Establishing Measured Natural Gas Operation Rights
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Resource Overview
This case study demonstrates how to use MATLAB for establishing measured natural gas operation rights in power plant portfolios, with risk assessment applications for New England power plants. The implementation involves MATLAB integration with Excel for comprehensive interface analysis. The application enables users to specify characteristics for 7 plant types, including capacity, heat rate, variable operations/maintenance costs, and minimum runtime parameters. Portfolio profitability and unit operation history can be backtested using simple dispatch strategies against historical natural gas and electricity prices. Risk metrics are computed through simulations implemented in MATLAB using gas and hybrid models, which simulate market prices for each dispatch scenario and calculate cash flows generated from plant operations based on projected electricity prices.
Detailed Documentation
This case study demonstrates how to use MATLAB to establish measured natural gas operation rights and apply risk assessment to power plant portfolios in New England. The implementation utilizes MATLAB-Excel integration to analyze all interfaces, allowing users to specify seven plant types with characteristics including capacity, heat rate, variable operations and maintenance costs, and minimum runtime parameters. Users can employ simple dispatch strategies to calculate profits and unit operation history data, while simulating market prices for each dispatch scenario to compute cash flows - all implemented through MATLAB programming. For risk evaluation, simulations using natural gas and hybrid models calculate future electricity prices. Using this data, we can analyze cash flow distributions and derive 90% and 95% cash flow values, along with risk measures for each plant and the generation asset portfolio. All these functionalities are provided through a streamlined Excel front-end interface. For deeper analysis, the "Introduction to ETRM Case Study" file can be used to examine different components, with MATLAB code implementing Monte Carlo simulations for price forecasting and portfolio optimization algorithms.
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- 1 Credits