Data reduction via clustering and averaging for contingency and reliability analysis

Kile, Håkon; Uhlen, Kjetil

doi:10.1016/j.ijepes.2012.07.011

Cited by 22 publications

(22 citation statements)

References 18 publications

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“…The main objective of this section is to provide some general guidelines for application of the scenario selection method [7], where the guidelines are based on practical experiences with the method, see, e.g., [14][15][16]. Similar ideas for data reduction, in the context of power system analysis, is found in [17][18][19].…”

Section: The Scenario Selection Methodsmentioning

confidence: 99%

“…The scenario selection method, first presented in [7], is designed to reduce the number of power market scenarios that has to be analysed in the reliability assessment. The scenario selection method finds groups of similar power market scenarios, and then, for each group, chooses one scenario to represent the group characteristics.…”

Section: Introductionmentioning

confidence: 99%

“…This will keep the sample variation of the full sample of power market scenarios more or less intact, but at the same time severely reduce the computational requirements of the reliability assessment. Reference [7], discusses the scenario selection method on a very general basis. In this paper, a set of general guidelines for practical applications of the scenario selection method is presented.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: The Scenario Selection Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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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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“…2) K-medoids Clustering: K-means is a widely used clustering technique in various applications [21]. What makes K-means convenient for power system applications is easy implementation on large-scale data set, and high efficiency as it works directly with the data.…”

Section: Clusteringmentioning

confidence: 99%

“…Here transmission topology and capacities are fixed; the OPF problem is solved by controlling the squared reference voltage value of dc converters (w t i ). The analytical solution to the full problem necessitates the equality of nodal payments (19), transmission revenues (21) and congestion revenue (20). However, since the OPF is solved for a fixed grid design (number of parallel lines N ij is pre-determined by the STEP block), the investment costs will not essentially equal transmission revenues.…”

Section: E Optimal Power Flow To Validate Clusteringmentioning

confidence: 99%

A Market-Based Transmission Planning for HVDC Grid—Case Study of the North Sea

Torbaghan

Gibescu

Rawn

et al. 2015

IEEE Trans. Power Syst.

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Abstract-There is significant interest in building HVDC transmission to carry out transnational power exchange and deliver cheaper electricity from renewable energy sources which are located far from the load centers. This paper presents an approach to solve a long-term transmission planning problem for meshed VSC-HVDC grids that connect regional markets. This is in general a nonlinear non-convex large-scale optimization problem with high computational burden, partly due to the many combinations of wind and load that become possible. We developed a two-step iterative algorithm that first selects a subset of operating hours using a clustering technique, and then seeks to maximize the social welfare of all regions and minimize the investment capital of transmission infrastructure subject to technical and economic constraints. The outcome of the optimization is an optimal grid design with a topology and transmission capacities that results in congestion revenue paying off investment by the end the project's economic lifetime. Approximations are made to allow an analytical solution to the problem and demonstrate that an HVDC pricing mechanism can be consistent with an AC counterpart existing onshore. The model is used to investigate development of the offshore grid in the North Sea. Simulation results are interpreted in economic terms and show the effectiveness of our proposed two-step approach.

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Reliability Evaluation in Transmission Systems

Singh

Mitra

2016

Smart Grid Handbook

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Composite power system reliability models provide a comprehensive methodology for evaluating the reliability of the bulk power system. These models include the generation and transmission facilities and appropriate network flow models. These models provide tools for rational decision making regarding cost–benefit analysis. This chapter discusses the component models of the power system, their interrelationships, and the network flow models needed. Various techniques, analytical as well as Monte Carlo, are described. Contemporary issues such as integration of renewable intermittent sources of energy and the interdependence of cyber and current‐carrying parts are also discussed.

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Data reduction via clustering and averaging for contingency and reliability analysis

Cited by 22 publications

References 18 publications

Scenario selection in composite reliability assessment of deregulated power systems

Scenario selection in composite reliability assessment of deregulated power systems

A Market-Based Transmission Planning for HVDC Grid—Case Study of the North Sea

Reliability Evaluation in Transmission Systems

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