As the global energy landscape shifts toward sustainability, microgrids incorporating Photovoltaic (PV) generation and Battery Energy Storage Systems (BESS) are becoming essential in commercial and industrial facilities. This research tackles the challenge of maintaining uninterrupted power supply to sensitive loads when grid disturbances occur. We propose a novel loss-of-mains detection method capable of identifying grid faults in under 3 milliseconds—well within the 10-millisecond threshold required for critical equipment to ride through the transition without disruption. Building on this fast detection, we develop inverter control strategies that enable a smooth transfer from grid-following to grid-forming operation while limiting transient overvoltage and overcurrent. Additionally, a coordinated operating sequence is introduced to ensure grid code compliance and proper management of distributed energy resources throughout the islanding process. The complete approach is validated experimentally using a dedicated prototype and a Power-Hardware-in-the-Loop (P-HIL) microgrid demonstrator, confirming its effectiveness and advancing the technology readiness level toward real-world deployment.

The growing integration of renewable energy sources and the privatization of energy systems are driving the restructuring of Power Distribution Networks (PDNs). Future PDNs are expected to evolve into distributed structures supported by Multi-Agent Systems (MASs). However, the autonomous actions of local agents create challenges for coordination, grid integration, and operational reliability, highlighting the need for advanced energy management solutions. This paper proposes a Peer-to-Peer-to-Grid (P2P2G) trading framework for efficient energy management in PDNs with autonomous agents. In the proposed framework, agents reduce operational costs by participating in P2P and P2G trading while respecting network operational issues. To address network constraints, Transactive Control (TC) signals and Network Charges (NCs) are introduced based on each agent’s contribution, enabling fair allocation of costs associated with congestion power losses through a transaction-tracing method. Furthermore, to preserve agents’ privacy and ensure scalability, a decentralized market-clearing process is developed using the Alternating Direction Method of Multipliers (ADMM). The effectiveness of the proposed approach is demonstrated through numerical studies conducted on modified IEEE 15-bus and 37-bus systems featuring various types of agents. Finally, results confirm that the framework not only respects agents’ preferences but also enhances PDN operation by alleviating congestion, reducing losses, and improving overall system efficiency.

The transition from fossil-fuel generation to a zero-carbon power system is driving rapid growth in distributed energy resources (DERs). These new resources create opportunities to provide flexibility to the Transmission System Operator (TSO). To enable secure use of this flexibility by the Transmission System Operator (TSO), the Distribution System Operator (DSO) must expose, at the point of common coupling, a compact and accurate description of flexible active/reactive power exchanges on PQ plane. This paper presents an optimization-based framework to construct the flexibility operation region for TSO–DSO coordination. The approach utilizes DistFlow model and incorporates with realistic operational constraints, including DERs characteristics, line current and voltage limits, formulated as a second-order cone optimal power flow (SOCP-OPF) problem. Boundary points of the flexibility region are determined through a direction-scan algorithm, and a convex hull is subsequently constructed to map the feasible flexibility boundary. The proposed framework is demonstrated on the IEEE 33-bus test system under different DER scenarios, with results highlighting its accuracy and computational efficiency.

The penetration of Inverter-Based Resources (IBRs) into the grid increased significantly in recent years. This poses a significant challenge to distance protection (DP). In fact, DP has been designed based on the behaviour of synchronous generator (SG) during faults. The behaviours of SGs and IBRs during faults are very different. Today, DP is used to protect transmission lines interconnected with IBRs. RTE, the French TSO, facing an increasing integration of IBRs is questioning its interconnection specifications in terms of selectivity support. This paper presents an analysis of the phase currents injected by a wind turbine using coupled sequence control (CSC) and decoupled sequence control (DSC) and their potential impact on the DP, in particular on phase selection. This study is carried out by using the EPRI benchmark FSC available in EMTP-RV. The results show that with CSC control, a single-phase-to-earth fault with low fault resistance, behaves as a phase-to-phase fault. Conversely, a phase-to-phase fault behaves as a single phase-to-earth fault. This can lead to incorrect selection of the faulted phase. The results also show that with DSC control, there is a slight improvement in the injection of negative sequence current compared to CSC control.

