The important role of feature selection when clustering load and generation scenarios

Kile, Håkon; Uhlen, Kjetil; Kjølle, Gerd Hovin

doi:10.1109/appeec.2013.6837115

Cited by 3 publications

(2 citation statements)

References 15 publications

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“…In particular, the choice of corrective actions strategy, the choice of operating state, and the inclusion of protection and control is important. The most important aspect seems to be the choice of the operating states, a finding that is well in line with results presented in [3,10]. To better understand the results presented in Figure 5, it is useful to investigate the interruption costs for all the buses in the network.…”

Section: Resultssupporting

confidence: 71%

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Enhanced method for reliability of supply assessment - an integrated approach

Gjerde

Kjølle

Jakobsen

et al. 2016

2016 Power Systems Computation Conference (PSCC)

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A comprehensive analysis of reliability of electricity supply to end users requires a unique set of models, methods and tools. Of special significance are long term power market models for predicting future operating states (generation and load patterns) and more detailed network simulation models for analysing consequences of contingencies. This paper describes an integrated approach for reliability of supply analysis, assessing reliability and interruption costs down to the specifics of different kinds of end users at different delivery points in the network model. Furthermore, the effects of power system protection, temporal variation of parameters, and corrective actions as part of the consequence analysis, are taken into account in the presented integrated approach. The results are illustrated through a case study on a realistic hydro dominated four-area meshed test system.

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Section: Resultssupporting

confidence: 71%

“…and import/export to neighbouring areas.' These operating states can be further grouped using different clustering functions to obtain representative scenarios that can significantly reduce the computational requirements [10].…”

Section: Integrated Methodologymentioning

confidence: 99%

Enhanced method for reliability of supply assessment - an integrated approach

Gjerde

Kjølle

Jakobsen

et al. 2016

2016 Power Systems Computation Conference (PSCC)

Self Cite

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Data set for power system reliability analysis using a four-area test network

et al. 2020

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Scenario selection in composite reliability assessment of deregulated power systems

Kile

Uhlen

Kjølle

2014

International Journal of Electrical Power & Energy Systems

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Power market analysis should be incorporated in reliability assessments of deregulated power systems. For the Nordic power system, this is done by using The Multi-area Power-market Simulator (EMPS) for long-term power market analysis, where EMPS finds the optimal socio-economic dispatch on a weekly basis, with respect to, e.g., hydro reservoir levels. The EMPS analysis results in a set of load and generation scenarios, and these scenarios are interpreted as a sample of future power market behaviour, and is used as basis for a reliability assessment. These load and generation scenarios are referred to as power market scenarios.The power market analysis produces a large number of power market scenarios, and to include all these scenarios in a reliability assessment results in excessive computation time. The scenario selection method is presented and discussed. Scenario selection is used to pick out a subset of the generated power market scenarios, to only use this subset of scenarios as a basis for the reliability assessment. It is shown that the scenario selection method can reduce the scenario set by about 90%, with little loss of accuracy in the reliability assessment.

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The important role of feature selection when clustering load and generation scenarios

Cited by 3 publications

References 15 publications

Enhanced method for reliability of supply assessment - an integrated approach

Enhanced method for reliability of supply assessment - an integrated approach

Data set for power system reliability analysis using a four-area test network

Scenario selection in composite reliability assessment of deregulated power systems

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