System and method for power quality control

Abstract

A system (100) for power quality control integrates a photovoltaic (PV) unit (102), converts solar energy into DC power, further inverts to AC, and supplies to the AC bus (104) through a DC / AC convertor (120). A wind turbine (WT) (106) generate AC power directly for the same bus (104) through a transformer (108). A battery energy storage system (BESS) (110) connected to the AC bus (104) stores excess energy and discharges during shortages. A distributed power flow controller (DPFC) (112), comprising a shunt converter and series converters without a DC link, regulates power flow and suppresses harmonics. A fractional order proportional–integral (FOPI) controller (114) generates compensating signals for voltage and current harmonics, with parameters tuned by a hybrid optimization technique (116). A monitoring and communication unit (118) links with the DPFC (112), FOPI controller (114), and optimization (116) to provide supervisory control, real-time data acquisition, and coordination with the system (100).

Description

FIELD OF INVENTION

[0001] The present disclosure pertains to electrical power systems. Moreparticularly, the disclosure relates to enhancing power quality in grid-connectedhybrid renewable energy systems by employing advanced control and optimizationstrategies that ensure improved stability, dynamic response, and effectivemitigationof power quality disturbances.BACKGROUND OF THE INVENTION

[0002] The following description of the related art is intended to providebackground information pertaining to the field of disclosure. This section mayinclude certain aspects of the art that may be related to various features of thepresent disclosure. However, it should be appreciated that this section is used onlyto enhance the understanding of the reader with respect to the present disclosure,and not as an admissions of the prior art.

[0003] The rapid integration of renewable energy sources into modern gridshas significantly increased the complexity of power distribution, resulting in majorchallenges for power quality management. Variability in renewable generationintroduces voltage fluctuations, frequency deviations, and harmonic distortions thatdegrade system stability and efficiency. Conventional control methods often fail toprovide adequate compensation under highly dynamic and nonlinear operatingconditions, leading to equipment stress, increased energy losses, and reliabilityconcerns in grid-connected hybrid renewable systems.

[0004] To address these challenges, the Distribution Power Flow Controller(DPFC) has emerged as a promising solution, offering decentralized control ofactive and reactive power while mitigating harmonic distortions. When integratedwith a meta-heuristic optimization approach, the DPFC can automatically tunecontrol parameters to achieve optimal harmonic suppression and reactive powercompensation under varying operating conditions. Further, the incorporation of aFractional Order Proportional-Integral (FOPI) controller provides enhancedflexibility and robustness compared to traditional PI controllers, enabling improveddynamic response, better adaptability to nonlinear loads, and superior performanceduring transient disturbances.

[0005] Nevertheless, despite these advancements, challenges remain inpractical deployment. Meta-heuristic techniques, while effective in exploringcomplex control spaces, can involve high computational requirements andconvergence delays that limit real-time applicability. Similarly, the performance ofFOPI controllers is sensitive to parameter initialization, and improper tuning maylead to instability or degraded compensation performance under suddendisturbances. Furthermore, the integration of DPFC units in large-scale distributedgrids raises concerns regarding coordination, scalability, and cost-effectiveness.These limitations underscore the need for refined optimization strategies,computationally efficient algorithms, and adaptive control frameworks to fullyrealize the potential of DPFC systems in hybrid renewable energy environments.

[0006] Therefore, a need exists for a control framework that combinesefficient optimization and adaptive strategies to enhance DPFC real-timeperformance, reduce computational load, enable self-tuning FOPI controllers, andsupport scalable coordination of multiple units for stable, cost-effective integrationin distributed renewable smart grids.OBJECTS OF THE PRESENT DISCLOSURE

[0007] .An object of the present disclosure is to provide a system thatimproves power quality in grid-connected hybrid renewable energy structures byminimizing voltage and current harmonics, thereby reducing equipment damageand energy losses

[0008] An object of the present disclosure is to provide a system thatprovide a flexible and decentralized control architecture using a Distribution PowerFlow Controller (DPFC) with multiple series converters distributed along thetransmission line, eliminating the need for a centralized DC link capacitor.

[0009] An object of the present disclosure is to enhance system stability anddynamic response to localized disturbances through the use of a Fractional OrderPI (FOPI) controller, which offers greater adaptability and robustness compared toconventional controllers.

[0010] An object of the present disclosure is to optimize control parametersautomatically and efficiently by employing a hybrid meta-heuristic optimizationapproach that combines the Tunicate Swarm Algorithm (TSA) and TeachingLearning-Based Optimization (TLBO), ensuring optimal performance undervarying grid conditions.

[0011] An object of the present disclosure is to reduce Total HarmonicDistortion (THD) to extremely low levels, surpassing the performance of existingsolutions such as UPFC and other conventional power quality improvementdevices.

[0012] An object of the present disclosure is to enable cost-effective andmodular deployment of power quality improvement solutions, making the systemsuitable for both large-scale and medium-sized power networks, and facilitatingeasy expansion and maintenance.

