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

Journal Article · Thu Aug 25 00:00:00 EDT 2016 · IEEE Transactions on Power Systems

DOI:https://doi.org/10.1109/TPWRS.2016.2602805· OSTI ID:1361479

Roald, Line ^[1]; Misra, Sidhant ^[2]; Krause, Thilo ^[1]; Andersson, Goran ^[1]

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1. Federal Inst. of Technology, Zurich (Switzerland). Power System Lab.
2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

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.

• Research Organization: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
• Sponsoring Organization: USDOE Laboratory Directed Research and Development (LDRD) Program
• Grant/Contract Number: AC52-06NA25396
• OSTI ID: 1361479
• Report Number(s): LA-UR--16-23855
• Journal Information: IEEE Transactions on Power Systems, Journal Name: IEEE Transactions on Power Systems Journal Issue: 2 Vol. 32; ISSN 0885-8950
• Publisher: IEEE
• Country of Publication: United States
• Language: English

Related Subjects

24 POWER TRANSMISSION AND DISTRIBUTION
Chance constraints
Energy Sciences
Mathematics
corrective control
optimal power flow
renewable integration