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This study aims to ameliorate the contribution capability of doubly-fed induction generator (DFIG) to participate in standalone microgrid operation. The islanded microgrid consists of a solar photovoltaic array for solar energy conversion and battery energy storage in addition to DFIG-based wind energy conversion system. Using a simplified control approach, the study describes multi-mode operation of a DFIG-based AC/DC microgrid using a stator-side solid-state transition switch (SSTS). Using SSTS operation, the DFIG stator can be seamlessly disconnected and reconnected from the point of common coupling without interrupting power to the loads in the microgrid. Additionally, non-ideal AC loads can be handled efficiently without the need for computationally exhaustive approaches to enhance stator voltages and currents. [ABSTRACT FROM AUTHOR]

Summary: Problems like intermittent photovoltaic (PV) power, disconnected PV arrays, etc. are brought on by the extensive integration of PV generation. In this article, a single‐stage PV‐integrated grid‐tethered system is controlled using a reconfigurative multiple random features kernel mean p‐power (MRFKMP) control algorithm. The algorithm circumvents the dependence of kernel parameter in the classic random Fourier features mapping and lower the computing complexity in the traditional multiple kernel learning adaptive filter. MRFKMP algorithm with a linear filter structure can reduce both the computational and storage cost. This is the novel application of MRFKMP algorithm to extract fundamental component of nonlinear load currents in PV‐integrated grid‐tied system. Furthermore, to increase the reliability of the system, a reconfigurable control is developed, which adaptive regulates DC link voltage from PV mode (PVM) during PV hours to active power filtering mode (AFM) during PV nonavailability/PV disconnection. On a created laboratory testbed, the applied control's practical feasibility for numerous scenarios is evaluated. Comparison with existing control algorithms reveals that the MRFKMP controller outperforms the LMF based PV system by 79% less peak‐to‐peak load current ripple and 60% less than the best performing SRF control algorithm. The grid current THD is 2.60%, which is 30% low than that presented by SRF technique. [ABSTRACT FROM AUTHOR]

The paper presents a normalized, varying step size-based least mean square-based control for a standalone microgrid and Ant Lion optimization-based maximum power point tracking. This modified version of the incremental conductance algorithm addresses issues like slow dynamic response, fixed step size issues, and steady state oscillations. Comparative analysis with well-known techniques shows that Ant Lion optimizes the tracking of maximum power points more accurately, with fewer oscillations and increased efficiency. Power management and power quality are maintained through proposed adaptive voltage source converter control. The proposed voltage control shows better performance under various dynamic and steady conditions. [ABSTRACT FROM AUTHOR]

Summary: This paper presents the performance of a single‐phase utility‐tied distribution static compensator (DSTATCOM) with nonlinear load operating under weak grid conditions. The DSTATCOM is controlled by a complex kernel risk‐sensitive p‐power (CKRSP) algorithm. Ever‐increasing nonlinearity of the load, rapidly increasing renewable energy system installed capacity, and rising heating loads, especially during the winter season, lead to various power quality issues that worsen during weak grid conditions. An advanced adaptive control scheme, that is, CKRSP, enforces the system to perform various multifaceted operations, including harmonics suppression, handling rapid load variations, voltage sag and swell, and active and reactive power control at the point of common coupling (PCC) during weak grid conditions. The proposed CKRSP algorithm outperforms conventional control algorithms regarding steady‐state error, convergence speed, and accuracy. During weak grid conditions, the proposed system ensures stable DC bus voltage with a reduced second harmonic component. This further assists the CKRSP control in better extracting the fundamental load current component using a smoother loss component of current iloss. The proposed system can handle various power quality issues during weak grid conditions while ensuring the overall system's stability. The laboratory prototype results show that the presented system performs satisfactorily under weak grid conditions per IEEE 519‐2014 standards. [ABSTRACT FROM AUTHOR]

In view of the stochastic nature of wind and solar energy, maintaining quality power in grid-connected hybrid energy system is crucial for efficient energy utilization, especially in the presence of non-linear loads. This paper deals with the control and performance assessment of grid-integrated hybrid energy system that comprises of doubly fed induction generator (DFIG) and photovoltaic (PV) system including battery energy storage (BES) as a stand-by supply to meet utility and load demand. In order to maintain power balance and address various power quality issues encountered with hybrid renewable integration along the source and the grid/load end, a dual-layer variable-step size adaptive control is implemented for the grid-interfaced converter of the proposed system. The variable step-size based dual-layer least mean square (LMS) adaptive control functions by extracting weights of various control signals (stator and load current) where the step-size parameter adjusts according to the conditions that limit the maladjustment error and increase the rate of convergence. The DC-link voltage control realized by bidirectional BES control reduces the steady-state error and fluctuations in the voltage. An artificial bee colony (ABC) optimization is adopted for optimal gain tuning of the DC-link voltage controller as a result of which the battery performance and grid-side converter performance is enhanced with the increased power exchange to the grid. The system model is developed in MATLAB/Simulink and controller performance is evaluated for diverse operating conditions including steady-state, unbalanced non-linear load conditions, wind-speed and solar irradiation variation and specified grid power modes. [ABSTRACT FROM AUTHOR]

