Frequency Regulation In Islanded Microgrid Research Articles

Model-free frequency regulation in islanded microgrids: An event-triggered adaptive dynamic programming approach

This paper is concerned with frequency regulation in islanded microgrids via an event-triggered adaptive dynamic programming method. Comparatively to the existing works, we relax the typical limitations on the system, namely, exactly known models, constant load impedances, and single operation mode. The adopted frequency regulation scheme can reach frequency synchronization within the acceptable bounds in the presence of the model uncertainties, operation mode switching, and time-varying loads with no need for any prior information on the system parameters. By employing an event-triggered scheme, the secondary controller is updated only at the aperiodic triggering instants which contributes to less transmission cost. Besides, the use of measurements can help the adaptive weights to be adjusted online in the approximation process, which allows the proposed controller to adapt to the disturbances in real time. Finally, tests including the islanding process and load variation are performed in MATLAB/SimPowerSystem to show the effectiveness of the proposed method.

A novel virtual inertia control strategy for frequency regulation of islanded microgrid using two-layer multiple model predictive control

This paper investigates the frequency performance problem of microgrids (MGs) integrated with renewable employing an energy storage system (ESS) equipped with virtual inertial control (VIC) support. To tackle the uncertainties related to the system operation, a two-layer multiple model predictive control (TLMMPC) method, consisting of nominal and ancillary MMPCs, is proposed to submit effective control signals to the ESS for improving system frequency performance. The ancillary MMPC generates the control commands for the VIC-based ESS utilizing the signals provided by the nominal MMPC and the frequency deviation signal of the actual system considering uncertainties and operating constraints. The control commands are generated to attain the minimum value of frequency response error with the least control endeavor while considering various operational and physical limitations. The TLMMPC method has the capability to work with different state of charge (SoC) levels to obtain the desired SoC and highest efficiency from the ESS and preserve the ESS’s longevity. The dynamic performance of the proposed TLMMPC technique is investigated on an islanded MG and compared to model predictive control (MPC), fractional-order MPC, and tilt-integral-derivative controllers under different scenarios. The results validate that the proposed TLMMPC technique significantly improves the system frequency response from viewpoints of settling time, peak overshoot, and undershoot and obtains the most efficient ESS compared to the other methods.

Distributed Weight Adaptive Control for Frequency Regulation of Islanded Microgrid

The consensus control method based on a multi-agent system has been widely applied in the distributed control and optimization of microgrids. However, the following drawbacks are still common in current research: (1) ignoring the influence of consensus control commands on the synchronization stability of the physical grid under primary control; (2) only focusing on improving one property ofcontrol performance, lacking comprehensive considerations of multiple properties. With the aim of solving these problems, in this paper we propose a weight-adaptive robust control strategy for implementing distributed frequency regulation of islanded microgrids. Firstly, the frequency synchronization stability of the physical layer is analyzed by means of a coupled oscillator theory and the design objectives of the controllable parameters for the information layer are formed. Subsequently, the relationship between the weight coefficients and the two important control performances of convergence speed and delay robustness is strictly analyzed. Based on this, an adaptive coefficient that can be autonomously adjusted according to the frequency deviation is designed to achieve a trade-off between convergence speed and delay robustness. Finally, three simulation studies are presented to verify the effectiveness of the proposed control strategy.

Real Time Simulation of Modified Bias Based Load Disturbance Rejection Controller for Frequency Regulation of Islanded Micro-Grid

Abstract The paper presents a real time modelling of self-reliant isolated grid comprising both governable and ungovernable sources. The frequency of this system must be maintained to its desired value by reducing its deviation occurred when there is a mismatch between the load demand and the actual power generation. In order to achieve it, the actual power output of the micro-grid is required to regulate. Therefore, an attempt is made in this paper to design a modified bias (MB) with LDR (load disturbance rejection) based PID (proportional integral derivative) Controller and it can also be called droop based controller (DBC). Simulation of the micro-grid system with proposed MB-LDR based control scheme is successfully done in Real Time Simulation platform using the digital simulator of OPAL-RT OP4510. Simulation results of the system for different conditions are presented and analysis is given in details. Thereafter, comparative performance of the results obtained using proposed MB-LDR based controller with that of LDR and classical controllers is made. Results show that the proposed MB-LDR based controller gives better response as compare to other two methods in terms of peak transient deviation, settling time and number of oscillations.

