A team of 5 MBA Students worked on an MBA+ project initiative sponsored by MP2 Energy to explore long run solar energy contracts, forecasting and mitigating associated weather-variability risks.
Company / Division / Operating Group Description
MP2 Energy is headquartered in The Woodlands, TX with diverse business operations in both the wholesale and retail electricity markets. We are truly a unique company in ERCOT in that our expertise and business model crosses all aspects of power in ERCOT and thus we refer to our model as one of a ‘Virtual Utility’ – combining wholesale and retail operations with knowledge and activity within the wholesale trading markets. In addition to being a Retail Electric Provider (REP), we are a registered Level IV Qualified Scheduling Entity with ERCOT responsible for scheduling and managing our own retail load, as well as managing over 1500 MW of wholesale power generation and over 325 MW of wholesale demand response for customers. Further, through our affiliate DGS, we also develop central and distributed generating assets. We are not simply a marketing or sales company, but are a risk management, power development and power operations firm first and foremost.
Business Issue to be Addressed
Evaluate the risk of agreeing to long run solar contracts. What is the probability and consequence of a cloudy January day where the solar production we expected is not available? How can we price a contract so that our financial risk is reduced? Specifically, look at the intra-day (and ultimately intra-hour) variability of distributed generation systems in ERCOT and compare them against the hourly solar production forecast to determine the variability coefficient. Then we would like to overlay cloud cover to the hourly data sets to see how much of the variability is due to cloud cover/weather and how much is for ‘other’ reasons. Then, we’d like to overlay the ERCOT market pricing to see when this variability occurs and how much of a market risk it is. Again, we suspect that it will be relatively low because the market prices index off heat which solar directly correlates to. Once we understand the true market risk of the solar intra-hour/intra-day variability of a single DG system, we can then develop our imbalance coefficient and “straddle” we need to factor in to our bundled solar standard offer rate.