This article describes the multi-objective spotted hyena optimization (MOSHO) based control of a three-phase three-wire grid-tied dual-stage PV system. The MOSHO delivers an optimized step size $ (\boldsymbol{\delta }) $ (δ) for the incremental conductance (InC) based maximum power point tracking (MPPT) algorithm, as well as optimizes the PI controller gains for DC bus voltage $ ({{{\mathbf V}_{{\mathbf dc}}}}) $ ( V d c ) regulation. The $ \boldsymbol{\delta } $ δ optimized MPPT facilitates the faster and more accurate tracking of maximum power point with fewer fluctuations at steady-state. The MOSHO optimized PI controller regulates the $ {\textrm{V}_{\textrm{dc}}} $ V dc and delivers better stability with reduced $ {\textrm{V}_{\textrm{dc}}} $ V dc variations in DC bus voltage during steady-state and dynamic states, i.e. irradiation variation, abnormal and unbalanced grid voltage. The optimized DC bus generates an accurate loss component of current, which further enhances the voltage source converter (VSC) performance in terms of precise reference currents generation and power quality improvement. The proposed system performs satisfactorily in a MATLAB simulation environment as per IEEE519 standards. [ABSTRACT FROM AUTHOR]

This work proposes a hydrological cycle-based optimisation technique for performance enhancement of a non-negative least mean mixed norm (NNLMMN) based voltage source control (VSC) for a three-phase grid integrated wind/photovoltaic (PV) system. Water cycle algorithm (WCA) is employed to tune the proportional–integral (PI) controller parameters of VSC to regulate voltage variations at DC link generated during dynamic load and wind conditions. This results in generation of a specific loss component (Iloss) of current to boost the performance of VSC. The NNLMMN control deals with system identification troubles with a non-negativity limitation in varied Gaussian noise conditions. It generates accurate Iloss to upgrade the ability of VSC to accurately extricate weight signals and the fundamental load current component in terms of improvement in DC link voltage (vdc) and total harmonic distortion. The proposed algorithm mitigates problems like voltage fluctuations besides performing operations like reactive power compensation, enhancement of power quality, load and power balancing at the point of coupling during steady-state and dynamic conditions. In conjunction with the NNLMMN algorithm, the proposed technique reduces the surplus mean square error iteratively, resulting in a compact expression of step size. The proposed topology stands out with an improved performance of vdc under wind gusts and the well-known bell-shaped irradiance curve. For relative evaluations, the performance of non-optimised PI and particle swarm optimised PI has been added to analyse the improved response of vdc and Iloss. Extensive simulation results obtained in MATLAB/Simulink are exhibited to corroborate the efficacy of the suggested system. [ABSTRACT FROM AUTHOR]

The paper presents a grid-connected microgrid with a photovoltaic system and a battery as a storage element. The optimal design and control of storage elements and power quality improvement are enhanced using sigmoid-function-based variable step size (SFB-VSS) adaptive LMS control. The DC-link voltage and battery current are enhanced using an ILA-optimization-based PI controller. Comparative analysis shows that an ILA-optimized PI controller improves battery stress and DC-link voltage fluctuations, enhancing overall system stability. The relative percentage error of Vdc is only 0.5714% for ILA-optimized values as compared to GA, PSO, and manually tuned PI gains which are 0.857%, 1.14285%, and 0.86%, respectively. ILA-optimized parameters also enhance battery current, reducing stress on the battery. The system was studied under various dynamic conditions, achieving power balance in all conditions. The system has the capability of seamless transfer of control from GC mode to SA mode when the grid is disconnected. The proposed VSC control shows better performance in steady-state and dynamic conditions, maintaining a THD under 5%, which follows IEEE standard 519, and providing better DC offset rejection, fewer oscillations in the weight component of the load, and better convergence. The proposed control also enhances the frequency of the grid, ensuring a smooth transition between modes. The system is simulated in the MATLAB Simulink environment, and all the optimization techniques were carried out offline. [ABSTRACT FROM AUTHOR]

This paper presents a path-finder algorithm (PFA) of meta-heuristic optimization for the performance enhancement of the bias compensated normalized maximum correntropy criteria (BCNMCC) based voltage source converter (VSC) control for a three-phase three-wire grid-tied dual-stage PV system. The DC link voltage ( V DC ) variations during induced dynamic conditions are minimized by PFA optimized PI controller which also generates an accurate loss component of current ( I d1 ) for enhancing the VSC control performance. The BCNMCC algorithm effectively performs the system identification and echo cancellation in the presence of Gaussian noises. An accurate I d1 improves the VSC ability to accurately extract the fundamental load current component and to produce precise weight signals. The BCNMCC performs multifunctional operations, i.e., reactive power compensation, harmonics elimination, load balancing, and power balancing at point of common coupling during steady-state and various dynamic conditions, i.e., grid-islanding & re-synchronization, irradiation variation, unbalanced load and fixed power mode. The proposed system is capable of operating under grid-tied and isolated mode due to the seamless transition of a VSC control from grid current control (GCC) to voltage control. The seamless transition of VSC control does not induce any major transients at the source and on the load side of the system. The hybrid energy storage system (HESS) with a battery, fuel-cell and ultra-capacitor further improves the reliability of the PV system and the stability of the overall system during both grid-tied and isolated operations. The proposed system performs satisfactorily under steady-state and diverse dynamic states as per IEEE519 standards. [ABSTRACT FROM AUTHOR]