[0013] An object of the present disclosure is to support seamless integrationof multiple renewable energy sources and energy storage systems for reliable andsustainable grid operation.SUMMARY

[0014] This section is provided to introduce certain objects and aspects ofthe present disclosure in a simplified form that are further described below in thedetailed description. This summary is not intended to identify the key features orthe scope of the claimed subject matter.

[0015] The present disclosure relates to electrical power systems, with aparticular focus on enhancing power quality in grid-connected hybrid renewableenergy systems. It introduces advanced control and optimization strategies designedto improve system stability, enhance dynamic response, and effectively mitigatepower quality disturbances.

[0016] An aspect of the present disclosure generally relates to a systemdesigned for effective power quality control in a grid-connected hybrid renewableenergy setup. It integrates multiple renewable sources, including photovoltaic (PV)units, and wind turbines (WT), all of which generate and supply alternating current(AC) power to a common AC bus. A battery energy storage system (BESS) isconnected to thisAC bus to store excess energy produced by the renewable sourcesand to release stored power during periods of energy shortfall, ensuring a stablepower supply. Central to the system is a Distributed Power Flow Controller(DPFC), which includes shunt and series converters but notably eliminates thetraditional direct current (DC) link between them. This DPFC regulates power flowand suppresses harmonics in the grid. A Fractional Order Proportional-Integral(FOPI) controller is coupled with the DPFC to further enhance power quality bygenerating compensating signals to mitigate both voltage and current harmonics.To optimize the performance of the FOPI controller, a hybrid optimizationtechnique is employed to accurately determine its proportional and integralparameters, ensuring efficient and adaptive control in varying grid conditions.

[0017] In another aspect, the present disclosure relates to a method thatoutlines an operation of a power flow control systemdesigned for integrating hybridrenewable energy. Initially, solar energy is harnessed by at least one photovoltaic(PV) unit, which generates direct current (DC) power that is subsequently convertedinto alternating current (AC) power via a DC-AC converter for delivery to a centralAC bus. Simultaneously, wind energy is captured by a wind turbine (WT) toproduce AC power, which is also supplied to the AC bus. Any surplus energygenerated by the PV unit and the WT is stored in a battery energy storage system(BESS) that is operatively connected to theAC bus, allowing the systemto maintaina consistent energy supply during fluctuations in demand. The overall power flowon theAC bus is actively regulated by a Distributed Power Flow Controller (DPFC),which manages load balancing and power quality. The DPFC's performance isfurther refined and controlled by a Fractional Order Proportional-Integral (FOPI)controller, which ensures precise harmonic mitigation and dynamic response.Together, these steps enable stable and efficient power management in a renewable30integrated grid environment.BRIEF DESCRIPTION OF DRAWINGS

[0018] The accompanying drawings, which are incorporated herein andconstitute a part of this disclosure, illustrate exemplary embodiments of thedisclosed methods and systems in which like reference numerals refer to the sameparts throughout the different drawings. Some drawings may indicate thecomponents using block diagrams and may not represent the internal circuitry ofeach component. It will be appreciated by those skilled in the art that the inventionof such drawings includes the disclosure of electrical components, electroniccomponents, or circuitry commonly used to implement such components.

[0019] FIG. 1 illustrates an exemplary representation of a functional blockdiagram representing a system for power quality control, in accordance withembodiments of the present disclosure.

[0020] FIG. 2 illustrates an exemplary representation of an architecturalblock diagram representing the system for power quality control, in accordancewith an embodiment of the present disclosure.

[0021] FIG. 3 illustrates an exemplary representation of a basic architecturalrepresentation of DPFC (Distribution Power Flow Controller), in accordance withan embodiment of the present disclosure.

[0022] FIG. 3A illustrates an exemplary representation of a basicarchitectural representation of UPFC (Unified Power Flow Controller), inaccordance with an embodiment of the present disclosure.

[0023] FIG. 4 illustrates an exemplary representation of a Simulinkrepresentation of the system for power quality control, in accordance with anembodiment of the present disclosure.

[0024] FIG. 5 illustrates an exemplary representation of a method flowdiagram representing a system for power quality control, in accordance with anembodiment of the present disclosure.DETAILED DESCRIPTION OF PRESENT DISCLOSURE

[0025] The present disclosure relates to electrical power systems, and morespecifically, to the enhancement of power quality in grid-connected hybridrenewable energy systems. The disclosure focuses on the implementation ofadvanced control and optimization strategies aimed at improving system stability,dynamic performance, and the effective mitigation of power quality disturbances

[0026] In an embodiment, the present disclosure generally relates to asystem for a comprehensive solution related to power quality control in gridconnectedhybrid renewable energy systems. It incorporates at least onephotovoltaic (PV) unit designed to convert solar energy into direct current (DC)power, subsequently transformed into alternating current (AC) power and suppliedto anAC bus.Additionally, the system includes at least one wind turbine (WT) usedto harness wind energy and directly generate AC power, also fed into the same ACbus. To manage power fluctuations and ensure energy availability during lowgeneration periods, a Battery Energy Storage System (BESS) remains operativelyconnected to the AC bus. The BESS stores excess AC power generated by the PVunit, and wind turbine, and discharges stored power back to the AC bus duringperiods of energy shortfall.

