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As the world grapples with the energy crisis, integrating renewable energy sources into the power grid has become increasingly crucial. Microgrids have emerged as a vital solution to this challenge. However, the reliance on renewable energy sources in microgrids often leads to low inertia. Renewable energy sources interfaced with the network through interlinking converters lack the inertia of conventional synchronous generators, and hence, need to provide frequency support through virtual inertia techniques. This paper presents a new control algorithm that utilizes the reinforcement learning agents Twin Delayed Deep Deterministic Policy Gradient (TD3) and Deep Deterministic Policy Gradient (DDPG) to support the frequency in low-inertia microgrids. The RL agents are trained using the system-linearized model and then extended to the nonlinear model to reduce the computational burden. The proposed system consists of an AC–DC microgrid comprising a renewable energy source on the DC microgrid, along with constant and resistive loads. On the AC microgrid side, a synchronous generator is utilized to represent the low inertia of the grid, which is accompanied by dynamic and static loads. The model of the system is developed and verified using Matlab/Simulink and the reinforcement learning toolbox. The system performance with the proposed AI-based methods is compared to conventional low-pass and high-pass filter (LPF and HPF) controllers. [ABSTRACT FROM AUTHOR]

In a world where the energy crisis is becoming overwhelming, demand for integrating renewable energy sources is increasing and forming microgrids is becoming an essential solution. The new microgrid systems, which depend mainly on renewable energy sources instead of conventional synchronous generators, come with a low inertia concern. This paper proposes a virtual inertia controller based on a high-pass filter (HPF) to support the frequency of the AC microgrid while maintaining the DC voltage of the DC microgrid within the nominal ranges in cases of contingencies. The proposed system encounters an AC-DC microgrid with a renewable energy source on the DC microgrid alongside constant power load and resistive loads, while on the AC microgrid side, a synchronous generator is used to present the low inertia of the grid with dynamic loads and static loads. The state-space linearized model of the system is developed and verified using Matlab Simulink. The dynamic response of the proposed controller is compared to the low-pas filter (LPF)-based controller. Moreover, the effect of changing the system's parameters on eigenvalues is investigated. [ABSTRACT FROM AUTHOR]

The wide use of communication layers in DC microgrids to transmit voltage and current measurements of each distributed generator unit (DGU) increases the possibility of exposure to cyber-attacks. Cyber-attackers can manipulate the measured data to distort the control system of microgrids, which may lead to a shutdown. This paper proposes distributed mitigation layers for the false data injection attacks (FDIA) on voltages and currents of DGUs in meshed DC microgrids. The proposed control strategy is based on integrating two layers for cyber-attack detection and mitigation to immune the primary and the secondary control loops of each DGU. The first layer is assigned to mitigate FDIAs on the voltage measurements needed for the voltage regulation task of the primary control loop. The second layer is devoted to the mitigation of FDIAs on the DGU current measurements, which are crucial for the secondary control level to guarantee the proper current sharing of each DGU. Artificial neural networks (ANNs) are employed to support these layers by estimating the authenticated measurements. Different simulation and experimental case studies are provided to demonstrate the proposed mitigation layers' effectiveness in detecting and mitigating cyber-attacks on voltage and current measurements. The simulation and experimental results are provided to evaluate the dynamic performance of the suggested control approach and to ensure the accurate operation of DC microgrids despite the existence of cyber-attacks on the measurements employed in the control strategy. Moreover, the control strategy succeeds to keep the maximum voltage error and the maximum error in current sharing within tolerance. [ABSTRACT FROM AUTHOR]

• To counteract the impact of FDIAs, two units for cyberattack detection and mitigation are proposed. • A braided Lyapunov- based state observer is proposed to estimate current and voltage signals for DGUs. • The proposed braided system eliminates the need for extra sensors. • The CMPN adaptive controller outperforms the tuned traditional PI and LMF controllers. • Robustness of the braided Lyapunov-based observer for cyberattack mitigation strategy is validated. The transferred data in microgrids is susceptible to cyberattacks. This paper presents a primary and secondary control loops integrated with units for detecting and mitigating cyberattacks for each distributed generator in a DC microgrid. Most of the literature focused on mitigating cyberattacks using supervised learning techniques. On the contrary, this paper introduces reliable state observer-based mitigation units for voltage and current cyberattacks. A braided Lyapunov-based state observer is proposed to generate accurate estimate of terminal voltage and current, simultaneously, without the need for external measurements. Afterwards, cyberattack mitigation controller is triggered to develop the appropriate corrective actions. Fast control action is essential for effective mitigation of cyberattacks, along with precise state estimation. Therefore, two adaptive PI controllers are introduced in the cyberattack mitigation units. Different case studies are provided to assess the performance of the suggested sensorless cyberattack detection and mitigation strategy. To prove the superiority of the proposed strategy, comparative studies are carried out with the scheme of mitigating cyberattacks based on artificial neural networks (ANNs). The Lyapunov based state observer showed a lower settling time of 0.4 s, lower voltage maximum peak overshoot of 0.16 %, almost zero voltage and current sharing errors, when compared to ANNs. [ABSTRACT FROM AUTHOR]

One of the most widely used techniques for controlling the dc microgrid is the droop control method. The associated problems of the droop-based systems, such as the current sharing errors and the voltage deviation are solved using current sharing loops and secondary control loop, respectively. This paper presents an adaptive droop scheme for dc microgrids to overcome the non-linearity of the system. The droop resistance is adjusted using the adaptive PI controller to eliminate the current sharing error of each unit in the microgrid. In addition, another adaptive PI controller is dedicated for the secondary loop to regulate the dc bus voltage of the microgrid by shifting the droop lines. In the proposed scheme, only the current and voltage at the dc bus of the microgrid need to transmit through low-bandwidth communication channels to individual units. Moreover, the sliding mode control, which is distinguished by robustness and fast dynamic response, is utilized to manipulate the output voltage and the input current of each converter, instantaneously. The dynamic performance of the proposed adaptive droop scheme is evaluated using the PSCAD/EMTDC simulation package. [ABSTRACT FROM AUTHOR]

