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/

Zendy Plus

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

Zendy Tools

Zendy Open

Operating power systems in a secure way constitutes a critical task for ensuring a well functioning society. However, security comes at the expense of additional investment and operational cost. The additional costs incurred to maintain a desired security level are expected to increase further due to the integration of Renewable Energy Sources (RES). This highlights the necessity to revisit certain operational concepts and construct novel design methodologies to achieve a better trade-off between a secure and an economic operation of the power network. This dissertation concentrates on quantifying this trade-off and proposes a mechanism for optimal decision making in the presence of uncertainty. We first introduce the concept of probabilistic security, where the system and security constraints are allowed to be violated with a prespecified probability. To achieve this, we formulate an optimal power flow problem with N-1 security constraints and infeed uncertainty (e.g wind power, loads) as a chance constrained optimization program. We then incorporate a generation-side reserve decision mechanism in the developed probabilistic security constrained optimal power flow framework. We model the deployed reserves as piecewise linear functions of the uncertainty and we optimize with respect to the coefficients of these functions and determine the required reserve capacity by the extreme values of the deployed reserves. In this way, another product of our production and reserve scheduling algorithm is the construction of a reserve strategy that can be deployed in real time operation. Analogously to the generation-side reserves, we also provide a representation for the reserves offered by demand response. Exploiting demandside capabilities for reserve provision allows a more economic operation of power systems since it results in lower total cost compared to the case

Optimal decision making for secure and economic operation of power systems under uncertainty