[0027] In an embodiment, to enhance the regulation of power flow andaddress power quality issues such as harmonic distortion, the system integrates aDistributed Power Flow Controller (DPFC). The DPFC comprises at least one shuntconverter and at least one series converter, notably configured without a directcurrent (DC) link between them. Despite the absence of this DC link, the DPFCeffectively regulates power flow and performs harmonic suppression within thegrid. Coupled to the DPFC, a Fractional Order Proportional-Integral (FOPI)controller, which generates compensating signals aimed at suppressing voltage andcurrent harmonics, so as to improve overall grid power quality. To optimize theperformance of the FOPI controller, the system employs a hybrid optimizationtechnique that dynamically determines the proportional and integral controlparameters.

[0028] FIG. 1 depicts a power quality control system (herein after system(100)) integrated with intelligent control and optimization methods for efficientpower management. The structure begins with a photovoltaic Unit (102), whichconverts solar irradiance into electrical energy. The output from this photovoltaicunit (102) flows into anAC Bus (104) by a DC / AC convertor (120) after necessarypower conditioning. A wind Turbine (WT) (106) also injects electrical energy intothe AC Bus (104) via a transformer (108) by harnessing kinetic energy from windand converting it into mechanical torque for driving a generator. The two renewablesources form the backbone of the hybrid system, ensuring diversified energyavailability and improved resilience against fluctuations in individual sources.

[0029] In an embodiment, the generated power from these units interactswith a Battery Energy Storage System (BESS) (110), which plays a crucial role inbalancing demand and supply. The battery absorbs surplus energy during low10demand periods and discharges stored energy during peak demand, thusmaintaining a continuous power supply. The system (100) also integrates with abidirectional power converter (118), which governs two-way energy exchangebetween the battery and the grid. The converter (118) ensures that stored DC powergets transformed into usable AC power when discharging and allows AC to DCconversion during charging, stabilizing both the battery operation and the AC Bus(104). A Distributed Power Flow Controller (DPFC) (112) acts as a key regulatorin the network, ensuring that active and reactive power are properly distributedamong interconnected components. This controller (112) enhances voltage stability,improves power factor, and minimizes transmission losses. Its performancedepends heavily on the Fractional Order Proportional-Integral (FOPI) Controller(114), which provides amore flexible and precise control strategy than conventionalPI controllers by using fractional calculus for tuning. This advanced controller (114)responds effectively to nonlinearities, system uncertainties, and fast-changing loadconditions.

[0030] In an embodiment, the tuning and adaptation of the fractionalcontroller (114) are driven by a hybrid optimization technique (116). This (116)represents a computational intelligence framework that combines multipleoptimization strategies, such as particle swarm optimization, genetic algorithms, ordifferential evolution, to achieve optimal parameter settings. Through thistechnique (116), the system (100) maintains robust stability, enhances dynamicresponse, and minimizes total harmonic distortion. The hybrid optimization ensuresthe fractional order controller continues to perform efficiently even under varyinginput conditions from the photovoltaic unit (102), and wind turbine (106).

[0031] In an embodiment, in operation, this integrated arrangement of thesystem (100) ensures reliable renewable energy utilization. For instance, during ascenario where solar irradiance drops due to cloud cover, the wind turbine (106)compensate for reduced solar output. If overall generation falls below demand, thebattery energy storage system (110) discharges power via the bidirectionalconverter (118). Conversely, in a case of excess renewable generation, thedistributed power flow controller (112) directs surplus energy to charge the battery(110). Throughout these variations, the fractional order PI controller (114),optimized by hybrid techniques (116), maintains power quality by reducingoscillations and providing stable voltage across the AC Bus (104).

[0032] In an embodiment, the hybrid optimization technique (116)incorporates at least one of a Tunicate Swarm Algorithm (TSA) or a Teaching-Learning-Based Optimization (TLBO). The purpose of this integration relates topower quality improvement in grid-connected hybrid renewable energy systemswhere multiple renewable sources, namely the photovoltaic unit (102), the windturbine (106) supply power to the AC bus (104). These sources are intermittent andintroduce issues such as voltage harmonics, current harmonics, sag, swell, andfluctuations. The distributed power flow controller (112) mitigates these problemsby injecting a compensating signal into the grid, and the tuning of its controlparameters is executed by the hybrid optimization technique (116).

[0033] In an embodiment, the TSAelement of the hybrid optimization (116)derives inspiration from tunicates that use jet propulsion for motion and adapteffectively in dynamic environments. TSA enables wide exploration of theparameter search space of the fractional order proportional-integral controller (114)and determines proportional gain, integral gain, and fractional order values thatminimize distortion. The algorithm responds efficiently to nonlinearities and abruptvariations from renewable energy sources.

