Hybrid AC-DC Microgrid Research Articles

Stability enhancement of battery energy storage and renewable energy-based hybrid AC/DC microgrids using terminal sliding mode backstepping control approaches

In this paper, a terminal sliding mode backstepping controller (TSMBC) has been proposed for various components of a hybrid AC/DC microgrid (HADMG) to enhance its dynamic stability. The proposed control technique is employed to generate switching control signals for converters, which serve as the primary interface between the DC bus and the AC bus in a hybrid microgrid. Additionally, this technique facilitates the interface of PMSG-based wind generators, solar photovoltaic generators, and battery energy storage systems with the DC bus. Through the implementation of the composite control technique, the global stability of the microgrid is ensured by driving all the states of the HADMG associated with various components to converge towards their intended values. Afterward, the Lyapunov control theory has been used to analyze the converter and inverter’s large-signal stability while ensuring the robustness of the proposed robust composite controller. Finally, an extensive simulation study was conducted on a hybrid microgrid to verify the efficacy of the designed controller in maintaining power balance amidst variations in the system’s operational regimes. Moreover, the effectiveness of the controller’s practical implementation is confirmed by real-time processor-in-the-loop analysis. Simulation results clearly show that the proposed TSMBC improves the overall dynamic performance of the hybrid microgrid with less overshoot (0%) and settling time (110 ms) in DC bus voltage when compared to the existing sliding mode controller.

Distributed Unified Control for Global Economic Operation and Resilience Reinforcement of Hybrid AC–DC Microgrids

The paralleled bidirectional interlinking converters (BILCs) of the hybrid AC/DC microgrid (HMG) provide a flexible and reliable power interaction way between AC and DC subgrids with high power density. A distributed unified control (DUC) is proposed for BILCs to achieve both resilience reinforcement and global economic operation of the HMG. For distributed generators (DGs), the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$f_{ac}-\lambda _{ac}$</tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$v_{dc}-\lambda _{dc}$</tex-math></inline-formula> economic droop controls are employed for AC DGs and DC DGs to decrease the individual subgrid's generation expense by equaling DGs' incremental expenses (IEs). For BILCs, the normalized AC subgrid's frequency and DC subgrid's voltage are coordinated to achieve the economic power interaction (EPI), which further decreases the total generation expense (TGE). Besides economic operation, the proposed DUC is capable of adopting different MG operation modes into a unified control structure without any mode switching. Paralleled BILCs are managed to reinforce the system resilience by supporting the DC voltage or AC voltage once all DC or AC DGs fail. In addition, the proposed DUC enables BILCs with plug-and-play characteristics, resistance to the maximum acceptable communication delay, and the communication disruption robustness. The corresponding hardware-in-the-loop (HIL) results verify the effectiveness of the proposed control strategy.

A fuzzy-logic-based smart power management strategy for reliability enhancement of energy storage system in a hybrid AC-DC microgrid with EV charging station

Abstract As Electric Vehicles (EVs) are considered as the future of the automobile industry, the demand for EV charging stations immensely rises. Though grid support can be expected for a microgrid (MG), it is highly advantageous to be self-reliant and be prepared for standalone operation for a long duration. This paper proposes a hybrid ac/dc microgrid (HMG) with an EV charging station in standalone mode with a smart power management strategy that increases the reliability of operation. Different modes of operation are designed according to power consumption levels and the operation of MG is switched between these modes considering the solar irradiance and battery bank state of charge. The decision-making system uses a combination of (a) fuzzy logic approach based on the state of charge of the energy storage system (ESS) and solar irradiance, adding to the intelligence of the system and providing smart reasoning capability and (b) logical decisions based on solar power and battery state of charge, considering all possible operating scenarios. With the proposed power management strategy in place, the standalone hybrid microgrid system is found to be able to prolong the discharge of the energy storage system under critical conditions of low battery state of charge and PV power availability and also under highly critical situations will be able to meet the critical load demand making use of the power available in the EV connected. Emphasis has also been given to maintaining the stability of the system while performing shifts in operating modes and during sudden changes in the scenario. Different operating conditions are recognized by the power management module in the model and an appropriate power management strategy is applied. Real-time simulation of the model was done in OPAL-RT real-time simulator using RT-LAB software and simulation results were reproduced.

