optimization of a hybrid diesel-wind generation plant with operational options. Renew. Energy 2013, 51, 364–372.
  40. Kaldellis, J.K.; Kavadias, K.A.; Filios, A.E. A new computational algorithm for the calculation of maximum wind energy penetration in autonomous electrical generation systems. Appl. Energy Jul. 2009, 86, 1011–1023.
  41. Alsayed, M.; Cacciato, M.; Scarcella, G.; Scelba, G. Multicriteria optimal sizing of photovoltaic-wind turbine grid connected systems. IEEE Trans. Energy Convers. 2013, 28, 370–379.
  42. Ma, T.A.; Yang, H.; Lu, L.; Peng, J. Technical feasibility study on a standalone hybrid solar-wind system with pumped hydro storage for a remote island in Hong Kong. Renew. Energy 2014, 69, 7–15.
  43. Kapsali, M.; Anagnostopoulos, J.S.; Kaldellis, J.K. Wind powered pumped-hydro storage systems for remote islands: A complete sensitivity analysis based on economic perspectives. Appl. Energy 2012, 99, 430–444.
  44. Baquero, G.; Esteban, B.; Riba, J.-R.; Rius, A.; Puig, R. An evaluation of the life cycle cost of rapeseed oil as a straight vegetable oil fuel to replace petroleum diesel in agriculture. Biomass Bioenergy 2011, 35, 3687–3697.
  45. Saremi, S.; Mirjalili, S.; Lewis, A. Grasshopper optimization algorithm: Theory and application. Adv. Eng. Softw. 2017, 105, 30–47.
  46. Lakum, A.; Mahajan, V. Optimal placement and sizing of multiple active power filters in radial distribution system using grey wolf optimizer in presence of nonlinear distributed generation. Electr. Power Syst. Res. 2019, 173, 281–290.
  47. Moghbel, M.; Masoum, M.A.; Fereidouni, A.; Deilami, S. Optimal sizing, siting and operation of custom power devices with STATCOM and APLC functions for real-time reactive power and network voltage quality control of smart grid. IEEE Trans. Smart Grid 2017, 9, 5564–5575.
  48. Li, Y.; Feng, B.; Li, G.; Qi, J.; Zhao, D.; Mu, Y. Optimal distributed generation planning in active distribution networks considering integration of energy storage. Appl. Energy 2018, 210, 1073–1081.
  49. Sarker; Goswami, S. Optimal location of unified power quality conditioner in distribution system for power quality improvement. Int. J. Electr. Power Energy Syst. 2016, 83, 309–324.
  50. Lund, H. Renewable energy strategies for sustainable development. Energy 2007, 32, 912–919.
  51. Shahzad, M.K.; Zahid, A.; Rashid, T.; Rehan, M.A.; Ali, M.; Ahmad, M. Techno-economic feasibility analysis of a solar-biomass off grid system for the electrification of remote rural areas in Pakistan using HOMER software. Renew. Energy 2017, 106, 264–273.
  52. Sen, R.; Bhattacharyya, S.C. Off-grid electricity generation with renewable energy technologies inIndia: An application of HOMER. Renew. Energy 2014, 62, 388–398.
  53. Patel, A.M.; Singal, S.K. Economic analysis of integrated renewable energy system for electrification of remote rural area having scattered population. Int. J. Renew. Energy Res. 2018, 8, 523–539.
  54. Yang, H.; Lu, L.; Zhou, W. A novel optimization sizing model for hybrid solar-wind power generation system. Sol. Energy 2007, 81, 76–84.
  55. Januar, R. Comparative Analysis of 20-MW Solar Thermal and PV Power Plant in Rongkop, Indonesia Using LCOE Simulation Method. J. Clean Energy Technol. 2017, 5, 383–388.
  56. Das, H.S.; Dey, A.; Wei, T.C.; Yatim, A.H.M. Feasibility analysis of standalone PV/wind/battery hybrid energy system for rural Bangladesh. Int. J. Renew. Energy Res. 2016, 6, 402–412.
  57. Mousa, M.; Sagar, V.R.; Gajbhiye, V.T.; Kumar, R. Pesticides persistence in/on fresh and dehydrated brinjal. J. Food Sci. Technol. 2004, 41, 429–431.
  58. Kamran, M.; Asghar, R.; Mudassar, M.; Ahmed, S.R.; Fazal, M.R.; Abid, M.I.; Zameer, M.Z. Designing and optimization of stand-alone hybrid renewable energy system for rural areas of Punjab, Pakistan. Int. J. Renew. Energy Res. 2018, 8, 2585–2597.
  59. Dash, D.K.; Sadhu, P.K.; Subudhi, B. Spider monkey optimization (SMO) – lattice Levenberg–Marquardt recursive least squares based grid synchronization control scheme for a three-phase PV system. Arch. Control. Sci. 2021, 31/3, 707–730.
  60. Bouakkaz, A.; Haddad, S.; Martín-García, J.A.; Gil-Mena, A.J.; Jiménez-Castañeda, R. Optimal scheduling of household appliances in off-grid hybrid energy system using PSO algorithm for energy saving. Int. J. Renew. Energy Res. 2019, 9, 427–436.