[0034] In an embodiment, the TLBO element, a classroom-based learningsystem consisting of two stages, the teaching phase and the learning phase. The bestsolution guides others in the teaching phase, and mutual knowledge transfer among solutions occurs in the learning phase. Within the system (100), TLBO refines the values identified by TSA and prevents premature convergence, thereby ensuring global optimization of the DPFC (112) control parameters. The hybrid use of TSA and TLBO (116) combines rapid exploration with strong refinement capability. Inoperation, the hybrid optimization ensures that the compensating signals of theDPFC (112) consistently improve power quality. Simulation on the IEEE 14-bussystem demonstrated that the TSA-TLBO tuned fractional order PI controller (114)reduced total harmonic distortion (THD) significantly, in some cases to values aslow as 0.0074716%, surpassing traditional methods like genetic algorithms or particle swarm optimization. The dual optimization structure (116) strengthens thesystem (100) by enabling stable operation, maintaining flexibility under fluctuatingrenewable conditions, and delivering a reliable and cost-effective alternative toconventional power flow controllers.

[0035] FIG. 2 illustrates a functional flow (200) from generation to quality enhancement of the system in a layered and interconnected manner. It highlights the energy sources and also the flow of power conditioning, control, and filtering mechanisms that ensure grid stability.At a generation stage, three resources operate in parallel.APhotovoltaic source generates DC power from solar irradiation, which undergoes conversion through a DC-AC inverter before reaching an AC bus. A wind turbine provides AC output, which is conditioned using an AC-AC converter for synchronization with a battery grid. A battery storage serves dual roles by storing excess generation and supplying backup during deficits, and its bidirectional inverter enables both charging and discharging through the AC bus. This triangular arrangement of PV, wind turbine, and battery establishes redundancy and flexibility in energy supply. From the AC bus, energy flows into the transmission network, where a distributed power flow controller, positioned as the central element for regulating quality. Here, DPFC expands its composition into shunt and series controllers. The shunt controller injects current into the system to maintain voltage balance at the bus, while multiple series controllers are distributed along thetransmission line to compensate for harmonics, correct line impedance, and control the power angle.

[0036] In an embodiment, a control mechanism is also emphasized in this illustration. A hybrid TLBO-TSA optimization block, directly linked with the DPFC through a FOPI controller. Real-time data from voltage and current measurement units has been fed into this control loop, allowing the optimization algorithms to continuously refine controller parameters. The TSA component explores wide variations in parameters for adaptability under fluctuating renewables, while TLBO refines them for precision. This dual approach ensures that corrective actions remain both fast and accurate under changing conditions. Additional emphasis is given to power filtering. A high-pass filter is connected downstream of the DPFC, targeting residual high-frequency harmonics that escape through compensation. The combination of distributed series controllers and filtering ensures that the transmitted power is nearly sinusoidal, thereby reducing Total Harmonic Distortion (THD) to extremely low values. This is particularly important for modern loads such as semiconductor devices, electric vehicle chargers, and communication systems that are sensitive to waveform distortions. As a whole, the figure outlines a multi-layer defense against power quality degradation generation redundancy at the source level, compensation through shunt and series controllers at the network level, and fine-tuned optimization at the control level.

[0037] FIG. 3 illustrates a basic architecture (300) of the Distribution Power Flow Controller (DPFC) that employs a coordinated arrangement of shunt and series controllers distributed along the distribution line. The distribution line, at the top, serves as the primary pathway for transmitting electrical power, and into this line, multiple series controllers are integrated. Each series controller contains AC-DC conversion units that inject compensating voltages into the line, enabling precise regulation of active and reactive power flow. Unlike a conventional Unified Power Flow Controller (UPFC), the DPFC eliminates the common DC link and instead relies on independent low-power series converters distributed across the network, thereby enhancing modularity and scalability.

[0038] In an embodiment, the series controllers in the architecture function as modular converters connected at various points of the distribution line. These converters operate independently, each handling a fraction of the compensation task, which results in improved system reliability since the failure of a single module does not disrupt the entire compensation process. This modular structure also ensures effective suppression of harmonics, reduction of voltage sags, and improved dynamic response under variable load and generation conditions. The shunt controller, located at the lower section and connected between the distribution line and ground through a transformer. This controller provides reactive power support and maintains voltage stability across the system. It also facilitates the exchange of active power with the grid when required, ensuring that imbalances caused by renewable generation variability are corrected rapidly. The shunt controller incorporates AC-DC conversion similar to the series units, ensuring harmonized control across the entire DPFC (112) system. Together, the distributed series controllers and the central shunt controller form the backbone of the DPFC (112), achieving enhanced controllability of power flow in the system (100). This architecture reduces installation costs by removing the centralized DC link but also offers flexibility, fault tolerance, and high adaptability for modern smart grid applications.