Comprehensive review on control schemes and stability investigation of hybrid AC-DC microgrid

The utility grid integration of distributed generation units is seen as one of the most accomplished through the use of microgrid. Control methods and stability analyses in the microgrid are continuously being investigated in the field of hybrid microgrid. The most reviewed control method is hierarchical control, consisting of primary, secondary, and tertiary layers. This paper reviews multiple schemes of primary control for current or voltage regulation, secondary control for voltage or current error correction, power-sharing in microgrid, and tertiary control for power flow and energy management in a hybrid microgrid system. Additionally, this study examines the benefits and drawbacks of several control architectures that function as distributed, centralized, and decentralized controls. The principle of operation and effectiveness of each microgrid architecture control method have been discussed. Specific control factors are investigated in this paper, including mode transition and coordinated control between numerous interlinking converter and energy storage systems. System stability is the main concern of microgrid for system engineer thorough knowledge of control strategies is the upmost requirement. Thus, this paper highlights control strategies, rotor angle, voltage and frequency instability in power systems, and methods for improving stability in microgrid are also reviewed.

An improvement of stability and dynamic response in hybrid AC-DC microgrids using optimal power control management

Microgrid topologies enable more effective use of renewable resources as well as the autonomous process. Microgrids are effective frameworks for managing dispersed assets such as renewable structures with small-scale distributed generator supplies. Smart grids are adaptable electricity networks that have arisen as a result of the introduction of new technologies and features. It is suggested that a three-terminal AC/DC hybrid microgrid with DC two and AC one terminal be used. A two dual active bridge (DAB) with cascaded H-bridge (CHB) converter with AC grid link-based interactions that connect isolated two DC buses are included in the suggested structure. To minimise the energy generation stages and power devices, the DAB converters are intrinsically linked to the CHB of DC rails based on the structure-specific requirements. To present the unnecessary grid currents and DC rail voltage issues exist by this revised structure topology by simply two power alteration stages, a better solution is suggested that employs zero-sequence voltage (ZSV) injection in the CHB converters. The impacts of managed settings on structure stability and dynamic responsiveness are investigated in order to reduce conflicts among ZSV injection by structure voltage/current regulation. This paper compares the performance of a PI and a PR for DC voltage regulation. A comparison of simulation results for both control approaches is provided. The major difficulty is to normalise the system model in order to identify the appropriate controller settings for robust control. The findings are confirmed and compared to the conventional regulator PI. The suggested 3-Φ AC current and DC rail voltage regulating approach's universal efficacy is proved by MATLAB/Simulink analytical model from the three and five-terminal hybrid AC/DC power structures.

Study of coordinated control strategy for hybrid AC–DC microgrid in islanding mode

As a kind of generation and distribution system with autonomous control, AC–DC hybrid microgrid plays a pivotal role in the transformation and development of modern power grids. To address the problems of microgrid system instability that occur in islanding mode, the study proposes a coordinated control strategy for hybrid AC/DC microgrid in islanding mode. First, the bidirectional AC/DC interconnection converter is modelled and parametrically designed; second, the control strategy of the interconnection converter in islanding mode is raised, including both active power control with double-loop control and seamless switching of operation modes with pre-synchronous control, and in the end, the effectiveness of the strategy is examined. The data display that under this strategy, the real and reactive power output gaps between the micro sources in the hybrid microgrid do not exceed 0.01 kW and 0.03 kVAR, respectively, and the current during islanding switching is more stable up to 32 A. This shows that the strategy effectively improves the shortcomings of the traditional regulation method, realizes the accurate distribution of real and reactive power, improves the power sharing between DC and AC subgrids, strengthens the stability and reliability of the hybrid microgrid, and helps to promote the technological progress of the hybrid microgrid and escorts the efficient and green development of the smart grid.

Design of voltage stabilizing control for a hybrid microgrid with state constraints based on the switching system

With the application and development of new energy generation technology and distributed power supply system, AC-DC hybrid microgrid has the comprehensive advantages of AC microgrid and DC microgrid, and it is significant to study the voltage stability of hybrid microgrid. Based on the switching system theory, the voltage stability control of the ac-dc hybrid micro-grid in grid-connected and the off-grid operation mode are studied in this paper. Considering that the AC and DC bus voltages of the microgrid are constrained in practical engineering applications, the Backstepping controller is designed by using the barrier Lyapunov function and Backstepping method. Considering that the equivalent resistance in the system can not be accurately measured and combined with adaptive control, it is more practical for practical engineering applications.

