Search Results (73)

The rapid transition toward a converter-dominated power system, driven by high penetration of inverter-based resources (IBRs), the explosive growth of artificial intelligence (AI) technologies, and large power electronic loads, is fundamentally altering grid dynamics and exposing critical limitations in conventional stability, protection, and planning frameworks. Traditional metrics, such as the short-circuit ratio (SCR), have been shown to be insufficient for capturing impedance interactions, control coupling, and multi-timescale dynamics in such systems. This paper develops a unified, control-aware, and impedance-based modeling framework that accurately represents both grid-following and grid-forming behaviors. It highlights the increasingly active role of large-scale loads as grid-interactive resources with significant impacts on frequency and voltage stability, particularly in weak grids. In addition, battery energy storage systems (BESSs) are identified as a key enabler for providing fast dynamic support and mitigating variability across multiple timescales. A hierarchical assessment methodology combining system-strength screening, impedance-based stability analysis, Nyquist evaluation, and EMT-oriented validation is proposed to bridge conventional planning studies and converter-dominated system assessment. Key findings demonstrate that the reliable operation of future grids requires moving beyond steady-state and phasor-domain assumptions toward EMT-based validation, adaptive protection schemes, and coordinated grid-forming control strategies. The study further emphasizes the need for harmonized, performance-based grid codes to ensure the consistent integration of both generation and large loads. Overall, this work provides a comprehensive framework for the modeling, analysis, and control of inverter-dominated power systems, addressing critical gaps in current methodologies and supporting the secure evolution of modern power grids. Full article

Recently, a new stability classification including the frequency, voltage, power angle, and impedance angle stability has been proposed. However, instability coupling among the voltage, power angle, and impedance angle may occur. Previous studies have investigated the coupling between the voltage and power angle. Nevertheless, system instability may also involve the voltage magnitude, power angle, and impedance angle. Dominant instability factor identification remains a research gap. Consequently, this paper proposes an Apparent Power Phasor Trajectory (APPT)-based identification method. Different from coupling analyses that mainly describe interaction relationships or stability boundaries, the APPT constructs comparable trajectory distance indicators in a unified apparent power phasor framework. Based on a two-node equivalent model of a grid-forming inverter, APPT sensitivity relationships and trajectory distance indicators are formulated under a unified metric. Numerical studies show that the proposed method identifies the dominant instability factor in representative scenarios. In the dynamic Kundur case, the overall consistency ratio reaches 95.01%. Simulation-based checks give accuracy values ranging from 97.07% in the reference setting to 90.94% under synchronization mismatch. Together with the IEEE 39 bus case, these results indicate that the APPT provides an interpretable basis for dominant instability factor identification in new power systems. Full article

The increasing penetration of inverter-based renewable energy sources has significantly reduced system inertia, leading to faster frequency deviations in low-inertia power systems. This paper proposes an asynchronous distributed model predictive control (AD-MPC) strategy to coordinate flywheel energy storage systems (FESSs) and battery energy storage systems (BESSs) for enhanced frequency stability in low-inertia power grids. A modified IEEE 39-bus system integrating a 3 MW wind energy conversion system (WECS), a 2 MW PV solar unit, and an electric vehicle (EV) load emulator unit was simulated to evaluate the system performance of the controller under a 30% increase in load disturbance. The results show that the coordinated FESS–BESS operation using the proposed AD-MPC controller achieves faster frequency recovery and reduces frequency deviation by 4% compared to single storage configurations. The proposed approach demonstrates that the high-speed FESS can provide a rapid inertial response, while the BESS delivers primary frequency support, offering a promising solution for maintaining dynamic stability in future renewable-dominated power systems. Full article

