Ikhlaq Hussain

As renewable energy sources and nonlinear loads are integrated into microgrids supplying isolated loads, they are becoming increasingly dynamic and challenging to operate. Power quality and stability of isolated microgrids may be adversely affected by nonlinear loads, which introduce reactive power demand, harmonic distortion, and rapid variations in active power. The paper describes a coordinated control framework for a doubly fed induction generator (DFIG)-based microgrid couples with Battery Energy Storage (BES) for reliable and continuous supply to isolated nonlinear loads, maximum power capture and power quality addressal capability. This control framework coordinates the rotor-side converter (RSC), load-side converter (LSC), and bidirectional DC–DC converter. For the RSC, static flux-oriented technique of vector control is used to maximize wind power extraction, while for the LSC, indirect current control based on synchronous reference frame (SRF) adjusts the point of common coupling (PCC) voltage and compensates for the reactive power and harmonic currents drawn due to presence of non-linear loads. By integrating a bidirectional DC–DC converter on the DC side of the microgrid, the BES balances the power mismatch caused by source variations and load fluctuations. While maintaining regulated PCC voltage and frequency, the DFIG and BES maintain continuous power supply to the isolated loads. MATLAB/Simulink 2023a is used to test the performance of the established control strategy pertaining to variable wind generation and non-linear load conditions. Power sharing between the DFIG and BES is effective, power quality is improved, PCC voltage is stable, and harmonic distortion is within the prescribed limits, confirming that the proposed DFIG–BES microgrid is suitable for isolated-load applications.

This paper presents a single-phase grid-integrated Photovoltaic (PV)-Battery energy storage system (BESS) controlled by a chaotic grey wolf optimized (CGWO) simplified hybrid affine projection algorithm (SH-APA). BES system is connected to DC bus via a bi-directional DC-DC converter (BDC) that regulates DC bus voltage (V_de) and BESS current (I_bat).CGWO-tuned fractional order PI (FOPI) controller in voltage control loop of BDC significantly reduces V_de deviation, eventually smoothening reference current for current control loop, ameliorating power quality, and BESS longevity. Assimilated BESS at DC bus permits system to switch between fixed (FPM) and variable power mode (VPM). In FPM, grid-tied PV-BESS delivers pre-committed power at point of intersection (POI), whereas in VPM, power balance at POI is maintained as per prevailing conditions. SH-APA-based VSC control accomplishes multiple operations, i.e., harmonics elimination, active power balancing, and reactive power requital at POI, during dynamic conditions, i.e., irradiation change, load variations and PV-DSTATCOM to DSTATCOM and vice-versa modes. Presented system operates satisfactorily as per IEEE 1547 standard.

In this article, a price adaptive power management control for a single phase residential system with electric vehicle (EV) is being presented. It takes advantage of dynamic pricing threshold to manage the net power exchange between the grid and the system. The proposed algorithm enables fast EV charging during low electricity prices time block, while allowing the EVs to discharge during sudden price hikes when prices exceed an adaptive price threshold set for the day. At night, during high tariffs, the EV operates in vehicle to home (V2H) mode, thus achieving cost minimization and grid stress alleviation. Meanwhile, the system control is performed through a novel application of the least lncosh VSC control. The least lncosh control mitigates the performance degradation of adaptive filtering control during impulsive conditions such as abrupt load changes and large outliers such as pricing changes. Moreover, the control also improves the grid side PQ with the local loads at the demand side by eliminating dominant harmonics, providing reactive power support, and operating the grid at the unity power factor, further improving the system efficiency. The system is verified by simulation results and experimental evaluation with comparisons made with PQ capability of several adaptive filtering techniques as well as economic savings.

This study delves into the advancements, challenges, and opportunities in the solar grid technology, emphasizing its integration into the existing power infrastructure. The proposed ML‐FOGI (multilayer fourth‐order generalized integrator) algorithm presents a promising solution for modern grid synchronization requirements, addressing challenges posed by the integration of renewable energy into the distributed generation. This technology enhances system robustness and dynamic response, particularly in weak distribution grids characterized by voltage distortions and imbalances. This innovative approach enhances system stability and performance, particularly in polluted grid conditions. Through MATLAB/Simulink modelling and experimental validation, the effectiveness of the proposed control strategy is investigated across diverse testing conditions. Emphasizing the significant role of the control strategy in enhancing power quality and grid stability in the solar photovoltaic systems, this research underscores the importance of robust and adaptive control mechanisms for optimizing performance and ensuring grid reliability in modern microgrid. This study delves into this complex issue of working of the grid connected photovoltaic (GCPV) system, emphasizing the importance of balanced unit templates and a stable DC link voltage with unpredictable grid harmonics. This research aims to enhance the resilience of solar PV systems against grid disturbances by drawing inspiration from the adaptable nature of ADALINE filters and adhering to the IEEE519 requirements. This study employs OPAL‐RT's resilient experimental configuration.

