AC-DC Microgrid Research Articles

A novel bio-inspired stochastic framework to solve energy management problem in hybrid AC-DC microgrids with uncertainty

A novel bio-inspired stochastic framework to solve energy management problem in hybrid AC-DC microgrids with uncertainty

An Active Damping Technique for PI and Predictive Controllers of an Interlinking Converter in an Islanded Hybrid Microgrid

This article highlights a voltage instability when the bidirectional interlinking converter (BIC) of a hybrid ac-dc microgrid operates as a constant power load (CPL). The instability is attributed to the impedance interactions seen at the dc port of the BIC. The BIC is operated with two different controllers, viz., a PI controller and a model predictive controller (MPC). In order to avert the instability, prohibiting impedance interactions is proposed as a design objective while determining the bandwidth of the PI controller. However, since a flexible control over bandwidth is not available with MPC, an active damping technique is proposed to address the instability. The proposed technique works equally well for the PI controllers with fixed or predetermined bandwidths. An important feature of the proposed technique is that it does not interfere with the original objectives of the controllers, once the instability is addressed. The technique comprises only one tuning factor, which does not depend on the BIC's internal parameters. As a result, it can easily be implemented as a general stabilizing scheme in any BIC. The efficacy of the proposed technique is verified through simulations, frequency-domain impedance analyses as well as experiments on a laboratory prototype of the BIC.

Unified Virtual Oscillator Control for Grid-Forming and Grid-Following Converters

A unified virtual oscillator controller (uVOC) is proposed, which enables a unified analysis, design, and implementation framework for both grid-forming (GFM) and grid-following (GFL) voltage-source converters (VSCs). Oscillator-based GFM controllers, such as dispatchable virtual oscillator control (dVOC), offer a rigorous analytical framework with enhanced synchronization but lack effective fault handling capability, which severely limits practical application. The proposed uVOC facilitates synchronization with an arbitrarily low grid voltage and fast overcurrent limiting; this enables effective fault ride-through unlike existing GFM controllers which typically switch to a back-up controller during the fault. GFM operation with uVOC is achieved in both grid-connected and islanded modes with seamless transitions between the two. In GFL converters, bidirectional power flow control and dc bus voltage regulation are achieved with uVOC. No phase-locked loop (PLL) is required for either GFL or GFM operation circumventing the synchronization issues associated with PLLs in weak grid applications. Detail small-signal models for GFM and GFL operation have been developed, and the systematic design guidelines for controller parameters are provided. The proposed controller is validated through hardware experiments in a hybrid ac-dc microgrid.

Sustainable and reliable hybrid AC/DC microgrid planning considering technology choice of equipment

Abstract Today, the microgrid is not a new concept, and its diverse benefits for the grid and also consumers have been proven. One of the effective ways to enhance penetration level of the microgrids is to improve economic affordability. This can be achieved by defining an optimal investment plan which has been studied for the several past decades. Previous researches have been proposed a model which used a set of typical values as input parameters of the components. As a result, the optimization results may not be fully implementable in practice. In this regard, this paper proposes a new planning model for a hybrid AC–DCmicrogrid which selects the best technology from a set of commercial models already available in the market in addition to optimally selecting the size (number) of each equipment. Among the microgrid equipment, this capability is considered for storage batteries and wind turbines considering their variety of parameters and market models. The proposed model, while linear, takes into account the various parameters of the equipment in addition to the reliability and emission constraints. Results of implementing the proposed model on a test case demonstrated that outputs of the proposed model are more applicable to real practical projects.

ANFIS Based Smart Control of Electric Vehicles Integrated with Solar Powered Hybrid AC-DC Microgrid

In the coming years, charging of electric vehicles (EVs) may impose significant power loads on the existing utility system. Alternatively, the integration of EVs with distributed generation units may cause several uncertainties in microgrids. In such situations, controlling the frequency of microgrids will be a challenging task. Consequently, this calls for the requirement of implementing proper control techniques for utilizing EVs potential to act both as source and load. This paper proposes and evaluates the performance of the Primary ANFIS MPPT Controller for PV systems and Secondary ANFIS EV Controller for EV charging stations. The Primary ANFIS MPPT controller strictly monitors the power extracted from photovoltaic systems in different temperature and irradiance conditions. The Secondary ANFIS EV Controller schedules charging/discharging of plugged-in EVs w.r.t microgrid’s frequency and EV battery’s state of charge. To investigate the performance of proposed smart controllers, a hybrid solar-powered AC-DC microgrid is designed and tested. Dynamic simulations performed in MATLAB/Simulink demonstrate the right performance of smart ANFIS controllers in terms of frequency control. Moreover, extensive comparison studies conducted between proposed methods and existing techniques justify the higher suitability of developed controllers.