This article explores the capability of Power Oscillation Damping (POD) control of Inverter-Based Resources (IBRs) installed in the distribution network to provide damping to the upstream transmission network. The studied system is the IEEE 9 bus benchmark, to which IBRs have been added at the consumption buses. Modal analyses and non-linear time-domain simulations have been carried out with DIgSILENT PowerFactory. First, the characterization of the system oscillatory modes derived from the participation factors is presented. Next, the impact of the POD control is compared according to the IBR location, through modal analysis. After proving the lack of adverse interaction among the three POD control locations, and with the PSS control, the behavior of the system including all POD controls has been assessed through non-linear time domain simulation, considering a torque step increase of one of the synchronous generators. The provided damping is illustrated with the power flows through the system lines. The reactive power response of the IBRs, as well as the consequences regarding system voltages have been discussed. In light of the results, a systematic addition of POD control of distributed IBRs is considered advantageous for the transmission system.

Emergence of the prosuming phenomenon inspired by environmental and financial incentives has led to a paradigm shift in energy markets and operational conditions of power distribution networks. As a result of this transition, Peer-to-Grid (P2G) and Peer-to-Peer (P2P) energy markets have received a lot of attention in recent years. These markets must prioritize the facilitation of fair and efficient energy trading while considering the preferences of both parties participating in these markets as well as Distribution System Operators (DSOs). In this context, ensuring the viability of the network's physical structure is essential. Without a robust physical structure, the energy trading process and the fulfillment of the parties'commercial obligations would be disrupted due to faults. Our proposed framework involves a fault-resilient energy management system in which P2G and P2P energy transactions are re-arranged based on factors such as the electrical distance of the dynamic physical route swept by P2P and P2G transactions and energy price. The electrical distance between end-users is calculated based on the dynamic configuration of the distribution network, which is adjusted due to the removal of faults and mitigation of emergencies such as line failures. In the developed framework, to reduce the overall operational cost of the community, an energy-sharing coordinator named Market Operator (MO) would then take into account the network configuration optimized by the Network Operator (NO). The obtained framework which joins the Network Re-configuration (NR) problem and the energy transactions re-arrangement problem in a hierarchical manner, is implemented on a 22-bus distribution system to evaluate its effectiveness in decreasing power losses and operational cost of grid-connected energy communities.

In the scope of energy transition, the increasing penetration of intermittent renewable energy generation has put the electrical system against a great challenge: real-time power balance between supply and demand. In this context, heating systems stand out as one of the most decisive controllable loads in commercial buildings and residential households. Managing peak load consumption by controlling electric heaters has excellent potential in demand-side management. This paper presents a method to reduce peak load consumption using a fuzzy-logic-based real-time control of heating systems while minimizing the rebound effect. The proposed solution is evaluated based on a digital twin of a real low-voltage distribution network containing 50 houses under different conditions of desired power exchange. This technique falls within the framework of the smart grid concept in order to make load consumption more active and intelligent, thereby increasing flexibility on the demand side.

This paper presents a Power Oscillation Damping (POD) controller, inspired by traditional Power System Stabilizer (PSS), as an additional control loop for Inverter Based Resources (IBRs) controlled in grid following (GFL) mode. The major idea is the contribution of several IBRs to damp electromechanical oscillations of the power system, in order to increase the power system hosting capacity. During frequency transients, the POD modifies the reactive power reference of the GFL control. The POD has the frequency measurement as input signal, and its tuning is based on the root locus design technique. This technique relies on the modal analysis, so the damping contribution is assessed through small signal stability metrics. The test case power system is a modified version of the Western System Coordinating Council (WSCC) 9-bus benchmark, which has been analysed using the DIgSILENT PowerFactory software. The results show that the proposed controller damps the electromechanical oscillatory mode in a similar way to the PSS, increasing the hosting capacity of renewables in terms of small-signal stability.