The increasing penetration of renewable energy sources in inverter-dominated microgrids introduces significant challenges for maintaining voltage and frequency stability under weak-grid and dynamically varying operating conditions. Conventional inverter control strategies, including droop control and virtual synchronous machine (VSM) methods, often exhibit limited adaptability and degraded transient performance under renewable intermittency and uncertain load variations. This paper proposes a physics-informed neural-network (PINN)-based supervisory framework for real-time grid-forming inverter control. The proposed approach embeds swing-equation dynamics, Kirchhoff-based electrical constraints, and stability-aware objectives directly into the neural-network optimization process to improve physical consistency, robustness, and operational reliability. The controller is trained offline and deployed for low-latency online inference on an NVIDIA Jetson AGX Xavier embedded platform. Simulation and hardware-in-the-loop validation results demonstrate improved transient stability, reduced frequency deviation, enhanced voltage regulation, and superior robustness compared with conventional droop, VSM, and purely data-driven neural-network controllers. The proposed framework achieved an average inference latency of approximately 0.7 ms while maintaining stable operation under renewable intermittency, load disturbances, and weak-grid conditions. The results demonstrate the potential of physics-informed machine learning for supervisory real-time control of inverter-dominated microgrids and intelligent renewable energy systems. Full article

AC microgrids with high penetration of inverter-based distributed energy resources (IBDERs) introduce major protection challenges due to reduced fault current levels, bidirectional power flows, and control-dependent fault behavior. Under these conditions, short-circuit current calculation and relay protection coordination become tightly coupled, since inaccurate fault modeling directly degrades relay sensitivity and selectivity. This review presents a protection-oriented assessment of state-of-the-art short-circuit calculation and relay protection strategies for AC microgrids. The analysis shows that conventional IEC-based fault models and static overcurrent protection schemes are insufficient for inverter-dominated networks. Generalized Δ-circuit–based modeling framework is identified as the most suitable foundation for microgrid fault analysis, as they enable inverter-aware phasor-domain representation and support both grid-connected and islanded operation. In addition, adaptive relay coordination approaches that incorporate time-varying IBDER participation and fault ride-through behavior demonstrate improved coordination robustness compared to conventional fixed settings, although their practical deployment remains constrained by network topology and communication requirements. Simulation results obtained on a representative microgrid case study confirm that the combined application of protection-oriented short-circuit modeling and adaptive relay coordination significantly improves fault detection reliability and coordination performance. The findings highlight the necessity of jointly addressing fault modeling and protection design to ensure reliable operation of inverter-dominated AC microgrids. Full article

Hybridizing concentrating solar power (CSP) with photovoltaics (PV) offers a pathway to combine low-cost daytime generation with dispatchable nighttime supply. This study compares two CSP–PV hybridization concepts for Midelt, Morocco, under a common tender-style design framework: (i) a co-located configuration in which PV and CSP interact at the grid level and (ii) an EH-integrated configuration in which an electric heater (EH) uses PV electricity to heat molten salt in a topping cycle. The main contribution of this study lies in the two-stage optimization workflow, in which leading candidates are selectively re-simulated at higher temporal resolution. This workflow is applied to a common design framework that compares EH-integrated and co-located concepts while considering multiple PV technologies and a broad set of interdependent sizing variables. A surrogate-assisted genetic algorithm evaluates more than 200,000 candidate designs across PV technology, inverter size, TES capacity, EH capacity, and battery energy storage system (BESS) size. The optimization minimizes the levelized cost of energy (LCOE) subject to a $200 {\mathrm{MW}}_{\mathrm{el}}$ export limit, a CAPEX ceiling, and a nighttime-delivery constraint of ${\mathrm{CF}}_{\mathrm{night}}\ge 39\%$. Candidate designs are screened at 600 s and selectively re-simulated at 120 s, showing that temporal refinement affects not only KPI values but also candidate feasibility, final ranking, and preferred component sizing. The lowest-LCOE solution is the EH-integrated bifacial configuration, achieving 64.5% overall capacity factor, ${\mathrm{CF}}_{\mathrm{night}}=39.1\%$, less than 0.1% curtailment, a specific CAPEX of $4698/kW, and an LCOE of 7.29 ¢/kWh. Pareto-front and parameter-trend analyses further show that stricter nighttime-delivery targets shift the dominant sizing levers and define a neighborhood of near-optimal solutions rather than a single fixed design. Full article

