Search Results (67)

The large-scale penetration of Distributed Energy Resources (DERs), the proliferation of Energy Communities, and the increasing provision of flexibility services are fundamentally transforming distribution network operation, rendering traditional Distribution Management Systems (DMSs) structurally inadequate. This paper addresses this structural gap by proposing and experimentally validating A-ISolE, a novel hybrid Artificial Intelligence (AI) architecture that natively integrates centralized and distributed intelligence within a unified DMS framework. The core scientific contribution of this work lies in the formulation and deployment of a coordinated, hierarchical AI paradigm in which cloud-level predictive and optimization modules dynamically interact with edge-level autonomous control agents. Specifically, the paper introduces: (1) an integrated forecasting state estimation pipeline with AI-enhanced grid observability; (2) intelligent fault location and optimal feeder reconfiguration algorithms embedded into operational control loops; and (3) distributed edge control strategies enabling autonomous yet coordinated microgrid stabilization. The architecture is validated on a real pilot microgrid in Sanremo (Italy). Experimental results demonstrate quantifiable gains in many parameters, substantiating the feasibility of hybrid centralized/distributed AI as a foundational paradigm for future resilient and decarbonized distribution networks. Full article

Island microgrids are highly vulnerable to extreme weather, which threatens operational stability and post-disaster recovery. To address the challenge of widespread power outages caused by typhoons, a novel coordinated framework is proposed which optimizes electric ships as mobile power sources to enhance island microgrid resilience. By integrating a hybrid wind field model with an improved wind-resistant A* algorithm, the framework synergistically optimizes dynamic scenario-aware ship routing and distribution network reconfiguration. The problem is formulated as a mixed-integer second-order cone programming (MISOCP) model. Case studies based on real-world data from Hengsha Island, Shanghai, demonstrate that the proposed dynamic routing strategy significantly outperforms static approaches. Specifically, critical load recovery rates are improved by at least 29% during the navigation-restricted phase and total load curtailment costs are reduced by 31.6%. These findings reveal this significance of integrating spatiotemporal environmental dynamics into optimization frameworks, providing a robust decision-making tool for island grid operators to maintain power supply to critical loads under evolving disaster conditions. Full article

Hybrid AC/DC microgrids (HMGs) are increasingly recognized as a solution for the transition toward future energy systems because they can combine the efficiency of DC networks with an AC system. Despite these advantages, HMGs still have challenges in protection, cybersecurity, and reliability. Conventional protection schemes often fail due to reduced fault currents and the dominance of power electronic converters in islanded or dynamically reconfigured topologies. At the same time, IEC 61850 protocols remain vulnerable to advanced cyberattacks such as Denial of Service (DoS), false data injection (FDIA), and man-in-the-middle (MITM), posing serious threats to the stability and operational security of intelligent power networks. Previous surveys have typically examined these challenges in isolation; however, this paper provides the first integrated review of HMG protection across three complementary dimensions: traditional protection schemes, cybersecurity threats, and artificial intelligence/machine learning (AI/ML)-based approaches. By analyzing more than 100 studies published between 2012 and 2024, we show that AI/ML methods in simulation environments can achieve detection accuracies of 95–98% with response times under 10 ms, while these values are case-specific and depend on the evaluation setting such as network scale, sampling configuration, noise levels, inverter control mode, and whether results are obtained in simulation, hardware in loop (HIL)/real-time digital simulator (RTDS), or field conditions. Nevertheless, the absence of standardized datasets and limited field validation remain key barriers to industrial adoption. Likewise, existing cybersecurity frameworks provide acceptable protection timing but lack resilience against emerging threats, while conventional methods underperform in clustered and islanded scenarios. Therefore, the future of HMG protection requires the integration of traditional schemes, resilient cybersecurity architectures, and explainable AI models, along with the development of benchmark datasets, hardware-in-the-loop validation, and implementation on platforms such as field-programmable gate array (FPGA) and μPMU. Full article

As renewable energy integration accelerates, the displacement of synchronous generators by inverter-based resources (IBRs) necessitates advanced grid-forming (GFM) control strategies to maintain system stability. While techniques such as Droop control, Virtual Synchronous Generator (VSG), and Dispatchable Virtual Oscillator Control (dVOC) are well-established, their comparative performance under coordinated cyber-physical stress remains underexplored. This paper presents a comprehensive Controller Hardware-in-the-Loop (CHIL) assessment of these three GFM strategies within a networked microgrid environment. Utilizing a co-simulation framework that integrates an OPAL-RT real-time simulator with the EXata CPS network emulator, we evaluate the dynamic resilience of each controller under islanded, parallel, and fault-induced reconfiguration scenarios. Experimental results demonstrate that the VSG strategy offers superior transient performance, characterized by faster settling times and enhanced fault-ride-through capabilities compared to the Droop and dVOC strategies. Furthermore, recognizing the vulnerability of connected microgrids to cyber threats, this study investigates the impact of False Data Injection (FDI) attacks on the control layer. To address this, a model-reference resilience layer is proposed and validated on a TI C2000 DSP. The results confirm that this protection mechanism effectively detects and mitigates attacks on control references and feedback measurements, ensuring stable operation despite cyber-physical disturbances. Full article