  61. Okonkwo, E.C.; Okwose, C.F.; Abbasoglu, S. Techno-economic analysis of the potential utilization of a hybrid PV-wind turbine system for commercial buildings in Jordan. Int. J. Renew. Energy Res. 2017, 7, 908–914.
  62. Bai, S.; Rao, K.V.S. Design and integration of solar-biomass hybrid energy system for drip irrigation pumping. J. Chem. Pharm. Sci. 2014, 247–248.
  63. Adaramola, M.S.; Agelin-Chaab, M.; Paul, S.S. Analysis of hybrid energy systems for application in southern Ghana. Energy Convers. Manag. 2014, 88, 284–295.
  64. Kim, S.-K.; Jeon, J.-H.; Cho, C.-H.; Ahn, J.-B.; Kwon, S.-H. Dynamic modeling and control of a grid-connected hybrid generation system with versatile power transfer. IEEE Trans. Ind. Electron. 2018, 55, 1677–1688.
  65. Arivoli, S.; Karthikeyan, R.; Chitra, V. Implementation of Suitable Control Strategy for Improved Dynamics in Hybrid Grid Connected System. In Proceedings of the 2021 International Conference on Computer Communication and Informatics (ICCCI), Coimbatore, India, 27–29 January 2021; pp. 1–7.
  66. Elsayed, A.T.; Mohamed, A.A.; Mohammed, O.A. DC microgrids and distribution systems: An overview. Electr. Power Syst. 2015, 119, 407–417.
  67. Naresh, M.; Tripathi, R.K. Intelligent control strategy for power management in hybrid renewable energy system. In Proceedings of the 2019 Innovations in Power and Advanced Computing Technologies (i-PACT), Vellore, India, 22–23 March 2019; pp. 1–5.
  68. Soliman, M.A.; Hasanien, H.M.; Azazi, H.Z.; El-kholy, E.E.; Mahmoud, S.A. Hybrid ANFIS-GA-based control scheme for performance enhancement of a grid-connected wind generator. IET Renew. Power Gener. 2018, 12, 832–843.
  69. García, P.; García, C.A.; Fernández, L.M.; Llorens, F.; Jurado, F. ANFIS-Based Control of a Grid-Connected Hybrid System Integrating Renewable Energies Hydrogen and Batteries. IEEE Trans. Ind. Inform. 2014, 10, 1107–1117.
  70. Hornik, T.; Qing-Chang, Z. A current-control strategy for voltagesource inverters in microgrids based onH∞ and repetitive control. IEEE Trans. Power Electron. 2011, 26, 943–952.
  71. Lamichhane, A.; Zhou, L.; Yao, G.; Luqman, M. LCL Filter Based Grid-Connected Photovoltaic System with Battery Energy Storage. In Proceedings of the 2019 14th IEEE Conference on Industrial Electronics and Applications (ICIEA), Xi’an, China, 19–21 June 2019; pp. 1569–1574.
  72. Patel, N.; Kumar, A.; Gupta, N.; Ray, S.; Babu, B.C. Optimized PI-4VPI Current Controller for Three-Phase Grid-integrated Photovoltaic Inverter under Grid Voltage Distortions. IET Renew. Power Gener. 2019, 14, 779–792.
  73. Iqbal, M.M.; Kafiul, I. Design and Simulation of A PV System with Battery Storage Using Bidirectional DC-DC Converter Using Matlab Simulink. Int. J. Sci. Technol. Res. 2017, 7, 403.
  74. Ruan, X.; Wang, X.; Pan, D.; Yang, D.; Li, W.; Bao, C. Introduction. In Control Techniques for LCL-Type Grid-Connected Inverter; Springer: Singapore, 2017; pp. 1–23.
  75. Guo, Y.; LI, J.; Shi, T.; Wang, X.; Miao, M. Research on Coordinated Control Strategies of Hybrid PV/CSP Power Plants. In Proceedings of the 2018 China International Conference on Electricity Distribution (CICED), Tianjin, China, 17–19 September 2018; pp. 2077–2081.
  76. Seema; Singh, B. Grid synchronization control for an autonomous PV-wind-battery based microgrid. In Proceedings of the 2018 IEEMA Engineer Infinite Conference (eTechNxT), New Delhi, India, 13–14 March 2018; pp. 1–6.
  77. Naqvi, S.B.Q.; Kumar, S.; Singh, B. A PV-Battery System Operating in Islanded and Grid Connected Modes with Shunt Active Filter Capability. In Proceedings of the IEEE Industry Applications Society Annual Meeting 2020, Detroit, MI, USA, 10–16 October 2020; pp. 1–8.
  78. Korada, N.; Mishra, M.K. Grid Adaptive Power Management Strategy for an Integrated Microgrid with Hybrid Energy Storage. IEEE Trans. Ind. Electron. 2017, 64, 2884–2892.
  79. Karimi-Ghartemani, M.; Khajehoddin, S.A.; Piya, P.; Ebrahimi, M. Universal Controller for Three-Phase Inverters in a Microgrid. IEEE J. Emerg. Sel. Top. Power Electron. 2016, 4, 1342–1353.
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