Recurrence of Sub-Synchronous Oscillation Accident of Hornsea Wind Farm in UK and Its Suppression Strategy

Yan, Xiangwu; Chang, Wenfei; Cui, Sen; Rassol, Aazim; Jia, Jiaoxin

doi:10.3390/en14227685

Cited by 11 publications

(7 citation statements)

References 22 publications

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“…The impact of each variable is quantified using Equation (18). By deducting the pre-disturbance energy from the post-disturbance energy for each data point and taking the average's absolute value, the required measure is derived.…”

Section: Sensitivity Analysismentioning

confidence: 99%

“…When dealing with SSO-disturbance-source location [16,17], the existing methods usually can only attribute the problem to a specific wind turbine, but lacks in-depth research on the internal control links of the wind turbine. This constraint could result in a lack of understanding of the oscillation's underlying cause, thus affecting effective control and management [18]. Based on the fine model of the D-PMSG converter, this paper not only analyzes the internal links of D-PMSG in detail but also accurately models its energy structure.…”

Section: Introductionmentioning

confidence: 99%

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Research on Sub-Synchronous-Oscillation Energy Analysis and Traceability Method Based on Refined Energy

Zhang,

Yang,

Zhou

et al. 2024

Energies

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At present, most studies use the direct method to analyze the oscillation problem of modern power systems. However, these studies often only simplify the external characteristics of the wind turbine and lack an in-depth understanding of its internal refined energy structure. In this paper, based on the direct-drive permanent magnetic synchronous generator’s detailed model (D-PMSG), combined with the dynamic energy of its port, layers of analysis are performed on the wind turbine’s internal connections, and a detailed model of the energy structure is created. Then, the interaction mechanism of each control link in the wind turbine is analyzed by combining the energy function of the wind turbine with the improved perturbation method. Finally, this paper constructs a sub-synchronous oscillation (SSO) scenario of weak damping and a forcing type and proves the accuracy and effectiveness of the traceability method based on the refined energy of D-PMSG. This traceability method based on refined energy is expected to provide a new solution to the stability problem caused by the integration of new energy.

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Section: Sensitivity Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on Sub-Synchronous-Oscillation Energy Analysis and Traceability Method Based on Refined Energy

Zhang,

Yang,

Zhou

et al. 2024

Energies

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“…The total power is equal to the total installed capacity of the wind turbines. For example, a wind farm with fifty 2 MW generators is modeled as one 100 MW generator [26]. The data attachments of these systems are given in the appendices.…”

Section: Model Of Dfig-based Wind Farmmentioning

confidence: 99%

Damping of Subsynchronous Resonance in Utility DFIG-Based Wind Farms Using Wide-Area Fuzzy Control Approach

et al. 2022

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This paper presents a novel fuzzy control scheme for damping the subsynchronous resonance (SSR) according to the wide-area measurement system (WAMS) in power systems including doubly fed induction generator (DFIG)-based wind farms connected to series capacitive compensated transmission networks. The SSR damping is attained by adding the fuzzy controller as a supplementary signal at the stator voltage loop of the grid-side converter (GSC) of DFIG wind farms. Additionally, time delays due to communication signals are important when using WAMSs. If the time delays are ignored, it causes system instability. In this paper, the time delays are modeled with a separate fuzzy input to the controller. The new fuzzy control approach is executed by using the angular velocity of synchronous generators (w) and its variation in the angular velocity (dw/dt). The effectiveness and success of the WAMS-based fuzzy controller is demonstrated by comparison with the particle swarm optimization (PSO) and imperialist competitive algorithm (ICA) optimization methods. The efficacy and validity of the planned auxiliary damping control are verified on a modified version of the IEEE second benchmark model including DFIG-based wind farms via time simulations using the MATLAB/Simulink toolbox.

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“…The planning and operation of today's power system need to be profoundly transformed to realize the above two improvements. For example, the blackout in the United Kingdom in 2019 was related to the decline of system inertia and anti-disturbance capability under a high proportion of renewable energy [10]. Renewable energy generators and related devices have very different operating characteristics from traditional devices, and the outputs of renewable energy are volatile and uncertain.…”

Section: Introductionmentioning

confidence: 99%

Application of reinforcement learning in planning and operation of new power system towards carbon peaking and neutrality

Sun¹,

Wang²,

Huang³

et al. 2023

Prog. Energy

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To mitigate global climate change and ensure a sustainable energy future, China has launched a new energy policy of achieving carbon peaking by 2030 and carbon neutrality by 2060, which sets an ambitious goal of building New Power System (NPS) with high penetration of renewable energy. However, the strong uncertainty, nonlinearity, and intermittency of renewable generation and their power electronics-based control devices are imposing grand challenges for secure and economic planning and operation of the NPS. The performance of traditional methods and tools becomes rather limited under such phenomena. Together with high-fidelity modeling and high-performance simulation techniques, the fast development of artificial intelligence (AI) technology, especially reinforcement learning (RL), provides a promising way of tackling these critical issues. This paper first provides a comprehensive overview of RL methods that interact with high-fidelity grid simulators to train effective agents for intelligent, model-free decision-making. Secondly, three important applications of RL are reviewed, including device-level control, system-level optimized control, and demand side management, with detailed modeling and procedures of solution explained. Finally, this paper discusses future research efforts for achieving the goals of full absorption of renewable energy, optimized allocation of large-scale energy resources, reliable supply of electricity, and secure and economic operation of the power grid.

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Recurrence of Sub-Synchronous Oscillation Accident of Hornsea Wind Farm in UK and Its Suppression Strategy

Cited by 11 publications

References 22 publications

Research on Sub-Synchronous-Oscillation Energy Analysis and Traceability Method Based on Refined Energy

Research on Sub-Synchronous-Oscillation Energy Analysis and Traceability Method Based on Refined Energy

Damping of Subsynchronous Resonance in Utility DFIG-Based Wind Farms Using Wide-Area Fuzzy Control Approach

Application of reinforcement learning in planning and operation of new power system towards carbon peaking and neutrality

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