The growing incorporation of distributed energy resources (DER) in power distribution grids, although pivotal to the energy transition, increases operational variability and amplifies the exposure to disturbances that can compromise resilience and the continuity of service during contingencies. Addressing these challenges requires both a shift toward flexible distribution architectures and the adoption of advanced power electronics interfacing systems. In this setting, this paper proposes a resilience-oriented strategy for medium-voltage (MV) distribution systems and clustered hybrid AC/DC microgrids interfaced through solid-state transformers (SSTs). When a fault occurs along an MV feeder segment, the affected microgrids naturally transition to islanded operation. However, once their local generation and storage become insufficient to sustain autonomous operation, the proposed framework reconfigures the power routing within the cluster by activating an emergency low-voltage DC (LVDC) power path that bypasses the faulted MV section. This mechanism enables controlled power sharing between microgrids during prolonged MV outages, ensuring the supply of priority loads without oversizing SSTs or reinforcing existing infrastructure. Experimental validation on a reduced-scale SST prototype demonstrates stable grid-forming and grid-following operation. The reliability of the proposed scheme is supported by both steady-state and transient experimental results, confirming accurate voltage regulation, balanced sinusoidal waveforms, and low current tracking errors. All tests were conducted at a switching frequency of 50 kHz, highlighting the robustness of the proposed architecture under dynamic operation. Full article

With the increasing penetration of the distributed generation and the growing variability of loads, flexible microgrids (FMGs) require operational strategies that can adapt to seasonal changes while maintaining reliable performance. To overcome the limitations of fixed-interval partition updates, this paper proposes a threshold-triggered dynamic operation strategy for FMGs. A composite partition-updating index is formulated by integrating an operation optimization index, which reflects network loss and hybrid energy storage (HES) cost, with a seasonal load uniformity index, so that partition reconfiguration is triggered only when scenario transitions significantly deteriorate operating performance. By enhancing seasonal load uniformity across partitions, the proposed framework reflects a symmetry-oriented operation philosophy for FMGs. An HES model is further established to coordinate short-term energy storage (STES) and long-term energy storage (LTES) across multiple timescales. In conjunction with remotely controlled switches (RCSs), the proposed framework enables adaptive adjustment of FMG boundaries and source scheduling under diverse seasonal conditions. A case study on the IEEE 123-bus distribution system demonstrates that the proposed strategy effectively reduces power fluctuations and redundant switching operations, improves seasonal load uniformity, and enhances both the operational flexibility and economic efficiency of FMGs. Full article

Multilevel inverters (MLI) have become the frontier in high-power medium voltage systems because of their unique property of generating sinusoidal voltage through smaller voltage increments. Although many MLI structures have been proposed over the years, most still rely on a large number of switches, which increases complexity and conduction losses. In this work, a reconfigurable, gable-shaped multilevel inverter module, capable of operating in both symmetric and asymmetric modes, is introduced for use in AC microgrid cluster environments. The design employs five DC sources and six semiconductor devices arranged in a gable layout, which helps shorten the conduction path while also reducing the total hardware count. As a result, the inverter becomes more compact, experiences lower switching losses, and proves more suitable for grid-connected operation. In symmetric mode, the inverter delivers an 11-level output, while the asymmetric arrangement produces 19 levels. The proposed concept is examined through MATLAB/Simulink (R2023a) studies, and its practicality is verified using a Hardware-in-the-Loop setup with an integrated data-acquisition system capable of delivering 10 kW of real power and handling up to 50% overload. These results confirm the suitability of the topology for real-time grid applications. Full article

