Distributed Frequency Control Research Articles

Privacy-preserving distributed frequency control for AC microgrids with constrained communication

Distributed control of AC microgrids is one of the most popular methods in the islanded operation mode. Whereas, most of the existing studies either do not consider the potential threat of privacy security or rely on the assumption of ideal communication networks. To this end, this paper presents a novel privacy-preserving distributed secondary frequency control strategy for the privacy protection problem of an islanded AC microgrid with constrained communication. The key contributions of this paper are threefold. (1) Different from the existing privacy-preserving approaches used in AC microgrids, a time-varying function is introduced to mask interactive information such that the frequency cannot be reconstructed by malicious attackers. (2) An event-triggered communication scheme is employed to cope with the constrained communication environment. (3) A privacy-preserving distributed event-triggered control strategy with communication delay is developed such that the frequency restoration and active power sharing of the microgrid are guaranteed. Moreover, the maximum communication delay that the proposed control can withstand is analyzed. Simulation results show the properties of the privacy preservation, the decrease of communication load, and the bounded communication delay allowed in the proposed control strategy.

Cooperative Hierarchical Control of Isolated Microgrids Considering Energy Storage System Aggregation

The integration of numerous energy storage systems (ESSs) improves the reliable and economic operation of microgrids but also enlarges the burden of control and communication systems. This paper proposes a cooperative hierarchical control for isolated microgrids with ESSs, which fully frees from the centralized paradigm and is therefore superior in flexibility and scalability. Firstly, the ESS cooperative control based on the distributed frequency controller is introduced for the state of charge (SoC) balance and the frequency regulation. Then, the ESS aggregation is considered. The aggregated ESS model is established and the real-time model parameters are derived by proposed distributed state observers. Finally, energy management is employed to allocate the output power between generators and the aggregated ESS. A detailed theoretical analysis of the dynamic and steady-state performance of proposed controllers and observers is provided. Simulations on the IEEE 33-bus and the 69-bus system verify the effectiveness of proposed methods.

Distributed Frequency Control of Heterogeneous Energy Storage Systems Considering Short-Term Ability and Long-Term Flexibility

Distributed Frequency Control of Heterogeneous Energy Storage Systems Considering Short-Term Ability and Long-Term Flexibility

Distributed leader-follower based adaptive consensus control for networked microgrids

Networked microgrids (NMGs) provide a promising solution for accommodating various distributed energy resources (DERs) and enhance its performance. However, the coordinated operation of the system with integration of a large number of DERs is major challenge. Therefore, this article aims to provide a distributed control strategy (DCS) based on a leader-follower framework for the coordination of multiple DERs in NMGs. A fuzzy optimized Recurrent Hopfield Neural Network (F-HNN) designed self-adaptive fractional order proportional integral derivative (FOPID) controller is proposed for distributed frequency control of NMGs. Initially, a Lyapunov-based objective function is derived for weight updation of the proposed network. The fuzzy approach is used to optimize the output of the HNN based on its gradients. The proposed F-HNN based DCS is implemented in MATLAB/Simulink and validated for frequency regulation of NMGs through hardware-in-the-loop simulation (HIL) using OPAL-RT. The results obtained are compared with the conventional FOPID HNN tuned and other classical controls. The self-adaptiveness of the controller is demonstrated for change in renewable power generation. Furthermore, the resiliency of the controller is tested with communication failures and, plug and play operation of MGs. The results obtained showed that the frequency of the NMG system is well regulated within the band of ±0.2 Hz. Also, the transient and steady state performance reveals that the proposed DCS is more significant than other techniques.

