Energy Trading & Risk Management with MATLAB Webinar Case Study
Actualizado 1 Sep 2016
The case study presented here demonstrates using MATLAB to build an application for measuring the risks associated with a portfolio of gas-fired power plants operated in New England. The application has an interface implemented in Excel with all of the analytics performed by MATLAB. The application allows the user to specify the characteristics of the 7 plants including the capacity, heat rate, variable operation and maintenance costs and minimum run time. This portfolio can be backtested using a simple dispatch strategy on historical gas and electricity prices to compute historical profit and plant operation statistics. The risk measures are computed by simulating gas and electricity prices into the future using a hybrid model implemented in MATLAB, simulating the dispatch for each scenario of market prices and computing cash-flows arising from the operation of the plants. The distribution of the cash-flows is analyzed to produce a 90% and 95% cash-flow at risk measure for each plant as well as for the portfolio of generation assets. All of this functionality is presented with a succinct Excel front end.
The document titled "Introduction to ETRM Case Study" will guide you through the different components of the analysis.
Note: The data used in this application is not provided with the MATLAB Central File Exchange entry. The data can be obtained from the New England ISO at http://www.iso-ne.com/. The Natural Gas spot price data can be obtained from the Wall Street Journal at http://www.wsj.com. You can still view the results of running each script on the data by viewing the MATLAB-published reports included in the archive and also linked below.
Siddharth Sundar (2023). Energy Trading & Risk Management with MATLAB Webinar Case Study (https://www.mathworks.com/matlabcentral/fileexchange/28056-energy-trading-risk-management-with-matlab-webinar-case-study), MATLAB Central File Exchange. Recuperado .
Compatibilidad con la versión de MATLAB
Compatibilidad con las plataformasWindows macOS Linux
Inspirado por: Intelligent Dynamic Date Ticks
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