Virtual Synchronous Machine/Dual-Droop Controller for Parallel Interlinking Converters in Hybrid AC–DC Microgrids

This paper addresses the operation of parallel interlinking converters (ICs) in hybrid AC–DC microgrids from different perspectives, then proposes a unified mitigation technique. Firstly, the influence of the system nonlinearity on circulating currents between parallel ICs is investigated. Secondly, it is shown that ICs might induce voltage harmonics due to the antiparallel diodes of the power electronic switches which are seen by the AC subgrid as nonlinear diode rectifiers. Lastly, the synchronization of ICs following abnormal operating conditions is discussed and new findings are presented. In order to enhance the operation of ICs and overcome the preceding challenges, a modified virtual synchronous machine (VSM) strategy with a dual-droop (DD) controller is proposed. The positive influence of the proposed VSM-DD controller on the overall system dynamics is clearly justified. Small-signal state-space modeling for the entire system is conducted to verify the results analytically. A nonlinear time-domain simulation model is developed using PSCAD/EMTDC to validate the impact of the VSM-DD controller experimentally.

Stability and reliability of low voltage hybrid AC-DC microgrids power flow model in islanding operation

The problem of decreasing and increasing power flow in hybrid AC-DC microgrids in island operations is the concern of this research. This condition arises if one sub-microgrid cannot supply load power requirements, either due to a decrease in power at the source or an increase in load on the sub-microgrid network. As a result, in this research used the bidirectional converter as an interlinking converter, the converter can change the power flow from the ac sub microgrid to the dc sub microgrid and vice versa. With this bidirectional converter, load power requirements can be met even though there is a power change in one of the sub microgrid. The simulation in this research support by Simulink/Matlab software. The model is built in a low voltage system, and the power flow analysis is in steady-state condition with two different cases. The simulation results show the stability and reliability of the power flow in both sub microgrid with stable frequency and voltage when power and load change occur.

Virtual Resistor Based Second-Order Ripple Sharing Control for Distributed Bidirectional DC–DC Converters in Hybrid AC–DC Microgrid

The hybrid ac-dc microgrid, consisting of ac subgrid and dc subgrid, is a promising structure to interconnect ac and dc systems to provide high quality and reliable electric energy. However, in single-phase microgrid or unbalanced three-phase microgrid, second-order ripples of the dc subgrid can lead to significant power quality issues. The ripple mitigation function can be added to existing bidirectional dc-dc converters (BDCs) or dc active power filters. Considering these ripple sources can be distributed in the dc subgrid, it is essential to develop ripple mitigation control schemes for distributed BDCs. In this article, a virtual resistor based ripple mitigation strategy is proposed. Autonomous accurate ripple current sharing can be achieved for BDCs installed closely, enabling flexible parallel of ripple mitigation converters. A comprehensive parameter design method is developed to ensure the accurate sharing for closely installed BDCs. For dc subgrid with significant line impedance, the control scheme provides the opportunity for supervisory control to further enhance ripple current sharing and mitigation performance. Both simulation and experimental results validate that the control method and the parameter design method are effective.