[0039] In an embodiment, The Distribution Power Flow Controller (DPFC) (112) comprises a plurality of modular compensation units that collectively provide distributed compensation in grid-connected Hybrid Renewable Energy Systems (HRES). Each unit functions as a smaller, low-cost converter that operates independently yet in coordination with others, eliminating the centralized DC link present in Unified Power Flow Controller (UPFC) systems. This distributed arrangement enhances system flexibility and reliability, as failures in one module do not compromise the operation of the entire DPFC (112). In operation, the DPFC (112) integrates with renewable energy inputs such as a photovoltaic (PV) unit (102), wind turbines (106), and battery energy storage systems (110), which feed into a common AC bus (104). The modular units of DPFC (112) inject compensating voltages or currents into the grid, thereby mitigating issues such asvoltage sags, swells, and harmonic distortions. Unlike centralized solutions, the distributed modules of DPFC (112) can target localized disturbances dynamically, ensuring rapid suppression of power quality issues. The control of the DPFC (112) is managed through the Fractional Order PI (FOPI) controllers (114), whose parameters are tuned using hybrid meta-heuristic optimization techniquescombining Tunicate Swarm Algorithm (TSA) and Teaching Learning-BasedOptimization (TLBO) (114). These optimization methods ensure that the DPFC(112) achieves minimal Total Harmonic Distortion (THD), reported as low as0.0074716% in simulations, while maintaining stable operation under variablerenewable inputs. Compared with UPFC, which requires a large DC link and comes with higher installation costs, the DPFC (112) demonstrates novelty by offeringdistributed modularity, faster dynamic response, and cost-effectiveness.

[0040] FIG. 3A depicts the basic architecture (300-A) of a Unified Power Flow Controller (UPFC) comprising a shunt converter (VSC1) and a series converter (VSC2) linked via a common DC capacitor (VDC). The shunt converter, through a shunt transformer, regulates bus voltage, exchanges reactive power, and supplies real power to the series converter. The series converter, connected via a series transformer, injects controllable voltage of variable magnitude and phase to influence active and reactive power flow, enabling load balancing, congestion management, and oscillation damping. Coordinated control of both converters provides independent real and reactive power regulation, surpassing devices like SVC or TCSC. The DC link facilitates power exchange between converters, while a control system modulates switching for stable operation. However, dependence on a large DC capacitor raises cost, complexity, EMI, and reliability concerns compared to the distributed DPFC (112) architecture.

[0041] In an embodiment, the UPFC and the DPFC (112) share a similar objective of controlling power flow and improving power quality in transmission systems, but they differ significantly in architecture and operation. In the UPFC, the systemis built with two large voltage source converters, one operating as a shunt controller and the other as a series controller, both linked by a common DC capacitor (VDC). This capacitor allows direct real power exchange between the twoconverters, but it also introduces a single-point dependency, meaning that any failure in the converters or DC link disrupts the entire system. In contrast, the DPFC (112) removes this centralized DC link by replacing the single large series converter with multiple distributed series converters spread along the transmission line. Each series unit has its own DC capacitor, and the exchange of real power with the shunt converter is carried out through the transmission line at the third-harmonic frequency. This distributed approach increases modularity, scalability, and system reliability, since the failure of one series module has minimal impact on overall operation. Additionally, the UPFC requires bulky equipment and high installation cost due to the large converters and cooling requirements, whereas the DPFC (112) employs smaller converters that are easier to manufacture, install, and maintain, with reduced cost and simplified replacement. Furthermore, while the UPFC only handles fundamental frequency components, the DPFC (112) deliberately utilizes harmonic frequencies for power exchange and applies high-pass filters for mitigation, enhancing its power quality performance. Overall, the DPFC (112) evolves as a more cost-effective, reliable, and modular alternative to the UPFC, overcoming the limitations of centralized architecture.

[0042] In an embodiment, the PV unit (102) forms a crucial part of the system (100) by generating electrical power directly from incident solar radiation. The photovoltaic cells inside the PV module (102) absorb sunlight and convert it into direct current (DC) power. However, since the commonAC bus (104) operates on alternating current, the DC power from the PVmodule (102) requires conversion before integration into the system. For this purpose, a DC-AC converter is incorporated within the PVunit (102). The DC-AC converter performs two primary functions, conversion of the generated DC into AC power and synchronization of this AC output with the AC bus (104). Synchronization ensures that the converted voltage, frequency, and phase angle align with the existing grid-connected AC bus (104), thereby enabling smooth power injection without introducing instability, voltage mismatch, or power quality issues.

[0043] In an embodiment, the DC-AC converter inside the PV unit (102) can adopt different inverter topologies, including voltage source inverters, currentsource inverters, or multilevel inverters, depending on system design requirements. In a grid-connected configuration, the DC-AC converter uses advanced pulse width modulation (PWM) techniques to minimize harmonic distortions and to regulate output waveforms close to a pure sinusoid. This reduces the risk of current harmonics that could otherwise propagate into the AC bus (104), protectingdownstream loads and sensitive equipment. To further ensure reliable operation, theconverter in the PV unit (102) integrates with control strategies that regulate DClink voltage, optimize maximum power point tracking (MPPT), and maintaindynamic stability under varying irradiance and temperature conditions. Forinstance, the PV unit (102) with its integrated DC-AC converter plays a stabilizing role by continuously adjusting its output according to the condition of the AC bus(104). During periods of high solar irradiance, the PV unit (102) injects more powerinto theAC bus (104), thereby reducing dependency on other sources like the windturbine or battery storage system. Conversely, under cloudy conditions, the DC-ACconverter ensures that even fluctuating solar input translates into a stable AC contribution synchronized with the AC bus (104). This ability to dynamicallyregulate conversion and synchronization allows the PV unit (102) to contributeeffectively to the hybrid system while maintaining grid compliance and supportingthe Distribution Power Flow Controller (DPFC) in enhancing overall power quality.

