Probabilistic risk-based management of distribution transformers by dynamic transformer rating
| Autor: | Guido Carpinelli, Antonio Bracale, Pasquale De Falco |
|---|---|
| Přispěvatelé: | Bracale, Antonio, Carpinelli, Guido, DE FALCO, Pasquale |
| Rok vydání: | 2019 |
| Předmět: |
Computer science
020209 energy Energy Engineering and Power Technology 02 engineering and technology Distribution transformer law.invention Dynamic transformer rating Operator (computer programming) law 0202 electrical engineering electronic engineering information engineering Ampacity Electrical and Electronic Engineering Transformer Load forecasting Probabilistic forecasting business.industry Risk-based management 020208 electrical & electronic engineering Probabilistic logic Renewable energy Reliability engineering Dynamic transformer rating Load forecasting Probabilistic forecasting Risk-based management Distributed generation visual_art Electronic component visual_art.visual_art_medium business |
| Zdroj: | International Journal of Electrical Power & Energy Systems. 113:229-243 |
| ISSN: | 0142-0615 |
| DOI: | 10.1016/j.ijepes.2019.05.048 |
| Popis: | Electrical distribution networks are often inadequate to comply with the increasing load demand and to enable new installation of distributed energy resources. This inadequacy may result in upgrading existing transformers of in disconnecting the entire load during demand peaks, and into wasting a portion of the total renewable energy produced during favorable weather conditions. Increasing the capacity of electrical distribution network components is therefore mandatory in order to avoid these negative circumstances; however replacing lines and transformers is costly, and often the benefits are not worth the investments. Fortunately, the capacity of distribution networks can be unlocked by managing the electrical components by their dynamic ratings, allowing operating them even beyond their rated ampacity for a limited interval of time. This paper proposes a new risk-based procedure to manage distribution transformers by their dynamic rating. Probabilistic forecasts of loads and ambient temperatures are the inputs of the procedure, which are obtained in this paper from quantile regression forests. The procedure quantifies, in a probabilistic framework, the insulation thermal ageing due to the transformer (over)load in terms of the cost sustained for rewinding the transformer. The corresponding estimated risk is made available to the distribution system operator, who may therefore take a decision comparing it to an arbitrary level of risk coverage, favoring either the power delivery to customers or the reduction of the transformer ageing rate; this level is formulated in this paper having an intuitive physical meaning, thus enabling its setting also by non-expert operators. Comprehensive numerical experiments based on actual data are presented under different configurations and scenarios, in order to validate the proposal from an energetic and economic point of view. |
| Databáze: | OpenAIRE |
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