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Microgrids comprising photovoltaic (PV), energy-storage systems and electric vehicles have received increasing attention. However, the increase in renewable energy sources, such as PVs, will introduce uncertainty factors to the frequency response, resulting in frequency fluctuations that can reduce power quality. Hence, we propose an outstanding learning-based control approach that combines a model of physical principles with a Gaussian Process (GP) learning approach. The learning model corrects the physical principles model and estimates its uncertainty. Simulations are performed by comparing the proposed controller with conventional model-predictive controllers. The results indicate that the learning-based controller proposed can adjust the frequency with less overshooting and a lower root mean square error compared to the conventional MPC control method.

Conventional centralized and distributed structures for secondary frequency control (SFC) in an islanded microgrid rely on communications. However, this may degrade the reliability of the system if communication delays or failures occur. As a potential alternative, several decentralized integral controls have emerged for SFC of islanded microgrids; however, these methods are limited by their inability to account for the unknown biased errors of real systems, which can accumulate in the controller of each generator causing clock drift and fighting among the generators. To overcome these issues, this paper proposes a novel SFC method for diesel generators in an islanded microgrid. With the proposed method, the frequency can be maintained at almost the nominal value by “frequency reference compensation control (FRCC)” with only local measurements that do not require telecommunications. Therefore, this approach prevents catastrophic circumstances due to communication failures and delays in islanded microgrids. The proposed controller has improved robustness against unknown biased errors, thus mitigating fighting among multiple diesel generators. To ensure system stability, small-signal stability analyses and common quadratic Lyapunov method were conducted with switched state-space modeling. The small-signal stability analyses show that the proposed method shifts the unstable eigenvalue at the critical point of the system matrix to the negative real part, ensuring the system is asymptotically stable. Control parameters are achieved via heuristic optimization called particle swarm optimization (PSO). Hardware in the loop simulations were performed to verify the feasibility of the proposed control method.

Matrix converters (MC) have been considered for applications in renewable power generation and microgrids. However, similar to other power electronic converter-interfaced power generation systems, the MC-interfaced system cannot provide inertia or damping effect to support the grid’s frequency or voltage. To improve the inertia and damping effect of the MC-interfaced distributed generation system and realize the grid-friendly connection of new energy power generation, a virtual synchronous generator (VSG) control strategy suitable for the MC-interfaced system is proposed. Aiming at the problem that the system frequency in the traditional VSG cannot be restored to the nominal value after the load power fluctuations, the VSG secondary frequency control strategy is introduced. To ensure a smooth grid connection, a synchronization control strategy based on virtual power has been designed. An experimental validation platform was built and the experimental results verify the correctness and effectiveness of the proposed control strategies for a grid-forming MC.

The increasing dominance of inverter-based resources (IBRs) in power generation leads to significantly faster frequency dynamics in modern power systems. Therefore, the secondary control within the classical hierarchical structure must operate significantly faster. However, high communication burdens are inherent to centralized implementations of secondary control. This paper proposes a faster, distributed model predictive control (MPC) scheme for secondary frequency control of inverter-based power systems. The controller predicts the IBRs’ local frequency dynamics by considering the impact of the primary control of nearby IBRs. To obtain an optimal model-predictive control problem consisting of distributable subproblems, we introduce a novel trimming procedure to the frequency divider concept, an analytical formulation that estimates the local frequency at system buses. These subproblems have a tunable degree of mutual coupling. The presented distributed MPC achieves fast, error-free frequency regulation in the presence of abrupt load changes while also being robust to communication losses of participating IBRs. By design, the distributed control relies on a sparse neighbor-to-neighbor communication structure and uses local MPC problems that do not scale in complexity with system size. Numerical simulations of the IEEE 39-bus system and an extended CIGRE medium voltage power system demonstrate the fast performance of the proposed distributed MPC scheme for secondary frequency control.

The integration of renewable resources in isolated systems can produce instability in the electrical grid due to its intermintency. In today's microgrids, which lack synchronous generation, physical inertia is substituted for inertia emulation. To date, the most effective approach remains the frequency derivative control technique. Nevertheless, within this method, the ability to provide virtual drooping is often disregarded in its design, potentially leading to inadequate development in systems featuring high renewable penetration and low damping. To address this issue, this paper introduces an innovative design and analysis of virtual inertia control to simultaneously mimic droop and inertia characteristics in microgrids. The dynamic frequency response without and with renewable energy sources penetration is comparatively analyzed by simulation. The proposed virtual inertia control employs a derivative technique to measure the rate of change of frequency slope during inertia emulation. Sensitivity mapping is conducted to scrutinize its impact on dynamic frequency response. Finally, the physical battery storage system of the University of Cuenca microgrid is used as a case study under operating conditions. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Harbin University of Science & Technology is the property of Journal of Harbin University of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As microgrids are the main carriers of renewable energy sources (RESs), research on them has been receiving more attention. When considering the increase in the penetration of renewable energy sources/distributed generators (DGs) in microgrids, their low inertia and high stochastic power disturbance pose more challenges for frequency control. To address these challenges, this paper proposes a model predictive control (MPC) secondary control that incorporates an unknown input observer and where RESs/DGs use a deloading virtual synchronous generator (VSG) control to improve the system's inertia. An unknown input observer is employed to estimate the system states and random power disturbance from the RESs/DGs and load to improve the effect of the predictive control. The distributed restorative power of each DG is obtained by solving the quadratic programming (QP) optimal problem with variable constraints. The RESs/DGs are given priority to participate in secondary frequency control due to the proper weighting factors being set. An islanded microgrid model consisting of multiple photovoltaic and wind power sources was built. The simulation results demonstrate that the proposed method improves the system frequency, restoration speed, and reduces frequency deviations compared with the traditional secondary control method. [ABSTRACT FROM AUTHOR]

