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Large photovoltaic (PV) penetrations into the electric grid resulted in new challenges such as reverse power flow and violation of voltage profile. The traditional methods for voltage regulation in a grid‐connected PV system are hardly adaptable to these changes as they only contain the local information which is used without the knowledge of how t...
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... The integration of high levels of PV systems into the electric grid has presented novel challenges, including issues related to reverse power flow and the violation of voltage profiles. A fault classification mechanism based on support vector machines is developed to enhance the efficiency of grid fault identification [25]. A synchronverter-based PV system has been developed by STATCOM (PV-STATCOM) to enable active and reactive power exchange with the grid. ...
... BFA [25] Soft computing ...
Static compensators (STATCOMs) are often used in distribution systems to enhance power quality. There is a need to enhance the performance of STATCOM to optimize its utilization and facilitate the provision of additional ancillary services. This paper employs the multilayer discrete noise-eliminating second order generalized integrator (MDNESOGI) to regulate the quasi-impedance source inverter (qZSI)-STATCOM for power exchange with the grid. Compared to conventional second-order generalized integrator (SOGI), MDNESOGI exhibits a higher capability for rejecting DC offset. In instances of abnormal grid operation or system malfunction, the inclusion of DC rejection capability enhances the robustness and reliability of the system. The suggested control algorithm only requires two integrators, three mathematical operators, and a damping factor, making it far easier to implement than transformation-based methods. The distorted load current is broken down into its active and reactive components using this control mechanism. The reference currents are then calculated by multiplying these parts by their corresponding voltage standards. The DC offset is reduced and transient oscillations in the weight component are eliminated by adjusting the damping factor. The suggested algorithm effectively handles power quality tasks like (a) reducing harmonic distortion, (b) compensating for reactive power, (c) adjusting for power factor, and (d) balancing the load under different conditions in the distribution system. The experimental study results are used to examine the stability of the proposed control scheme in both static and dynamic scenarios. In addition, a comparison to traditional methods is provided to demonstrate the new method’s superiority. Experimentation results show that the suggested controller is superior to its contemporaries in all scenarios where power quality is a factor, meeting the IEEE standard requirements.
... Detection of grid accident events [139] is also important in the decision-making process for emergency operations. In order to detect such system accidents, ML approaches such as the autoregressive (AR) model [140], K-nearest neighbor (K-NN) approach [141,142], SVM [140,[142][143][144][145], Random Forest [142,146,147], Bayesian network [148], adaptive neuro fuzzy inference system (AN-FIS) [149], auto-encoder [150], CNN [151,152], and LSTM [153] have been applied in various studies. In particular, ref. [154] considered the application of a bootstrap-based ensemble learning scheme in the decision-making process for control against fault-induced delayed recovery [155]. ...
The widespread introduction of functionally-smart inverters will be an indispensable factor for the large-scale penetration of distributed energy resources (DERs) via the power system. On the other hand, further smartization based on the data-centric operation of smart inverters (S-INVs) is required to cost-effectively achieve the same level of power system operational performance as before under circumstances where the spatio-temporal behavior of power flow is becoming significantly complex due to the penetration of DERs. This review provides an overview of current ambitious efforts toward smartization of operational management of DER inverters, clarifies the expected contribution of machine learning technology to the smart operation of DER inverters, and attempts to identify the issues currently open and areas where research is expected to be promoted in the future.
... Along with the growth of renewable energy resources is the widespread deployment of grid-tied power converters. However, the switching feature of power converters, together with the intermittent and stochastic behaviors of renewable energy sources, challenge the power quality (PQ) of modern power systems [1][2][3][4][5][6]. Typical PQ issues, such as voltage sags/swells, reactive currents, voltage/current harmonics, and voltage/current imbalances, may cause undesirable power losses, equipment malfunction, and even blackouts [7][8][9][10]. ...
Distributed static compensators (DSTATCOMs) are grid-connected power electronic equipment dedicated to compensating reactive power as well as improving voltage regulation in distribution networks. They eclipse conventional compensation approaches, such as capacitor banks, in terms of flexibility and effectiveness. Despite their identified advantages, STATCOMs with voltage droop are subject to weak grid-induced stability problems, as first revealed by this paper. Specifically, the voltage droop controller that couples the amplitude of point of common coupling (PCC) voltages to the reactive current reference creates a local control loop. Such a loop greatly deteriorates system stability in weak grids, which feature large and variable grid impedances. To address such stability problems, we propose a novel virtual resistance control scheme, which improves system stability through mitigation of local control loop gains in the low-frequency band. Experimental results obtained from a DSTATCOM prototype clearly demonstrate the correctness of stability analysis and the effectiveness of stability improvement.
