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Experimental Studies with Real-Time Hardware-in-Loop Microgrid Structure and its Components
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This paper proposes an adaptive dynamic reference control for power converters in a microgrid. Conventionally, two separate controllers are required to control the input current and the dc bus voltage. The proposed adaptive dynamic reference control eliminates the need for an additional controller by utilizing a simple discrete-time model to generate appropriate input current reference for the dc bus voltage regulation. The proposed technique is easy to design and guarantees a dynamic convergence of the dc bus voltage to its nominal reference even during non-idealities in the system, such as model parameter uncertainties, sensor imperfections, and unmodelled dynamics. A simple design procedure of the control parameters for the desired converter response is also provided based on a theoretical analysis. Unlike traditional linear controllers, the control parameter design of the proposed model is independent of the converter's operating point. Finally, the performance of the proposed technique is validated experimentally by using a finite control set model predictive control of a typical grid-connected application and is compared with both conventional dynamic reference control and traditional linear controller.
This paper presents an improved control strategy for a doubly fed induction generator (DFIG) during unbalanced grid voltage conditions. The proposed strategy was applied in both synchronization and grid connected conditions. The synchronization process is carried by controlling the extracted positive and negative sequence components of the stator q-axis voltage to follow the grid q-axis voltage. This strategy can be accomplished by controlling the positive and negative sequence components of rotor d-axis current. By perturbing the rotor d-axis current, the stator EMF builds up and follows the grid voltage accurately. The stator frequency and the phase difference between the stator and grid voltage are compensated by adjusting the stator d-axis positive and negative voltage components to zero. After synchronization, the proposed control strategy focuses on regulating the average stator active and reactive power control by controlling the positive components of q and d-axis currents, respectively. The second target is to minimize the generator torque ripple by controlling the rotor negative sequence components. In the same time, the grid side converter is controlled to minimize the grid power pulsations to reduce the impact of the unbalanced grid voltage. This study focuses in enhancing the dynamics of DFIG during the unbalanced grid voltage by using Multivariable State Feedback (MSF) current controllers. Experiments are carried out to validate the performance improvement by using the proposed method. The simulation and experimental results showed a superior performance of the proposed control strategy.
Reliability is of critical importance for the microgrid (MG) and deserved more attention. Aiming at photovoltaics (PV) and energy storage system (ESS) based MG, the microturbine (MT), PV, ESS and comprehensive load (CL) which is composed of hourly time-varying component, stochastic component, and controllable component, are chronologically modeled and combined with model of load shedding minimization and sequential Monte Carlo (SMC) simulation algorithm. Then, the reliability assessment framework is developed and employed in the comprehensive case studies. Firstly, varying characteristics of reliability indices, including loss of load probability (LOLP), average service availability index (ASAI), system average interruption duration index (SAIDI), system average interruption frequency index (SAIFI) and customer average interruption duration index (CAIDI), over PV penetration are investigated, and the surge effect of SAIFI (SE-SAIFI) is especially put forward and studied, followed by the principle of PV capacity decision considering SE-SAIFI. Secondly, the clear pictures of reliability profiles over ESS sizes are depicted and analyzed, following with a novel method to reasonably decide ESS sizes based on the definition of expected hourly redundant power (EHRP). At last, reliability indices of multiple scenarios with different percentages of controllable load are calculated and the benefits of load management are analyzed in the viewpoint of reliability of standalone MG. Results of the case studies also confirm the necessities of reliability assessment during the MG planning and size optimization, and the validity of the methodologies developed in this work.
The smart grid is expected to revolutionize existing electrical grid by allowing two-way communications to improve efficiency, reliability, economics, and sustainability of the generation, transmission, and distribution of electrical power. However, issues associated with communication and management must be addressed before full benefits of the smart grid can be achieved. Furthermore, how to maximize the use of network resources and available power, how to ensure reliability and security, and how to provide self-healing capability need to be considered in the design of smart grids. In this paper, some features of the smart grid have been discussed such as communications, demand response, and security. Microgrids and issues with integration of distributed energy sources are also considered.
As we transition towards a power grid that is increasingly based on renewable
resources like solar and wind, the intelligent control of distributed energy
resources (DER) including photovoltaic (PV) arrays, controllable loads, energy
storage and plug-in electric vehicles (EVs) will be critical to realizing a
power grid that can handle both the variability and unpredictability of
renewable energy sources as well as increasing system complexity. Realizing
such a decentralized and dynamic infrastructure will require the ability to
solve large scale problems in real-time with hundreds of thousands of DERs
simultaneously online. Because of the scale of the optimization problem, we use
an iterative distributed algorithm previously developed in our group to operate
each DER independently and autonomously within this environment. The algorithm
is deployed within a framework that allows the microgrid to dynamically adapt
to changes in the operating environment. Specifically, we consider a commercial
site equipped with on-site PV generation, partially curtailable load, EV charge
stations and a battery electric storage (BES) unit. The site operates as a
small microgrid that can participate in the wholesale market on the power grid.
We report results for simulations using real data that demonstrate the ability
of the optimization framework to respond dynamically in real-time to external
conditions while maintaining the functional requirements of all DERs.
