When customers sell demand response into a regional capacity market (such as PJM’s Reliability Pricing Model, known as the RPM), how much credit should they earn for agreeing to curtail demand and...
Renewable portfolio standards bring volatility to Mid-Columbia markets.
and the associated large differences with on-peak prices, will provide incentives for these changes. The low prices will also change power purchasing strategies for industries and utilities. While the risk of energy purchasing likely will increase, the advantages of taking the risk also will increase dramatically.
The present RPS standards will accentuate price instability in the Mid-Columbia market. Negative spot prices will be a feature of our market in the years ahead as oversupply conditions expand with additional mandated renewable resources. It’s likely to make non-dispatchable base load resources less competitive. It’s also likely to make contractual resources, where third parties take the volatility risk, very competitive for industry and traditional utilities.
1. The California renewable portfolio standard (RPS) was enacted in 2002 under Senate Bill 1078, accelerated in 2006 under Senate Bill 107, and expanded in 2011 under Senate Bill 2. The California RPS program requires investor-owned utilities, electric service providers, and community choice aggregators to increase procurement from eligible renewable energy resources to 33 percent of retail sales by 2020. In Oregon, Senate Bill 838 enacted in April 6, 2007, required the state’s Department of Energy to create an RPS under which electric utilities must derive 25 percent of annual retail electricity sales from renewable energy resources by calendar year 2025. In Washington, Initiative 937, a successful ballot initiative in November 2006, required large utilities to obtain 15 percent of their electricity from new renewable resources, such as solar and wind, by 2020, and to undertake cost-effective energy conservation.
5. In 2012 a good water year and the rapidly increasing level of renewables – primarily
wind – contributed to an unusual situation: off-peak energy prices in the Mid-Columbia market fell below zero on 65 days. This is the second year when negative prices were so
significant. The first year, 2011, had negative off-peak prices on 62 days.
7. The statistical relationship using ordinary least squares indicates a degree of heteroskedasticity. The use of Cochrane-Orcutt corrects for the inefficiency of ordinary least squares in the presence of heteroskedasticity. The use of just three explanatory variables – hydro generation, wind generation, and gas prices – is meant only to illustrate the relationship of these variables to spot prices. This is hardly a complete model of the Mid-Columbia market.
10. Monte Carlo modeling is an approach to forecasting where the model is run once for each pick of a set of random variables. The name references testing roulette strategies by spinning the roulette wheel many times to see what the expected outcome is. Each spin of the wheel is referred to as one “game.” In this case, we ran the WECC 20,000 times to get expected values across hydro and wind picks. We used the normal distribution for hydroelectric generation. We derived a uniform