Details

Autor(en) / Beteiligte

• Fang, Duo
• Zou, Mingzhe
• Coletta, Guido
• Vaccaro, Alfredo
• Djokic, Sasa Z.

Titel

Handling uncertainties with affine arithmetic and probabilistic OPF for increased utilisation of overhead transmission lines

Ist Teil von

• Electric power systems research, 2019-05, Vol.170, p.364-377

Ort / Verlag

Elsevier B.V

Erscheinungsjahr

2019

Link zum Volltext

Quelle

ScienceDirect Journals (5 years ago - present)

Beschreibungen/Notizen

• •Correlation of uncertainties in wind energy and load profiles from field records.•Optimal power flow with dynamic thermal rating for day-ahead planning.•Combining affine arithmetic and probabilistic (Monte Carlo) methods.•Identification of low-risk wind curtailment strategies for wind integration. Large-scale integration of variable and unpredictable renewable-based generation systems poses significant challenges to the secure and reliable operation of transmission networks. Application of dynamic thermal rating (DTR) allows for a higher utilisation of transmission lines and effectively avoids high-cost upgrading and/or reinforcing of transmission system infrastructure. In order to efficiently handle ranges of uncertainties introduced by the variations of both wind energy sources and system loads, this paper introduces a novel optimization model, which combines affine arithmetic (AA) and probabilistic optimal power flow (P-OPF) for DTR-based analysis of transmission networks. The proposed method allows for the improved analysis of underlying uncertainties on the supply, transmission and demand sides, which are expressed in the form of probability distributions (e.g. for wind speeds, wind directions, wind power generation and demand variations) and related interval values. The paper presents a combined AA-P-OPF method, which can provide important information to transmission system operators for evaluating the trade-off between security and costs at a planning stage, as well as for selecting optimal controls at operational stage. The AA-P-OPF methodology is illustrated for a day-ahead planning, using a case study of a real transmission network and a medium size test distribution network.