Improving the autonomy of islanded microgrids through frequency regulation

In stand-alone operation, microgrids are susceptible to potential shortages in generation capacity, requiring a consideration of all technically feasible opportunities to conserve energy in order to keep the islanded grid operational for as long as possible. In this sense, the network autonomy capacity must be considered in the islanded microgrid frequency control formulation, alongside the traditional concern related to the accomplishment of the dynamic frequency regulation requirements. This paper proposes a new outlook for secondary frequency regulation in islanded microgrids denoted as conservation frequency reduction (CFR). The proposed approach exploits the frequency dependency characteristics of microgrids by intentionally reducing the reference setpoint of the islanded network frequency in a controllable way in order to decrease the network’s demand and improve the autonomy duration of islanded microgrids, i.e., availability to supply demand in islanded mode; while ensuring the system operation within permissible limits. The results indicate that the proposed approach is able to significantly enhance islanded microgrids autonomy capacity while guaranteeing its frequency of operation within satisfactory dynamic and steady-state limits.

Distributed Secondary Control for Active Power Sharing and Frequency Regulation in Islanded Microgrids Using an Event-Triggered Communication Mechanism

This paper is concerned with active power sharing and frequency regulation in an islanded microgrid under event-triggered communication. A distributed secondary control scheme with a sampled-data-based event-triggered communication mechanism is proposed to achieve active power sharing and frequency regulation in a unified framework, where neighborhood sampled-data exchange occurs only when the predefined triggering condition is violated. Compared with traditional periodic communication mechanisms, the proposed event-triggered communication mechanism shows some prominent ability in reducing the number of communication among neighbors while guaranteeing the desired performance level of microgirds. By employing the Lyapunov-Kravovskii functional method, some sufficient conditions are derived to characterize the effects of control gains, system parameters, and sampling period on stability of microgrids. Finally, case studies on a modified IEEE 34-bus test system are conducted to evaluate the performance of the proposed distributed control scheme, showcasing its effectiveness, robustness against load changes, and plug-and-play ability.

Frequency regulation in islanded microgrid considering stochastic model of wind and PV

Frequency regulation in islanded microgrid considering stochastic model of wind and PV

A Maximum Power Loading Factor (MPLF) Control Strategy for Distributed Secondary Frequency Regulation of Islanded Microgrid

Microgrids rely on both primary and secondary frequency control techniques to maintain system stability. Secondary frequency control effectively minimizes frequency fluctuations by adjusting the active power reference in each power inverter, but requires complex and costly interequipment communication. In this paper, we propose a distributed secondary frequency control strategy for microgrids containing multiple virtual synchronous generator (VSG) units based on a new maximum power loading factor (MPLF) concept. The MPLF algorithm facilitates power sharing by dynamically identifying the maximum VSG loading factor at each time instance, and then using this value as a unified reference signal for all the VSGs in the microgrid. The active power reference for each VSG will be adjusted based on the unified reference signal, subsequently the secondary frequency control can be realized. The proposed strategy does not require high-bandwidth communication since the MPLF data are transmitted among the VSGs using low-bandwidth communication. We also develop small-signal models for the control architecture to analyze the influence of major proportional–integral control parameters and communication latency. The MPLF control strategy is implemented using custom digital signal processor controllers, and experimentally validated using hardware in loop simulations. Finally, the new control paradigm demonstrates significant tolerance for communication delay or failure, which we purposely introduced in our investigation.

