View source for Projects:2020s2-7521 Probabilistic forecasting of energy prices in the National Electricity Market (NEM)

[[Category:Projects]]
[[Category:Final Year Projects]]
[[Category:2020s2|106]]
== Introduction ==
The landscape of the power system operation drastically changed since the restructuring of the industry and national electricity market establishment in   1998.   These   changes   have   been   exacerbated   in   recent   years   by introducing intermittent renewable resources (such as wind and PV farms) into the grid. As a result, price volatility is more than ever. In this situation,planning to enter/leave the market and how to bid in the market became a  difficult  task  that  needs  advanced  decision-making  tools  to  predict  not only the most probable scenarios but also the risks involved.

In this project, we want to develop a probabilistic forecasting algorithm for energy prices in  the  NEM  considering  some  external  factors/predictors.  

This  project provides  an  opportunity  to  learn  about  electricity  market  and  NEM operation,  times  series  analysis  and  probabilistic  prediction  algorithms, data science and programming in Python/MATLAB, and collaborate/write a research paper/report on the study.
=== Project team ===
==== Project students ====
* Hao Wang
* Yueran Zhu
==== Supervisors ====
* Dr Ali Pourmousavi Kani
==== Advisors ====

=== Objectives ===


== Background ==
=== Topic 1 ===

== Method ==

== Results ==

== Conclusion ==

== References ==
[1] a, b, c, "Simple page", In Proceedings of the Conference of Simpleness, 2010.

[2] ...