In this article, a wind-driven doubly fed induction generator (DFIG), battery, and photovoltaic (PV) array-based system with advanced discrete second-order sequence filter-frequency locked loop control for grid-side converter (GSC) is presented. The improved grid-side control provides the reactive power demand of load connected at the point of common coupling. The GSC control provides active and reactive power sharing and mitigates the power quality issues at unbalanced and nonlinear load conditions. Moreover, it gives a satisfactory performance during the dynamic wind speeds and load variation. The maximum wind power is extracted using the tip speed ratio algorithm. The necessary quantity of reactive power for DFIG is delivered by the rotor-side converter (RSC). The battery with a bidirectional converter is connected to the common dc link of the DFIG. The battery is used to maintain the dc-link voltage between RSC and GSC and it stores the power in light-load conditions. It provides the load demand during lower wind speed and solar irradiation. The maximum solar power is extracted by well-established incremental conductance (InC) algorithm, which provides optimum performance during the high dynamic variation of solar irradiation. Moreover, the InC algorithm increases the system's stability and reduces costs. It is easy to implement and handle nonlinearity. The feedforward PV component is added with the active load current component to improve the dynamic behavior of the system. Simulated and test results show the performance of the developed system in different dynamic conditions, such as load unbalancing, changes in PV insolation, and change in speed from the cut-in to cut-out speeds of the wind turbine. Moreover, obtained results show the battery behavior during different dynamic conditions.
This article presents a photovoltaic (PV)-battery and wind driven doubly fed induction generator (DFIG) based grid-connected system with an improved multifunctional control scheme for grid-side converter (GSC). A three-stage improved reduced-order multiple integrator control is used to maintain the reactive power into the grid as well as it regulates the dc-link voltage across the GSC. The grid side control improves power quality in different abnormal conditions. Moreover, it behaves in such a way that it reduces the rise time, the maximum peak overshoot, as well as the settling time during the transients. The rotor side converter is used to provide the required amount of reactive power using the field-oriented control, for the wind power generator (WPG). A DFIG is used as a WPG. The single-stage PV array and a battery with bidirectional converter are connected to the common dc link of the GSC. The battery helps to extract the maximum wind power in light load conditions. The charging and discharging of the battery depend on the renewable energy generation and load demand. The dynamic behavior is improved by adding a PV feedforward term with the total active load current component. Here, the stator current total harmonic distortion (THD) and grid current THD are maintained as per the IEEE standard. Simulated and test results show the performance of the developed system in different dynamic conditions, such as load unbalancing, changes in PV insolation, and change in speed from the cut-in to cut-out speeds of the wind turbine. Moreover, these results show the battery behavior during different dynamic conditions.
This paper presents a control of a micro-grid at an isolated location fed from wind and solar based hybrid energy sources. The machine used for wind energy conversion is doubly fed induction generator (DFIG) and a battery bank is connected to a common DC bus of them. A solar photovoltaic (PV) array is used to convert solar power, which is evacuated at the common DC bus of DFIG using a DC-DC boost converter in a cost effective way. The voltage and frequency are controlled through an indirect vector control of the line side converter, which is incorporated with droop characteristics. It alters the frequency set point based on the energy level of the battery, which slows down over charging or discharging of the battery. The system is also able to work when wind power source is unavailable. Both wind and solar energy blocks, have maximum power point tracking (MPPT) in their control algorithm. The system is designed for complete automatic operation taking consideration of all the practical conditions. The system is also provided with a provision of external power support for the battery charging without any additional requirement. A simulation model of system is developed in Matlab environment and simulation results are presented for various conditions e.g. unviability of wind or solar energies, unbalanced and nonlinear loads, low state of charge of the battery. Finally a prototype of the system is implemented using a 5 kW solar PV array simulator and a 3.7 kW wound rotor induction machine and experimental results are produced to reaffirm the theoretical model and design.
This paper proposes a multi-input muti-output (MIMO) control strategy for dispatchable power electronic based distributed energy resources (DERs) in islanded mode operation of microgrids. The controller is designed based on the dq model of the DER unit. Cascade, feedforward and internal model control (IMC) principle, incorporating the theory of integral control and repetitive controller, are used. The proposed controller regulates the voltage at the output of DERs under any load (balanced, unbalanced and harmonic) variation and/or fault condition. The stability of the closed-loop system has been investigated. Enhanced phase-locked loop (EPLL) is used to determine the system variables in the dq frame under unbalanced (and balanced) operating conditions. The structure of the EPLL is further modified to regulate the microgrid frequency and a stability analysis of proposed frequency control loop is presented. The performance of the proposed controller is verified through test case studies, carried out on an autonomous microgrid with single and multiple DER units.
The necessity to solve global warming problems by reducing CO2 emission in the electricity generation field had led to increasing interest in microgrids (MGs), particularly those containing the renewable sources such as solar and wind generation. Wind speed fluctuations cause high variations in the output power of a wind turbine which cause fluctuations in frequency and voltage of the MG during islanding mode and originate stability problems. In this paper, three techniques are proposed for solving and reducing the consequences of this problem. In the first technique, we develop a new fuzzy logic pitch angle controller. In the second technique, we design an energy-storage ultracapacitor which directly smoothes the output power of the wind turbine and enhances the performance of the MG during the islanding mode. In the third technique, storage batteries are used to support the MG in the islanding mode.