Loading...
hidden

View Mobile version

Meta navigation

Startseite – Hochschule Luzern

Language selection and important links

  • Contents
  • Contact
  • Login
  • De
  • En
Search

Main navigation

School navigation

  • Engineering and Architecture
  • Business
  • Computer Science
  • Social Work
  • Art and Design
  • Music

Sub-navigation

  • Degree Programmes
  • Continuing Education
  • Research
  • International
  • Campus
  • About us
  • News

Sub-navigation

Breadcrumbs

  1. Research Research
  2. Tariff analysis for ELCOM Tariff analysis for ELCOM

Tariff analysis for ELCOM

This project investigates the application of machine learning to support the evaluation of electricity prices and tariffs of network operators in Switzerland.

Brief information

School:

Computer Science and Information Technology

Status:

Completed

Period:

01.12.2019 - 31.12.2020

Overview

This project investigates the application of machine learning to support the evaluation of electricity prices and tariffs in Switzerland. ElCom is Switzerland's independent regulatory authority in the electricity sector. ElCom is responsible for monitoring compliance with the Swiss Federal Electricity Act and the Swiss Federal Energy Act, taking all necessary related decisions, and pronouncing rulings where required. ElCom monitors electricity prices and rules on disputes relating to network access. Additionally, it observes electricity supply security and regulates issues relating to international electricity transmission and trading. ElCom is responsible for ruling on disputes concerning feed-in tariffs and between network operators and independent producers (approx. 650 organizations). The operators' electricity tariff is determined by factors such as types of power stations, grid size, and many more. While the organizations propose prices for each year, ELCOM has to assess the validity of each suggestion. In this project, we want to explore the application of machine learning to support ELCOM employees in their evaluation process. More specifically, we want to apply Anomaly Detection and cluster analysis to identify abnormal tariff suggestions.

hidden

Facts

Type of project

Forschung

Internal organisations involved
  • Computer Science and Information Technology
Funding
  • Private / Stiftungen
hidden

Persons involved: internal

Project manager
  • Daniel Pfäffli
Member of project team
  • Marc Bravin
  • Andrin Bürli
  • Donnacha Daly
  • Sita Mazumder
  • Tobias Mérinat
  • Marc Pouly

Brief information

School:

Computer Science and Information Technology

Status:

Completed

Period:

12/01/2019 - 12/31/2020

Project Head

Daniel Pfäffli

Highly Specialised Senior Research Associate

+41 41 757 68 28

Show email

Footer(s)

FH Zentralschweiz

Social media links

  •  Facebook
  •  Instagram
  •  Twitter
  •  LinkedIn
  •  YouTube
  •  Flickr

Contact

Logo Lucerne University of Applied Sciences and Arts

Lucerne University of Applied Sciences and Arts


Werftestrasse 4
6002 Luzern

+41 41 228 42 42

info@hslu.ch

Direct entry

  • A bachelor's degree –
  • A master's degree –
  • Prospective Students (Continuing & Executive Programmes)
  • Unternehmen & Institutionen
  • Media Relations
  • For Students
  • For Members of Staff

Quick link

  • People Finder
  • University Buildings & Campus Locations
  • News
  • Libraries
  • Events
  • Jobs & Karriere
  • Home
  • Hiring Rooms

Static links

  • Newsletter
  • Data protection notice
  • Publishing Acknowledgements
Logo Swissuniversities

QrCode

QrCode
We use cookies on this site to give you the best browsing experience. By continuing to navigate this site or closing this banner you accept this use of cookies. For more information please visit our privacy policy.
OK