Investigating the influence of a booking system based on dynamic forecasting and pricing on power flow reliability

Ahmad Fayyaz Bakhsh; Florian Samm; Thomas Kienberger; Julia Vopava-Wrienz

doi:10.1049/icp.2025.1783

Investigating the influence of a booking system based on dynamic forecasting and pricing on power flow reliability

Chair of Energy Network Technology (540)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Power load forecasting, dynamic forecasting, and pricing are the topics included in this study. The forecasting model used in this study, Long Short-Term Memory (LSTM), was extended to provide dynamic forecasts. Dynamic forecasts and improved forecasting performance are necessary for creating a dynamic pricing strategy for electric vehicle (EV) charging. The available capacity of the local distribution grid determines the dynamic price. The limited grid capacity can result in restrictions for charging electric vehicles. Additionally, dynamic forecasting and dynamic pricing are the bases for a booking system that enables customers to reserve a time slot for charging their vehicles. Photovoltaic (PV) generation and the maximum free grid capacity are considered to provide incentives for charging at certain times. Finally, a comparison is made between the effects of EV charging on the grid with and without the dynamic pricing approach and the booking system.

Original language	English
Title of host publication	28th International Conference and Exhibition on Electricity Distribution (CIRED 2025)
Pages	1162-1166
Number of pages	5
Volume	2025
Edition	14
ISBN (Electronic)	9781807050207, 9781807050351, 9781807050375, 9781837242634, 9781837242900, 9781837242917, 9781837243143, 9781837243150, 9781837243167, 9781837243235, 9781837243341, 9781837243358, 9781837245277, 9781837246847, 9781837246854, 9781837247004, 9781837247011, 9781837247028, 9781837247035, 9781837247042, 9781837247059, 9781837247257, 9781837247264, 9781837247271, 9781837247295, 9781837247325, 9781837247332, 9781837249916
DOIs	https://doi.org/10.1049/icp.2025.1783
Publication status	Published - Oct 2025

Bibliographical note

Publisher Copyright:
© The Institution of Engineering & Technology 2025.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Dynamic Forecasting
Dynamic Pricing
Energy Forecasting
Long Short-Term Memory

Access to Document

10.1049/icp.2025.1783

Cite this

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title = "Investigating the influence of a booking system based on dynamic forecasting and pricing on power flow reliability",

abstract = "Power load forecasting, dynamic forecasting, and pricing are the topics included in this study. The forecasting model used in this study, Long Short-Term Memory (LSTM), was extended to provide dynamic forecasts. Dynamic forecasts and improved forecasting performance are necessary for creating a dynamic pricing strategy for electric vehicle (EV) charging. The available capacity of the local distribution grid determines the dynamic price. The limited grid capacity can result in restrictions for charging electric vehicles. Additionally, dynamic forecasting and dynamic pricing are the bases for a booking system that enables customers to reserve a time slot for charging their vehicles. Photovoltaic (PV) generation and the maximum free grid capacity are considered to provide incentives for charging at certain times. Finally, a comparison is made between the effects of EV charging on the grid with and without the dynamic pricing approach and the booking system.",

keywords = "Dynamic Forecasting, Dynamic Pricing, Energy Forecasting, Long Short-Term Memory",

author = "\{Fayyaz Bakhsh\}, Ahmad and Florian Samm and Thomas Kienberger and Julia Vopava-Wrienz",

note = "Publisher Copyright: {\textcopyright} The Institution of Engineering \& Technology 2025.",

year = "2025",

month = oct,

doi = "10.1049/icp.2025.1783",

language = "English",

volume = "2025",

pages = "1162--1166",

booktitle = "28th International Conference and Exhibition on Electricity Distribution (CIRED 2025)",

edition = "14",

}

Investigating the influence of a booking system based on dynamic forecasting and pricing on power flow reliability. / Fayyaz Bakhsh, Ahmad ; Samm, Florian ; Kienberger, Thomas et al.
28th International Conference and Exhibition on Electricity Distribution (CIRED 2025). Vol. 2025 14. ed. 2025. p. 1162-1166.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Investigating the influence of a booking system based on dynamic forecasting and pricing on power flow reliability

AU - Fayyaz Bakhsh, Ahmad

AU - Samm, Florian

AU - Kienberger, Thomas

AU - Vopava-Wrienz, Julia

PY - 2025/10

Y1 - 2025/10

N2 - Power load forecasting, dynamic forecasting, and pricing are the topics included in this study. The forecasting model used in this study, Long Short-Term Memory (LSTM), was extended to provide dynamic forecasts. Dynamic forecasts and improved forecasting performance are necessary for creating a dynamic pricing strategy for electric vehicle (EV) charging. The available capacity of the local distribution grid determines the dynamic price. The limited grid capacity can result in restrictions for charging electric vehicles. Additionally, dynamic forecasting and dynamic pricing are the bases for a booking system that enables customers to reserve a time slot for charging their vehicles. Photovoltaic (PV) generation and the maximum free grid capacity are considered to provide incentives for charging at certain times. Finally, a comparison is made between the effects of EV charging on the grid with and without the dynamic pricing approach and the booking system.

AB - Power load forecasting, dynamic forecasting, and pricing are the topics included in this study. The forecasting model used in this study, Long Short-Term Memory (LSTM), was extended to provide dynamic forecasts. Dynamic forecasts and improved forecasting performance are necessary for creating a dynamic pricing strategy for electric vehicle (EV) charging. The available capacity of the local distribution grid determines the dynamic price. The limited grid capacity can result in restrictions for charging electric vehicles. Additionally, dynamic forecasting and dynamic pricing are the bases for a booking system that enables customers to reserve a time slot for charging their vehicles. Photovoltaic (PV) generation and the maximum free grid capacity are considered to provide incentives for charging at certain times. Finally, a comparison is made between the effects of EV charging on the grid with and without the dynamic pricing approach and the booking system.

KW - Dynamic Forecasting

KW - Dynamic Pricing

KW - Energy Forecasting

KW - Long Short-Term Memory

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U2 - 10.1049/icp.2025.1783

DO - 10.1049/icp.2025.1783

M3 - Conference contribution

VL - 2025

SP - 1162

EP - 1166

BT - 28th International Conference and Exhibition on Electricity Distribution (CIRED 2025)

ER -

Investigating the influence of a booking system based on dynamic forecasting and pricing on power flow reliability

Abstract

Bibliographical note

UN SDGs

Keywords

Access to Document

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Cite this