[0044] In an embodiment, the (FOPI) controller (114) forms the central regulating mechanism for the system (100). The FOPI controller (114) comprises three main parameters, proportional gain (KP), integral gain (Ki), and a fractional order parameter (λ). The fractional order parameter (λ) is mathematically constrained within the range greater than 0 and less than 1, providing an additional degree of freedom for control compared to conventional PI controllers. This fractional-order characteristic enhances the adaptability of the system under fluctuating input conditions arising from intermittent Renewable Energy Sources (RES) such as Wind Turbines (WT) and Photovoltaic (PV) units. In conventional integer-order PI control, the response often suffers from overshoot or limited robustness, whereas the inclusion of fractional calculus in the FOPI controller (114)allows smoother dynamic response and higher resilience against uncertainties in grid operation.

[0045] In an embodiment, in operation, the proportional gain (KP) within the FOPI controller (114) dictates the immediate response strength to deviations in voltage or current, effectively improving transient performance. The integral gain (Ki) within the FOPI controller (114) addresses long-term steady-state errors by eliminating voltage offsets and suppressing harmonics generated due to nonlinear loads or variable RES output. The fractional order parameter (λ), being within the range of 0 < λ < 1, fine-tunes the memory effect of the integrator, meaning the system (100) retains partial influence from historical error values. This property allows gradual compensation rather than abrupt corrections, reducing oscillations and ensuring better damping in DPFC-based hybrid grids. For instance, a λ value closer to 0 enhances damping of fast disturbances, while a λ value approaching 1 strengthens long-term harmonic suppression.

[0046] In an embodiment, for the DPFC configuration, the FOPI controller (114) governs both the series converters responsible for current regulation and the shunt converters responsible for voltage support. Through this dual regulation, voltage sags, swells, and harmonic distortions in HRES networks are minimized. The integration of the hybrid Tunicate Swarm Algorithm (TSA) and Teaching-Learning Based Optimization (TLBO) ensures that the values of proportional gain (KP), integral gain (Ki), and fractional order parameter (λ) within the FOPI controller (114) are tuned optimally. For instance, under simulation studies on the IEEE 14-bus system, optimized tuning of these parameters resulted in significant improvement of power quality indices, including a reduction in Total Harmonic Distortion (THD) to low levels. Therefore, the FOPI controller (114), by leveraging proportional gain (Kₚ), integral gain (Ki), and fractional order parameter (λ), serves as a superior alternative to conventional control techniques in DPFC-driven renewable integrated grids. Its fractional-order adaptability improves dynamic stability, suppresses harmonics more effectively, and ensures reliable power delivery under the uncertain behavior of renewable sources.

[0047] In an embodiment, The FOPI controller (114) ensures that the Distribution Power Flow Controller (DPFC) responds effectively to power quality challenges in hybrid renewable energy environments. The controller (114) is utilized to receive tuning values from a Black Widow Optimization (BWO) algorithm, which dynamically refines the key parameters of proportional gain (KP) and integral gain (Ki). The proportional gain (KP) directly governs the response speed of the controller to system disturbances, enabling quick adjustments when voltage or current harmonics arise. The integral gain (Ki) accumulates past errors to eliminate steady-state deviations, ensuring that compensation signals provided to the DPFC maintain long-term accuracy in restoring voltage and current profiles. The Black Widow Optimization (BWO) algorithm operates as a meta-heuristic evolutionary technique inspired by the aggressive reproduction and survival strategies of black widow spiders. Through this mechanism, the BWO algorithm iteratively refines (KP) (1) and (Ki) by simulating natural selection, where weaker parameter sets are discarded and stronger candidates propagate through crossover and mutation. As a result, the FOPI controller (114) avoids limitations of conventional tuning methods such as trial-and-error or gradient descent, which often struggle with convergence under nonlinear grid conditions. The integration of the BWO algorithm with the FOPI controller (114) ensures that the compensating signals injected by the DPFC are optimally aligned with grid requirements in real time. For instance, when sudden fluctuations in hybrid renewable energy sources such as photovoltaic or wind turbine systems occur, the tuned values of (KP) and (Kj) enable the controller to minimize total harmonic distortion (THD) and stabilize both active and reactive power flow.