Hybrid AC/DC control techniques with improved harmonic conditions using DBN based fuzzy controller and compensator modules

Hybrid AC–DC microgrid provides highly distributed generation receiving capacity by reducing multiple power conversions in individual AC or DC microgrids. Thus, the control of grid variables in a hybrid AC–DC microgrid is complicated due to erroneous frequency transients and the impact of negative sequence components. Hence, a novel Synchronous Reference Frame Phase-Locked Loop (SRF-PLL) with Self-curing decoupling network is introduced in which this network provides synchronization and distinguishes positive and negative sequences in discrete blocks. To eliminate fluctuation of grid variables in ac and dc sides, a novel Switched Tuned Arm Filter (STAF) and Variable Voltage Stabilization Compensator (VVSC) Multi-loop controller including central Deep Belief Network (DBN) with Fuzzy controller is presented. In which STAF Multi-loop controller use tuned circuits to suppress higher-order harmonics. Also, a central DBN with a fuzzy controller provides a control signal to an ac/dc converter to regulate power transmission. Additionally, in order to stabilize the dynamic voltage and compare the DC bus voltage with the reference value, the VVSC Multiloop controller uses a PWM to compare the DC bus voltage. Then the proposed techniques are simulated in Simulink platform and the results achieved stabilized voltage, low RMSE, and low delay.

A Unidirectional Hierarchical Control Structure With Zero Power Sharing Error for Hybrid AC/DC Microgrid

The desire for decreasing the stress on the individual AC and DC sources motivates accurate load sharing in Hybrid AC/DC microgrids (HMGs). The conventional hierarchical control scheme suffers from error in active power sharing among the DC sources and inaccurate reactive power sharing in the AC microgrid, which result from the local property of voltage. To circumvent this issue, a unidirectional hierarchical control scheme, which employs a combination of central and local secondary controllers is proposed in this paper. For each of the DC and AC microgrids, the central secondary controller eliminates the voltage/frequency deviations through a common control signal, which is broadcasted to the sources and interlink converter (IC). In addition, the DC and AC PCC voltages are broadcasted to the sources and IC. The local secondary controller (power sharing correction unit) of each source alters the central secondary control signal based on the PCC voltage. By incorporation of the PCC voltage in the droop characteristics of the sources and the control loop of IC, the error in active/reactive power sharing is eliminated. The stability of the proposed scheme is analyzed through small signal analysis. Simulation and experimental results are presented to validate the proposed control method.

A Data-Driven Convex Model for Hybrid Microgrid Operation With Bidirectional Converters

Bi-directional converters (BDCs) facilitate the high efficiency of hybrid AC/DC microgrids (HMs). However, the HM operation is rather challenging due to the non-convex system model. This letter develops a data-driven convex model for HM operation involving BDCs. First, a least squares approximation method with data-driven weight functions is proposed to linearize BDC efficiency behavior. Then, the convex linear HM model is formulated by combining this linearized model with an analysis of the conditions ensuring non-simultaneous BDC inverting and rectifying operations. The low approximation error and high computational efficiency of the proposed model are demonstrated based on an analysis of numerical studies.

An Energy Trading Framework for Interconnected AC–DC Hybrid Smart Microgrids

This paper proposes a three-stage energy trading framework (ETF) for interconnected AC-DC hybrid microgrids (IHMGs) in the presence of renewable distributed generators (DGs) and battery energy storage systems (BESSs). The proposed ETF aims at minimizing the operating cost of each microgrid (MG), and it includes three stages: a pre-trading stage, a trading stage, and a post-trading stage. The ETF determines the optimal hourly trading prices and powers while preserving the privacy of information for each MG. The proposed framework allows each MG to schedule its operation economically and reliably through optimizing its local resources (i.e., DGs and BESSs) as well as exchanging power with neighboring MGs and the main grid. The proposed ETF takes into account the internal topology and power flow constraints for different types of MGs (i.e., AC, DC, and AC-DC hybrid MGs). The proposed three-stage ETF is tested using a case study that includes different types of MGs with different types of loads and DGs. The effectiveness of the proposed ETF is verified through a comparison with the base-case system for both grid-connected and isolated modes of operation.