The energy transition is rapidly increasing the penetration of inverter-based resources (IBRs), thereby reducing the share of conventional directly grid-connected synchronous generation in modern power systems. In scenarios with very high shares of IBRs, potentially reaching 100% inverter-based operation, key features that have traditionally guaranteed power system stability and security, such as inertia, short circuit strength, fault response, and damping of oscillations, are significantly changing. This review paper examines the main challenges of operating and planning power systems with a high penetration of inverter-based resources. These challenges are grouped into three main areas: (i) technical issues, including frequency and voltage stability, system strength, fault behavior, control interactions and oscillations; (ii) regulatory issues, such as the evolution of grid codes, ride-through requirements, grid-forming specifications and testing, compliance assessment, and model validation; and (iii) market issues, focusing on how non energy services, like synthetic inertia, damping, voltage support, and stability services, are defined, measured, and procured. The paper discusses the compromises between system performance, implementation costs, and overall system robustness, relying on lessons learned from existing specifications and international standards. Finally, it outlines key research needs and provides recommendations for developing coherent technical requirements and market mechanisms to support the reliable operation of inverter-dominated power systems. Full article

To address the key problems of low-frequency oscillation and insufficient regulation accuracy at the Point of Common Coupling (PCC) in hydro–wind–photovoltaic hybrid systems, which are caused by the randomness of wind and photovoltaic output, the water-hammer effect of hydropower units, and multi-source power coupling, a joint control strategy based on Fractional-Order Proportional Integral Derivative (FOPID) and Co-evolutionary Multi-objective Particle Swarm Optimization (CMOPSO) is proposed. First, a small-signal transfer function model of the system covering photovoltaic inverters, doubly fed induction generators (DFIGs), hydropower units and voltage-source converter-based high-voltage direct current (VSC-HVDC) converter stations is established to accurately characterize the water-hammer effect and multi-source dynamic coupling characteristics. Second, a Caputo-type FOPID controller is designed. Compared with traditional integer-order controllers with limited tuning flexibility, the FOPID controller utilizes its five degrees of freedom to address specific multi-source coupling challenges. This precisely compensates for the non-minimum phase lag caused by the water-hammer effect in hydropower units via the fractional derivative link, and effectively smooths the impact of stochastic wind–solar fluctuations on PCC voltage through the memory characteristics of the fractional integral link. This multi-parameter regulation mechanism prevents a trade-off between response speed and overshoot suppression, achieving effective decoupling of complex multi-source dynamic interactions. Third, a dual-objective optimization framework with the Integral of Time-weighted Absolute Error (ITAE) and Oscillatory Disturbance Risk Index (ODRI) as the objectives is constructed. The multi-population co-evolution mechanism of the CMOPSO algorithm is adopted to solve the Pareto-optimal solution set, realizing the coordinated optimization of dynamic response accuracy and oscillation instability risk. Finally, comparative simulations are carried out on the Simulink platform with traditional PI/FOPI controllers and optimization algorithms such as Multi-objective Particle Swarm Optimization based on the Decomposition/Simple Indicator-Based Evolutionary Algorithm (MPSOD/SIBEA). The results show that the proposed strategy can effectively suppress low-frequency oscillations in the range of 0~30 Hz. Compared with the traditional PI controller, the PCC voltage overshoot is reduced by more than 40%, the oscillation decay time is shortened by 33%, the ITAE and ODRI indices are decreased by 12.58% and 2.47%, respectively, and the stability of DC bus voltage is significantly improved. Its robustness and comprehensive control performance are superior to existing methods, providing an efficient and stable control scheme for power electronics-dominated complex new energy grid-connected systems. Full article

Medium-voltage (MV) networks are increasingly relying on grid-forming inverter-based resources (IBRs) due to the worldwide transition towards renewable energy sources. This transformation poses considerable challenges for traditional protection schemes that were initially developed for systems powered by inertia-based generation. Key challenges include the low and controlled contributions of fault current, two-way power flows, diminished system inertia, and swiftly changing transient behaviors. These elements weaken the effectiveness of standard protection methods such as overcurrent, distance, and differential protection schemes. A critical review of recent advancements in adaptive protection schemes, impedance-based techniques, virtual synchronous machines, and enhancements in inverter control is provided. However, despite these advancements, current solutions frequently lack validation in real-world scenarios, encounter difficulties in detecting high-impedance faults, and face scalability issues. There remains a demand for protection strategies that are resilient, coordinated, and specifically designed to address the distinct dynamics of MV systems dominated by grid-forming inverters. Full article