The interoperability of wind and solar energy is a potential alternative to improve reliability and reduce the probability of an energy supply crisis. Due to the stochastic nature of both the sources, maintaining high quality performance in grid-intertie hybrid energy systems, particularly for nonlinear loads, is essential for efficient use of energy. This article presents a novel Gaussian kernel least mean sixth (GKLMSi) grid interactive algorithm for the hybrid renewable energy system along with adaptively controlled dc link voltage. GKLMSi adaptive control effectively tracks various time varying power quality events such as, voltage fluctuations, load disturbances, reactive power variations, and harmonic parameters that are of high-order nonlinearities. The adaptive dc link voltage control reduces the stress on the converters during voltage fluctuations and generates sufficient dc link voltage reference for the converter current control. This minimizes switching losses and enhances the reliability and effectiveness of the system especially during the abnormal voltage operations.

This work proposes the techno-economic analysis of a three-phase, three wire grid integrated third-generation perovskite solar cells-wind energy conversion system (PSC-WECS) controlled by a two-level voltage source converter (VSC) which is driven by the application of polynomial zero-attracting least mean square (PZA-LMS) algorithm. The proposed algorithm enhances the dynamic performance of the system by introducing sinusoidal grid currents with low total harmonic distortion (THD) which enhances system performance by providing acceptable outcomes under dynamic loading, fluctuating wind velocity, and solar insolation by compensating for load reactive power and balancing load and power demands at the point of coupling. This work replaces the conventional silicon PVs with PSCs to improve the economics of power generation thanks to their higher efficiency. For relative comparisons, the performance of the proposed 36kWPSC-WECS is compared with the conventional silicon PV-WECS. The results reveal that the proposed system has a low net present cost (NPC) of $68843 compared to the conventional system which costs $160917, translating to a reduction of 58% in total cost. Sensitivity Analysis (SA) is performed to analyse the dependence of optimal solutions on the uncertainty of key variables namely NPC, cost of energy (COE), windspeed & insolation. The results show that the total NPC is more sensitive to the COE and the average wind speed as compared to the other variables. Moreover, the area covered by the proposed system is reduced by 50% while as the cost of power generation is reduced by 72% due to the high efficiency of PSCs. The results obtained in MATLAB/Simulink and HOMER to determine the optimum quantity of the renewable energy sources (RES) model demonstrate the effectiveness of the recommended system.

This article presents application of generalized robust logarithmic family (GRLF) framework derived least absolute difference (LAD) Algorithm implemented for active power filters (APF) for PQ enhancement. The presented GRLF-LAD algorithm successfully eliminates lower as well as higher order errors from the harmonically rich nonlinear load currents and thus results in accurate fundamental component extraction. Weak power grids are characterised by distorted grid voltages and riddled with inherent harmonics. Conventional techniques such as synchronous reference frame (SRF) algorithm are unable to filter out the harmonics from grid voltages and this results in oscillations in D-Q components. This leads to generation of a distorted reference current and thus unsatisfactory APF performance. In this article, the grid voltages are processed by modified second-order generalized integrator with quadrature signal generator (QSG-SOGI) based algorithm. The harmonic rejection capabilty of QSG-SOGI is far superior than other tested algorithms. QSG-SOGI shows remarkable improvement of approximately 99.35% than SRF and 96.02% than SOGI in terms of percentage improvement. The performance of presented APF is verified experimentally on a developed prototype and tested rigorously against load variations, grid voltage variations as well as grid distortions. The GRLF-LAD algorithm is found to be approximately 36.04% faster than APA and about 45.16% faster than LMS in terms of dynamic response and about 11.19% better than LMS in accurate current component extraction. The total harmonic distortion (THD) content of presented algorithm is found to be well within the IEEE-519 std.

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 V_dc 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.

This study illustrates that the employment of a compensator can boost the performance of a solar PV distribution system, when there is volatility in the utility voltage. A two-step control system was used in this investigation. DC- DC converters employ a fuzzy logic controller (FLC) in its first stage to monitor the PV arrays maximum power output. First, the DC voltage is amplified and regulated, and then it is supplied to the voltage source converter (VSC). An open-loop PI controller is utilized so that the DC link voltage may be maintained at a consistent level. The second step is to figure out the DSTATCOM’s reference current. A reference current can be calculated if the quantity of energy produced by solar PV, the amount of electricity required by the loads in the network, and the amount of power lost in the DC links are all known. The SLMK controller calculates the fundamental value of required load current using ADALINE as a reference. When the utility side is pure, generating unit templates under balanced grid conditions comes naturally. However, this is rarely present on the distribution side. Hence, cleaning up dirty grids using multi- delayed signal cancellation (MDSC) yields unit vectors under distorted grid scenarios. This study used MATLAB/Simulink to show how a 32-kW solar photovoltaic array works and to assess the system’s efficiency in both normal testing circumstances and non-linear load situations. To ensure IEEE519 and IEEE 1547 conformance, the MATLAB-simulated system is put through power factor correction (PFC) and harmonics reduction tests in the presence and absence of solar power to replicate utility-side voltage abnormalities.