Two-level distributed fully-predictive frequency control scheme for inverter-based AC Microgrid considering communication delay

Amid the current development of decentralized renewable energy sources, the research of multi-agent-based control for the next generation of the intelligent power system has become one of the most trending and worth-noticing topics in the smart grid research community. Serving as a contribution to the research orientation, this paper proposes a novel two-layer distributed fully-predictive frequency control scheme for an inverter-based three-phase three-wire AC microgrid. The key feature of the suggested methodology is the incorporation of objective functions and dynamic models as constraints in the predictive formulation of both primary and secondary layers in the microgrid control hierarchy. In our study, the controller is designed based on constrained cost function minimization using Quadratic Programming (QP) and the utilization of local measurements and information from surrounding distributed generators to achieve the desired control action. Along with the integration of virtual impedance, second-order generalized integrator phase-lock loop, and harmonic suppression constraint functions, the proposed control scheme shows great response against all variations of load changes, communication delay, communication network failure, and Plug-n-Play capability test. The performance of the proposed controller is verified and evaluated on the 4-DGs microgrid model using MATLAB/Simulink environment.

A Multiagent Quantum Deep Reinforcement Learning Method for Distributed Frequency Control of Islanded Microgrids

This article proposes a data-driven method for distributed frequency control of islanded microgrids based on multiagent quantum deep reinforcement learning (DRL). The proposed method combines the conventional DRL framework with quantum machine learning, and can adaptively obtain the optimal cooperative control strategy. The microgrid secondary frequency control is organized in a distributed manner in which each agent performs the control action only based on the local and neighboring information. To solve the DRL problem, the deep deterministic policy gradient algorithm is derived to tune the agents’ parameters. Simulation tests are performed on an islanded microgrid with four distributed generators and a 13-bus microgrid. The results demonstrate that the proposed method can effectively regulate the frequency with better time-delay tolerance, and displays the quantum advantage in parameter reduction.

TokenSmart: Distributed, Scalable Power Management in the Many-core Era

Centralized power management control systems are hitting a scalability limit. In particular, enforcing a power cap in a many-core system in a performance-friendly manner is quite challenging. Today’s on-chip controller reduces the clock speed of compute domains in response to local or global power limit alerts. However, this is opaque to the operating system (OS), which continues to request higher clock frequency based on the workload characteristics acting against the centralized on-chip controller. To address these issues, we introduce TokenSmart, which implements a set of scalable distributed frequency control heuristics within the OS, using a novel token-based mechanism. The number of system-allocated power tokens represents the maximum allowable power consumption; and the OS governor orchestrates a token-passing (or sharing) algorithm between the compute engines. Token allocation count increase (decrease) corresponds to a increase (decrease) of clock frequency. The compute units are connected in a ring-topology allowing minimal meta-data to be passed along with the token value for regulating power budget. We explore different heuristics to assign tokens smartly across the units. This results in efficient power regulation and sustenance of turbo frequencies over a longer duration. Our proposed methodology can be implemented in hardware with multiple on-chip controllers, or in software where each set of cores acts as a compute unit. The methodology is currently implemented within the Linux kernel of a real IBM POWER9 many-core system and experimentally verified on different real world workloads such as Redis, Cassandra, PostgreSQL along with a micro-benchmark such as rt-app. Our experiments indicate the increase in throughput for all the workloads along with the benefit of power savings. For instance, results show a considerable boost of about 4% in throughput of both the PostgreSQL and Redis benchmark with a substantial savings in power consumption (18% and 37%, respectively). If the approach is implemented in hardware, then our experimental analysis speculates the throughput to increase up to 14% in PostgreSQL benchmark.

Event-Based Distributed Fuzzy Load Frequency Control for Multiarea Nonlinear Power Systems With Switching Topology

This article investigates the event-based distributed fuzzy load frequency control approach for nonlinear interconnected power systems under a switching topology. Specifically, nonlinear factors and uncertain parameters existing in turbine and governor dynamics are modeled and analyzed under the interval type-2 fuzzy method. New memory-based adaptive event-triggered mechanisms, whose directions and threshold parameters are dynamically updated based on the output change trend and relative output error of multiple memories, are proposed to further save network energy. Aiming at communication topology changes in multiarea power systems, a novel switched control system is established by introducing a time-varying communication matrix. Then, the system’s asymptotic stability is ensured by the piecewise Lyapunov–Krasovskii method. Furthermore, to further relax stability conditions, slack matrices are considered with the boundary information of membership functions. Finally, three-area power systems are shown to demonstrate the effectiveness of proposed distributed load frequency control strategies.

