Development of a DSO support tool for congestion forecast
Journal article, 2021

This paper presents a novel DSO support tool with visualisation capability for forecasting network congestion in distribution systems with a high level of renewables. To incorporate the uncertainties in the distribution systems, the probabilistic power flow framework has been utilised. An advanced photovoltaic production forecast based on sky images and a load forecast using an artificial neural network is used as the input to the tool. In addition, advanced load models and operating modes of photovoltaic inverters have been incorporated into the tool. The tool has been applied in case studies to perform congestion forecasts for two real distribution systems to validate its usability and scalability. The results from case studies demonstrated that the tool performs satisfactorily for both small and large networks and is able to visualise the cumulative probabilities of nodes voltage deviation and network components (branches and transformers) congestion for a variety of forecast horizons as desired by the DSO. The results have also shown that explicit inclusion of load-voltage dependency models would improve the accuracy of the congestion forecast. For demonstrating the applicability of the tool, it has been integrated into an existing distribution management system via the IoT platform of a DMS vendor, Atos Worldgrid.

Author

Ankur Srivastava

Chalmers, Electrical Engineering, Electric Power Engineering, Power grids and Components

David Steen

Chalmers, Electrical Engineering, Electric Power Engineering, Power grids and Components

Anh Tuan Le

Chalmers, Electrical Engineering, Electric Power Engineering, Power grids and Components

Ola Carlson

Chalmers, Electrical Engineering

Ioannis Bouloumpasis

Chalmers, Electrical Engineering, Electric Power Engineering, Power grids and Components

Quoc Tuan Tran

The French Alternative Energies and Atomic Energy Commission (CEA)

Lucile Lemius

Atos Worldgrid SAS

IET Generation, Transmission and Distribution

1751-8687 (ISSN) 1751-8695 (eISSN)

Vol. In press

ENABLING FLEXIBILITY FOR FUTURE DISTRIBUTION GRID (FLEXIGRID)

European Commission (EC) (864048), 2019-11-01 -- 2023-04-30.

Integrated cyber-physical solutions for intelligent distribution grid with high penetration of renewables (UNITED-GRID)

European Commission (EC) (773717), 2017-11-01 -- 2020-04-30.

Driving Forces

Sustainable development

Areas of Advance

Energy

Subject Categories

Other Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1049/gtd2.12266

More information

Latest update

8/26/2021