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Currently, renewable energy sources (RESs) are gradually replacing traditional power sources that use fossil fuels. In some countries, such as Vietnam, RESs are developed on a massive scale and are concentrated in some key areas. This causes negative impacts on a power system when its transmission system is not deployed synchronously to release their capacity from these new renewable energy plants. An important challenge today is to ensure frequency stability in power systems with high uncertainty in RES output power. Additionally, the system requires solutions to prevent transmission line overloads during periods when RESs make a substantial contribution to the electricity generation capacity. Therefore, this paper builds an automatic generation control (AGC) system for a two-area power system with high penetration of RESs. This AGC system model aims to maintain system frequency stability amid unpredictable changes in RESs while also ensuring that tie-lines transmit the predetermined power levels to mitigate frequent congestion. By continuously monitoring and adjusting the system's frequency, the challenges posed by the inherent variability of RESs can be effectively mitigated. The AGC model is simulated on DIgSILENT PowerFactory software and tested with a 106-bus system. The simulation results of this study show that the AGC system operates effectively, ensuring that the frequency returns to the rated value and maintaining the exchange capacity on the tie-lines after occurrences of RES power decrease events. [ABSTRACT FROM AUTHOR]

Wind power systems (WPs) are complex non‐linear systems with varying parameters affected by environmental changes, including wind speed fluctuations. Extracting maximum power from WPs poses a significant challenge due to these factors. Direct power control (DPC) is a highly effective technique known for its simplicity and ease of implementation. However, it suffers from power ripples caused by the use of hysteresis comparators and switching tables that operate at variable frequencies. To address this issue, this paper presents the robust neural controller (NC) based on DPC, which replaces the switching tables. The Double‐Fed Induction Generator (DFIG) is the chosen generator for the studied WP system due to its advantageous features. The NC‐DPC effectively regulates the exchange of active and reactive powers between the DFIG and the system, maximizing power extraction from the WP system while reducing Total Harmonic Distortion and enhancing overall system quality. The effectiveness of the NC‐DPC is evaluated through MATLAB simulations and further supported by experimental data obtained using the Real‐Time Interface of the dSPACE‐DS1104 Controller card. [ABSTRACT FROM AUTHOR]

The increasing interactivity between energy carrier networks such as electrical, natural gas (NG), and heating can be appropriately used for improving the operation optimality along with overcoming some challenges of those systems. With such a view, this paper studies the practical issue of power transmission lines congestion management in integrated multicarrier energy systems (MCESs) and makes a comparison with the only electrical operation mode. The MCES consisting of electrical and NG network infrastructures with exchanged energy between them is modelled by considering the several local energy hubs and their electrical and heat loads. Rescheduling of energy sources (power plants and gas wells) and demand side management in both electrical and NG networks have been utilized as the two important tools in the developed congestion alleviation framework. The proposed method confirms that the provided flexibility in the integrated operation of the MCESs can lead to a remarkable reduction in the congestion management cost index. Implementing the proposed congestion management framework on an assumed test MCES with a combined 39‐bus New England power system and 20‐node Belgium NG system demonstrates its effectiveness and applicability for the system operators. The issue of power transmission lines congestion management in integrated multi‐carrier energy systems (MCESs) has been studied. The proposed method confirms that the provided flexibility in the integrated operation of the MCESs can lead to reduction in the congestion management cost. [ABSTRACT FROM AUTHOR]