Modern power systems integrate ancillary services (ASs) to provide security and quality of service in real-time operation (RTO) due to the intense frequency variations caused by the uncertainty of solar–wind generation. To this end, the ancillary services market focuses on power reserves for secondary and tertiary frequency control. The adjustment and dispatch of reserves from plants are manual instructions executed by the system operator in order to maintain the frequency within the normal operating range (49.80 ≤ f ≤ 50.20 Hz). This work proposes a methodology for the economic modeling of the ancillary services market in real time using a dynamic hourly mathematical model that integrates the variability of solar–wind generation, a demand monitoring curve, and the trajectory of marginal cost (MgC). This is a segmented methodology in which plants with costs close to the marginal cost are identified in real time using the Supramarginal (SMg) and Inframarginal (IMg) methods. Finally, this economic model for real-time power reserve reallocation represents an innovation in the ancillary services market because its results allow for the operation costs (OC) of the reserves to be reduced by up to 60% and for the displacement of marginal costs to be reduced by 10 to 40% with respect to traditional methodologies such as the economic merit list and the technical minimum methodology, which cause plants to operate without economic justification. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Integrating renewable energy through inverter-based generators has decreased the power system's inertia. Reduced inertia may lead to frequency instability during power imbalance disturbances, particularly in an isolated power system with limited inertia. The Battery Energy Storage System (BESS) and a virtual inertia (VI) emulation control system have become popular to mitigate this issue. Nonetheless, the BESS utilization for VI emulation is highly dependent on the availability of BESS capacity, which may affect the energy cost. Therefore, developing a VI emulation control strategy that requires less energy and can recover the state of charge (SoC) to a desired level to optimize BESS utilization is required. This paper proposes a VI control with an SoC recovery strategy through coordination with the generators' secondary frequency control. Instead of relying on the frequency, such as in the conventional approach, the controlled signal of the generators' secondary frequency control also includes the VI power and BESS SoC. Hence, the generators can contribute to lowering the VI required energy and recovering the BESS SoC. The results show that the proposed method outperforms the conventional method by requiring around 36% lower energy and the ability to maintain the BESS SoC. [ABSTRACT FROM AUTHOR]

The growing number of renewable energy replacing conventional generators results in a loss of the reserve for frequency control in power systems, while many industrial power grids often have excess energy supply due to abundant wind and solar energy resources. This paper proposes a secondary frequency control (SFC) strategy that allows industrial power grids to provide emergency high-voltage direct current (HVDC) power support (EDCPS) for emergency to a system requiring power support through a voltage source converter (VSC) HVDC link. An architecture including multiple model predictive control (MPC) controllers with periodic communication is designed to simultaneously obtain optimized EDCPS capacity and minimize adverse effects on the providing power support (PPS) system. Moreover, a model of a virtual power plant (VPP) containing aluminum smelter loads (ASLs) and a high penetration of wind power is established for the PPS system. The flexibility and controllability of the VPP are improved by the demand response of the ASLs. The uncertainty associated with wind power is considered by chance constraints. The effectiveness of the proposed strategy is verified by simulation results using the data of an actual industrial power grid in Inner Mongolia, China. The DC voltage of the VSCs and the DC in the potlines of the ASLs are also investigated in the simulation.

The integration of renewable resources in isolated systems can produce instability in the electrical grid due to its intermintency. In today’s microgrids, which lack synchronous generation, physical inertia is substituted for inertia emulation. To date, the most effective approach remains the frequency derivative control technique. Nevertheless, within this method, the ability to provide virtual drooping is often disregarded in its design, potentially leading to inadequate development in systems featuring high renewable penetration and low damping. To address this issue, this paper introduces an innovative design and analysis of virtual inertia control to simultaneously mimic droop and inertia characteristics in microgrids. The dynamic frequency response without and with renewable energy sources penetration is comparatively analyzed by simulation. The proposed virtual inertia control employs a derivative technique to measure the rate of change of frequency slope during inertia emulation. Sensitivity mapping is conducted to scrutinize its impact on dynamic frequency response. Finally, the physical battery storage system of the University of Cuenca microgrid is used as a case study under operating conditions.

