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Title: Corrective Control to Handle Forecast Uncertainty: A Chance Constrained Optimal Power Flow

Higher shares of electricity generation from renewable energy sources and market liberalization is increasing uncertainty in power systems operation. At the same time, operation is becoming more flexible with improved control systems and new technology such as phase shifting transformers (PSTs) and high voltage direct current connections (HVDC). Previous studies have shown that the use of corrective control in response to outages contributes to a reduction in operating cost, while maintaining N-1 security. In this work, we propose a method to extend the use of corrective control of PSTs and HVDCs to react to uncertainty. We characterize the uncertainty as continuous random variables, and define the corrective control actions through affine control policies. This allows us to efficiently model control reactions to a large number of uncertainty sources. The control policies are then included in a chance constrained optimal power flow formulation, which guarantees that the system constraints are enforced with a desired probability. Lastly, by applying an analytical reformulation of the chance constraints, we obtain a second-order cone problem for which we develop an efficient solution algorithm. In a case study for the IEEE 118 bus system, we show that corrective control for uncertainty leads to a decrease inmore » operational cost, while maintaining system security. Further, we demonstrate the scalability of the method by solving the problem for the IEEE 300 bus and the Polish system test cases.« less
Authors:
ORCiD logo [1] ;  [2] ;  [1] ;  [1]
  1. Federal Inst. of Technology, Zurich (Switzerland). Power System Lab.
  2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Report Number(s):
LA-UR-16-23855
Journal ID: ISSN 0885-8950
Grant/Contract Number:
AC52-06NA25396
Type:
Accepted Manuscript
Journal Name:
IEEE Transactions on Power Systems
Additional Journal Information:
Journal Volume: 32; Journal Issue: 2; Journal ID: ISSN 0885-8950
Publisher:
IEEE
Research Org:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org:
USDOE Laboratory Directed Research and Development (LDRD) Program
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; Energy Sciences; Mathematics; Chance constraints; corrective control; optimal power flow; renewable integration
OSTI Identifier:
1361479

Roald, Line, Misra, Sidhant, Krause, Thilo, and Andersson, Goran. Corrective Control to Handle Forecast Uncertainty: A Chance Constrained Optimal Power Flow. United States: N. p., Web. doi:10.1109/TPWRS.2016.2602805.
Roald, Line, Misra, Sidhant, Krause, Thilo, & Andersson, Goran. Corrective Control to Handle Forecast Uncertainty: A Chance Constrained Optimal Power Flow. United States. doi:10.1109/TPWRS.2016.2602805.
Roald, Line, Misra, Sidhant, Krause, Thilo, and Andersson, Goran. 2016. "Corrective Control to Handle Forecast Uncertainty: A Chance Constrained Optimal Power Flow". United States. doi:10.1109/TPWRS.2016.2602805. https://www.osti.gov/servlets/purl/1361479.
@article{osti_1361479,
title = {Corrective Control to Handle Forecast Uncertainty: A Chance Constrained Optimal Power Flow},
author = {Roald, Line and Misra, Sidhant and Krause, Thilo and Andersson, Goran},
abstractNote = {Higher shares of electricity generation from renewable energy sources and market liberalization is increasing uncertainty in power systems operation. At the same time, operation is becoming more flexible with improved control systems and new technology such as phase shifting transformers (PSTs) and high voltage direct current connections (HVDC). Previous studies have shown that the use of corrective control in response to outages contributes to a reduction in operating cost, while maintaining N-1 security. In this work, we propose a method to extend the use of corrective control of PSTs and HVDCs to react to uncertainty. We characterize the uncertainty as continuous random variables, and define the corrective control actions through affine control policies. This allows us to efficiently model control reactions to a large number of uncertainty sources. The control policies are then included in a chance constrained optimal power flow formulation, which guarantees that the system constraints are enforced with a desired probability. Lastly, by applying an analytical reformulation of the chance constraints, we obtain a second-order cone problem for which we develop an efficient solution algorithm. In a case study for the IEEE 118 bus system, we show that corrective control for uncertainty leads to a decrease in operational cost, while maintaining system security. Further, we demonstrate the scalability of the method by solving the problem for the IEEE 300 bus and the Polish system test cases.},
doi = {10.1109/TPWRS.2016.2602805},
journal = {IEEE Transactions on Power Systems},
number = 2,
volume = 32,
place = {United States},
year = {2016},
month = {8}
}