This paper proposes a local sliding mode control (SMC) strategy for frequency regulation and active power sharing in islanded microgrids (MGs). Unlike advanced strategies, either droop-based or droop-free, that rely on inter-inverter communication, the proposed method operates in a fully decentralized manner, using only measurements available at each inverter. In addition, it adopts a minimalist structure that avoids adaptive laws and consensus mechanisms, which simplifies implementation. A discontinuous control law is derived to enforce sliding dynamics on a frequency-based surface, ensuring robust behavior in the face of disturbances, such as clock drifts, sudden load variations, and topological reconfigurations. A formal Lyapunov-based analysis is conducted to establish the stability of the closed-loop system under the proposed control law. The method guarantees that steady-state frequency deviations remain bounded and predictable as a function of the controller parameters. Simulation results demonstrate that the proposed controller achieves rapid frequency convergence, equitable active power sharing, and sustained stability. Owing to its communication-free design, the proposed strategy is particularly well-suited for MGs operating in rural, isolated, or resource-constrained environments. A comparative evaluation against both conventional droop and communication-based droop-free SMC approaches further highlights the method’s strengths in terms of resilience, implementation simplicity, and practical deployability. Full article

Traditional centralized highway energy systems exhibit significant resilience shortcomings in the face of climate change mitigation requirements and increasingly frequent extreme weather events. Meanwhile, prevailing microgrid control strategies remain predominantly focused on economic optimization under normal conditions, lacking the flexibility to address dynamic risks or the interdependencies between transportation and power systems. This study proposes an adaptive, risk-driven control framework that holistically coordinates power generation infrastructures, microgrids, demand-side loads, energy storage systems, and transport dynamics through continuous risk assessment. This enables the system to dynamically shift operational priorities—from cost-efficiency in stable periods to robustness during emergencies. A multi-objective optimization model is established, integrating infrastructure resilience, operational costs, and traffic impacts. It is solved using an enhanced evolutionary algorithm that combines the non-dominated sorting genetic algorithm II with differential evolution (NSGA-II-DE). Extensive simulations under extreme weather scenarios validate the framework’s ability to autonomously reconfigure operations, achieving 92.5% renewable energy utilization under low-risk conditions while elevating critical load assurance to 98.8% under high-risk scenarios. This strategy provides both theoretical and technical guarantees for securing highway renewable energy system operations. Full article

To address the overvoltage problem in distribution networks with large-scale photovoltaic (PV) integration, this paper proposes an interactive game-based voltage optimization control strategy based on microgrid cluster partitioning. A multi-agent control architecture is constructed, including a dynamic partitioning layer, a parallel independent optimization layer, and an interactive game optimization layer. In the dynamic partitioning layer, microgrid clusters are formed considering coupling degree, voltage regulation capability, and cluster scale. In the parallel optimization layer, a network reconfiguration-based control model is established for utility-owned microgrids, and a PV active/reactive power regulation model is developed for PV microgrids, enabling independent cluster-level control. In the game optimization layer, a non-cooperative game model is formulated to coordinate voltage regulation among clusters. The effectiveness of the proposed method is demonstrated on an actual 10 kV feeder system. Full article

With the integration of a large number of flexible distributed resources, microgrids have become an important form for supporting the coordinated operation of power sources, grids, loads, and energy storage. The flexibility provided by the point of common coupling is also a crucial regulating resource in power systems. However, due to the complex network constraints within microgrids, such as voltage security and branch capacity limitations, the flexibility of distributed resources cannot be fully reflected at the point of common coupling. Moreover, the flexibility that can be provided externally by different network reconfiguration strategies shows significant differences. Therefore, this paper focuses on optimizing reconfiguration strategies to enhance grid-connected flexibility. Firstly, the representation methods of grid-connected power flexibility and voltage regulation flexibility based on aggregation are introduced. Next, a two-stage robust optimization model aimed at maximizing grid-connected power flexibility is constructed, which comprehensively considers the aggregation of distributed resource flexibility and reconfiguration constraints. The objective is to maximize the grid-connected power flexibility of the small-micro parks. In the first stage of the model, the topology of the small-micro parks is optimized, and the maximum flexibility of all distributed resources is aggregated at the PCC. In the second stage, the feasibility of the solution for the PCC flexible operation range obtained in the first stage is verified. Subsequently, based on strong duality theory and using the column-and-constraint generation algorithm, the model is effectively solved. Case studies show that the proposed method can fully exploit the flexibility of distributed resources through reconfiguration, thereby significantly enhancing the power flexibility and voltage support capability of the small-micro parks network at the PCC. Full article

In this paper, a very fast and reliable strategy for load restoration utilizing optimal distribution feeder reconfiguration (DFR) is developed. The automated network configuration switches can improve the resilience of a microgrid (MG) equipped with a centralized and coordinated energy management system (EMS). The EMS has the authority to reconfigure the distribution network to fulfil high priority loads in the entire network, at the lowest cost, while maintaining the voltage at desirable bounds. In the case of islanded operation, the EMS is responsible for serving the high priority loads, including the establishment of new MGs, if necessary. This paper discusses the main functionality of the EMS in both grid-connected and islanded operation modes of MGs. The proposed model is developed based on a mixed-integer quadratically constrained program (MIQCP), including an optimal power flow (OPF) problem to minimize the power losses in normal operation and the load shedding in islanded operation, while keeping voltage and capacity constraints. The proposed framework is implemented on a modified IEEE 33-bus test system and the results show that the model is fast and accurate enough to be utilized in real-life situations without a loss of accuracy. Full article