In recent decades the power system has become a complex network, to design a load frequency control (LFC) requires solving a complex equation. Optimisation techniques are essentially required to optimise the parameters of different controllers used for LFC issues in the power system. In a unified power system, the LFC is examined from all angles using different optimisation strategies to optimise the conventional PI, PID, cascaded, and fuzzy controllers as well as recently designed controllers. This manuscript specifically reviews the use of soft computing techniques in the frequency regulation of the power system with single/multiple areas that include conventional, renewable, and combinations of both, with FACTS devices and certain energy storage devices such as superconductor magnetic energy storage (SMES) and battery sources. Furthermore, deregulated power systems and microgrids are also considered for the study. To regulate LFC under various disturbances such as generation rate constraints (GRC) and dead band control, a few additional control approaches are utilised. Models of the power system are discussed and analysed. In addition, the merits and drawbacks of the studied techniques/structures that address design and implementation issues—as well as control issues that relate to the LFC problems—have been discussed. [ABSTRACT FROM AUTHOR]

Power system stability has been suffering increasing threats with the ever-growing penetration of intermittent renewable generation such as wind power and solar power. Battery energy storage systems (BESSs) could mitigate frequency fluctuation of the power system because of their accurate regulation capability and rapid response. By dividing the Area Control Error (ACE) signal and the State of Charge (SOC) of battery energy storage systems into different intervals, the frequency control task of BESSs could be determined by considering the frequency control demand of the power grid in each interval and SOC self-recovery. The well-developed model predictive control can be employed to attain the optimal control variable sequence of BESSs in the following time, which can determine the output depths of BESSs and action timing at different intervals. The simulation platform MATLAB/Simulink is used to build two secondary frequency control scenarios of BESSs for providing frequency regulation service. The feasibility of the presented strategy is demonstrated by simulation results of a sample system. [ABSTRACT FROM AUTHOR]

This paper applies a new state feedback control to a distributed secondary voltage and frequency control in an islanded microgrid. The problem is focused on the output consensus of the multi-agent systems, which is converted to a first-order dynamic system. The inverter-based distributed generations play as agents in the proposed control strategy. It is assumed that the distributed generators communicate through a communication network modeled by a directed graph (digraph). The distributed output consensus is used to design the secondary controllers. Such innovative controllers synchronize distributed generators' output voltages and frequencies to their reference values by a novel state feedback approach. Compared to the existing consensus protocols, the proposed method provides a different innovative solution to the secondary voltage and frequency control of microgrids, which has a better response in case of communication failures. Finally, extensive and comparative simulations have been presented to verify the validity of the proposed control strategy and the system performance.

Photovoltaic (PV) distributed generators (DGs) are inherently stochastic and have low inertia owing to their weather dependence and connection to an inverter. Frequency regulation presents a significant challenge for the high penetration of PV-DGs to microgrids. Recently, a virtual synchronous generator (VSG) has been proposed to enhance the inertia of microgrids because it mimics the behavior of synchronous generators. However, few studies have utilized VSG-based DGs for secondary frequency regulation owing to their stochastic power output. In this study, a model predictive control scheme integrated with two-layer moving-horizon estimation (TL-MHE) observer is proposed and applied to the secondary frequency control of a PV high-penetration microgrid. The local observer estimates the power disturbances in each PV-DGs, whereas the centralized observer estimates the system states and load disturbances. The two-layer observer design decouples multiple observations and reduce the order of the observation equations. Compared with conventional centralized observer-based controllers, the proposed scheme can obtain better observation results. The model prediction controller optimizes the restorative power from each DG in real time to minimize frequency fluctuations, thus affording better control performance. Simulation results show that the proposed TL-MHE method can accelerate the system frequency recovery, reduce frequency- fluctuations peaks, and reduce frequency deviation by more than 80% compared with the conventional method. • A model predictive control scheme integrated with two-layer moving-horizon estimation observer is proposed. • The two-layer observer design decouples multiple observations and reduce the order of the observation equations. • We use deloading virtual synchronous generator control to make the renewable energy participating in the secondary frequency regulation. • The proposed method overcomes the stochasticity of each generating unit and load. [ABSTRACT FROM AUTHOR]

At present, battery energy storage systems (BESS) have become an important resource for improving the frequency control performance of power grids under the situation of high penetration rates of new energy. Aiming at the problem that the existing control strategy is not sufficient for allocating the frequency regulation power instructions, a hierarchical distributed coordinated control strategy for BESS to participate in the automatic generation control (AGC) of a regional power grid is proposed. At the upper layer, the state of charge (SOC) of BESS and the technical characteristics of different frequency regulation power sources are comprehensively considered to complete the coordinated distribution of frequency regulation commands between BESS and traditional generators; at the lower layer, for the purpose of optimizing the economic operation of the regional power grid, the distributed consistency algorithm is used to control the distributed BESS in order to realize the fine management of power output of BESS. The simulation results indicate that this control strategy can give full play to the technical characteristics of different frequency power sources and improve the frequency regulation of the power grid. The excessive power consumption of BESS is successfully avoided, and the continuous operation of BESS is realized. [ABSTRACT FROM AUTHOR]