Operation and Control of a Hybrid Coupled Interlinking Converter for Hybrid AC/Low Voltage DC Microgrids

The respective advantages of ac and dc microgrids lead to the blooming development of the hybrid ac/dc microgrid, which consists of ac and dc microgrid tied by an interlinking converter. A new structure of hybrid coupled interlinking converter (HCIC), which composed of a converter in series with a static VAR compensator (SVC), is proposed for hybrid ac and low voltage dc (LVdc) microgrids. Moreover, a new droop control method is correspondingly developed for the proposed HCIC. Its fundamental active and reactive power flow in the hybrid ac/dc microgrid is controlled by P-δ and Q-P-V droop control for converter part of the HCIC, and P-Q-α droop control is proposed for SVC part of the HCIC. Furthermore, a fast harmonic control is given based on a decoupled control strategy to improve the filtering characteristics of SVC part of the HCIC, suppress the harmonic power, and/or inject active power. Finally, simulation and experimental results are provided to verify that the proposed HCIC for hybrid ac/LVdc microgrids has the ability of good power flow control and power quality compensation, which not only meets the power flow requirements with low rating system, but also greatly promotes the development of more robust hybrid ac/dc microgrids.

Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands

The high growth of the automotive industry reveals the very bright future of this technology and its high penetration effects on the human society. No doubt that the random and volatile charging demand of these devices would affect the power grid optimal operation and scheduling which may be regarded as a new challenge. Therefore, this paper investigates the stochastic scheduling of hybrid AC/DC microgrids considering the plugin hybrid electric vehicles charging demands, distributed all over the grid. Three different charging patterns, called coordinated, uncoordinated and smart charging models with different characteristics for the charger type, capacity and market share are proposed. Moreover, different types of renewable energy sources including wind turbine, solar panel and fuel cell are modeled and considered in the scheduling process of the hybrid microgrid. In order to mitigate the charging effects of electric vehicles on the hybrid AC–DC microgrid operation, some remotely switches are considered in the system which make it possible for changing the topology and power flow way. In order to model the uncertainty effects, a data-driven framework based on point estimate method and support vector machine is developed. This would make it possible to extract out the standard deviation value of the uncertain parameters and reflect their impacts on the microgrid operation problem through the limited concentration points. A novel evolving solution based on flower pollination algorithm is also proposed to solve the problem optimally. An IEEE standard test system is used as the hybrid AC/DC microgrid case study to assess the performance of proposed model.

Simplified Hybrid AC–DC Microgrid With a Novel Interlinking Converter

Hybrid ac–dc microgrids (HMG) have become more popular recently because of their superior features in comparison with pure ac and dc microgrids (MGs). HMGs have fewer power converters and are more flexible than pure ac and dc MGs, but the number of converters in HMG is still significant, especially when the dc part of HMG has several voltage levels. A new simplified and more flexible architecture for HMGs that features a new multiport interlinking converter (IC) is proposed in this article. Using the proposed IC, the number of power electronic converters in an HMG with several dc bus voltages can be reduced without increasing the number of active switches in the IC or the complexity of its control system. In this article, the new simplified HMG architecture is presented, and the operation of the proposed IC as a single unit and as a part of a simplified HMG are explained, along with its features. Experimental results obtained from a scaled-down prototype are also presented to confirm the feasibility of the multiport interlinking converter. Simulation results that show the effect of load variations in the intermediate bus architecture dc bus on the operation of the HMG are also presented as well.

Research on Improved Droop Control of AC-DC Microgrid Bidirectional Converter Based on Power

The bidirectional converter in AC / DC hybrid microgrid is an important link to balance the power on both sides of AC and DC, Its control method is extremely important. This paper proposes an improved droop control strategy for bidirectional converter using DC-side power amount control. This control can autonomously and smoothly switch in rectifyer, inverter and idle modes. Utilizing DC-side power control avoids normalized calculations. Strategy meets two modes of island and grid connection, eliminating the need for multiple control strategy switches. Simulation results show that the DC bus voltage and AC frequency are near the rated value, which guarantees the stable operation of the AC-DC hybrid microgrid.

Optimization of Hybrid AC DC Microgrid in Grid Connected Mode

The instability of the production of renewable energy resources (RESs) is a major problem for its installation and integration with the utility grid. A hybrid AC/DC microgrid facilitates the good operation of RESs with a storage system in grid-tied mode and the possibilities of smart energy management. The present work is being carried out on smart control strategy for a hybrid AC/DC microgrid (HMG). This paper deals with a real-time Hybrid control system (HCS) for a grid-connected HMG where the supervisory control based totally on fixing an optimization hassle objectives to minimize operating cost with the maximum usage of renewable resources, minimum usage of the utility grid, extending energy storage systems (ESS) lifetime. The power references for renewable energy resources (RESs) are scheduled by the use of CPLEX solver which uses as input strength measurement, archived facts and stored climate forecast statistics previously measured regarding the modern status. The experimental study verifies well the supervision methodology; thus, the proposed algorithm respects the optimization in real-time operation under different constraints.

