Scheduling of Wind Farms for Optimal Frequency Response and Energy Recovery

Paola, Antonio De; Angeli, David; Štrbac, Goran

doi:10.1109/tcst.2016.2514839

Cited by 28 publications

(25 citation statements)

References 18 publications

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“…Based on the magnitude of disturbance ∆P L , both metrics should be kept within prescribed limits by selecting appropriate H and R terms, respectively. Furthermore, the time-domain solution for frequency deviation can be derived by substituting (20) into (23) as follows:…”

Section: A System Frequency Modeling With Wt Si Controlmentioning

confidence: 99%

Towards Optimal System Scheduling With Synthetic Inertia Provision From Wind Turbines

Chu

Markovic

Hug

et al. 2020

IEEE Trans. Power Syst.

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The undergoing transition from conventional to converter-interfaced renewable generation leads to significant challenges in maintaining frequency stability due to declining system inertia. In this paper, a novel control framework for Synthetic Inertia (SI) provision from Wind Turbines (WTs) is proposed, which eliminates the secondary frequency dip and allows the dynamics of SI from WTs to be analytically integrated into the system frequency dynamics. Furthermore, analytical system frequency constraints with SI provision from WTs are developed and incorporated into a stochastic system scheduling model, which enables the provision of SI from WTs to be dynamically optimized on a system level. Several case studies are carried out on a Great Britain 2030 power system with different penetration levels of wind generation and inclusion of frequency response requirements in order to assess the performance of the proposed model and analyze the influence of the improved SI control scheme on the potential secondary frequency dip. The results demonstrate that the inclusion of SI provision from WTs into UC can drastically impact the overall system costs.Index Terms-synthetic inertia, frequency response, unit commitment, recovery effect, secondary frequency dip

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Section: A System Frequency Modeling With Wt Si Controlmentioning

confidence: 99%

Towards Optimal System Scheduling With Synthetic Inertia Provision From Wind Turbines

Chu

Markovic

Hug

et al. 2020

IEEE Trans. Power Syst.

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show abstract

“…Constraint (15) ensures that WTGs can only adjust their output power with maximum ramp-up/ramp-down rates. Constraint (16) shows that the power generation from a WTG is always lower than its available power at t + 1.…”

Section: Minmentioning

confidence: 99%

“…The central controller gathers information from all local WTGs' controllers and determines the power generation of the WF system by sending out set-point to each individual WTG. The authors in [16] have presented a new methodology for the scheduling of WTGs that provide frequency response. The proposed scheduling has been implemented with a centralized approach that requires a two-way communication channel between the WTGs and a central entity.…”

Section: Introductionmentioning

confidence: 99%

“…It can be observed from the literature survey that most of the existing studies have mainly focused on developing EMSs for WFs based on either centralized approaches [15,16] or decentralized approaches [17][18][19]. In a large WF system, both centralized and decentralized EMSs could face many difficulties and challenges.…”

Section: Introductionmentioning

confidence: 99%

“…In a large WF system, both centralized and decentralized EMSs could face many difficulties and challenges. For instance, in a centralized EMS, a two-way communication channel between the WTGs and the central entity is required [15,16]. With a huge number of WTGs allocated in a large area of the WF system, the development of a centralized management system is often expensive and the computational burden for the central entity also significantly increases.…”

Section: Introductionmentioning

confidence: 99%

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Hybrid Energy Management System for Operation of Wind Farm System Considering Grid-Code Constraints

et al. 2019

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In this paper, a hybrid energy management system is developed to optimize the operation of a wind farm (WF) by combining centralized and decentralized approaches. A two-stage optimization strategy, including distributed information sharing (stage 1); and centralized optimization (stage 2) is proposed to find out the optimal set-points of wind turbine generators (WTGs) considering grid-code constraints. In stage 1, cluster energy management systems (CEMSs) and transmission system operator (TSO) interact with their neighboring agents to share information using diffusion strategy and then determine the mismatch power amount between the current output power of WF and the required power from TSO. This amount of mismatch power is optimally allocated to all clusters through the CEMSs. In stage 2, a mixed-integer linear programming (MILP)-based optimization model is developed for each CEMS to find out the optimal set-points of WTGs in the corresponding cluster. The CEMSs are responsible for ensuring the operation of WF in accordance with the requirements of TSO (i.e., grid-code constraints) and also minimizing the power deviation for the set-points of WTGs in each cluster. The minimization of power deviation helps to reduce the internal power fluctuations inside each cluster. Finally, to evaluate the effectiveness of the proposed method, several case studies are analyzed in the simulations section for operation of a WF with 20 WTGs in four different clusters.

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Analytically derived fixed termination time for stepwise inertial control of wind turbines—Part II: Application strategy

Guo¹,

Bao²,

Ding³

et al. 2020

International Journal of Electrical Power & Energy Systems

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Scheduling of Wind Farms for Optimal Frequency Response and Energy Recovery

Cited by 28 publications

References 18 publications

Towards Optimal System Scheduling With Synthetic Inertia Provision From Wind Turbines

Towards Optimal System Scheduling With Synthetic Inertia Provision From Wind Turbines

Hybrid Energy Management System for Operation of Wind Farm System Considering Grid-Code Constraints

Analytically derived fixed termination time for stepwise inertial control of wind turbines—Part II: Application strategy

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