Abstract
The objective of this deliverable is to present the requirements for adapting available tools/models and identifying data needs for probabilistic reliability analysis and optimal decision-making in the short-term decision making process. It will serve as a basis for the next tasks of GARPUR work package 6 addressing to the requirements of RMAC criterion developed in work package 2, and also to validate the functional specifications of the GARPUR Quantification Platform (work carried out in work package 7) as well as for designing the pilot test requirements in work package 8. The report has been written by several partners, two of them being European TSOs, and the four other being academic partners. Special attention has been paid to address every topic in short-term decision making process as considered within GARPUR, and so that no important issue has been forgotten in the grey zones at the interfaces between the short-term operation planning and real-time decision making process.
Adhering to the title of the task, the various chapters in the deliverable discusses the exogenous factors, i.e., load forecasting, component failure rates and influence of weather and renewable energy sources. Accurate estimation of the variation of uncertainty behind exogenous and endogenous factors is crucial to support reliable calculations/estimations by proposed approaches for short-term RMAC and real-time RMAC, as described in work package 2. Cross-border exchanges, operational reserves and outage duration are extensively studied for short-term operation planning. Contingency selection in real-time is discussed with special focus on risk-based contingency selection. Failure of corrective action and recent trend in energy management services in real-time is also tackled in this report. Some advanced models exist in scientific literature to characterize the spatio-temporal variation and correlations of relevant factors. Some of these models have been proposed in academia, and offer improved representation with respect to those models currently in use by TSOs. The most relevant to GARPUR are presented and discussed in this report.
This report also outlines the gaps that might hinder implementation of the new approaches of GARPUR for reliability assessment and control, and provides recommendations for bridging them towards pilot testing in GARPUR, and for further improvement/extension beyond GARPUR.
Adhering to the title of the task, the various chapters in the deliverable discusses the exogenous factors, i.e., load forecasting, component failure rates and influence of weather and renewable energy sources. Accurate estimation of the variation of uncertainty behind exogenous and endogenous factors is crucial to support reliable calculations/estimations by proposed approaches for short-term RMAC and real-time RMAC, as described in work package 2. Cross-border exchanges, operational reserves and outage duration are extensively studied for short-term operation planning. Contingency selection in real-time is discussed with special focus on risk-based contingency selection. Failure of corrective action and recent trend in energy management services in real-time is also tackled in this report. Some advanced models exist in scientific literature to characterize the spatio-temporal variation and correlations of relevant factors. Some of these models have been proposed in academia, and offer improved representation with respect to those models currently in use by TSOs. The most relevant to GARPUR are presented and discussed in this report.
This report also outlines the gaps that might hinder implementation of the new approaches of GARPUR for reliability assessment and control, and provides recommendations for bridging them towards pilot testing in GARPUR, and for further improvement/extension beyond GARPUR.
| Original language | English |
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| Publisher | TU Delft |
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| Number of pages | 118 |
| Publication status | Published - 2016 |
Bibliographical note
Project no.:608540; Project acronym: GARPUR; Project full title: Generally Accepted Reliability Principle with Uncertainty modelling and through probabilistic Risk assessmentCan only be accessed internally by the project partners