Comparative Assessment of Control Strategies Used in a Hybrid AC-DC Micro-Grid Consisting of Composite Energy Sources

In the present paper, comparative assessment of two important available intelligent control strategies namely the Mamdani fuzzy logic controller and the T–S fuzzy controller used for DC-link voltage control in DC micro-grid is carried out, first. Then, a new inverter control technique is proposed to maintain the inverter voltage as well as the DC-link voltage in a hybrid AC-DC micro-grid. The DC micro-grid under study comprises of photovoltaic system, permanent magnet synchronous generator-based wind energy system, battery energy storage system, fuel cell, electrolyzer and DC loads. The complete DC Micro-grid along with its correlated control algorithms are examined and accessed through MATLAB/Simulink environment.

A Vehicle-to-Microgrid Framework With Optimization-Incorporated Distributed EV Coordination for a Commercial Neighborhood

In this paper, an improved vehicle-to-microgrid (V2M) framework is proposed for a commercial locality operating as a hybrid ac–dc microgrid, which optimally coordinates electric-vehicle (EV) storages in a distributed manner. An aggregator model is proposed that solves the economic dispatch problem of parked EV storages in a centralized fashion and generates power references in real time for the designed EV storage controllers. Unlike the conventional EV storage controller, the proposed optimization-incorporated distributed EV storage controller can switch from decentralized to distributed control mode or vice versa based on situations and utilizes a sparse vehicle-to-vehicle communication network. The power flow between the ac and dc subgrids is managed by interlinking converters (IC). The IC control structure is augmented by combining voltage- and power-based droop-control schemes in the power control loop. This modification enables simultaneous ac and dc bus voltage regulations. Case studies are carried out to validate the efficacy of the developed framework with a real commercial network and loads. The results exhibit robust performance of the overall system for generation-demand variability, transitions between islanded and grid-tied conditions, and user-preferred EV disconnections and time delay.

Coordinated Power Management of the Subgrids in a Hybrid AC–DC Microgrid with Multiple Renewable Sources

ABSTRACTThis paper presents the assessment of the operation and control of hybrid AC–DC microgrid (HMG) integrated with alternative energy sources. The system is analyzed by incorporating fuzzy logic and adaptive neuro-fuzzy inference system (ANFIS) based controllers in the control scheme of battery. Photovoltaic array and fuel cell system are coupled to the DC bus and an electrolyzer based hydrogen storage system is used for energy storage in the DC subgrid. The output of the wind energy system along with the battery is fed to the AC bus through an inverter. The AC and DC subgrids are integrated through an interlinking converter which is controlled to facilitate power exchange between the subgrids based on the frequency of AC bus and DC bus voltage. Appropriate power management is achieved within the subgrids and between the subgrids by the coordinated control schemes employed in the HMG. The main focus of this article is the analysis of the impact of incorporating conventional proportional–integral controller, fuzzy logic controller and ANFIS based controller in the control scheme of the battery when the subgrids are subjected to power fluctuations. By employing the ANFIS based controller, the transients in the voltage and power output of the battery system are minimized and deviations occurring in the AC bus voltage during load variations are reduced.

A modified holomorphic embedding method based hybrid AC-DC microgrid load flow

Load flow study is a steady state analytical tool for power system network analysis where mostly iterative numerical methods are used to solve the load flow equations. But with the rise in complexity of the power networks due to amalgamation of both AC and DC power system within a network, the convergence time of these iterative load flow algorithms has been increased quite high. To resolve this problem a recursive load flow method has been developed called Holomorphic Embedding Load Flow Method (HELM) which reduces time complexity and also increase the probability of existence of the load flow solution. Here a new holomorphic embedding load flow problem formulation for a hybrid AC-DC microgrid system using line impedance values has been proposed. By using Padẽ approximant, we solve this holomorphic embedding load flow functions which guarantees the solution of load flow problem. Comparative study with well-known load flow methods over different test cases and a practical Indian distribution grid shows the efficiency and applicability of this method over the hybrid power networks.

