Capacity Markets – Renewable Generation

This post is part of a multi-part series on capacity markets.

Capacity Markets – Definition

Capacity Markets – Background

Capacity Markets – A look across the United States

Capacity Markets – Renewable Generation

In a previous post, I described how electricity markets in the US provide incentives for independent power generators to build and maintain generating capacity.  Capacity ensures that the grid has sufficient ability to generate the necessary electricity during peak hours.  These markets function well for traditional natural gas power plants which can be turned on and off fairly easily.  The post looks at the current methodology for valuing the capacity of renewable intermittent resources, such as wind or solar.

In general, wind blows stronger at night, but this chart of the power output 

every day for a month of a California wind farm shows that there can be 

quite a lot of variability

Peak hours for the grid in most of the United States are during the summer afternoons when buildings have their air conditioner turned on (the exceptions are winter-peaking areas in the northern United States where customers have a lot of baseboard electric heating).  Often, the wind is not blowing its strongest on hot afternoons.  In addition, while these hours tend to be sunny, there could be significant cloud cover during an important hour, or the air conditioning load could remain high at dusk when the sun sets.  Wind and solar cannot be counted on to be available the same as a natural gas combustion turbine.

This one day chart of the power output from a photovoltaic solar
installation shows the impact that cloud cover can have on solar power.
Geographic diversity of solar power throughout the state should mute
many of these variations for the purpose of system-wide capacity. 

On the other hand, conventional power plants such as a natural gas power plan is not available all the time either, and it still receives capacity value.  Conventional resources have scheduled maintenance, and unplanned outages.  Moreover, even if wind and solar do not always perform at their maximum rated output during peak hours, surely they are providing some benefit which could be estimated statistically.

California has attempted to address this issue by creating a net qualifying capacity (NQC) methodology to determine the amount of resource adequacy a power plant of a given technology provides.  Resource adequacy, as I mentioned previously, is the closest thing California has to a forward capacity payment.

The NQC for renewables is determined by an “exceedance methodology”, calculate by California state regulators: the public utilities commission (CPUC), the energy commission (CEC), and the ISO (CAISO).  The exceedance approach measures the minimum amount of generation produced by the resource in a certain percentage of peak hours.  The exceedance level used to calculate the QC of wind and solar resources is 70%.  Another way to describe the exceedance level is that the 70% exceedance level of a resource’s production profile is the maximum generation amount that it produces at least 70% of the time (during peak hours).  The peak hours, for the purpose of the exceedance methodology calculation, are 5 hours a day, 4-9 p.m. November to March and 1-6 p.m. April to October.**  These hours vary regionally, and would not make sense for a grid at a different latitude than California. 

To determine the minimum production level of solar and wind resources for 70% of the peak hours, California looks at historical values for load data and power output from solar and wind resources.  Typically, an average of the past 3 years is used.

NQC values for renewable power resources are dependent on seasonality, geographic diversity of the resource, and site specific factors. Anecdotally, I would expect the NQC value of a solar facility to be approximately 25-35% of its installed capacity (measured in MWs), and the NQC value for wind to be approximately 10-20%.

**5 hours a day year round is a relatively conservative metric because the industry standard for determining capacity among distributed resources is the top 250 load hours of the year.  250 hours is an “eyeballed” number for the peak hours in which the grid is most likely to have an outage.  A more rigorous loss of load probability (LOLP) analysis is done for reliability planning, but for economic estimates of resource planning, 250 hours will usually suffice.  5 hours a day is roughly 20% of the hours in the year, whereas 250 hours is less than 3% of the hours in the year.