The droop control is the most effectively used technique for load current sharing in DC microgrid. The disadvantages of the conventional droop controllers are the increased voltage deviation and current sharing errors when the load current is increased. This paper presents two improved techniques for current sharing in DC microgrids. In the first technique, the droop resistance is updated for each converter in the microgrid to eliminate the current sharing error. The current sharing reference for each converter is calculated based on the ratio of its rating to the load current. Hence, the load current is the only parameter that needs to be communicated to the current sharing loops. The second proposed technique is based on utilizing optimal droop resistances to eliminate the need for current sharing loops and their associated communications. The harmony search (HS) technique is utilized to attain the optimal droop resistances which results in minimizing the error in the current sharing. A comparison is made between the results obtained using the HS technique and the particle swarm optimization technique. The dynamic performance of the droop controller using the proposed current sharing loop and the proposed optimal droop parameters is evaluated using the PSCAD/EMTDC simulation package. [ABSTRACT FROM AUTHOR]

Distributed generation and distributed energy storage systems can be controlled to improve power system stability. This article proposes control strategies for adopting distributed generation units to autonomous microgrids. The proposed distributed generation interface is utilized not only to control the active power flow, but also to provide essential ancillary services, such as voltage regulation and frequency control, to the autonomous microgrid. A coordinated voltage and frequency control of the inverter-based distributed generation and distributed energy storage system is presented. Moreover, a frequency estimation algorithm based on orthogonal filters is adopted for the frequency control loop. One advantage of the proposed control system is its unified structure for the different operating modes. Extensive simulations of the proposed coordinated control of the inverter-based distributed generation and distributed energy storage system are conducted to evaluate the dynamic performance of the proposed microgrid. [ABSTRACT FROM AUTHOR]

• A finite-state-machine (FSM) based controller for microgrid converters is presented. • Performance recovery controller accounts for uncertainties and parameters variations. • The dynamic performance of DC microgrids based on FSM controller is limited. • Results showed fast response and resiliency of the performance recovery controller. • Unlike PI, performance recovery controller successfully manages disturbances. Droop technique is extensively adopted in dc microgrids, for both islanded and grid-connected modes of operation. However, voltage regulation and proper current sharing are considered as the major challenges in droop techniques. Moreover, changes in system parameters and wide load demand variations degrade the operational performance and the efficiency of the dc microgrid. In this paper, a finite-state-machine (FSM) based controller for the inner loop of microgrid converters is utilized. Although the FSM controller operates in voltage mode and requires no current sensors, the dynamic performance of the microgrid converters is limited. Thus, a distributed consensus output voltage tracking based on the performance recovery controller is presented which adopts nonlinear observers for the microgrid converters to account for model uncertainties and disturbances due to parameters variations. The dynamic performance and robustness of the FSM controller and performance recovery controller are assessed using PSCAD/EMTDC simulation. Moreover, a comparative study with the classical Proportional-Integral (PI) controller is presented, considering both rating-based and cost-based current sharing schemes of the dc microgrids. [ABSTRACT FROM AUTHOR]

• The paper proposes a decentralized droop-based control technique power flow through the ILC, meanwhile, to keep the dc microgrid voltage and the ac microgrid frequency within their acceptable ranges. • To overcome the continuous operation of ILC, The modified droop control based CMPN algorithm is used to determine the necessity of operation of hybrid microgrid by estimating the status of the ac and dc microgrids by comparing local measurements with their critical values at both sides. • An adaptive filtering algorithm based on continuous mixed P-norm (CMPN) algorithm is utilized for the proposed autonomous control strategy to insure adaptive tuning of the controller parameters. The variable step size feature of the CMPN algorithm results in fast response compared to other techniques such as robust mixed-norm and the least absolute deviation techniques. The robustness against impulsive noise while having fast convergence, compared to other algorithms, render the CMPN algorithm to be an effective technique for online adaptation of the PI controller used for the ILC, especially in an islanded archetype to maintain the stability of the network. • A comparison between the proposed strategy based on both CMPN algorithm and adaptive PI control under different loading conditions are implemented to validate the proposed methodology. This paper proposes a new adaptive communication-less control strategy to enhance the dynamic performance of the interlinking converter (ILC) of a remote hybrid microgrid. The proposed autonomous strategy is based on the continuous mixed P-norm (CMPN) algorithm to simultaneously maintain the frequency of ac-side and the voltage of dc-side of the ILC within their acceptable ranges under various conditions. The variable step nature of the CMPN algorithm and robustness ensure stable operation of the proposed strategy for the ILC. In addition, the power sharing between both sides of the ILC is achieved by a modified ac-dc droop control to avoid using any communication systems between different distributed generators (DG). Moreover, a simple algorithm is used to determine the desired power flow direction based on local measurements of dc voltage and frequency. The proposed CMPN algorithm provides an online adaption of the controller's parameters to avoid the need for fine tuning or optimization techniques under various operating conditions. The dynamic performance of the proposed autonomous control strategy is evaluated using the PSCAD/EMTDC simulation package under different operating modes. The results demonstrate the superior dynamic performance of the proposed strategy based on the CMPN algorithm compared to the adaptive PI (API) controller in terms of fast response and tight regulation of power flow, voltage and frequency under different conditions. Compared to API, it has been found that the proposed controller results in more improvement of the dc-side voltage within the operating frequency range of the ac-side of the ILC. [ABSTRACT FROM AUTHOR]