Integrating renewable energy through inverter-based generators has decreased the power system’s inertia. Reduced inertia may lead to frequency instability during power imbalance disturbances, particularly in an isolated power system with limited inertia. The Battery Energy Storage System (BESS) and a virtual inertia (VI) emulation control system have become popular to mitigate this issue. Nonetheless, the BESS utilization for VI emulation is highly dependent on the availability of BESS capacity, which may affect the energy cost. Therefore, developing a VI emulation control strategy that requires less energy and can recover the state of charge (SoC) to a desired level to optimize BESS utilization is required. This paper proposes a VI control with an SoC recovery strategy through coordination with the generators’ secondary frequency control. Instead of relying on the frequency, such as in the conventional approach, the controlled signal of the generators’ secondary frequency control also includes the VI power and BESS SoC. Hence, the generators can contribute to lowering the VI required energy and recovering the BESS SoC. The results show that the proposed method outperforms the conventional method by requiring around 36% lower energy and the ability to maintain the BESS SoC.

• Modeling unknown dynamics of microgrids using Gaussian processes. • The model of the MPC controller consists of a physical model and a data model based on Gaussian processes. • Frequency control of a microgrid consisting of photovoltaics, energy storage and electric vehicles is considered. • The proposed method overcomes the stochasticity of each generating unit and load and the parameter uncertainty of the physical models. Microgrids comprising photovoltaic (PV), energy-storage systems and electric vehicles have received increasing attention. However, the increase in renewable energy sources, such as PVs, will introduce uncertainty factors to the frequency response, resulting in frequency fluctuations that can reduce power quality. Hence, we propose an outstanding learning-based control approach that combines a model of physical principles with a Gaussian Process (GP) learning approach. The learning model corrects the physical principles model and estimates its uncertainty. Simulations are performed by comparing the proposed controller with conventional model-predictive controllers. The results indicate that the learning-based controller proposed can adjust the frequency with less overshooting and a lower root mean square error compared to the conventional MPC control method. [ABSTRACT FROM AUTHOR]

This paper applies a new state feedback control to a distributed secondary voltage and frequency control in an islanded microgrid. The problem is focused on the output consensus of the multi-agent systems, which is converted to a first-order dynamic system. The inverter-based distributed generations play as agents in the proposed control strategy. It is assumed that the distributed generators communicate through a communication network modeled by a directed graph (digraph). The distributed output consensus is used to design the secondary controllers. Such innovative controllers synchronize distributed generators' output voltages and frequencies to their reference values by a novel state feedback approach. Compared to the existing consensus protocols, the proposed method provides a different innovative solution to the secondary voltage and frequency control of microgrids, which has a better response in case of communication failures. Finally, extensive and comparative simulations have been presented to verify the validity of the proposed control strategy and the system performance. [ABSTRACT FROM AUTHOR]

With the increasing penetration of the renewables, power system requires more resources with high ramping rate in the secondary frequency control (SFC). Battery energy storage system (BESS) is regarded as an effective one to follow the regulation signals. Meanwhile, the optimal operation of BESS cluster brings challenges to independent system operator (ISO), as more BESSs are involved in a control area. Specifically, the control center tries to take full advantages of the characteristics of BESS meeting frequency regulation requirement, and to follow the state of charge (SoC) limitation in BESS distribution. Therefore, a degree of participation (DP) based SFC for BESS cluster is proposed in this paper. In detail, a fuzzy-logic inference system (FLIS) is applied to determine a proper DP by considering the system frequency regulation requirements and BESS SoC. Also, the coefficients of the BESS operation cost function vary with DP, and the distribution of BESS in SFC is achieved to minimize the operation cost of BESS cluster by quadratic programming algorithm (QPA). At last, the promising results shows the BESS is well arranged by the proposed DP-based SFC, balancing the system frequency regulation requirement and BESS SoC limitation.

In recent decades the power system has become a complex network, to design a load frequency control (LFC) requires solving a complex equation. Optimisation techniques are essentially required to optimise the parameters of different controllers used for LFC issues in the power system. In a unified power system, the LFC is examined from all angles using different optimisation strategies to optimise the conventional PI, PID, cascaded, and fuzzy controllers as well as recently designed controllers. This manuscript specifically reviews the use of soft computing techniques in the frequency regulation of the power system with single/multiple areas that include conventional, renewable, and combinations of both, with FACTS devices and certain energy storage devices such as superconductor magnetic energy storage (SMES) and battery sources. Furthermore, deregulated power systems and microgrids are also considered for the study. To regulate LFC under various disturbances such as generation rate constraints (GRC) and dead band control, a few additional control approaches are utilised. Models of the power system are discussed and analysed. In addition, the merits and drawbacks of the studied techniques/structures that address design and implementation issues—as well as control issues that relate to the LFC problems—have been discussed.

