Cost-reflective Tariff Design

Project outline

This work aims to build knowledge around the design of more cost-reflective tariffs.  Cost-reflective tariffs should, in theory, charge customers according to the costs they impose on network businesses. This should ensure that customers cover the costs they cause and, very importantly, now see price signals that incentivise efficient investment and operation of their own loads, storage and distributed generation. 

CEEM has been interested in this work for a number of years, including a number of papers and presentations as shown below. We have most recently developed a Tariff Tool that can be used to assess various impacts of different tariff designs.

Development of the Tariff Tool

The work is supported by Energy Consumers Australia, Project 'Tariff Assessment Tool, No 814. We have developed a modelling tool to assist stakeholders wishing to contribute to network tariff design in the Australian National Electricity Market. It is an open source modelling tool to assist stakeholders in assessing the implications of different possible network tariff designs, and hence facilitate broader engagement in the relevant rule making and regulatory processes in the NEM. Our tool takes public energy consumption data from over 5000 households in NSW, and allows users test a wide range of existing, proposed and possible tariffs structures to see their impacts on network revenue and household bills. Demographic survey data of the households allows you to explore the impacts of these tariffs on particular household types – for example, families with young children.  The tool can also show how well different tariffs align these household bills with a households’ contribution to network peak demand.  The tool and data are open source – you can check, validate and add your own data sets; test existing or even design your own tariffs, and validate and even modify the underlying algorithms.

Download the Tariff Tool!

Matlab version:

You can download the Tariff Tool here. TDA is available in windows and Mac versions. You should first install the Matlab Compiler Runtime (MCR) version 2016b (MCR9.1) and then run the TDA.exe (or TDA.app for mac). Please refer to TDA tool wiki page on Github for more information. Please email any comments and bugs here.

Python version:

The tool is now available in python version as well with new features and functionalities. Check out the release page for latest release or the actual github page for the source codes.

Load data

The tool currently uses household load data from the Smart Grid Smart Cities dataset. If you can provide any more household load data, please get in contact with us!

The Reference Committee for this work is:

UNSW Research Project Team:

Navid Haghdadi

Nicholas Gorman

Robert Passey

Anna Bruce

Sharon Young

Iain MacGill