With the fast development of renewable energy, system operators intend to require renewable energy generation to have more grid support capabilities. This paper studies the grid‐connected control strategy of a battery‐free medium‐voltage direct current (MVDC) system with distributed photovoltaic generation units (DPVGUs), aiming to realize the rapid grid support function to AC grid frequency. Firstly, a scheme for the MVDC system can keep some reserve capacity is provided. At this moment, DPVGUs execute a master‐slave coordinated control strategy, that is, the master DPVGU adopts an improved DC constant voltage control strategy to maintain the MVDC bus voltage, and the remaining DPVGUs adopt an improved droop control strategy to quickly provide corresponding power. Secondly, when the frequency deviation of AC grid exceeds the deadband of primary frequency control, fast frequency response (FFR) control strategy of the modular multilevel converter is proposed, aiming to actively transmit some or all of the reserved power of the MVDC system to the AC grid and can quickly provide frequency support to AC grid. In FFR control strategy, an additional control strategy is added on the vector control strategy. Finally, simulation studies are carried out in RTDS to verify the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This paper examines the critical topic of load frequency control (LFC) in shipboard microgrids (SMGs), which face challenges due to low system inertia and the intermittent power injection of renewable energy sources. To maintain a constant frequency (even under system uncertainties), a robust and well-tuned controller is required. In this paper, a study was conducted first by examining the performance of three different controller architectures, in order to determine which is the most-appropriate for the multi-energy SMG system. The time delays that occur due to communication links between the sensors and the controller were also considered in the analysis. The controllers were tuned using a very recent bio-inspired optimization algorithm called the jellyfish search optimizer (JSO), which has not been used until recently in LFC problems. To assess the tuning efficiency of the proposed optimization algorithm, the SMG's frequency response results were comprehensively compared to the results obtained with other bio-inspired optimization algorithms. The results showed that the controllers with gains provided by the JSO outperformed those tuned with other bio-inspired optimization counterparts, with improvements in performance ranging from 19.13% to 93.49%. Furthermore, the robustness of the selected controller was evaluated under various SMG operational scenarios. The obtained results clearly demonstrated that the controller's gains established in normal conditions do not require retuning when critical system parameters undergo a significant variation. [ABSTRACT FROM AUTHOR]

There are few pieces of research on switched reluctance generator (SRG) that accomplish optimal performance torque control, most prefer to use voltage, speed, or power control strategies. This paper proposes a direct average torque control (DATC) for SRG applied to wind energy conversion systems (WECS). The SRG is driven by an asymmetric half‐bridge converter (AHB), and an external chopper regulates the DC‐bus voltage. In the DATC strategy, the switching logic is modified, so that the machine operates in the generator mode. The dynamic behavior of an artificial neural network (ANN)‐based and the conventional co‐energy‐based torque estimation methods are discussed. Thereafter, the proposed DATC is compared to the direct power control (DPC) strategy. For both strategies, lookup tables are created to store the optimal switching angles. These lookup tables are optimized to achieve a trade‐off between torque ripple minimization and efficiency maximization. Experimental results show that the DATC strategy presents a lower torque ripple than the DPC method over the entire speed range. In contrast, DPC delivers superior efficiency for low and medium speeds. [ABSTRACT FROM AUTHOR]

Integrating Power Electronics Converters (PECs)‐based renewable energy sources can establish a weak grid due to the substantial inertia reduction leading to severe frequency fluctuations. In this paper, a control strategy based on the Virtual Synchronous Generator (VSG) concept is designed for a three‐phase Modular Multilevel Converter (MMC) connected to a weak grid. The proposed VSG control approach improves the frequency response during transient mode, resulting in a 66.7% enhancement at the Point of Common Coupling (PCC). The proposed strategy is shaped within four control loops wherein the VSG‐dependent output current control possesses the duty of enriching the MMC output current tracking capability. Focusing on the MMC output current‐based transfer function, the effectiveness of this capability is guaranteed using the frequency domain analysis including the Nyquist and Bode diagrams. Moreover, a comprehensive discussion was carried out regarding the impact of VSG on the voltage of submodule capacitors and the circulating current. Simulation results in MATLAB/Simulink environment validate the accuracy and weak grid‐connected MMC performance under the proposed VSG‐based control technique. To further verify the superiority of the proposed strategy, two control techniques including Droop and SEBIR are compared with the VSG proposed controller. [ABSTRACT FROM AUTHOR]

As the grid‐connected interface device of wind and photovoltaic power generation, the voltage source converter (VSC) must pass the low voltage ride‐through (LVRT) test. However, existing literature demonstrates that under weak grid conditions, there is a possibility of severe fluctuations in the terminal voltage of VSC during transiting from the pre‐sag normal operation mode to the LVRT mode. Unfortunately, it will make VSC frequently enter and exit LVRT mode. In order to address the tricky problem of transient instability of VSC riding‐through severe grid voltage sag under the weak grid, in this paper, the full‐order large‐signal model of VSC is established first. Then, based on the established model, the analysis indicates VSC will face the risk of losing stability under the weak grid during LVRT due to current transients. By studying the impacts of low short circuit ratio (SCR) on the basin of attraction of the post‐sag equilibrium point, the intrinsic mechanism of VSC losing stability under weak grid conditions is revealed. Moreover, considering that the transient stability is related to the current control, the stability‐enhanced LVRT control ensuring both small‐signal stability and transient stability of VSC during LVRT is proposed. Finally, the correctness of the above theoretical analysis is verified by real‐time simulation [ABSTRACT FROM AUTHOR]

