Imagine the electric grid. We flip a switch, and the lights turn on. Simple, right? But ensuring there's *always* enough power available, especially during peak demand times (like hot summer afternoons when everyone runs air conditioning), is a complex challenge. This is the problem of resource adequacy.
Traditionally, regulated monopolies built power plants based on long-term forecasts. In modern, restructured electricity markets, generators primarily earn money by selling the energy ($\text{MWh}$) they produce in the "energy market". However, this can lead to a problem known as the "missing money" issue.
Power plants, especially those that only run during peak demand times ("peakers"), have high fixed costs (construction, maintenance) but might not run often enough to recover these costs solely from energy sales. Price caps, often imposed for political reasons during high-demand periods, can further limit their revenue. If investors fear they won't recover their costs, they won't build enough capacity, potentially leading to shortages.
Think of it like this: building a power plant is expensive. If you only get paid when you actually produce electricity, and you might only be needed a few hours a year, would you build it? Maybe not, even if it's crucial for reliability during those few hours.
As the presentation notes (Slide 2), the cost of having too little capacity (shortages, blackouts) is generally considered much higher than the cost of having a bit too much.
One solution is a Capacity Market. Instead of just paying for energy produced ($\text{MWh}$), these markets pay generators for being *available* to produce power, measured in capacity ($\text{MW}$). It's like paying an insurance premium to guarantee that generation resources will be there when needed.
The key questions in designing a capacity market are:
Early capacity markets often used a "vertical demand curve" approach (referred to as ICAP - Installed Capacity - in the presentation, Slide 5). This means setting a fixed target quantity of capacity. If suppliers offer less than the target, they face a steep penalty (or the price goes very high); if they offer more, the price drops significantly (often to zero for the excess).
More recent designs, like the PJM Reliability Pricing Model (RPM) discussed in the presentation (Slide 7), use a "sloped demand curve". This approach recognizes that the value of additional capacity gradually decreases. We're willing to pay a lot for the capacity needed to meet basic reliability, but less for extra "cushion".
Let's visualize these two approaches. The demand curve shows the price the market operator is willing to pay for different quantities of available capacity.
The vertical curve creates a knife-edge situation: a small change in supply around the target can cause a massive swing in price. The sloped curve, often called a Variable Resource Requirement (VRR) curve, aims for smoother price adjustments.
The presentation highlights a key finding from dynamic simulations (Slides 8-9): sloped demand curves tend to lead to more stable markets over time. Why? Because they provide smoother price signals to investors.
Let's simulate a simplified capacity market over several years. We'll model generators making investment/retirement decisions based on expected profits, influenced by the capacity price and the Cost of New Entry (CONE) - the estimated annualized cost of building a new reference power plant. The simulation incorporates some randomness to represent forecast errors and market volatility.
Goal: Compare how market stability (price volatility, reserve margin consistency) differs between the vertical and sloped demand curve designs.
Run the simulation with both the "Vertical" and "Sloped" demand curve settings. Observe:
The simulation demonstrates the core argument presented: the shape of the demand curve significantly impacts market dynamics and investment signals. A sloped curve acts as a shock absorber, leading to potentially more efficient outcomes over the long run.
The presentation indicates that PJM's RPM, using a sloped demand curve, was successful in attracting new investment and retaining existing capacity (Slides 11-12). ISO New England also implemented a forward capacity market with similar goals (Slide 13).
However, capacity markets are not without challenges (Slide 13):
Capacity markets are a tool designed to address the "missing money" problem and ensure long-term resource adequacy in competitive electricity markets. The design of these markets, particularly the shape of the demand curve, has significant implications for market stability and investment efficiency.
As demonstrated through the simplified dynamic simulation, using a sloped demand curve (like PJM's RPM) can dampen boom/bust cycles, provide clearer investment signals, and potentially lead to more stable reserve margins and lower long-term costs compared to a vertical demand curve approach. While challenges remain, this design feature represents a key evolution in ensuring a reliable power supply.
This interactive explanation is based on the presentation "Capacity Markets: Principles & What's Happening in the US" by Benjamin F. Hobbs (July 2010). The simulation is a simplified model intended for illustrative purposes.