Reconfigurable new energy storage can effectively address the security and limitation issues associated with traditional battery energy storage. To enhance the reliability of the microgrid system and ensure power balance among generation units, this paper proposes a power coordination control strategy based on reconfigurable energy storage. First, a new microgrid system incorporating reconfigurable energy storage, photovoltaic power generation, and a supercapacitor is introduced. By leveraging the structural advantages of reconfigurable energy storage, the potential safety hazards of traditional battery energy storage can be mitigated and the reliability of the microgrid system can be improved. Second, a novel control strategy for reconfigurable energy storage, photovoltaic units, and supercapacitors is proposed. The reconfigurable energy storage achieves constant current charge/discharge control through a DC-DC converter, while the supercapacitor maintains DC bus voltage stability via another DC–DC converter. Next, the power flow relationship within the microgrid system is analyzed. The dynamic reconfiguration characteristics of the reconfigurable energy storage, combined with the high power density of the supercapacitor, enable dynamic compensation of the photovoltaic power generation unit to meet the load’s power demand. Finally, a simulation model is developed in the MATLAB/Simulink environment to compare and analyze the power compensation effects of traditional energy storage and reconfigurable energy storage. The results demonstrate that the proposed control strategy achieves constant current charge/discharge control for reconfigurable energy storage, addressing the issue of battery life degradation caused by the continuous variation in charge/discharge current when traditional energy storage compensates for photovoltaic fluctuations. Additionally, the proposed control strategy can effectively and rapidly adjust the system’s power output, mitigating power fluctuations caused by variations in photovoltaic generation and load changes in the microgrid system, thereby improving the system’s reliability and stability. Full article

In the past, providing an online and real-time response to cyber–physical attacks in large-scale power microgrids was considered a fundamental challenge by operators and managers of power distribution networks. To address this issue, an innovative framework is proposed in this paper, enabling real-time responsiveness to cyberattacks while focusing on the techno-economic energy management of large-scale power microgrids. This framework leverages the large change sensitivity (LCS) method to receive immediate updates to the system’s optimal state under disturbances, eliminating the need for the full recalculation of power flow equations. This significantly reduces computational complexity and enhances real-time adaptability compared to traditional approaches. Additionally, this framework optimizes operational points, including resource generation and network reconfiguration, by simultaneously considering technical, economic, and reliability parameters—a comprehensive integration often overlooked in recent studies. Performance evaluation on large-scale systems, such as IEEE 33-bus, 69-bus, and 118-bus networks, demonstrates that the proposed method achieves optimization in less than 2 s, ensuring superior computational efficiency, scalability, and resilience. The results highlight significant improvements over state-of-the-art methods, establishing the proposed framework as a robust solution for real-time, cost-effective, and resilient energy management in large-scale power microgrids under cyber–physical disturbances. Full article

The integration of electrolyzers and fuel cells can cause voltage fluctuations within microgrids if not properly scheduled. Therefore, controlling voltage and reactive power becomes crucial to mitigate the impact of fluctuating voltage levels, ensuring system stability and preventing damage to equipment. This paper, therefore, seeks to enhance voltage and reactive power control within reconfigurable microgrids in the presence of innovative power-to-hydrogen technologies via electrolyzers and hydrogen-to-power through fuel cells. Specifically, it focuses on the simultaneous coordination of an electrolyzer, hydrogen storage, and a fuel cell alongside on-load tap changers, smart photovoltaic inverters, renewable energy sources, diesel generators, and electric vehicle aggregation within the microgrid system. Additionally, dynamic network reconfiguration is employed to enhance microgrid flexibility and improve the overall system adaptability. Given the inherent unpredictability linked to resources, the unscented transformation method is employed to account for these uncertainties in the proposed voltage and reactive power management. Finally, the model is formulated as a convex optimization problem and is solved through GUROBI version 11, which leads to having a time-efficient model with high accuracy. To assess the effectiveness of the model, it is eventually examined on a modified 33-bus microgrid in several cases. Through the results of the under-study microgrid, the developed model is a great remedy for the simultaneous operation of diverse resources in reconfigurable microgrids with a flatter voltage profile across the microgrid. Full article