Probabilistic load models and Monte Carlo simulations used in distribution system planning

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CIRED 2019 - 1672.pdf (952.17 KB)

Paper number

1672

Working Group Number

Conference name

CIRED 2019

Conference date

3-6 June 2019

Conference location

Madrid, Spain

Peer-reviewed

Yes

Short title

Convener

Authors

Tønne, Erling, NTE Nett AS, Norway
Sand, Kjell, NTNU, Norway
Foosnæs, Jan Andor, NTE Nett AS, Norway

Abstract

Today’s deterministic fit-and-forget methodology for distribution system planning is not suitable for planning of the future smart distribution grid. Alternative methodologies have been developed. The paper describes the new approach and compares it with todays practice. The ongoing and continuing increase in grid connection of distributed generation from renewable energy sources and change in consumption patterns will make the power flow more unpredictable and stochastic than before.  Generation from renewables is normally unregulated (e.g. solar and wind) and will vary a lot. Measurements show that the increased use of energy efficient but power-intensive equipment (like heat pumps, electric vehicles and induction cookers) together with time-varying tariffs, give faster dynamics in consumption patterns and a more stochastic behaviour of the power flow.   Reliable models for loads and generation variations and development are essential for the long-term development of the distribution and transmission grid. Poor models will probably result in a large difference between the estimated and real (measured) loads, and this again will result in wrong decisions and over- or underinvestment in the grid. The Distribution System Operators (DSOs) will get a lot more data from smart meters, new sensors, control systems etc. that can be used to make better load estimations and forecasts.  A new probabilistic method for load and generation modelling utilizing new data from smart meters have been developed and compared with today’s deterministic method. The new models have been used in probabilistic network load flow calculations by Monte Carlo simulations and shows promising results.

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Publisher

AIM

Date

2019-06-03

Published in

CIRED 2019 Conference

Permanent link to this record

https://cired-repository.org/handle/20.500.12455/516
http://dx.doi.org/10.34890/742

ISSN

2032-9644

ISBN

978-2-9602415-0-1