... Therefore, GCPS has attracted significant attention among researchers [2,3]. These systems have DC to AC converters or inverters as the "core" component since they are responsible for the grid forming, grid feeding, and grid supporting operations of the PV systems [4]. A general structure of a GCPS with two-stage three-phase inverter is shown in Fig. 1. ...
Over the past few years, the power electronic converters have gained significant attraction among researchers, especially as an interface between distributed generation (DG) systems and the grid. Hence, it is imperative to establish a path for enhancing the operation of power electronic converters, and improve their reliability. Further, it is identified that for a solar photovoltaic (PV) inverter the power module construction intricacy and the complex operating conditions may degrade the reliability of these modules, affecting the functional efficiency of the overall grid-connected PV systems (GCPS). These constraints are considered to have a serious impact on the safety and failure cost especially associated with the grid-connected PV inverters (GCPIs). Therefore, it becomes crucial to have a clear understanding on the health monitoring strategies and reliability aspects corresponding to GCPIs. Consequently, it is also necessary to arrange all the information regarding major failure modes and categorize their root-cause analysis specific to GCPIs. In light of the above requirements, this paper contributes to the current research in making the GCPS more robust, efficient and reliable. The review identifies a comprehensive list of various failure modes in the inverter power modules and capacitors, and provides a broad view of their detection and localization approaches available in the literature.
... Moreover, it is identified that enhancing active power injections and reducing active power oscillations are highly prioritized instead of providing voltage support. In [10], [11], the LVRT capability of a hybrid power system is enhanced by reinforcement learning techniques through convertible static compensators. The connection of additional static compensation devices is considered as a solution for achieving voltage support but incurs additional cost. ...
This paper develops a fault ride-through (FRT) control strategy for achieving low voltage ride through (LVRT) in single-phase grid-connected photovoltaic (PV) systems (GCPVS). The proposed control system adapts a neural network (NN) classifier for islanding classification and model predictive control (MPC) for achieving the control of the two-stage PV system. This control scheme takes advantage of the nonlinear nature of the power converters and develops a cost function-based approach to achieve fast and efficient control. Besides, the proposed controller provides voltage support to the grid during voltage sags by injecting minimum reactive current within the threshold. The operation of the proposed control strategy is verified by performing simulation tests on a GCPVS by creating a sag type of fault in the utility. Further, laboratory experiments were carried out with the developed controller. The results ensure that the proposed control system adheres to the grid requirements by enabling voltage support during grid faults.
... This mode uses the under-voltage protection system of the PV plant, as shown in Fig. 1. During this condition, the PV inverter disconnects from the grid when the voltage varies between ± 6 % of nominal voltage for more than a stipulated time of 2 secs [27], [28]. The considered protection relay is depicted in Fig. 1 This article has been accepted for publication in a future issue of this journal, but has not been fully edited. ...
This paper presents a dynamic voltage support (DVS) scheme for achieving low voltage ride-through (LVRT) with a grid connected photovoltaic (PV) inverter during the voltage sag fault. The DVS scheme is achieved by formulating an additional reactive active current control (ARACC) mode which is developed from a conventional reactive current control (RCC) approach. This provides stable operation of the system and achieves higher effectiveness due to the lower X/R ratio at the point of common coupling (PCC) in low voltage (LV) networks. Further, the performance of the proposed controller is assessed by simulating a system for voltage sag faults. Further, the proposed controller tested with the real-time simulations and experimental setup for voltage sag conditions. The results presented demonstrate that the active and reactive power is regulated in concordance with grid code requirements. The controller achieves LVRT within the time limits of grid standard during symmetrical faults, which makes it appropriate for fast transient events. This operates the PV system under its nominal capacity, avoiding unwanted grid disconnection events.
... Reactive power is supplied to provide stability to the grid voltage during voltage deviation [19]. During grid fault or voltage sag, reactive power is supplied to provide static grid support and reactive current is injected for dynamic grid support [20]. At times, the DGs remain connected with the grid during fault condition for certain period as discussed in pervious sections. ...
