Data-Driven Look-Ahead Unit Commitment Considering Forbidden Zones and Dynamic Ramping Rates

2019 ◽  
Vol 15 (6) ◽  
pp. 3267-3276 ◽  
Author(s):  
Ziliang Jin ◽  
Kai Pan ◽  
Lei Fan ◽  
Tao Ding
Keyword(s):  
Unit Commitment ◽  
Data Driven ◽  
Look Ahead

scholarly journals Data-Driven Distributionally Robust Chance-Constrained Unit Commitment With Uncertain Wind Power

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 135087-135098 ◽  
Author(s):  
Zhichao Shi ◽  
Hao Liang ◽  
Venkata Dinavahi
Keyword(s):  
Wind Power ◽  
Unit Commitment ◽  
Data Driven ◽  
Distributionally Robust

Multistage Robust Look-Ahead Unit Commitment with Probabilistic Forecasting in Multi-Carrier Energy Systems

2021 ◽  
Vol 12 (1) ◽  
pp. 70-82 ◽  
Author(s):  
Yizhou Zhou ◽  
Mohammad Shahidehpour ◽  
Zhinong Wei ◽  
Guoqiang Sun ◽  
Sheng Chen
Keyword(s):  
Unit Commitment ◽  
Energy Systems ◽  
Probabilistic Forecasting ◽  
Look Ahead ◽  
Carrier Energy

A two-stage robust optimization for PJM look-ahead unit commitment

2013 ◽  
Author(s):  
Qianfan Wang ◽  
Xing Wang ◽  
Kwok Cheung ◽  
Yongpei Guan ◽  
Frederick S. Stu Bresler
Keyword(s):  
Robust Optimization ◽  
Unit Commitment ◽  
Two Stage ◽  
Look Ahead

scholarly journals Fast Heuristic AC Power Flow Analysis with Data-Driven Enhanced Linearized Model

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3308
Author(s):  
Xingpeng Li
Keyword(s):  
Power Systems ◽  
Power System ◽  
Power Flow ◽  
Flow Model ◽  
Reactive Power ◽  
Unit Commitment ◽  
Flow Analysis ◽  
Data Driven ◽  
Dc Power ◽  
Ac Power

Though the full AC power flow model can accurately represent the physical power system, the use of this model is limited in practice due to the computational complexity associated with its non-linear and non-convexity characteristics. For instance, the AC power flow model is not incorporated in the unit commitment model for practical power systems. Instead, an alternative linearized DC power flow model is widely used in today’s power system operational and planning tools. However, DC power flow model will be useless when reactive power and voltage magnitude are of concern. Therefore, a linearized AC (LAC) power flow model is needed to address this issue. This paper first introduces a traditional LAC model and then proposes an enhanced data-driven linearized AC (DLAC) model using the regression analysis technique. Numerical simulations conducted on the Tennessee Valley Authority (TVA) system demonstrate the performance and effectiveness of the proposed DLAC model.

A data-driven approach for multi-objective unit commitment under hybrid uncertainties

Energy ◽  
2018 ◽  
Vol 164 ◽  
pp. 722-733 ◽  
Author(s):  
Min Zhou ◽  
Bo Wang ◽  
Tiantian Li ◽  
Junzo Watada
Keyword(s):  
Unit Commitment ◽  
Data Driven ◽  
Multi Objective ◽  
Data Driven Approach
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