In modern distribution networks, integration of distributed generations (DGs) at consumer premises is common. However, islanding detection in such a grid‐tied distributed generation (GTDG) network is the topmost challenge to ensure power quality and reliable operation. This paper presents a modified passive islanding detection scheme (MPIDS) for the GTDG network, using a One‐D recursive Median filter (ODRMF) algorithm. Firstly, at the point of common coupling (PCC), 3‐phase voltage is acquired. Next, the ODRMF is employed to extract 3rd harmonic and residuals from the acquired voltage signal. Afterward, two novel islanding detection indices developed are: (1) First change detection (FCD), which is calculated from the residuals, and (2) delta selected harmonic distortion (∆SHD), which is computed from 3rd harmonic content of the voltage signal. Finally, variations in the two indices are compared with the threshold to identify islanding. To validate the efficacy of the presented MPIDS, rigorous simulations in MATLAB/ Simulink are conducted on the UL‐1741 and IEEE 13‐bus GTDGs systems under different conditions. The results illustrate that the presented strategy is highly reliable in all assessed conditions and can detect the islanding as well as non‐islanding incidents effectively under balanced and unbalanced load/generation conditions with a very low non‐detection zone. [ABSTRACT FROM AUTHOR]

Inertial response from grid‐followers (GFLs) is deemed to be "synthetic" due to a slow response. In contrast, grid‐forming (GFM) inertial response is deemed to be faster and therefore "true" and more useful for frequency stability. This paper explores the differences and similarities between an established example of a GFM and a GFL inertial controller by carrying out parametric sweeps at different operating conditions. The analysis aims to assist the ongoing efforts to quantify grid stabilising phenomena, particularly the recent adaptation of the British grid code to incorporate GFM converters. The optimal tuning configurations are identified, showing that some configurations of the GFL can achieve fast inertial provision on strong grids. These configurations are shown to contain the grid frequency as effectively as the GFM, despite the opposing consensus in the literature. The results also highlight the importance of voltage‐source behaviours in determining the initial evolution of grid frequency. Although a blanket inclusion of all GFL inertial configurations is not appropriate, equally, the existing blanket disqualification could limit the assets available to support GFMs (who will certainly be required to stabilise the grid in a fundamental sense) and could inhibit the rate that the net zero transition can occur. [ABSTRACT FROM AUTHOR]

To solve the oxygen supply problem of proton exchange membrane fuel cell (PEMFC), this paper presents a reduced‐order active disturbance rejection control method for PEMFC air intake system based on the estimation of oxygen excess ratio(EOER‐RADRC). First, a control‐oriented third‐order nonlinear model was established based on PEMFC air intake system. Then, based on the control‐oriented model, the disturbance extended state observer was designed to solve the problem of unmeasured cathode pressure parameters in the calculation of oxygen excess ratio (OER), and realize the real‐time estimation of OER. Next, aiming at the large phase lag of active disturbance rejection control (ADRC), a reduced‐order ADRC method based on reduced‐order extended state observer was proposed by a variable substitution technique. So, the proposed method reduces the observation phase lag and improves the dynamic response performance under good anti‐disturbance ability. Finally, the simulation and hardware‐in‐the‐loop experience results showed that the proposed method has an excellent control effect compared with other methods. [ABSTRACT FROM AUTHOR]

Abstract With the increasing needs to decarbonise existing energy systems, there is an effort to integrate small‐scale distributed generation sources, such as wind generators, with the electric demand in circuits known as microgrids. The operation of distributed variable renewable resources is subject to an optimum operating regime, ahead of real‐time, which relies on output forecast. However, many wind speed forecast models are designed for centralised controllers, which are vulnerable to control failures. A suitable wind forecast model for a distributed control system is, therefore, required for optimal and reliable use of renewable generation. This paper presents a comparison of wind speed forecast models suited for distributed control, evaluating them in terms of the statistical significant difference in accuracy and computational resource requirements. This is essential since computational resources are limited in distributed control schemes. The data used in this paper is the historical wind speed of the Auchencorth Moss Atmospheric Observatory from 2016 to the end of 2019. Two forecast model types based on Auto‐regression and Artificial Neural Network (ANN) are compared using the Diebold‐Mariano test. Results show that ANN models with parallel hidden layers have the highest accuracy with statistical significant difference, while remaining suitable for microgrid distributed control.

