Generating Electricity Price Forecasting Scenarios to Analyze Whether Price Uncertainty Impacts Tariff Performance

Goedegebure, Niels; Hennig, R.J.

doi:10.1109/PMAPS53380.2022.9810603

Generating Electricity Price Forecasting Scenarios to Analyze Whether Price Uncertainty Impacts Tariff Performance

Title

Generating Electricity Price Forecasting Scenarios to Analyze Whether Price Uncertainty Impacts Tariff Performance

Author

Goedegebure, Niels (Student TU Delft)
Hennig, R.J. (TU Delft Energy and Industry)

Date

2022

Abstract

A higher share of renewables and electric vehicles increase the risk of congestion in electricity distribution systems. New distribution tariff designs have been proposed to prevent congestion. However, most modeling of tariff performance assumes deterministic price information. This paper proposes a method to assess the impact of price uncertainty for network tariffs, using price forecasting scenarios in a simulation model. Electricity price forecasting scenarios are generated by analyzing autoregressive forecasting errors and recursively generating time-series. The scenarios are used as price forecasting inputs in a model case study of tariff performance in a Dutch context. Results show a reduction in congestion frequency and charging costs using forecasts in this model setup, likely by enabling longer time horizons. Highest peaks however are larger when using forecasts for the fixed and capacity-based tariffs. Overall, this method provides insight into performance of new tariffs in electricity grids, incorporating the impact of price uncertainty.

Subject

Network tariffs
distribution networks
demand response
e, electricity price forecasting
electric vehicles

To reference this document use:

http://resolver.tudelft.nl/uuid:ac49c4b1-e2e8-4d27-b7a5-c59248ae97ea

DOI

https://doi.org/10.1109/PMAPS53380.2022.9810603

Publisher

IEEE

ISBN

978-1-6654-1212-4

Source

2022 17th International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2022