Event-Based Distributed Frequency Control in Harsh Communication Conditions

In this article, distributed control methods are widely applied in the operation of distributed generators (DGs) in modern power grids. As distributed control, the control operation depends greatly on information exchange among neighboring distributed controllers, where harsh communication conditions (e.g., limited communication rates and accidental communication failures) may cause significant performance deterioration. Therefore, it is necessary to investigate distributed control of DGs under imperfect communication conditions in practical systems. This article proposes an event-based distributed DG frequency control strategy. By introducing an event-based update mechanism for real-time DG data measurements and the communication topology, the adaptability of the control strategy to low communication rates and communication failures is significantly enhanced. Besides, the above-mentioned nonideal communication conditions, the proposed control also shows high adaptability to communication delays. Furthermore, an optimal design method of the control parameters is developed, which ensures proper steady-state performance and optimizes the dynamic performance of the proposed control. Simulations based on MATLAB/Simulink and hardware experimental validations using dSPACE under various conditions verify the effectiveness of the proposed control.

Consensus-Based Distributed Secondary Frequency Control Method for AC Microgrid Using ADRC Technique

To ensure safe and reliable operation, the ability to ride through various disturbances is vital for a microgrid with multi-inverters. As the voltage and frequency support comes from the power-electronic-based inverters, it is necessary to find a proper control strategy to improve the rejection ability of the DG inverter against disturbances. In this regard, this paper proposes a new distributed secondary frequency control approach for islanded microgrids, in which the main purpose is to remove the frequency deviation under droop control method with better disturbance rejection performance. Unlike many traditional approaches which rely on a detailed control model, the proposed one needs little model information thanks to the model-independent characteristic of active disturbance rejection control (ADRC) technique. A linear extended state observer is introduced to estimate the useless model dynamics (including unknown disturbances, unmodeled dynamics and nonlinear dynamics) which are then compensated in the control input. After the active compensation procedure, the nonlinear frequency control model can be converted into a quasi-linear model, based on which a proportional distributed control algorithm is established to restore the frequency and equalize the active power among the DGs. Simulation results based on a four-inverter-based microgrid show that the proposed approach achieves frequency restoration, active power sharing, as well as satisfactory disturbance rejection performance.

Bandwidth Allocation-Based Distributed Event-Triggered LFC for Smart Grids Under Hybrid Attacks

In this study, a bandwidth allocation-based distributed event-triggering load frequency control (LFC) has been developed for smart grids to deal with hybrid cyber-attacks, for example, denial-of-service (DoS) attacks and false data injection (FDI) attacks. Firstly, to prevent hybrid cyber-attacks from causing open-loop unstable operation of the LFC systems, we propose a distributed event-triggering communication (ETC) strategy. To attain the maximum usage of bandwidth, a dynamic bandwidth allocation mechanism is integrated with the ETC approach on the basis of resource availability and error between the current state and equilibrium state. This bandwidth reservation and allocation approach aim at detecting attacks and assigning bandwidth to the different channels of distribution networks. Then, by virtue of the Lyapunov approach, the exponential stability criteria are established. Further, the exclusion of Zeno behavior of the designed systems is proved during the control process. Finally, comprehensive case studies show that the proposed method can improve the utilization rate of the network resource.

Distributed Model Predictive Frequency Control of Inverter-Based Networked Microgrids

This paper proposes a distributed frequency control method for an off-grid inverter-based networked microgrid system (NMS) with loads, renewable generators and energy storage devices (ESDs). The frequency regulation problem is formulated as a model predictive control (MPC) problem that aims to maintain the supply-demand power balance within each microgrid and scheduled net power interchange among connected microgrids at minimal regulation costs. The charging/discharging efficiencies as well as energy capacities of ESDs, and constraints on bus voltages are also considered. The proposed MPC problem is solved by a distributed projection-based algorithm via information sharing between adjacent buses. The effectiveness of the proposed method is validated by simulations implemented in Matlab/Simulink.