Power system stability has been suffering increasing threats with the ever-growing penetration of intermittent renewable generation such as wind power and solar power. Battery energy storage systems (BESSs) could mitigate frequency fluctuation of the power system because of their accurate regulation capability and rapid response. By dividing the Area Control Error (ACE) signal and the State of Charge (SOC) of battery energy storage systems into different intervals, the frequency control task of BESSs could be determined by considering the frequency control demand of the power grid in each interval and SOC self-recovery. The well-developed model predictive control can be employed to attain the optimal control variable sequence of BESSs in the following time, which can determine the output depths of BESSs and action timing at different intervals. The simulation platform MATLAB/Simulink is used to build two secondary frequency control scenarios of BESSs for providing frequency regulation service. The feasibility of the presented strategy is demonstrated by simulation results of a sample system.

At present, battery energy storage systems (BESS) have become an important resource for improving the frequency control performance of power grids under the situation of high penetration rates of new energy. Aiming at the problem that the existing control strategy is not sufficient for allocating the frequency regulation power instructions, a hierarchical distributed coordinated control strategy for BESS to participate in the automatic generation control (AGC) of a regional power grid is proposed. At the upper layer, the state of charge (SOC) of BESS and the technical characteristics of different frequency regulation power sources are comprehensively considered to complete the coordinated distribution of frequency regulation commands between BESS and traditional generators; at the lower layer, for the purpose of optimizing the economic operation of the regional power grid, the distributed consistency algorithm is used to control the distributed BESS in order to realize the fine management of power output of BESS. The simulation results indicate that this control strategy can give full play to the technical characteristics of different frequency power sources and improve the frequency regulation of the power grid. The excessive power consumption of BESS is successfully avoided, and the continuous operation of BESS is realized.

Consensus-based control has been widely applied in the frequency/voltage restoration and power sharing of microgrids. Considering the existence of plug-and-play devices and accidental communication failures in microgrids, the physical and cyber structure of a microgrid may be time-varying, where the performance of traditional consensus-based control methods under ideal cases may not be guaranteed. This article proposed a novel finite-time consensus-based secondary frequency control strategy, i.e., a control strategy with finite-time convergence performance. The convergence time of the proposed control strategy is independent of both the structure and operation states of the microgrid, which guarantees the effectiveness of the control strategy under flexible operating conditions. Moreover, a detailed performance analysis of the finite-time control strategy is presented, and an optimal design method of the control parameters is developed, which significantly improves the performance of the finite-time control strategy. The flexibility of the proposed control strategy, as well as the effectiveness of the optimal design method, is verified by both simulation and experimental results. [ABSTRACT FROM AUTHOR]

With the large-scale integration of renewable power generation, frequency regulation resources (FRRs) are required to have larger capacities and faster ramp rates, which increases the cost of the frequency regulation ancillary service. Therefore, it is necessary to consider the frequency regulation cost and constraint along with real-time economic dispatch (RTED). In this article, a data-driven distributionally robust optimization (DRO) method for RTED considering automatic generation control (AGC) is proposed. First, a Copula-based AGC signal model is developed to reflect the correlations among the AGC signal, load power and renewable generation variations. Secondly, samples of the AGC signal are taken from its conditional probability distribution under the forecasted load power and renewable generation variations. Thirdly, a distributionally robust RTED model considering the frequency regulation cost and constraint is built and transformed into a linear programming problem by leveraging the Wasserstein metric-based DRO technique. Simulation results show that the proposed method can reduce the total cost of power generation and frequency regulation. [ABSTRACT FROM AUTHOR]

With the increasing penetration of renewables in power systems, frequency regulation is proving to be a major challenge for system operators using slower conventional generation, and alternative means to provide faster regulation are being actively sought. The participation of demand side management in ancillary service provision is proven in some energy markets, yet its full potential to benefit frequency regulation, including the exploitation of fast power ramping capability of some devices, is still undergoing research. In this study, a novel approach to improve the speed of response of load frequency control, a secondary frequency control approach is proposed. The proposed control is enabled by an effective location identification technique, is highly resilient to anticipated system changes such as reduction of inertia, and enables fully decentralised power system architectures. The effectiveness of the approach is demonstrated and compared to that of present day regulation control, by means of real‐time simulations incorporating appropriate time delays conducted on a five‐area reduced model of the Great Britain power system. The applicability of the method is further proven under realistic communications delays and measurements experimentally using a controller and power hardware‐in‐the‐loop setup, demonstrating its critical support for enabling the stable operation of future power systems.

