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Generation Adequacy Analysis of Multi-Area Power Systems With a High Share of Wind Power
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems. (Integration of Renewable Energy Sources Group)
KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems. (Integration of Renewable Energy Sources Group)ORCID iD: 0000-0002-8189-2420
2018 (English)In: IEEE Transactions on Power Systems, ISSN 0885-8950, E-ISSN 1558-0679, Vol. 33, no 4, p. 3854-3862Article in journal (Refereed) Published
Abstract [en]

There is growing concern regarding generation adequacy within the power system industry. The ever-increasing injection of intermittent renewable resources makes it harder than before to estimate the reliability of modern power systems using traditional approaches. This paper develops a framework for estimating the reliability of modern power systems that have considerable levels of wind power generation. Monte Carlo simulation is applied using a very efficient importance sampling technique based on the cross-entropy method as well as the Copula theory. Tailor-made importance sampling functions for conventional generation, load, and wind power generation drastically reduce the number of samples required to estimate reliability parameters of interest. The methodology enables simulation of multi-area power systems with considerable amount of correlated wind power generation in each of the different areas. Simulation results confirm the efficiency as well as the accuracy of the proposed method and show that it is orders of magnitude faster than crude Monte Carlo simulation.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018. Vol. 33, no 4, p. 3854-3862
Keywords [en]
Monte Carlo simulation, cross-entropy (CE) method, power system reliability, Copula theory, wind power, importance sampling, correlation, loss of load probability (LOLP), expected power not served (EPNS)
National Category
Energy Systems
Identifiers
URN: urn:nbn:se:kth:diva-240222DOI: 10.1109/TPWRS.2017.2769840ISI: 000436009500033Scopus ID: 2-s2.0-85034237938OAI: oai:DiVA.org:kth-240222DiVA, id: diva2:1270819
Note

QC 20181214

Available from: 2018-12-14 Created: 2018-12-14 Last updated: 2018-12-14Bibliographically approved

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Tomasson, EgillSöder, Lennart

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