Novel properties of heterogeneous delay in inverter-based cyber–physical microgrids under fully distributed control

Inverter-based microgrids will be vital components of future energy systems with large-scale integration of renewable energy resources. To cope with the low inertia problem induced by inverters, fully distributed control has been shown to effectively improve system stability owing to its fast response capability. Investigating the property of multiple delays in distributed control architecture is critical to guide its practical implementation in cyber–physical systems. Compared with power systems equipped with decentralized or centralized controllers, inverter-based cyber–physical microgrids under fully distributed control have a more complicated and heterogeneous delay environment. Existing, proven delay properties in centralized systems, such as the delay merge property that measurement and control delays of decentralized power system stabilizers can be merged for small-signal stability analysis, are not applicable to distributed systems To investigate the novel delay properties in distributed systems, we first propose a block-matrix-based cyber–physical model considering heterogeneous delays for inverter-based microgrids under fully distributed control. Then, we derive and prove the novel properties of heterogeneous delay in such systems. Finally, we perform numerical tests based on a real-world 7-bus islanded microgrid and a modified PG&E 69-bus microgrid under fully distributed frequency control. Our findings show that the impacts of measurement delay and control delay of one distributed controller on system stability are equivalent only if all distributed controllers are identical. Moreover, as the diversity of distributed controllers increases, the heterogeneous delay property becomes more significant.

H ∞ distributed frequency control with unknown communication delays and parametric uncertainties

<i>H</i> _∞ distributed frequency control with unknown communication delays and parametric uncertainties

An enhanced second-order-consensus-based distributed secondary frequency controller of virtual synchronous generators for isolated AC microgrids

Virtual synchronous generator (VSG) control is a promising control method in microgrid (MG) for the inertia support characteristic. However, the VSG inherits the oscillation feature of synchronous generator (SG), thus the active power and frequency oscillation may be observed when VSG control is applied. In MG, the oscillation may cause the unreasonable dynamic active power sharing among VSGs. Subsequently, the VSGs are prone to overload and even unstable, and the existing works based on consensus control cannot suppress the oscillation effectively. In order to tackle this problem, this paper proposes an enhanced second-order-consensus-based distributed secondary frequency controller by introducing the active power second-order consensus control, and reveals the oscillation suppression capacity of the second-order consensus algorithm in depth. Since there is no specific control requirement for the second-order variables, i.e., the change rate of active power and frequency of MG in steady state, the proposed controller can be simplified by replacing the integral control of second-order variables with the proportional control of first-order variables, i.e., active power and frequency, thus the communication data volume will not increase comparing to the traditional first-order-consensus-based controller. This paper also provides a small-signal model of MG with the proposed controller to evaluate the system dynamic performance and design the parameters. Finally, the simulation results verify the effectiveness of the proposed controller.

The impact of synchronous distributed control period on inverter-based cyber–physical microgrids stability with time delay

Inverter-based microgrids under fully synchronous distributed control have broad prospects in multi-agent-based energy systems. Such a system is a typical cyber–physical system. Studying the impact of a synchronous control period on system stability is the pre-requisite for practical deployment of a distributed control architecture with a proper synchronous period. However, simulation-based methods provide little theoretical insight into how synchronous control period influences system stability. Additionally, control-period determination methods based on the convergence analysis of a distributed algorithm cannot sufficiently consider the dynamic characteristic of a physical inverter-based microgrid. In this paper, a synchronized cyber–physical state-transition model of distributed inverter-based microgrids considering multiple time delays from a cyber–physical perspective is proposed. The stability criterion of the system under certain synchronous control periods with multiple time delays is obtained. Furthermore, considering multiple stochastic switching delays with infinite combinations of states, the corresponding stability criterion is also obtained based on switched system theory. The stable interval of the synchronous control period for such cyber–physical power systems can be determined based on the proposed stability criteria and algorithm. A real-world microgrid under fully distributed frequency control is tested and simulated by Simulink simulations to verify the accuracy of the obtained stable synchronous control period.