This paper examines the critical topic of load frequency control (LFC) in shipboard microgrids (SMGs), which face challenges due to low system inertia and the intermittent power injection of renewable energy sources. To maintain a constant frequency (even under system uncertainties), a robust and well-tuned controller is required. In this paper, a study was conducted first by examining the performance of three different controller architectures, in order to determine which is the most-appropriate for the multi-energy SMG system. The time delays that occur due to communication links between the sensors and the controller were also considered in the analysis. The controllers were tuned using a very recent bio-inspired optimization algorithm called the jellyfish search optimizer (JSO), which has not been used until recently in LFC problems. To assess the tuning efficiency of the proposed optimization algorithm, the SMG’s frequency response results were comprehensively compared to the results obtained with other bio-inspired optimization algorithms. The results showed that the controllers with gains provided by the JSO outperformed those tuned with other bio-inspired optimization counterparts, with improvements in performance ranging from 19.13% to 93.49%. Furthermore, the robustness of the selected controller was evaluated under various SMG operational scenarios. The obtained results clearly demonstrated that the controller’s gains established in normal conditions do not require retuning when critical system parameters undergo a significant variation.

Abstract The increasing interactivity between energy carrier networks such as electrical, natural gas (NG), and heating can be appropriately used for improving the operation optimality along with overcoming some challenges of those systems. With such a view, this paper studies the practical issue of power transmission lines congestion management in integrated multicarrier energy systems (MCESs) and makes a comparison with the only electrical operation mode. The MCES consisting of electrical and NG network infrastructures with exchanged energy between them is modelled by considering the several local energy hubs and their electrical and heat loads. Rescheduling of energy sources (power plants and gas wells) and demand side management in both electrical and NG networks have been utilized as the two important tools in the developed congestion alleviation framework. The proposed method confirms that the provided flexibility in the integrated operation of the MCESs can lead to a remarkable reduction in the congestion management cost index. Implementing the proposed congestion management framework on an assumed test MCES with a combined 39‐bus New England power system and 20‐node Belgium NG system demonstrates its effectiveness and applicability for the system operators.

Abstract With the fast development of renewable energy, system operators intend to require renewable energy generation to have more grid support capabilities. This paper studies the grid‐connected control strategy of a battery‐free medium‐voltage direct current (MVDC) system with distributed photovoltaic generation units (DPVGUs), aiming to realize the rapid grid support function to AC grid frequency. Firstly, a scheme for the MVDC system can keep some reserve capacity is provided. At this moment, DPVGUs execute a master‐slave coordinated control strategy, that is, the master DPVGU adopts an improved DC constant voltage control strategy to maintain the MVDC bus voltage, and the remaining DPVGUs adopt an improved droop control strategy to quickly provide corresponding power. Secondly, when the frequency deviation of AC grid exceeds the deadband of primary frequency control, fast frequency response (FFR) control strategy of the modular multilevel converter is proposed, aiming to actively transmit some or all of the reserved power of the MVDC system to the AC grid and can quickly provide frequency support to AC grid. In FFR control strategy, an additional control strategy is added on the vector control strategy. Finally, simulation studies are carried out in RTDS to verify the effectiveness of the proposed control scheme.

Abstract Wind power systems (WPs) are complex non‐linear systems with varying parameters affected by environmental changes, including wind speed fluctuations. Extracting maximum power from WPs poses a significant challenge due to these factors. Direct power control (DPC) is a highly effective technique known for its simplicity and ease of implementation. However, it suffers from power ripples caused by the use of hysteresis comparators and switching tables that operate at variable frequencies. To address this issue, this paper presents the robust neural controller (NC) based on DPC, which replaces the switching tables. The Double‐Fed Induction Generator (DFIG) is the chosen generator for the studied WP system due to its advantageous features. The NC‐DPC effectively regulates the exchange of active and reactive powers between the DFIG and the system, maximizing power extraction from the WP system while reducing Total Harmonic Distortion and enhancing overall system quality. The effectiveness of the NC‐DPC is evaluated through MATLAB simulations and further supported by experimental data obtained using the Real‐Time Interface of the dSPACE‐DS1104 Controller card.