A significant number of 5G base stations (gNBs) and their backup energy storage systems (BESSs) are redundantly configured, possessing surplus capacity during non-peak traffic hours. Moreover, traffic load profiles exhibit spatial variations across different areas. Proper scheduling of surplus capacity from gNBs and BESSs in different areas can provide sustainable frequency support for the power system without compromising the operation of 5G network. In this paper, a comprehensive strategy is proposed to safely incorporate gNBs and their BESSs (called "gNB systems") into the secondary frequency control procedure. Initially, an aggregated model is developed using a state space method to capture the state of a cluster of heterogeneous gNB systems (gNBs-cluster). Subsequently, a utility function is defined to evaluate the quality of 5G network operation in a normalized manner. Based on this utility function, an aggregated control method is proposed, including real-time available power estimation and model predictive control (MPC) for the gNBs-cluster, which ensures the 5G network operation within the security constraint during demand response processes. Simulations, utilizing actual device data, demonstrate the effectiveness of the proposed method in improving power system frequency performance while guaranteeing the safety and reliability of the 5G network. • Joint control architecture integrates gNB systems into power system control. • Aggregated model captures state of heterogeneous gNBs-cluster efficiently. • Utility function scores gNBs-cluster state in a normalized manner. • Broadcast-based aggregated control reduces communication needs. • Utility-based MPC ensure secure 5G network operation during demand response. [ABSTRACT FROM AUTHOR]

The increased penetration of renewable energy sources (RES) and electric vehicles (EVs) is resulting in significant challenges to the stability, reliability, and resiliency of the electrical grid due to the intermittency nature of RES and uncertainty of charging demands of EVs. There is a potential for significant economic returns to use vehicle-to-grid (V2G) technology for peak load reduction and frequency control. To verify the effectiveness of the V2G-based frequency control in a microgrid, modeling and simulations of single- and multi-vehicle-based primary and secondary frequency controls were conducted to utilize the integrated components at the Canadian Centre for Housing Technology (CCHT)-V2G testing facility by using MATLAB/Simulink. A single-vehicle-based model was validated by comparing empirical testing and simulations of primary and secondary frequency controls. The validated conceptual model was then applied for dynamic phasor simulations of multi-vehicle-based frequency control with a proposed coordinated control algorithm for improving frequency stability and facilitating renewables integration with V2G-capable EVs in a microgrid. This proposed model includes a decentralized coordinated control of the state of charge (SOC) and charging schedule for five aggregated EVs with different departure times and SOC management profiles preferred by EV drivers. The simulation results showed that the fleet of 5 EVs in V2B/V2G could effectively reduce frequency deviation in a microgrid.

This article investigates the operation of offshore wind farm connected by parallel diode‐rectifier‐based HVDC (DR‐HVDC) and HVAC links. A secondary voltage control is proposed to control the offshore AC voltage amplitude by regulating the DC voltage of the DR‐HVDC link. A secondary frequency control and a phase angle control are proposed to adjust the reactive power reference in the primary control, which synchronise the offshore point of common coupling (PCC) frequency and phase angle to those of the HVAC link. Such secondary voltage control, frequency control, and phase angle control enable seamless transition from DR‐HVDC mode to parallel mode. A tertiary power control scheme is further proposed to control the active power flow distribution between DR‐HVDC and HVAC links through the regulation of PCC phase angle. To ensure smooth transition from HVAC mode to parallel mode, a virtual DC power control is proposed to control the virtual DC power at zero prior to the connection of the DR‐HVDC link. A small‐signal model of the parallel system is developed, and the stability analysis is carried out for the proposed control scheme. Simulation results in PSCAD/EMTDC verify the proposed control under normal and fault conditions. [ABSTRACT FROM AUTHOR]

• Dynamic event-triggered robust secondary frequency controller is proposed. • It provides a good balance between dynamic performance and communication burden. • The controller design does not depend on the full-order state matrices of the plant. • Communication intervals are enlarged by the dynamic event-triggered mechanism. • Simulation on detailed models verifies the effectiveness of Dynamic event-triggered robust secondary frequency controller. The permeability of renewable energy sources rapidly increases in the microgrid for economic and environmental concerns. However, the uncertainty of renewable energy may lead to frequency fluctuation or even instability in the microgrid. This paper proposes a dynamic event-triggered robust secondary frequency control scheme for the islanded microgrid to handle the uncertainty of the renewable energy source. In addition to the enhancement of frequency stability, the communication burden is also considered in this work. The proposed dynamic event-triggered communication scheme provides a good balance between dynamic performance and communication burden. Based on the discontinuous Lyapunov function, the stability analysis helps the optimal gain selecting. Given the designed controller, the derived theorems in this paper can help to examine whether the communication system fulfills the requirements from the controllers. To validate the proposed method, case studies are carried out based on two typical microgrids. The simulation results are compared with conventional frequency controllers. It shows that the proposed controller outperforms other types of controllers in term of the frequency response performance and communication burden. [ABSTRACT FROM AUTHOR]