Power flow control of hybrid micro-grids using modified UIPC

This work introduces a replacement advent for power flow control of interconnected AC-DC micro-grids in hybrid micro-grids connected to grids. It also supports implementing an Adaptive Neuro Fuzzy Inference System (ANFIS) controlled modified Unified Inter-Phase Power Controller (UIPC). For study, a classic hybrid micro-grid connected to grid comprising of a AC micro-grid and a DC micro-grid is taken into account. These micro-grids are interconnected employing a modified UIPC, rather than using the power converters connected in parallel. As the first input of this paper is the standard structure of UIPC, which used three power converters in every phase. It was then modified such as number of power converters is used less and implemented for the control of the exchange of power between AC-DC micro-grids. In every phase there is one power electronic converter in the improved structure. It is called as Line Power Converter (LPC). Also there is Bus Power Converter (BPC) to regulate the voltage of the DC bus. The Line Power Converters links the AC micro-grid to the main grid. The DC buses are also linked with them. It can be operated in Inductance Mode (IM) as well as Capacitance Mode (CM). The control structure of LPCs has an Adaptive Fuzzy Logic Controller in it. For hybrid micro-grids, the capability of the suggested power flow control strategy is confirmed by the MATLAB simulation results.

A REVIEW ON HYBRID AC/DC MICROGRIDS: OPTIMAL SIZING, STABILITY CONTROL AND ENERGY MANAGEMENT APPROACHES

Electricity is the greatest gift of science to humanity reached for civilization where electricity is used for all purposes. However, in recent times a paradigm shift is evolving in the generation of electrical energy from the concept of using major generating plants to minor generating units allied to the distribution systems in the form of microgrids with alternative energy sources called renewables. Around the world renewable energy use is on the rise and these alternate energy sources can generate pollution-free electrical energy to the society. Although these are new centers and units with diminishing cost, there are still many challenges in operation and control of islanded and grid-connected microgrids configured in both AC and DC. Uniting the benefits of microgrids of AC and DC, Hybrid AC-DC Microgrids (HACDC) were developed.Thus, it is relatively imperative to investigate the optimal size, stability control, and strategies of economic efficiency operation of HACDC microgrid. Hence a great review on optimal sizing methods, stability control, and energy management strategies using various iterative and intelligence techniques published in different articles proposed by many authors were presented in this paper.

A Secured Energy Management Architecture for Smart Hybrid Microgrids Considering PEM-Fuel Cell and Electric Vehicles

This article assesses the energy management of reconfigurable residential smart hybrid AC/DC microgrids considering the combined heat and power (CHP) loads as well as the electric vehicles charging/discharging behaviors. A holistic model is developed for the proton exchange membrane fuel cell to retrieve the unwanted thermal energy generated at the operation time. The proposed model makes use of the unoccupied capacity of the fuel cell for producing/storing hydrogen for the later usage and increasing its efficiency. A stochastic framework is designed using point estimate method (PEM) to capture the uncertainties of the photovoltaic and wind turbine forecast error, power company price, the operating temperature of the proton exchange membrane fuel cell, the price for natural gas, price for selling hydrogen, and the pressure of the H2 and O2 in the fuel cell stack. The PEM approach has shown superior advantages in terms of accuracy and running time. Considering the complex and nonlinear structure of the proposed framework, a proficient optimization technique based on the teacher learning algorithm (TLA) is devised. A two-phase modification method is proposed to increase the algorithm variety and help its convergence characteristics. The performance of the proposed algorithm is compared with the TLA, particle swarm optimization (PSO) algorithm and genetic algorithm (GA). For enhancing the security of the energy and data transaction within the system, a directed acyclic graph (DAG)-based security framework is introduced to guarantee the performance of the system against the subversive accesses. By using this scheme, the essential data of the units are recorded and secured in the form of public, private and transaction blockchains. The economic characteristics of the proposed method are assessed on a residential hybrid AC-DC microgrid test system.