The rapid integration of distributed solar photovoltaic (PV) generation is reshaping low-voltage distribution grids (LVDGs), creating voltage rise, reverse power flow, and congestion challenges for distribution system operators (DSOs). Flexibility in generation and demand, broadly understood as the capability to adjust generation or consumption in response to variability and uncertainty in net load, is increasingly central to cost-effective grid operation under high PV penetration. This review examines flexibility and controllability options in LVDGs, focusing on voltage regulation methods, supply- and demand-side flexibility resources, and market-based coordination mechanisms. The Norwegian Regulation on Quality of Supply (FoL) provides the regulatory context: it enforces 1 min average voltage compliance, stricter than the 10 min averaging window of EN 50160, making short-duration voltage excursions operationally significant and directly influencing the trade-off between curtailment, grid reinforcement, and local flexibility measures. Inverter-based active–reactive power control emerges as the most cost-effective overvoltage mitigation option, complemented by local battery energy storage systems (BESS) and demand response for congestion relief and energy shifting. Key gaps include limited LV observability, insufficient application of quasi-static time series (QSTS) assessment in planning, and underdeveloped DSO-aggregator coordination frameworks. Combined inverter control, feeder-end storage, and demand-side flexibility can defer costly reinforcements, particularly in rural 230 V IT feeders where voltage constraints dominate. Full article

The proliferation of renewable energy resources has brought numerous challenges to conventional power systems, as grid integration is predominantly achieved through inverter-interfaced technologies such as photovoltaic (PV) plants and Type-IV wind turbines. Unlike synchronous generators (SGs), inverter-based resources (IBRs) exhibit fundamentally different fault behavior by limiting fault current magnitudes, typically within 1.0–1.2 per unit. Furthermore, the phase angle and sequence composition of the injected fault current are largely dictated by the inverter control strategy rather than by the network impedance. Consequently, distance protection schemes developed under assumptions of system homogeneity, a fixed source-to-impedance ratio (SIR), high fault current contribution, and large inertia may exhibit unreliable performance in inverter-dominated power networks. In this work, the influence of IBRs on key distance protection elements, such as starting elements, fault classification techniques, and impedance calculation with or without inter-feed, is reviewed and evaluated using simulations in PSCAD 5.0 software. Further, reduced grid inertia introduces operational limitations in power swing blocking (PSB) schemes, which are discussed in this paper. This work presents an overview of IBR fault responses and critically summarizes prior work on distance protection in IBR-dominated grids, highlighting key challenges, probable solutions, and the current research status to enhance understanding for further research. Full article

Rapid urbanization and agricultural expansion in arid regions have profoundly altered carbon cycles and landscape stability. Focusing on the Hexi Corridor, China, this study integrates multi-source geospatial data (1990–2020) to analyze the spatiotemporal evolution and driving factors of land-use carbon emissions (LUCE) and landscape ecological risks (LER). By integrating carbon accounting, LER assessment, bivariate spatial autocorrelation, and the Optimal Parameter Geographic Detector (OPGD), we quantify the intricate relationship between carbon dynamics and landscape integrity. Results indicate a transformative pattern of anthropogenic expansion and natural contraction, with a 2315.49 km² net loss of unused land. Net carbon emissions surged 4.6-fold, while forest and grassland sinks exhibited a significant “lock-in effect” due to fragile ecological foundations. Simultaneously, LER followed an “inverted U-shaped” trajectory; the refined 5 × 5 km grid scale revealed a significant drop in high-risk areas from 44.65% to 10.96% following ecological restoration. Spatial analysis reveals a significant “spatial mismatch” between LUCE and LER, with oases manifesting “high carbon–low risk” clustering. Driver detection confirms a driving asymmetry. LUCE is dominated by anthropogenic factors (nighttime light, q > 0.90), whereas LER is profoundly constrained by natural backgrounds. Future governance must shift toward a collaborative system centered on source-based emission control and precise regional management to synergize low-carbon transition with landscape security. Full article