Adaptive Neural Network Q-Learning-Based Full Recurrent Adaptive NeuroFuzzy Nonlinear Control Paradigms for Bidirectional-Interlinking Converter in a Grid-Connected Hybrid AC-DC Microgrid

The stability of a hybrid AC-DC microgrid depends mainly upon the bidirectional interlinking converter (BIC), which is responsible for power transfer, power balance, voltage solidity, frequency and transients sanity. The varying generation from renewable resources, fluctuating loads, and bidirectional power flow from the utility grid, charging station, super-capacitor, and batteries produce various stability issues on hybrid microgrids, like net active-reactive power flow on the AC-bus, frequency oscillations, total harmonic distortion (THD), and voltage variations. Therefore, the control of BIC between AC and DC buses in grid-connected hybrid microgrid power systems is of great importance for the quality/smooth operation of power flow, power sharing and stability of the whole power system. In literature, various control schemes are suggested, like conventional droop control, communication-based control, model predictive control, etc., each addressing different stability issues of hybrid AC-DC microgrids. However, model dependence, single-point-failure (SPF), communication vulnerability, complex computations, and complicated multilayer structures motivated the authors to develop online adaptive neural network (NN) Q-learning-based full recurrent adaptive neurofuzzy nonlinear control paradigms for BIC in a grid-connected hybrid AC-DC microgrid. The proposed strategies successfully ensure the following: (i) frequency stabilization, (ii) THD reduction, (iii) voltage normalization and (iv) negligible net active-reactive power flow on the AC-bus. Three novel adaptive NN Q-learning-based full recurrent adaptive neurofuzzy nonlinear control paradigms are proposed for PQ-control of BIC in a grid-connected hybrid AC-DC microgrid. The control schemes are based on NN Q-learning and full recurrent adaptive neurofuzzy identifiers. Hybrid adaptive full recurrent Legendre wavelet-based Neural Network Q-learning-based full recurrent adaptive NeuroFuzzy control, Hybrid adaptive full recurrent Mexican hat wavelet-based Neural Network Q-learning-based full recurrent adaptive NeuroFuzzy control, and Hybrid adaptive full recurrent Morlet wavelet-based Neural Network Q-learning-based full recurrent adaptive NeuroFuzzy control are modeled and tested for the control of BIC. The controllers differ from each other, based on variants used in the antecedent part (Gaussian membership function and B-Spline membership function), and consequent part (Legendre wavelet, Mexican hat wavelet, and Morlet wavelet) of the full recurrent adaptive neurofuzzy identifiers. The performance of the proposed control schemes was validated for various quality and stability parameters, using a simulation testbench in MATLAB/Simulink. The simulation results were bench-marked against an aPID controller, and each proposed control scheme, for a simulation time of a complete solar day.

Reinforcing Data Integrity in Renewable Hybrid AC-DC Microgrids from Social-Economic Perspectives

The microgrid (MG) is a complicated cyber-physical system that operates based on interactions between physical processes and computational components, which make it vulnerable to varied cyber-attacks. In this article, the impact of data integrity attack (DIA) has been considered, as one of the most dangerous cyber threats to MGs, on the steady-state operation of hybrid microgrids (HMGs). Additionally, a novel method based on the sequential hypothesis testing approach is proposed to detect DIA on the renewable energy sources’ metering infrastructure and improve the data security within the HMGs. The proposed method generates a binary sample, which is used to compute a test statistic that is further used against two thresholds to decide among three alternatives. The performance of the suggested method is examined using an IEEE standard test system. The results illustrated the acceptable performance of the proposed methodology in detection of DIAs. In addition, to evaluate the effect of DIA on the operation of the HMGs, DIAs with different severities are launched on the measured power generation of renewable energy resources like wind turbines. The results showed that a successful DIA on renewable units can severely affect the operation of electric grids and cause serious damage.

Operation and coordination control scheme of an enhanced AC–DC hybrid microgrid under abnormal distribution network

AbstractConsidering that the AC–DC hybrid microgrid (HMG) is connected to the low‐voltage distribution network (DN) where voltage faults occur most commonly, the fault ride‐through (FRT) capability and power quality performance of the HMG under abnormal DN conditions have become a critical issue. In this paper, a decentralized coordination control scheme based on an improved topology is proposed for the grid‐interactive HMG to guarantee uninterrupted and high power‐quality operation during grid faults. The method of it includes: (1) a new HMG topology is presented by adding a series transformer (ST), which is inserted between the DN and HMG; (2) an improved coordination control strategy that considers the interaction between converters of the enhanced HMG. Based on the proposed method, the operation modes of the system are introduced, and the specific design process and small‐signal model analysis of the proposed control scheme are presented. Finally, the simulated and experimental results show that the proposed method can keep both AC and DC bus voltage stable and improve the fault ride‐through capability and power quality of the HMG under abnormal DN conditions.