Deep multi‐agent Reinforcement Learning for cost‐efficient distributed load frequency control

The rise of microgrid-based architectures is modifying significantly the energy control landscape in distribution systems, making distributed control mechanisms necessary to ensure reliable power system operations. In this article, the use of Reinforcement Learning techniques is proposed to implement load frequency control (LFC) without requiring a central authority. To this end, a detailed model of power system dynamic behaviour is formulated by representing individual generator dynamics, generator rate and network constraints, renewable-based generation, and realistic load realisations. The LFC problem is recast as a Markov Decision Process, and the Multi-Agent Deep Deterministic Policy Gradient algorithm is used to approximate the optimal solution of all LFC layers, that is, primary, secondary and tertiary. The proposed LFC framework operates through centralised learning and distributed implementation. In particular, there is no information interchange between generating units during operation. Thus, no communication infrastructure is necessary and information privacy between them is respected. The proposed framework is validated through numerical results and it is shown that it can be used to implement LFC in a distributed and cost-efficient manner.

Modeling of Time-Delayed Distributed Cyber-Physical Power Systems for Small-Signal Stability Analysis

Compared with a power system under centralized control, a power system under fully distributed control has stronger interdependence between its physical side and cyber side. Such a system is a typical cyber-physical system (CPS). The time delay problem is one of the most critical issues in the application of distributed control for power systems. First, a distributed information flow model is established considering multiple sources of time delay, especially the communication delay between neighboring agents. Second, combining the dynamics of physical power systems, a general model of time-delayed CPS under fully distributed control is proposed, especially for inverter-based microgrids. Third, the stability of the time-delayed CPS is analyzed based on the proposed model with a critical eigenvalue tracking algorithm. A real-world microgrid with DGs under fully distributed frequency control is tested for small-signal stability analysis. The findings show that the stability of the distributed CPS with multiple sources of time delay depends on not only the absolute value of time delays but also the coordination of time delays and that the delay merging property in centralized mode is not relevant in a distributed CPS. The accuracy of the model and the obtained stability margin are verified by Simulink simulations.

Robust and Resilient Distributed Optimal Frequency Control for Microgrids Against Cyber Attacks

The optimal frequency control of autonomous microgrids (MGs), i.e., to achieve fast frequency recovery and dynamic power adjustment of the distributed generators in proportion to predefined participation factors, can be achieved in a fully distributed way based on the subgradient consensus protocol. However, such a distributively controlled MG is susceptible to different types of cyber attacks infiltrated from different locations. In this article, a robust and resilient distributed optimal frequency control scheme is proposed to address the threat of cyber attacks. It is facilitated by introducing an auxiliary networked system interconnecting with the original cooperative control system. On condition that the cyber attacks are within certain ranges, the robust design can maintain the functionalities by significantly attenuating the impact. Otherwise, the cyber attacks can be easily detected, and resilient reactions can be taken to mitigate their influences via isolation. Simulation results in a modified IEEE 34-bus MG validate the effectiveness of the proposed approach.

TokenSmart: Distributed, Scalable Power Management in the Many-Core Era

Centralized power management control systems are hitting a scalability limit. In particular, enforcing a power cap in a many-core system in a performance-friendly manner is quite challenging. Today’s on-chip controller reduces the clock speed of compute domains in response to local or global power limit alerts. However, this is transparent to the operating system (OS), which continues to request higher clock frequency based on the workload characteristics acting against the centralized on chip controller. To address these issues, we introduce TokenSmart, which implements a scalable distributed frequency control heuristics within the OS, using a novel token-based mechanism. The compute units are connected in a ring-topology allowing minimal meta-data to be passed along with the token value for regulating power budget. We explore different heuristics to assign tokens smartly across the units. This results in efficient power regulation and sustenance of turbo frequencies over a longer duration. The methodology is implemented within the Linux kernel of a real IBM POWER9 many-core system. The experimental results show a considerable boost of about 4 percent in throughput of PostgreSQL benchmark with a tangible 18 percent decrease in power consumption.