[0048] In an embodiment, to ensure energy balancing under fluctuating generation and consumption scenarios, the AC bus (104) is connected to the bidirectional power converter (118). The bidirectional power converter (118) establishes controlled two-way energy flow between the Battery Energy Storage System (BESS) (110) and the AC bus (104), thereby enabling both charging and discharging operations depending on system requirements. When excess power is generated from renewable sources photovoltaic arrays, the bidirectional powerconverter (118) directs this surplus energy from the AC bus (104) into the BESS (110) for storage. Conversely, during power scarcity or peak demand conditions, the same converter (118) allows the BESS (110) to discharge stored energy back into the AC bus (104), thereby ensuring grid stability and continuous supply to connected loads. This dual functionality transforms the BESS (110) into a dynamicbuffer that not only smoothens intermittent generation but also improves thereliability of the overall hybrid renewable energy system (100). Furthermore, thebidirectional power converter (118) performs essential power conditioningfunctions. It regulates voltage and frequency alignment between the DCcharacteristics of the BESS (110) and the AC nature of the bus (104). This regulation prevents harmonics, voltage sag, or swell issues from propagating intothe grid. The converter (118) also facilitates seamless transitions between chargingand discharging modes, governed by real-time control algorithms, ensuring that theflow of active and reactive power remains within permissible quality limits.In an embodiment, the shunt and series converters incorporate dedicated control circuitry governed by the FOPI controller (114), wherein the shunt converter injects compensating reactive power to suppress voltage disturbances and stabilize theAC bus (104), thereby ensuring steady-state operation of connected renewable units and loads. The series converter, coordinated with the FOPI controller (114), dynamically injects voltage to correct current distortions from nonlinear loads and renewable fluctuations, with the fractional-order parameter (λ) enabling precise harmonic mitigation across a wider frequency range than conventional PI control. Together, the shunt and series converters operate as a coordinated unit, with the shunt stabilizing voltage and the series mitigating current harmonics, thereby ensuring real-time power quality enhancement within the DPFC (112) framework and offering a flexible, distributed, and cost-effective alternative to centralized UPFC solutions.

[0049] FIG. 4 illustrates a Simulink model (400) of the power flow control device, comprising a PV unit converting solar irradiance to AC via an inverter, a wind turbine supplying AC directly, and a bidirectional BESS for storing surplus and supplying deficit power. These resources connect to the AC bus regulated by aDPFC, which includes a shunt converter and distributed series converters to control active / reactive power, suppress voltage disturbances, and mitigate harmonics. A FOPI controller governs the DPFC with proportional, integral, and fractional parameters, tuned by a hybrid optimization algorithm to enhance THD, voltage stability, and frequency regulation. Together, the model demonstrates a flexible, adaptive, and high-quality integration of renewable generation and storage with the grid.

[0050] In an embodiment, the mathematical behaviour of the FOPI controller (114) is expressed through its transfer function, which extends the capabilities of a classical PI controller by introducing a fractional-order integral term. The general form isIFOPIPKDKSλ=+, where PK is the proportional gain, IKis the integral gain, S is the complex frequency variable in the Laplace transform, λand is the fractional order of the integrator (where 0<λ<1). Unlike conventional PI controllers, which utilize integer-order integration, the FOPI controller (114) introduces a fractional-order element that offers an additional degree of freedom in controller design. This flexibility allows for more precise tuning of the dynamic response of the system. By adjusting the value of λ the controller (114) can effectively balance the trade-off between speed and stability, enhancing robustness of the system (100) under varying operating conditions. This makes the FOPI controller (114) especially suitable for complex, nonlinear, or time-varying systems such as those found in hybrid renewable energy setups.

[0051] FIG. 5 illustrates an exemplary representation of a method flow diagram (500) representing the proposed system (100) for power quality control.

[0052] As illustrated, in step (502), the method (500) includes generating DC power from solar energy through at least one photovoltaic (PV) unit (102) associated with the system (100).

[0053] As illustrated, in step (504), the method (500) includes converting the DC power into AC power through a DC / AC convertor (120) for supply to an AC bus (104) integrated within the system (100).

[0054] As illustrated, in step (506), the method (500) includes deriving AC power from wind energy through a wind turbine (WT) (106) associated with the system (100) to transmit into the AC bus (104) via a transformer (108).

[0055] As illustrated, in step (508), the method (500) includes accumulating a surplus energy from the PV unit (102) and the wind turbine (WT) (106) by a battery energy storage system (BESS) (110), operatively connected to the photovoltaic unit (102).

[0056] As illustrated, in step (510), the method (500) includes regulating (510), power flow of theAC bus (104) through an operatively connected distributed power flow controller (DPFC) (112).

[0057] As illustrated, in step (512), the method (500) includes controlling the operation of the DPFC (112) through an operatively coupled fractional order proportional-integral (FOPI) controller (114).

[0058] It should be understood that the foregoing embodiments are presented by way of illustration and not limitation, and that various modifications and alternatives may be devised by those skilled in the art without departing from the scope of the present disclosure.ADVANTAGES OF THE PRESENT DISCLOSURE

[0059] The present disclosure provides a system that enhances power quality in grid-connected hybrid renewable energy systems by suppressing voltage and current distortions, thereby preventing equipment degradation and minimizing inefficiency-related energy losses.

