Iet Generation Transmission & Distribution最新文献

Effective pre- and post-disaster strategies are crucial for mitigating the impacts of extreme events and enhancing the resilience of networked microgrids (NMGs). However, traditional methods often fail to comprehensively and efficiently consider fault scenarios before disasters, and the inefficient challenge of addressing large-scale post-disaster recovery problems necessitate advanced computational approaches. This paper proposes a quantum-assisted resilience enhancement framework for power distribution systems with NMGs, fully accounting for potential failure risks. The main contributions include a two-stage quantum-assisted resilience enhancement framework that integrates quantum amplitude estimation (QAE) for quantifying failure risks, and generating scenarios, the quantum-encoded model establishment, and the proposed quantum surrogate absolute-value Lagrangian relaxation (Q-SAVLR) algorithm for achieving quantum-accelerated parallel optimization. Numerical tests on a modified IEEE system show that our approach reduces computation time by roughly 40%–75% relative to the classical solver, enabling faster repair resource deployment and more efficient resilience optimization for NMGs.

This paper introduces a coordinated state estimation (CSE) approach designed to achieve a unique reference solution for both transmission and distribution systems. The CSE framework additionally addresses the challenges related to balanced bus requirements within distribution system state estimation (DSSE). Specifically, the CSE method models a transmission boundary bus as a reference bus for the execution of DSSE. Furthermore, the methodology constructs a consistency check vector based on the estimated variables of the modelled reference bus, thereby ensuring the coherence of the solution for the entire power system. To manage the substantial complexity of the problem, the CSE approach employs a parallel estimation strategy. This paper validates the CSE technique through a comprehensive analysis of different power transmission and distribution system combinations. The study focuses on the IEEE 14-bus and New England 39-bus systems as transmission networks, alongside the IEEE 13-node and 37-node feeders as distribution networks. Validation is conducted using MATLAB and DIgSILENT PowerFactory software tools.

The term “hosting capacity”, in the context of power systems, was first introduced in March 2004 and has since resulted in a range of applications and research. Network operators commonly use the concept to quantify the ability of their networks to accept new production and consumption. Academic research on hosting capacity took off seriously after 2010 and has resulted in thousands of publications. This paper presents a brief history of the early years of hosting capacity studies, gives an overview of the status of both applications and research, summarises the different methods and types of studies, and correlates all that with the underlying fundamental principles of the hosting capacity concept, as it was introduced in 2004. The main focus of this paper is to review and relate these methods and studies to the fundamental principles. Having a clear understanding of these fundamental principles enables a wide range of applications for hosting capacity studies with detailed methods and models. However, it also requires transparency to ensure a coherent analysis, correct interpretation of the results, and an open discussion between stakeholders. With research on hosting capacity, it is important to refer to the fundamental principles; with applications, it is important to maintain transparency and objectivity.

The rapid integration of renewable energy generation has significantly reduced the flexibility regulation capacity of power systems, necessitating the exploration of adjustable resources on the load side to establish a novel ‘source-load interaction’ balancing mechanism. Air conditioning (AC) load, as a critical demand response resource, has garnered increasing attention. However, existing AC load control strategies are either heavily influenced by user behaviour uncertainty or overly reliant on communication and measurement infrastructure. Moreover, most approaches adopt random switching control methods, which fail to maximise user participation willingness and overlook the dynamic variations in user responsiveness, ultimately limiting their practical effectiveness. To address these challenges, this study proposes a dynamic scheduling model that comprehensively considers the aggregated response potential of AC loads and the characteristics of multiple flexible load types, thereby fully exploiting the coordinated regulation capability of load-side resources. Targeting a low-carbon community scenario (incorporating distributed wind power and residential users), the model is formulated with the dual objectives of maximising wind power accommodation and minimising source-load power deviation. A greedy algorithm is employed to iteratively solve the maximum available response capacity and actual dispatchable quantity of AC loads in each time slot, enabling dynamic updates of potential assessment and scheduling decisions. Case studies validate the effectiveness of the proposed model in enhancing wind power utilisation and optimising load scheduling, providing a feasible solution for source-load coordination in modern power systems.

This paper proposes a comprehensive reliability assessment method for flexible interconnected distribution networks (FIDNs) with soft open point (SOP) incorporation and coordinated multi-device load restoration. The following research work is conducted: first, a reliability function for hybrid modular multi-level converters (MMCs) is developed based on actual topological structures, with sub-module (SM) correlation and redundancy configurations comprehensively considered. Moreover, various SOP ports fault scenarios and their corresponding control strategies for distribution network faults are analysed, and an improved virtual flow method is proposed to satisfy network radiality and connectivity constraints during load restoration. On this basis, a mixed-integer second-order cone programming (MISOCP) model for FIDN load restoration is formulated, aiming to maximise load restoration through multi-device coordinated output. Furthermore, load nodes are classified based on their restorability post-fault, and optimal load restoration is performed under fault scenarios generated by Monte Carlo sampling, with system reliability indices further calculated. Finally, the effectiveness of the proposed method is validated on a modified 37-node system and the modified IEEE 123-node test system.