Resilient distributed optimal generation dispatch for lossy AC microgrids

In this paper, we consider the problem of designing a distributed algorithm, resilient against communication delays and packet drops, for coordinating the response of distributed energy resources (DERs) in AC microgrids so as to minimize electrical line losses and generation cost, and to ensure that the microgrid network constraints are satisfied. The proposed algorithm can be utilized as a secondary or tertiary controller for frequency regulation in islanded microgrids, or to coordinate DERs for providing frequency regulation services to the bulk grid when microgrid is in grid-connected mode. We validate the practical usefulness of the theoretical results through numerical simulations involving the IEEE 39-bus system.

Unified Probabilistic Modeling of Wind Reserves for Demand Response and Frequency Regulation in Islanded Microgrids

Islanded microgrids provide unique challenges due to the lack of transmission support, requiring local energy supply and grid regulation architecture. This paper presents a unified probabilistic assessment of wind reserves for demand response (DR) and frequency regulation in islanded microgrids. A multivariate nonparametric kernel density estimation algorithm is used to generate the probabilistic models of the wind resource, electrical demand, and predicted performance of wind generation. These models are numerically combined to evaluate the capability of wind generation to act as a dynamic reserve and predict its performance for DR, secondary generation, and frequency regulation in an islanded system. The probabilistic model captures multivariate cross-correlation, nonstationary environmental and load behavior, as well as multimodality in their underlying probability distributions. A case study is conducted to validate the proposed model, which predicts wind generation effectiveness for varying load profiles, wind profiles, and generation capacities. PLEXIM simulation software is used to implement a model microgrid to demonstrate the integration of wind generation and its regulatory capabilities. The proposed algorithm has applications in power system planning and operation, and it provides a method using probabilistic data set for long term energy management and optimization of islanded microgrids.

Distributed Model Predictive Secondary Voltage Control of Islanded Microgrids With Feedback Linearization

This paper presents a novel distributed secondary control method for both voltage and frequency regulation in islanded microgrids. Firstly, the large-signal dynamic model of inverter-interfaced distributed generation (DG) is formulated in the form of a multi-input multi-output nonlinear system, which can be converted to a partly linear one using input–output feedback linearization. Then, the linear-distributed model predictive controller is designated in each DG to realize the secondary voltage control by incorporating the forecasted behaviors of the local and neighboring DG units. Through the receding optimization index of every update process, the implementation of optimal control action accelerates the convergence rate for voltage magnitudes to the reference value. Following, after transforming the nonlinear DG dynamics into a first-order linear system, a distributed proportional integral algorithm is introduced in the frequency restoration while maintaining the accurate active power sharing. Our approach utilizes the distributed architecture, which indicates superior reliability and flexibility compared to the centralized manner; moreover, it can accommodate diverse uncertainties in communication links, model parameters, and time delays. Simulation results are provided to verify the effectiveness of the proposed control methodology.

An Intelligent Droop Control for Simultaneous Voltage and Frequency Regulation in Islanded Microgrids

Voltage and frequency of microgrids (MGs) are strongly impressionable from the active and reactive load fluctuations. Often, there are several voltage source inverters (VSIs) based distributed generations (DGs) with a specific local droop characteristic for each DG in a MG. A load change in a MG may lead to imbalance between generation and consumption and it changes the output voltage and frequency of the VSIs according to the droop characteristics. If the load change is adequately large, the DGs may be unable to stabilize the MG. In the present paper, following a brief survey on the conventional voltage/frequency droop control, a generalized droop control (GDC) scheme for a wide range of load change scenarios is developed. Then to remove its dependency to the line parameters and to propose a model-free based GDC, a new framework based on adaptive neuro-fuzzy inference system (ANFIS) is developed. It is shown that the proposed intelligent control structure carefully tracks the GDC dynamic behavior, and exhibits high performance and desirable response for different load change scenarios. It is also shown that the ANFIS controller can be effectively used instead of the GDC. The proposed methodology is examined on several MG test systems.