With the increasing penetration of renewables in power systems, frequency regulation is proving to be a major challenge for system operators using slower conventional generation, and alternative means to provide faster regulation are being actively sought. The participation of demand side management in ancillary service provision is proven in some energy markets, yet its full potential to benefit frequency regulation, including the exploitation of fast power ramping capability of some devices, is still undergoing research. In this study, a novel approach to improve the speed of response of load frequency control, a secondary frequency control approach is proposed. The proposed control is enabled by an effective location identification technique, is highly resilient to anticipated system changes such as reduction of inertia, and enables fully decentralised power system architectures. The effectiveness of the approach is demonstrated and compared to that of present day regulation control, by means of real‐time simulations incorporating appropriate time delays conducted on a five‐area reduced model of the Great Britain power system. The applicability of the method is further proven under realistic communications delays and measurements experimentally using a controller and power hardware‐in‐the‐loop setup, demonstrating its critical support for enabling the stable operation of future power systems. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this study, the authors represent a modelling to analyse and simulate renewable power generation for two area power systems in the presence of high penetrated wind farm. The performance of assumed power systems may hazard without appropriate frequency amelioration methodologies. To complete the LFC model for two area power systems, the combination of automatic generation control and automatic voltage regulation of thermal units is considered. Due to the decline in the total inertia of power system associated with wind farm contribution, the self‐tuning and adaptive fuzzy‐based PID droop can be proposed in the structure of wind turbines instead of the fixed/traditional PID droop in de‐loaded area to ameliorate the frequency excursions. Besides, the artificial bee colony algorithm can tune the parameters of membership functions for input and output signals based on a multi‐objective function (MOF). The proposed strategy control is proved to be accurately stable under various load changes and yields more satisfactory performance in comparison to the conventional PID droop. This research generally includes wind farm collaboration in the frequency control by inertia, primary and secondary frequency control. [ABSTRACT FROM AUTHOR]

This paper examines the provision of demand-side ancillary services using building thermodynamics and heating ventilation and air-conditioning (HVAC) systems. In particular, we consider the secondary frequency control service where the load has to declare a power capacity and a nominal power at the beginning of the regulation period and then in real-time track the received regulation signal around its declared nominal power. A hierarchical control scheme is proposed in this paper. The local building controllers at the lowest level track the temperature setpoints received from the thermal flexibility controller which maximizes the flexibility of building’s thermal consumption. At the highest level, the electrical flexibility controller controls the HVAC system while maximizing the flexibility provided to the grid. The two flexibility control layers are based on robust optimization methods. A control oriented model of a typical HVAC system is developed, and simulations are carried out to demonstrate the efficacy of the proposed approach. Results show that extra flexibility may be attained by exploiting the coefficient of performance (COP) of the chiller. Furthermore, occupant comfort increases as a consequence of providing ancillary services. [ABSTRACT FROM AUTHOR]

A comprehensive modular state-space model of a microgrid is developed that handles basic components and loads, as well as inverter-based generation, such as PQ inverter and voltage-source inverter (VSI). Specifically, the developed model is suitable for control design utilizing the nominal set-point values of frequency and voltage of the VSI inverters, and active and reactive power set points of the PQ inverters. The model is also useful for small-signal stability assessment and enhancement. It is shown that when a PQ inverter is added to the system, the low-frequency modes of the power-sharing dynamics drift to new locations and the relative stability is improved. Meanwhile, to preserve the power-sharing stability, a decentralized droop controller of paralleled VSI inverters is designed. Finally, the dynamic model is used to design and implement distributed secondary frequency controllers taking into consideration the characteristics of storage devices. The proposed modeling and control methodologies are demonstrated using an 11 bus microgrid with and without PQ inverters. [ABSTRACT FROM AUTHOR]

Load frequency control (LFC) is one of the most challenging problems in multi-area power systems. In this paper, we consider power system formed of distinct control areas with identical dynamics which are interconnected via weak tie-lines. We then formulate a disturbance rejection problem of power-load step variations for the interconnected network system. We follow a top-down method to approximate a centralized linear quadratic regulator (LQR) optimal controller by a distributed scheme. Overall network stability is guaranteed via a stability test applied to a convex combination of Hurwitz matrices, the validity of which leads to stable network operation for a class of network topologies. The efficiency of the proposed distributed load frequency controller is illustrated via simulation studies involving a six-area power system and three interconnection schemes. In the study, apart from the nominal parameters, significant parametric variations have been considered in each area. The obtained results suggest that the proposed approach can be extended to the non-identical case.

The extensive development of renewable energies in power systems causes several problems due to intermittent output power generation. To tackle the challenge, demand response contribution to ancillary service is currently well recognized under the smart grid infrastructure. The application of the heat pump water heater (HPWH) as a controllable load in primary frequency control is well presented in the literature; however, the motivation of this paper is to use HPWHs for secondary frequency control. To this end, a model predictive control (MPC) method for a two-area power system incorporating HPWHs to contribute to secondary frequency control is proposed in this paper. A detailed model of HPWH is employed as a controllable load to control the power consumption during water heating. The MPC method predicts the future control signals using a quadratic programming-based optimization. It uses the system model, past inputs and outputs, as well as system control signals to predict the next signals. The effective performance of the proposed method for the two-area power system with HPWH is demonstrated for different scenarios of load changes, intermittent renewable power generation and parameter variations as the sensitivity analysis.

