English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

The integration of large-scale renewable generation has major implications onthe operation of power systems, two of which we address in this work. First,system operators have to deal with higher degrees of uncertainty due toforecast errors and variability in renewable energy production. Second, withabundant potential of renewable generation in remote locations, there is anincreasing interest in the use of High Voltage Direct Current lines (HVDC) toincrease transmission capacity. These HVDC transmission lines and theflexibility and controllability they offer must be incorporated effectively andsafely into the system. In this work, we introduce an optimization tool thataddresses both challenges by incorporating the full AC power flow equations,chance constraints to address the uncertainty of renewable infeed, modelling ofpoint-to-point HVDC lines, and optimized corrective control policies to modelthe generator and HVDC response to uncertainty. The main contributions aretwofold. First, we introduce a HVDC line model and the corresponding HVDCparticipation factors in a chance-constrained AC-OPF framework. Second, wemodify an existing algorithm for solving the chance-constrained AC-OPF to allowfor optimization of the generation and HVDC participation factors. Usingrealistic wind forecast data, for 10 and IEEE 39 bus systems with HVDC linesand wind farms, we show that our proposed OPF formulation achieves good in- andout-of-sample performance whereas not considering uncertainty leads to highconstraint violation probabilities. In addition, we find that optimizing theparticipation factors reduces the cost of uncertainty significantly.

Chance-Constrained AC Optimal Power Flow Integrating HVDC Lines and Controllability