Stochastic Optimisation of Trading Strategies in Sequential Electricity Markets.
When generating energy with a portfolio with a big portion of renewables generation, there is a high uncertainty of how much energy will be generated (Q [MW], generated power and P [Euros/MW], price). Objetive of the paper is to build a optimisation model for trading that includes a risk-neutral portfolio owner and then expand it to a risk-avertion portfolio owner.
Explanation of the Blog
This blog is oriented towards the summary and analysis of the paper Stochastic Optimisation of Trading Strategies in Sequential Electricity Markets. For this, the sections in here will be explanations of the paper in a summarised ways and trying to use words as simple as possible.
Summary
When individual traders own a portfolio with high shares of renewables, uncertainty in future price $ Euros/MW $ and energy production quantity $ MW $ increases.
The objetive of the paper is to controll the trading of a portfolio with renewables energy production and controllable production (gas, diesel, among others).
The conclusions, as expected are that a trader risk-neutral will prefer to take bigger risks in intra day operations. (Later, will be explained that there are 3 markets, Intra-Day, Day-Ahead and Reserve Market).
Introduction
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Deterministic v/s Stochastic. Deterministic events always gives the same ouput given an identical input. Stochastic events Involves randomness, it’s possible to produce different outputs given a “identical” inputs. As an example, imagine yourself want to go and ask a calculator to your university library. The Problem
Suppose you and your classmates want to study in the Student Center study room, and you also need to borrow calculators.
Some natural questions that may arise are:
- What is the probability that a calculator is available?
- Is there a free table?
- Is there a small study room available?
- From the Student Center’s perspective, is it worth having more calculators? Or is it an unnecessary expense?
What do we need to know to answer these questions?
Motivation
Problem: Study Room at the Student Center (CAI)
Deterministic variables of the problem
These are known and fixed values:
- Number of chairs and tables
- Number of chairs per table
- Number of study boxes
- Number of calculators
Stochastic (random) variables of the problem
These are uncertain and vary randomly:
- Arrival of students to the study room
- Arrival of students requesting calculators
- Time students spend in the room
As a brief introduction to the problem, it could be summarised as a cause-effect system that can be seen as follow:
- Because of Renewable Energy Integration into the portfolio, Uncertainty increases.
- The existence of an auction system which includes a Day Ahead, Intra-day and reserve market makes it a more difficult system to analyse.
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Nowadays, the way to face this market is based on deterministic softwares, gut feeling of the trading specialists, among others.
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For This reason, the paper intends to use a MILP software to model a trader with a portfolio that includes renewable generation units (volatille) and controllable units.
- The idea is to model the german market. Including the * reserve market * , * spot market * & * Day Ahead market. *. the box below has more information related to the markets.
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The difference between the Reserve, Spot and Day Ahead markets is…….
Literature Review and Research Gap
It is important to mention that the focuss of the paper is on the individual approach. The two more important are the optimal dispatch problem (unit commitment) and the optimal trading problem.
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The main importance of the unit commitment and optimal trading problem.
Market Description
Methodology
# Example Child Subsection 1 # Example Child Subsection 2