[0060] The present disclosure provides a system that a flexible, decentralized DPFC-based control architecture with distributed series converters that eliminate the need for a central DC link capacitor, while a FOPI controller enhances stability and dynamic response to localized disturbances through its robust and adaptive control.

Claims

1. A system (100) for power quality control, comprising: at least one photovoltaic (PV) unit (102) to convert solar energy into direct current (DC) power, further into alternating current (AC) power, and to supply the AC power to an AC bus (104) through a DC / AC convertor (120); at least one wind turbine (WT) (106) to generate alternating current (AC) power from wind energy and supply the AC power to the AC bus (104) through a transformer (108); a battery energy storage system (BESS) (110) operatively connected to the at least one photovoltaic (PV) unit (102) to store the excess AC power by converting it into DC power generated by the wind turbine (106) with the help of an AC to DC convertor (rectifier) (122) and the DC power is stored in the BESS generated by the at least one photovoltaic unit (102), and to discharge stored power to the AC bus (104) via DC / AC converter during energy shortfall; a distributed power flow controller (DPFC) (112) operatively connected to the AC bus (104), the DPFC (112) comprising at least one shunt converter and at least one series converter, wherein a direct current link between at least one shunt converter and at least one series converter is eliminated, the DPFC being configured to regulate power flow and to perform harmonic suppression in absence of said direct current link; a fractional order proportional-integral (FOPI) controller (114) operatively coupled to the DPFC (112) to generate a compensating signal for suppression of voltage harmonics and current harmonics in the grid; and a hybrid optimization technique (116) to determine proportional and integral control parameters of the FOPI controller (114).

2. The system (100) as claimed in claim 1, wherein The system (100) as claimed in claim 1, wherein the DPFC (112) comprises a plurality of modular compensation units to provide distributed compensation.

3. The system (100) as claimed in claim 1, wherein the PV unit (102) comprises a DC-AC converter to convert the DC power into AC power and to synchronize the converted power output with the AC bus (104).

4. The system (100) as claimed in claim 1, wherein the FOPI controller (114) comprises a proportional gain (Kp), an integral gain (Ki), and a fractional order parameter (X), wherein the fractional order parameter (X) being constrained within a range of greater than 0 and less than 1.

5. The system (100) as claimed in claim 5, wherein the FOPI controller (114) is configured to receive tuning values from a Black Widow Optimization (BWO) algorithm, said BWO algorithm to adjust the proportional gain (Kp), and the integral gain (Ki).

6. The system (100) as claimed in claim 1, wherein the AC bus (104) is connected to a bidirectional power converter (118) enable bidirectional power transfer between the BESS (110) and the AC bus (104).

7. The system (100) as claimed in claim 1, wherein the shunt converter and the series converter comprise control circuitry to suppress voltage disturbances and to mitigate current-related distortions.

8. A power flow control device (200), comprising: a photovoltaic (PV) unit (202) integrated within the device (200), said PV unit (202) designed to convert solar energy into direct current (DC) power and further into (AC) and transmit it to an AC bus (204) associated with the device (200); a wind turbine (WT) (206) integrated within the device (200), said WT (206) being oriented to generate AC power from wind energy and to deliver the AC power to the AC bus (204) and excess wind power is stored in BESS (110) with help of the AC to DC convertor (rectifier) (122). a battery energy storage system (BESS) (208) operatively connected to the AC bus (204), said BESS (208) being used for bidirectional energy flow to accumulate surplus energy from the PV unit (202) and to discharge stored energy during periods of power shortfall; a distributed power flow controller (DPFC) (210) comprising at least one shunt converter (210-A) and at least one series converter (210-B), operatively connected to the AC bus (204), said DPFC (210) being used to regulate power flow and enhance power quality by suppressing voltage disturbances and mitigating current-related distortions of the device (200); a fractional order proportional-integral (FOPI) controller (212) functionally connected to the DPFC (210), the FOPI controller (212) comprising proportional gain, integral gain, and a fractional order parameter to regulate the operation of the DPFC (210) for stable power flow control and improved power quality; and a hybrid optimization algorithm (214) communicatively coupled to the FOPI controller (212), said algorithm (214) being oriented to tune the FOPI controller (212) parameters for improved stability and power quality of the device (200).

9. A method (500) for executing a power flow control system (100), the method (500) comprising the steps of: generating (502), DC power from solar energy through at least one photovoltaic (PV) unit (102) associated with the system (100); converting (504), the DC power into AC power through a DC / AC convertor (120) for supply to an AC bus (104) integrated within the system (100); deriving (506), AC power from wind energy through a wind turbine (WT) (106) associated with the system (100) to transmit into the AC bus (104) via a transformer (108); accumulating (508), a surplus energy from the PV unit (102) and the wind turbine (WT) (106) by a battery energy storage system (BESS) (110), operatively connected to the photovoltaic unit (102); regulating (510), power flow of the AC bus (104) through an operatively connected distributed power flow controller (DPFC) (112); and controlling (512), the operation of the DPFC (112) through an operatively coupled fractional order proportional-integral (FOPI) controller(114).