Abstract Integrating Power Electronics Converters (PECs)‐based renewable energy sources can establish a weak grid due to the substantial inertia reduction leading to severe frequency fluctuations. In this paper, a control strategy based on the Virtual Synchronous Generator (VSG) concept is designed for a three‐phase Modular Multilevel Converter (MMC) connected to a weak grid. The proposed VSG control approach improves the frequency response during transient mode, resulting in a 66.7% enhancement at the Point of Common Coupling (PCC). The proposed strategy is shaped within four control loops wherein the VSG‐dependent output current control possesses the duty of enriching the MMC output current tracking capability. Focusing on the MMC output current‐based transfer function, the effectiveness of this capability is guaranteed using the frequency domain analysis including the Nyquist and Bode diagrams. Moreover, a comprehensive discussion was carried out regarding the impact of VSG on the voltage of submodule capacitors and the circulating current. Simulation results in MATLAB/Simulink environment validate the accuracy and weak grid‐connected MMC performance under the proposed VSG‐based control technique. To further verify the superiority of the proposed strategy, two control techniques including Droop and SEBIR are compared with the VSG proposed controller.

Abstract There are few pieces of research on switched reluctance generator (SRG) that accomplish optimal performance torque control, most prefer to use voltage, speed, or power control strategies. This paper proposes a direct average torque control (DATC) for SRG applied to wind energy conversion systems (WECS). The SRG is driven by an asymmetric half‐bridge converter (AHB), and an external chopper regulates the DC‐bus voltage. In the DATC strategy, the switching logic is modified, so that the machine operates in the generator mode. The dynamic behavior of an artificial neural network (ANN)‐based and the conventional co‐energy‐based torque estimation methods are discussed. Thereafter, the proposed DATC is compared to the direct power control (DPC) strategy. For both strategies, lookup tables are created to store the optimal switching angles. These lookup tables are optimized to achieve a trade‐off between torque ripple minimization and efficiency maximization. Experimental results show that the DATC strategy presents a lower torque ripple than the DPC method over the entire speed range. In contrast, DPC delivers superior efficiency for low and medium speeds.

In this work is considered the connection of a photovoltaics (PV) solar plant to the main grid through a Direct Current (DC) MicroGrid and a hybrid storage system, composed of a battery and a supercapacitor, in order to satisfy constraints of grid connection (the so-called Grid-Codes). The objective, and main contribution of this paper, is to stabilize the DC MicroGrid voltage in spite of large variations in production and consumption, using a nonlinear hierarchical easy-to-implement control strategy. Here is presented the MicroGrid's control design based on detailed models of the photovoltaic energy sources and the storage systems. Such DC grids may present an unstable behavior caused by the PV's intermittent output power, by switching ripples from the power converters and their power electronics, and oscillatory currents produced by some types of loads. Therefore, the system is subject to both fast and slow variations, and its stabilization is based on different technologies of storage, such as battery and supercapacitor, and control algorithms designed thanks to the use of time-scale separation between different components of the storage systems. The obtained nonlinear results are stronger than current linear controllers, allowing to keep operating margins around the voltage reference. At the same time, in this work, insights from power systems practice have been used, aiming to obtain a very simple and easy-to-implement control scheme. Detailed simulation results are provided to illustrate the behavior and effectiveness of the proposed stabilization technique. [ABSTRACT FROM AUTHOR]

Abstract As the grid‐connected interface device of wind and photovoltaic power generation, the voltage source converter (VSC) must pass the low voltage ride‐through (LVRT) test. However, existing literature demonstrates that under weak grid conditions, there is a possibility of severe fluctuations in the terminal voltage of VSC during transiting from the pre‐sag normal operation mode to the LVRT mode. Unfortunately, it will make VSC frequently enter and exit LVRT mode. In order to address the tricky problem of transient instability of VSC riding‐through severe grid voltage sag under the weak grid, in this paper, the full‐order large‐signal model of VSC is established first. Then, based on the established model, the analysis indicates VSC will face the risk of losing stability under the weak grid during LVRT due to current transients. By studying the impacts of low short circuit ratio (SCR) on the basin of attraction of the post‐sag equilibrium point, the intrinsic mechanism of VSC losing stability under weak grid conditions is revealed. Moreover, considering that the transient stability is related to the current control, the stability‐enhanced LVRT control ensuring both small‐signal stability and transient stability of VSC during LVRT is proposed. Finally, the correctness of the above theoretical analysis is verified by real‐time simulation

This study focuses on analyzing the robust stability regions and robustness margin of a time‐delayed load frequency control (LFC) system with Electric Vehicles (EVs) using the Kharitonov Theorem. Communication time delays in LFC systems can jeopardize stability and reliability, leading to suboptimal controller performance. Integrating EVs into LFC systems enhances dynamical stability but introduces additional complexity. Therefore, it is crucial to employ robust analysis and controller design techniques to ensure system stability. In this study, we utilize the Kharitonov Theorem to determine the robust stability regions and stability boundaries in the parameter plane of the Proportional‐Integral (PI) controller. By considering communication time delays and parametric uncertainties in the LFC system with EVs (LFC‐EVs), the robust PI controller gains using these methods are efficiently computed. To evaluate the performance of the theoretically computed robust controller parameters, time‐domain simulations are conducted. [ABSTRACT FROM AUTHOR]