Real-Time Machine Learning-based fault Detection, Classification, and locating in large scale solar Energy-Based Systems: Digital twin simulation

The current study considers numerous renewable energy resources, distributed power generation units, energy storage, and plug-in hybrid electric vehicles (PHEV) in order to propose a reliable large-scale energy management framework that can be applied to islanded and grid-connected operations of renewable hybrid AC-DC microgrids (MGs). The framework uses a bat optimization algorithm (BOA) for minimizing the operating costs of the network and in addition introduces an intrusion detection system (IDS) according to the sequential hypothesis testing (SHT) method for detecting identity-enabled cyber-attacks (i.e classification of Sybil attacks, masquerading attacks) on the wireless-enabled advanced metering infrastructures (AMI). The suggested IDS uses the received signal strength (RSS) amount for distinguishing various signal resources and detecting cyberattacks. An IEEE 33-bus testing system has been used to construct a real-time hybrid MG in order to determine the reliability and efficiency of the suggested framework.

Self-Synchronizing Control Enabling Disruption-Free Operation and Seamless Mode Transitions in Wind–Solar Based Hybrid AC/DC Microgrid

This paper introduces a novel self-synchronizing control architecture for the power converters in a hybrid AC/DC microgrid (HMG), wherein, the doubly fed induction generator (DFIG) and the solar photovoltaic (SPV) array are utilized for wind and solar generation, respectively. The self-synchronizing control enables the HMG to remain functional and provides a disruption-free power at all the four identified operation modes. Different operation modes are enforced due to grid islanding or DFIG wind generator disconnection scenarios. Meanwhile, the shifting among these four operation modes culminate into eight possible transition phases. The HMG's self-synchronizing control is devised to achieve seamless operation at all possible transition phases, and avoids any voltage spikes or transient overcurrents. Such a seamless transition functionality becomes increasingly vital in case of the DFIG-SPV based HMG. This is due to the direct interconnection of DFIG stator with the utility grid that renders the system largely vulnerable to any un-synchronized transition. Therefore, major research emphasis of this work is on the development of a novel methodology for ensuring a disruption-free operation and seamless mode transitions in a DFIG-SPV based HMG. The HMG control is based on a new affine projection sign algorithm (APSA), which supplements the HMG with unity power factor operation and load unbalance/harmonics mitigation. The viability of the HMG and its self-synchronizing control at various mode transition phases and system dynamics are extensively tested on an experimental rig developed in the laboratory. Test results endorse the feasibility of the self synchronizing control, while, a comparative analysis demonstrates the superiority of the APSA scheme over other state-of-art approaches.

Control of ILC in an Autonomous AC–DC Hybrid Microgrid With Unbalanced Nonlinear AC Loads

This article presents a multiobjective control scheme for a bidirectional interlinking converter (ILC) of renewable energy based ac–dc hybrid microgrid. The prime focus of the power management algorithm is to feed the ac loads, and dc loads from ac source, and photovoltaic battery energy storage (BES), respectively. The second objective is to utilize the solar power to maximum capacity, by feeding it to dc load, BES, and ac load, in the given order of priority. The ac and dc subgrids operate independently, while supporting each other in case of overloading/underloading, thus reducing the amount of power reserve required in each, and eliminating the need of dump loads. The ANFIS-MN-based power quality control is integrated in order to ensure the total harmonics distortion of ac source current remains below 5% as per IEEE 519 standard, irrespective of the nature of load connected. In addition, the ILC control prevents any negative sequence currents from entering the ac source, even if there is any open circuit fault leading to unbalanced loading on the three phases. The performance of ANFIS-MN-based ILC control is demonstrated to be superior when compared with the conventional and contemporary techniques under different scenarios.

A Control Stage for Parallel-Connected Interlinking Converters in Hybrid AC–DC Microgrids

Having two or more interlinking converters connected in parallel in hybrid microgrids has some benefits, like modularity, flexibility, and redundancy. However, the parallelization of the inverters leads to circulating currents that can cause system malfunctions. This work uses a method for suppressing low-frequency circulating currents in interlinking converters by controlling the zero-sequence component of the phase currents, showing that the control structure is valid for interlinking converters. The proposed control scheme has been applied to two parallel interlinking inverters of 5 kW and 2.5 kW, respectively. The interlinking inverters are connected to the grid, and they control the voltage in the DC bus of the hybrid microgrid. To validate the concept, simulation and experimental results are shown.

Power quality improvement of the grid-tied hybrid AC-DC microgrids by adding the bi-directional series converter

Power quality improvement of the grid-tied hybrid AC-DC microgrids by adding the bi-directional series converter

Power quality improvement of the grid-tied hybrid AC-DC microgrids by adding the bi-directional series converter

Power quality improvement of the grid-tied hybrid AC-DC microgrids by adding the bi-directional series converter