... Decentralized coordination control does not use any communication structure among control entities and solely relies on local measurements. 21,64,65,[124][125][126][127] In contrast, centralized control utilizes a supervisory control employing a sophisticated communication link. 22,128,129 Distributed control architecture is based on a communication network exclusively among the local controllers without having a centralized control. ...
... Considering the STATCOM and PV inverter, two types of coordinating schemes are discussed. 64,126 One is based on a staged reactive power PI-controller, which utilizes the output reactive current control signal of the STATCOM as an input of the PV inverter. 64 In this way, the STATCOM is mainly responsible for generating reactive power unless additional reactive power is also required from the PV inverter to overcome a severe fault. ...
... Another approach uses a hierarchical coordinated structure. 126 The first layer control only utilizes the reactive power injection/absorption of the PV inverter and, in case it is insufficient to meet the grid code F I G U R E 7 Coordinated reactive power control based on local measurements 65 requirement, the second layer control is then activated in which the STATCOM provides the reactive power regulation. The scheme is tested subject to support vector machine (SVM)-based grid fault classification. ...
In recent years, the development of renewable energy sources (RESs) and their integration with the conventional power network have increased significantly. Due to the power grid transformation brought about by the large penetration of power electronics converter-based RESs such as wind and solar photovoltaic (PV), the operation and control of the interconnected power system has become a challenging task with respect to sustaining its stability and reliability. Power systems are confronted by several new stability issues because the dynamic behavior of converter-interfaced renewable sources differs from conventional generation. In this respect, static synchronous compensator (STATCOM), a shunt connected flexible AC transmission system (FACTS), is recognized as a fundamental solution for maintaining power system stability. This paper presents a thorough and state-of-the-art review of STATCOM control in wind- and/or PV-interfaced power systems for enhancing system performance by addressing key stability issues related to rotor angle stability, voltage stability, and resonance stability. A comprehensive analysis of various control techniques of STATCOM based on conventional, adaptive, nonlinear, predictive, robust, and coordinated control and soft computing techniques is provided. Furthermore, the function of the grid-side converter of the wind/PV plant as a STATCOM is also evaluated. Finally, the shortcomings of existing research are highlighted, current control challenges are presented, and several topics for future research are suggested. This paper provides researchers the opportunity to consider the current state of research and develop new control schemes for STATCOM to further improve the stability of modern power grids.
... In [117], a droop-based LVRT technique is discussed in which the variation in the DC link voltage is monitored and in the case of a drop, maximum power point tracking (MPPT) is switched to the ride through mode of the controller. Further, in [118], a coordinated reactive power injection control is proposed that utilizes the FACT device along with the inverter control for reactive power injection based on the priority assigned and injection requirement. ...
The use of artificial intelligence (AI) is increasing in various sectors of photovoltaic (PV) systems, due to the increasing computational power, tools and data generation. The currently employed methods for various functions of the solar PV industry related to design, forecasting, control, and maintenance have been found to deliver relatively inaccurate results. Further, the use of AI to perform these tasks achieved a higher degree of accuracy and precision and is now a highly interesting topic. In this context, this paper aims to investigate how AI techniques impact the PV value chain. The investigation consists of mapping the currently available AI technologies, identifying possible future uses of AI, and also quantifying their advantages and disadvantages in regard to the conventional mechanisms.
... Furthermore, the PV array and boost converter MPPT configurations are connected with the single phase PVIs. These PVIs operate the PV system in both grid forming/ feeding/supporting and load demand satisfying modes [30]- [32]. The control structure of these PVIs is dependent on the nested current and voltage control loops discussed in Section II. ...
The demand for integration of solar-based photovoltaic (PV) system to meet the energy need of residential buildings is growing very rapidly. However, the energy management system of these buildings has become an emerging area of research due to the rapid implementation of PV systems. The objective of this work is to propose an intelligent controller to share power generation of two PV sources for energy supply in buildings. The control is implemented using an adaptive neuro fuzzy inference system (ANFIS). The proposed methodology is developed with two different rooftop PV systems to achieve sharing of generated power as per the load profiles. The proposed design has better utilization of PV system installed in a residential area, and the results depict the maximum utilization of solar power.