Renewable energy generation cannot be consistently predicted or controlled. Therefore, it is currently not widely used in the electricity market, which requires dependable production. In this study, reliability‐ and variance‐based controls of energy storage strategies are proposed to utilize renewable energy as a steady contributor to the electricity market. For reliability‐based control, photovoltaic (PV) generation is assumed to be registered in the power generation plan. PV generation yields a reliable output using energy storage units to compensate for PV prediction errors. We also propose a runtime state‐of‐charge management method for sustainable operations. With variance‐based controls, changes in rapid power generation are limited through ramp rate control. This study introduces new reliability and variance indices as indicators for evaluating these strategies. The reliability index quantifies the degree to which the actual generation realizes the plan, and the variance index quantifies the degree of power change. The two strategies are verified based on simulations and experiments. The reliability index improved by 3.1 times on average over 21 days at a real power plant. [ABSTRACT FROM AUTHOR]

This research proposes a cost‐efficient microinverter. The proposed microinverter can eliminate the leakage current using common‐ground configuration. It uses three switches and only one of them operates at high frequency. In addition, a passive lossless snubber is applied to limit voltage stress and provide soft‐switching performance for the high‐frequency switch. A pair of coupled inductors is used to provide higher voltage gain which makes it possible to keep the operating duty cycle in the normal range and makes the proposed inverter suitable for AC module application. The input current of the proposed microinverter is continuous which reduces the loss of the input capacitor by high‐frequency current component reduction. The operating principle of the proposed inverter is described in both positive and negative current modes. In positive current mode, the proposed microinverter works similar to SEPIC converter and in negative current mode its performance is similar to CUK converter. The dynamic behavior of the proposed microinverter is analyzed through simulation and a simple PI controller is designed to accommodate the worst case. Theoretical loss analysis is applied and finally the results of this research are compared with other researches. The performance of the proposed inverter is justified by simulation and practical results of a 300‐watts prototype. [ABSTRACT FROM AUTHOR]

A model-free deep reinforcement learning (DRL) method is proposed in this article to maximize the total power generation of wind farms through the combination of induction control and yaw control. Specifically, a novel double-network (DN)-based DRL approach is designed to generate control policies for thrust coefficients and yaw angles simultaneously and separately. Two sets of critic-actor networks are constructed to this end. They are linked by a central power-related reward, providing a coordinated control structure while inheriting the critic-actor mechanism's advantages. Compared with conventional DRL methods, the proposed DN-based DRL strategy can adapt to the distinctive and incompatible features of different control inputs, guaranteeing a reliable training process and ensuring superior performance. Also, the prioritized experience replay strategy is utilized to improve the training efficiency of deep neural networks. Simulation tests based on a dynamic wind farm simulator show that the proposed method can significantly increase the power generation for wind farms with different layouts. [ABSTRACT FROM AUTHOR]

In this work is considered the connection of a photovoltaics (PV) solar plant to the main grid through a Direct Current (DC) MicroGrid and a hybrid storage system, composed of a battery and a supercapacitor, in order to satisfy constraints of grid connection (the so-called Grid-Codes). The objective, and main contribution of this paper, is to stabilize the DC MicroGrid voltage in spite of large variations in production and consumption, using a nonlinear hierarchical easy-to-implement control strategy. Here is presented the MicroGrid’s control design based on detailed models of the photovoltaic energy sources and the storage systems. Such DC grids may present an unstable behavior caused by the PV’s intermittent output power, by switching ripples from the power converters and their power electronics, and oscillatory currents produced by some types of loads. Therefore, the system is subject to both fast and slow variations, and its stabilization is based on different technologies of storage, such as battery and supercapacitor, and control algorithms designed thanks to the use of time-scale separation between different components of the storage systems. The obtained nonlinear results are stronger than current linear controllers, allowing to keep operating margins around the voltage reference. At the same time, in this work, insights from power systems practice have been used, aiming to obtain a very simple and easy-to-implement control scheme. Detailed simulation results are provided to illustrate the behavior and effectiveness of the proposed stabilization technique.