This paper analyses the performance of a Power Oscillations Damping (POD) controller through small-signal stability analysis. The POD is installed in a photovoltaic (PV) power plant controlled in conventional grid-following (GFL) mode. During frequency transients, the POD modifies the reactive power reference of the GFL control, in order to damp electromechanical power system oscillations. The transmission power grid IEEE 9-bus benchmark has been analysed in DIgSILENT PowerFactory software. The PV plant capacity, its location in the network, and the power system operating conditions are considered. Particularly, the analysis of a few specific consumption and generation conditions shows that the electromechanical oscillatory modes of the system are more critical in case of peak load, as it happens for 100 % synchronous generation. The main results are twofold: (i) the significant contribution of the POD to damping electromechanical modes in the scenario of winter evening peak consumption, when the PV plant does not inject active power to the grid, which coincides with the most poorly damped electromechanical modes; and (ii) the lack of negative interaction between PSS and POD controllers.

Recent advancements in the 4.0-technology domain, especially in the fields of Information and Communications Technology (ICT) and Internet of Things (IoT), allow power systems to be supervised and commanded from afar in a more complex and intelligent manner. According to the Smart Grid Architecture Model (SGAM), this is made possible with data exchange by implementing protocols and data models on top of the components layer. Digital twin (DT) - a virtual copy of a physical system - has become a vital tool and more realistic than any simulation models since this technology takes into consideration communication latency for real-time applications. Integrating renewable energy sources, being intermittent in nature while increasing grid's flexibility, has introduced a voltage-stability threat to the network. For this purpose, the authors showcase a solution to deal with voltage control using artificial-intelligence-based (AI) optimizations. The technique to synchronize and exchange data between the grid and its digital twin is also demonstrated in the process. The proposed method is validated and performed based on a real low-voltage distribution network located in France.

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Control models of power grids are rapidly evolving. New control models are adopting hierarchical distributed strategies in which local energy communities are involved in the decision-making process. In such control models, local energy communities are able, through demand response strategies, to provide aggregated flexibility services to the grid. However, this requires the implementation of available flexibility computation strategies capable of maximizing flexibility when required, while considering local preferences. This paper proposes an advanced local flexibility computation strategy adapted for hierarchical distributed control models. The strategy is applied to a proposed grid control model, at a distribution level, referred to as 'cloud -edge'.

This editorial summarises the papers selected for publication in the Special Issue on Advances in Volt/Var Control for Active Distribution Networks with High-Level Intermittent Renewable Energy Resources. The Special Issue contains 13 high-quality papers which are classified into novel models of VVC (3 papers), design of VVC framework (3 papers), data-driven VVC (5 papers), and VVC in special power systems (2 papers). The Special Issue can provide advanced VVC methods with invaluable insights to enhance renewable energy utilisation efficiency, power loss reduction for public infrastructure, and guarantee high power quality for end-users.

In the context of increasingly necessary energy transition, the precise modeling of profiles for low-voltage (LV) network consumers is crucial to enhance hosting capacity. Typically, load curves for these consumers are estimated through measurement campaigns conducted by Distribution System Operators (DSOs) for a representative subset of customers or through the aggregation of load curves from household appliances within a residence. With the instrumentation of smart meters becoming more common, a new approach to modeling profiles for residential customers is proposed to make the most of the measurements from these meters. The disaggregation model estimates the load profile of customers on a low-voltage network by disaggregating the load curve measured at the secondary substation level. By utilizing only the maximum power measured by Linky smart meters, along with the load curve of the secondary substation, this model can estimate the daily profile of customers. For 48 secondary substations in our dataset, the model obtained an average symmetric mean average percentage error (SMAPE) error of 4.91% in reconstructing the load curve of the secondary substation from the curves disaggregated by the model. This methodology can allow for an estimation of the daily consumption behaviors of the low-voltage customers. In this way, we can safely envision solutions that enhance the grid hosting capacity.

