DSO risk management strategies for reducing risk caused by actions in future flexibility markets

The lack of visibility of the actions of new actors such as aggregators and customers providing demand side response and other ancillary services will present new risks to Distribution System Operators (DSO’s) in both their planning of new investments and in the day to day running of the system. The key question is how will DSO’s identify these potential risks, value them and then act on them to safe guard the operation of their network systems and protect their financial performance? This paper presents a methodology / approach for assessing/quantifying such risks, to help understand the impact of various mitigation strategies. At the heart of this framework, lies an Agent Based Modelling tool, which models the interactions of key agents such as aggregators, generators, independent system/market place operators and domestic/industrial customers.

Authors

Institutions

Publication Details

Journal
IET conference proceedings.
Published
2025-01-01
DOI
https://doi.org/10.1049/icp.2024.1976
Primary Topic
Risk Management in Financial Firms
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

DSO risk management strategies for reducing risk caused by actions in future flexibility markets

Ivana Kockar, Gary Howorth
IET conference proceedings.
Risk Management in Financial Firms
article

DSO risk management strategies for reducing risk caused by actions in future flexibility markets

Ivana Kockar, Gary Howorth
article en

Abstract

The lack of visibility of the actions of new actors such as aggregators and customers providing demand side response and other ancillary services will present new risks to Distribution System Operators (DSO’s) in both their planning of new investments and in the day to day running of the system. The key question is how will DSO’s identify these potential risks, value them and then act on them to safe guard the operation of their network systems and protect their financial performance? This paper presents a methodology / approach for assessing/quantifying such risks, to help understand the impact of various mitigation strategies. At the heart of this framework, lies an Agent Based Modelling tool, which models the interactions of key agents such as aggregators, generators, independent system/market place operators and domestic/industrial customers.

IET conference proceedings.Vol. 2024(5)
University of Strathclyde (GB)
Openalex Percentile: Top 99%
Risk Management in Financial Firms
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.