Annual energy yield alone cannot fully characterize photovoltaic (PV) system performance, because similar yearly totals may conceal substantial operational differences under varying environmental conditions. This study presents a statistical comparison of co-located fixed-tilt and single-axis tracking PV arrays operating in an 11.9 kWp grid-connected plant in Malatya, Türkiye (38.389° N, 38.426° E). Both systems consisted of a total of thirty-six 330 W monocrystalline modules—eighteen connected in series for the single-axis tracking subsystem and eighteen for the fixed-tilt subsystem—all interfaced to a single Huawei SUN2000 inverter and operated under identical climatic exposure. Seasonal analysis showed that tracking benefit strongly depended on radiation availability. During winter, daily production was similar, and the fixed configuration occasionally generated slightly higher energy (January: 28.43 vs. 27.65 kWh; December: 23.55 vs. 20.88 kWh). In summer, tracking produced significantly higher output (113.89 vs. 77.30 kWh in July), corresponding to approximately 47% improvement, while differences in spring and autumn remained below 6%. Statistical indicators revealed strong seasonal variability. The coefficient of variation ranged from 0.61 to 0.68 in winter and decreased to 0.06 to 0.12 in summer. Percentile analysis showed similar lower production limits but higher upper production thresholds for tracking (July P90 ≈ 121 vs. 81 kWh). Tracking gain increased with irradiance and decreased under humid and rainy conditions dominated by diffuse radiation. The results indicate that tracking alters the temporal distribution and probability characteristics of PV generation rather than providing a constant annual gain. Integrating statistical metrics with meteorological parameters enables a more representative performance evaluation than annual yield alone. Full article

Conventional fault analysis and calculation methods developed for synchronous-generator-dominated power systems exhibit limited applicability to distribution networks with high penetration of distributed generation (DG). These methods cannot provide a reliable theoretical basis for fault characteristic analysis or protection coordination. Existing studies on this scenario have primarily focused on the integration of grid-following (GFL) inverter-based resources (IBRs). By contrast, research on the integration of grid-forming (GFM) IBRs—particularly the virtual synchronous generator (VSG), which enables stable and sustainable utilization of renewable energy resources as synchronous generators—remains significantly inadequate. Therefore, this paper introduces a concise fault analysis and calculation method tailored to distribution networks with VSG-type DGs. First, the control strategy of the VSG-type DGs is examined, and the active-power response characteristics of VSG-type DGs are analyzed for faults in distribution networks. Equivalent models of a typical distribution network with VSG-type DGs are then established for symmetrical and asymmetrical faults. Subsequently, leveraging the active power–frequency and reactive power–voltage dependencies, a fault calculation method for distribution networks is proposed and its generality is examined. The method is convenient to implement and computationally efficient. It requires no detailed information on internal PI controller parameters or time constants of the control loops. PSCAD/EMTDC simulations are performed to verify the high accuracy and suitability of the proposed method for multi-DG scenarios, which facilitates the integration of VSG-type DGs in distribution networks. Full article

This study investigates the impact of monitoring infrastructure characteristics (specifically sensor penetration and measurement accuracy) on the effectiveness of voltage regulation and congestion management within distribution networks. As distribution system operators transition toward active management, the integration of Distributed renewable Generation (DG) and demand response introduces significant physical and cyber-physical uncertainties. To address these challenges, a smart grid service framework has been employed to optimize flexibility resources from aggregated users and DG inverters through a genetic algorithm. The framework was tested on the IEEE European Low Voltage Test Feeder across various scenarios defined by distributed monitoring systems’ penetration and their measurement accuracy. Results show that sensor penetration has a dominant impact: increasing monitoring coverage from 0% to 100% raises the percentage of cases with fewer than one residual congestion from 46.2% to 91.9% (sensors with an accuracy class of 2%), reaching 97.9% with an accuracy class of 0.5%, while voltage violations are eliminated under full monitoring. These findings suggest that widespread sensor deployment, with a suitable measurement accuracy, is a fundamental prerequisite for reliable and efficient smart grid operation. Full article