With high renewable power penetration, uncertainty and intermittence of renewable sources become major concerns of power system planning and operation. Large and fast wind speed change may cause great variation of active power generation, which may lead to system stability and reliability problems. The response speeds of the committed conventional generators (CGs) for frequency regulations are critical for system reliable and stable operation. The slow response of the committed CGs may result in power shortage or surplus, which may affect system frequency. This paper proposes a technique to evaluate operational reliability and efficiency problems of power systems with high wind power penetration from frequency aspect. Energy unnecessarily consumed and less supplied during system frequency control processes are modeled in detail. The reliability and economic indexes are formulated with considering system dynamic frequency control processes. The IEEE-RTS79 is used to verify the proposed models and method. [ABSTRACT FROM AUTHOR]

Model predictive control (MPC) has been widely studied for regulating frequency in stand-alone microgrids (MGs), owing to the advantages of MPC such as fast response and robustness against the parameter uncertainties. Understanding the impacts of system parameters on the control performance of MPC could be useful for the designing process of the controller to achieve better performance. This study analyzes the impact of system parameters on the control performance of MPC for frequency regulation in a stand-alone MG. The typical stand-alone MG, which consists of a diesel engine generator, an energy storage system (ESS), a wind turbine generator, and a load, is considered in this study. The diesel engine generator is in charge of primary frequency control whereas the ESS is responsible for secondary frequency control. The stand-alone MG is linearized to obtain the dynamic model that is used for designing MPC-based secondary frequency control. The robustness of MPC against the variation of system parameters is also analyzed in this study. A comparison study of MPC and proportional-integral (PI) control is presented. Simulation results show that MPC has a faster response time and lower overshoot compared to PI control. In addition, the robustness of MPC against the system uncertainties is stronger than conventional PI control. [ABSTRACT FROM AUTHOR]

As a small‐scale power system, microgrid (MG) will lose support from the main grid if it switches to islanded mode because of the pre‐planned scheduling or unplanned disturbances. To synchronise the frequency and voltage to their reference values, a secondary frequency and voltage cooperative control is proposed in this study. The proposed secondary control can synchronise the frequency and voltage to their reference values in finite time and achieve the active power sharing simultaneously. Moreover, it is suitable for switching communication architecture. The MG is considered as multi‐agent systems and the system stability is proved by multi‐agent theory and finite‐time stability theory. A simulation system is established in Matlab/Simulink environment, and the results show the effectiveness of the proposed controller. [ABSTRACT FROM AUTHOR]

This paper presents an exciting finding for the power industry: The parameters of secondary frequency control based on integral or proportional integral control can be tuned to achieve economic operation and frequency regulation simultaneously within a considerable short period. We show that if the power imbalance is represented by frequency deviation, an iterative dual-ascent-based economic dispatch solving is equivalent to integral control. An iterative method of multipliers based economic dispatch is equivalent to proportional integral control. Similarly, if the controller parameters of the secondary frequency controls are chosen based on generator cost functions, these secondary frequency controllers achieve both economic operation and frequency regulation simultaneously. [ABSTRACT FROM AUTHOR]

With the increasing proportion of renewable energy in microgrids (MGs), its stochastic fluctuation of output power has posed challenges to system safety and operation, especially frequency stability. Virtual synchronous generator (VSG) technology, as one effective method, was used to smoothen frequency fluctuation and improve the system’s dynamic performance, which can simulate the inertia and damping of the traditional synchronous generator. This study outlines the integration of VSG-controlled energy storage systems (ESSs) and traditional synchronous generators so they jointly participate in secondary frequency regulation in an independent MG. Firstly, a new uncertain state-space model for secondary frequency control is established, considering the measurement noises and modelling error. Then, an improved linear quadratic Gaussian (LQG) controller is designed based on stochastic optimal control theory, in which the dynamic performance index weighting matrices are optimized by combining loop transfer recovery (LTR) technology and the distribution estimation algorithm. On the issue of secondary frequency devices’ output power allocation, the dynamic participation factors based on the ESS’s current state of charge (SOC) are proposed to prevent the batteries’ overcharging and overdischarging problems. The energy storage devices’ service life can be prolonged and OPEX (operational expenditure) decreased. Multiple experimental scenarios with real parameters of MGs are employed to evaluate the performance of the proposed algorithm. The results show that, compared with the lead-compensated-proportional-integral-derivative (LC-PID) control and robust μ-control algorithms, the proposed stochastic optimal control method has a faster dynamic response and is more robust, and the fluctuations from renewable energy and power loads can be smoothened more effectively.