The distribution systems may experience damages initiated by various events, which could result in extended network failures. These failures threaten the reliability of distribution systems and negatively impact prosumers satisfaction, and finally cause economic losses. Respectively, one of the most important issues of future distribution systems is managing failures in the presence of energy-trading plans in which prosumers participate to gain profit. In order to effectively reduce the economic losses caused by system outages, this paper proposes a two-stage Service Restoration (SR) model for prosumer-based distribution systems. The proposed model coordinates prosumers through switching and network reconfiguring (NR) in the first stage and then reschedules them and revises energy trading adjustments in the second stage. The objective functions defined in each stage are modeled as a MILP-based optimization problem. The developed simulation is conducted on the IEEE 33-bus test distribution system to evaluate the efficacy of the proposed strategy, where the results show the benefit of the developed model in improving the reliability of the system.

Grid forming function in Battery Energy Storage System is a key component for ensuring reliable power supply of a microgrid. The proposed contribution is dealing with the design of dual loop proportional resonant controller in abc stationary frame for grid forming inverter. Using this new control structure, we bring flexibility to control each phase independently. The control structure is validated with laboratory experiment using 4 kW inverters and DSPACE Power Hardware in the Loop (P-HIL).

The recent advancements of 4.0 technologies, especially Information and Communications Technology (ICT) and Internet of Things (IoT), have facilitated power systems to be remotely supervised and controlled. In the Smart Grid Architecture Model (SGAM), communication and information layers are the first two layers to be built on top of the component layer by integrating different protocols and data models. Along with renewable energy sources, which are intermittent in nature but add up to the flexibility of the grid, voltage stability has become one of the main research topics in recent years. In this paper, the authors demonstrate the solution to synchronize and exchange data between the grid and its different components via a digital twin (DT) model for a Geographically Distributed Voltage Control (GDVC) strategy. The proposed method will then be validated and carried out based on a real low-voltage grid in the East of France named SOREA.

The development of low CO 2 equivalent emissions energy sources, like distributed generation, tends to reduce the global inertia of power systems by default. This phenomenon impacts grids stability and the main synchronous generators. In this paper, a methodology is proposed to evaluate the evolution of the synchronizing torque coefficient under the effect of this inertia reduction. The results, detailed for each machine of the IEEE 10-generator 39-bus power system, show a linear trend as a function of system inertia. The methodology to model inertia reduction as well as considering other parameters than synchronizing torque are discussed in the paper.

The development of low CO 2 equivalent emissions energy sources, like distributed generation, tends to reduce the global inertia of power systems by default. This phenomenon impacts grids' stability and the main synchronous generators. In this paper, a methodology is proposed to evaluate the evolution of the synchronizing torque coefficient under the effect of this inertia reduction. The results, detailed for each machine of the IEEE 10- generator 39-bus power system, show a linear trend as a function of system inertia. The methodology to model inertia reduction as well as considering other parameters than synchronizing torque are discussed in the paper.

The requirement for coordination of distributed energy resources in the future power system provides an incentive to move from the current high level of centralized control to a more distributed control paradigm. In this paper, an agent-based distributed optimal power flow is proposed to optimize the operation of the power system. The optimal power flow problem is built in the general consensus optimization formulation in matrix based formulation. The agent is then designed to realize the operation of the multi-agent system in the cyber-physical system. Agents have ability of collecting local measurement data, communicating with neighbor agents and implementing alternating direction method of multiplier. Each agent accesses to limited information but can give decision to solve the global problem. The performance is evaluated on the IEEE 9 bus by using a cyber Hardware-in-the-Loop platform with a cluster of hardware agents, a real-time simulator OPAL-RT and a real communication network.