The fast restoration of the grid infrastructure after a grid failure is essential for a reliable energy supply. In this research, grid restoration by ramp-up of a 400 MW combined cycle power plant, supported by four hydropower generators (100 MW) and three pumps (23 MVA) in a 110-kV island grid in Upper Austria, is investigated. The objective is to test ramp-up feasibility and to develop a simulation model which further is verified by the measurement results from the real-world field tests. Findings include successful ramp-up with different inertia scenarios, frequency dips up to 1.15 Hz, and challenges by connecting inverter-based loads. The study underscores the importance of testing restoration strategies to ensure effective island operation during blackouts and to obtain results for simulation model verification. In addition, the influence of the usage of standard parameters on simulation results, thus insufficient knowledge of the controller parameters of the turbine controller, is analysed.

The paper presents results and experiences from Strømflex, a large-scale demonstration project, which was deployed at Norwegian DSO - Lede for evaluating the potential for activation of flexibility in the distribution network. The objective is to demonstrate how flexibility resources at different types of customers can be realised for the benefit of the DSO. The study focuses on the verification of the actually activated explicit flexibility volumes, practical estimation of baseline levels for the involved customer groups as well as considering consequences of the activations as rebound effect. The study defines the levels of the uncovered realistic flexibility potential, which varies across different customer groups. Finally, the study acknowledges well-functioning and reliability of the installed control technologies and concludes that the explicit activation of flexibility largely worked as intended in the pilot and has therefore a significant up-scaling potential.

With the increasing emphasis on green energy transformation, power systems are evolving into a “double high” structure characterised by a high integration of renewable energy sources and extensive use of power electronics. This transformation leads to more complex system topologies, necessitating improvements in monitoring and control measures. Traditional model-based approaches for identifying power oscillation disturbance sources are increasingly inadequate for the demands of modern power systems. The rapid development of Wide Area Measurement Systems (WAMS) has heightened interest in leveraging system response data for disturbance source localisation. This paper introduces a data-driven numerical method that combines energy functions with logistic regression, enhancing localisation accuracy by utilising power oscillation mechanisms and response data—and specifically improving accuracy by 15–22% over traditional methods. The proposed method identifies potential disturbance sources, ranging from minor random load fluctuations to significant forced power oscillations. A key innovation is the application of logistic regression for the automatic classification and localisation of disturbance sources, reducing the need for manual intervention and addressing the limitations of traditional energy function methods. Validation on WSCC 9-bus, New England 39-bus and 197-bus systems demonstrates 99.5% accuracy for single-source disturbances and 84.5-96.1% for multi-source scenarios, outperforming SVM (98.6%) and LDA (95.4%) while reducing computation time to 0.03s. By quantifying disturbance source localisation in power oscillations, this approach significantly enhances both the accuracy and efficiency of the localisation process.

This paper presents a novel perspective on providing adaptive virtual inertia (AVI), aimed at improving DC voltage stability in Multi-Terminal High Voltage DC (MT-HVDC) grids while simultaneously enhancing frequency response in AC grids. The proposed approach introduces an innovative Virtual Synchronous Generator (VSG) that supplies AVI for the AC systems. Additionally, a new control strategy for the Power Electronics Converters (PECs) that supply the MT-HVDC grid is presented, referred to as dcVSG, to provide AVI for this grid. Utilising both controllers concurrently enables adaptive and simultaneous virtual inertia provision on both DC and AC grids, while effectively leveraging the operational capabilities of the PECs. In this regard, the DC voltage and the AC grid frequency are considered as control parameters. The AVI is dynamically adjusted according to the PEC operating point. Specifically, the calculated maximum AVI is sensitive to the increase and reduction of the control parameter, demonstrating appropriate distinct values in response. This behaviour aims to utilise the PEC's maximum power capacity. The small-signal stability of the proposed system is analysed by focusing on the influence of virtual inertia on overall stability. Also, to assess the stability of the proposed controllers, Lyapunov stability theory, alongside a series of detailed simulation analyses, is conducted utilising the Cigre-DCS3 test grid. The simulation outcomes indicate that the proposed coordinated strategy yields a 20% reduction in DC voltage deviation while also enhancing frequency nadir. Additionally, it achieves over a 60% decrease in the rate of change of voltage (RoCoV) on the DC side and a 68% reduction in the rate of change of frequency (RoCoF), specifically when compared to methods that rely solely on the headroom power of the PEC to deliver maximum virtual inertia.

With advancements in semiconductor technology, switching frequencies of 10–20 kHz, enabled by SiC MOSFETs, are becoming viable for megawatt-scale converters, significantly reducing switching losses and filter size. This highlights SiC MOSFETs' potential in future power conversion. However, careful system design is crucial for stable operation. This paper examines active and passive methods to improve small-signal stability in weak grids across practical switching frequencies achievable by SiC MOSFETs and Si IGBTs. Multi-parallel inverters and various grid scenarios emulate real-world conditions. The findings reveal that while both damping methods enhance stability margins, they exhibit distinct trade-offs. Passive damping, requiring a lower quality factor at lower switching frequencies, results in higher damping losses, while active damping achieves similar stability with minimal losses. Both improve resonance stability but have limited impact on low frequencies. Additionally, results show that combining a phase compensator with active damping improves stability for both low and high-frequency ranges. A summary table presenting the analysis of component costs, power losses and system stability margins for different converter designs was provided, which can assist designers in identifying trade-offs to achieve the optimal design with Si IGBTs and SiC MOSFETs for the targeted application.