Article, 2024

Frequency constrained unit commitment considering reserve provision of wind power

Applied Energy, ISSN 0306-2619, 1872-9118, Volume 361, Page 122898, 10.1016/j.apenergy.2024.122898

Contributors

Jiang, Boyou 0000-0002-0254-3151 [1] Guo, Chuangxin (Corresponding author) [1] Chen, Zhe [2]

Affiliations

  1. [1] Zhejiang University
    2. [NORA names: China; Asia, East];
  2. [2] Aalborg University
    3. [NORA names: AAU Aalborg University; University; Denmark; Europe, EU; Nordic; OECD]

Abstract

Large-scale wind power integration not only requires extra flexibility for power system operation but also leads to declining system inertia and raises concerns regarding frequency stability. Pertinent studies have substantiated the capability of wind turbines (WTs) to provide reserves via pitch angle control (PAC) and rotor speed control (RSC). In this study, a comprehensive modeling approach is employed for the first time to capture WTs’ reserve capacities while accounting for the exogenous uncertainty associated with wind speed and the decision-dependent uncertainty regarding the control decisions including pitch angle and rotor speed. Subsequently, a two-stage frequency constrained stochastic unit commitment model incorporating WTs’ reserve provision is formulated to jointly optimize the unit commitment, generation, and reserves from both conventional generating units (CGUs) and WTs. To enhance computational tractability, a deep neural network based framework is adopted in combination with piece-wise linearization to linearize the nonlinear terms regarding PAC and RSC. Furthermore, two solution acceleration strategies tailored to the model’s characteristics are proposed. Case studies show that (i) the proposed model effectively develops the reserve potential of WTs, leading to a reduction in reserve cost and wind curtailment; (ii) the proposed acceleration strategies significantly improve the solution efficiency, reducing the solution time by 62.88% and 15.71% in the IEEE 9-bus and 118-bus systems, respectively.

Keywords

IEEE, IEEE 9-bus, Pertinent studies, acceleration, acceleration strategy, angle, angle control, approach, associated with wind speed, capability, capability of wind turbines, capacity, case study, cases, characteristics, combination, commitment, commitment model, comprehensive modeling approach, computational tractability, concerns, control, control decisions, conventional generation units, cost, curtailment, decision, decision-dependent uncertainty, declining system inertia, deep neural networks, efficiency, exogenous uncertainty, flexibility, framework, frequency, frequency stability, generation, generation units, inertia, integration, large-scale wind power integration, linearity, model, model characteristics, modeling approach, network, neural network, nonlinear terms, operation, piece-wise linear, pitch, pitch angle, pitch angle control, potential of wind turbines, power, power integration, power system operation, provision, reduction, reserve, reserve capacity, reserve cost, reserve potential, reserve provision, rotor, rotor speed, rotor speed control, solution, solution efficiency, solution time, speed, speed control, stability, stochastic unit commitment model, strategies, study, system, system inertia, system operation, term, time, tractability, turbine, uncertainty, unit commitment, unit commitment model, units, wind, wind curtailment, wind power, wind power integration, wind speed, wind turbines

Funders

  • National Natural Science Foundation of China
  • China Scholarship Council

Data Provider: Digital Science

LINKS
-

Matching Records in NORA

SUBJECTS
+

METRICS
+