A case study shows how today's typical tariffs can force some industrial electric customers to subsidize others.
There ought to be a better way for electric utilities to set prices for...
other generators. Even if a plant is only able to provide energy, its valuation needs to take into account the interaction of prices in forward, spot and ancillary services markets. A structural model makes possible volatility analysis, which captures the systematic effects of key driver distributions and interactions. By running multiple scenarios based on Monte Carlo sampling of the distributions of fundamental market drivers, one can obtain the volatility distribution of both energy and ancillary service prices. The drivers' distributions are changeable, given new information or a need to explore scenarios under changed conditions.
Whereas a time-series model will not be able to account for the occurrence of price spikes, a structural model can derive a reasonable estimate of their likelihood, given the coincidence of less likely values among key drivers over multiple scenarios. For a long-term structural simulation, the number, severity and duration of price spikes will all result from the other system conditions encompassed by the model. Indeed, price spikes may provide crucial revenue to enable a plant's profitable operation. In asset valuation, insights into these phenomena can prove decisive.
Most importantly, a structural approach offers the ability not only to capture the prices in the electricity markets based on rational bidding by participants, but incorporates the dynamic interaction of prices in the various markets.
A Case Study:
Simultaneous Bidding in Multiple Markets
Consider an illustration of the impact of earning revenues from multiple product markets. I use an MMOPF-type model to derive the revenues of a CC unit and a simple-cycle CT unit whose characteristics are displayed in Table 1. The study will compare asset valuations based only on the forward price curve of energy against what the units could earn if they are bid simultaneously on other products in the ancillary services and spot markets. The model outputs used are prices for energy, regulation up, regulation down, spinning and non-spinning reserves, replacement reserve and real-time. The prices for these multiple products are displayed in Table 2 and compared graphically in Figure 1 for all the hours in a particular day.
What happens if plants bid only on one product, in the day-ahead market for energy in the power exchange?
ENERGY ONLY. First, the forward curve is used to derive purely forward energy market-based revenues. Note that from Table 1, the marginal cost of the CC is $15.07. In the day-ahead PX market, a bid of $0 will allow the generator to be dispatched in every hour, and obtain revenue over marginal cost in most hours. It is better for the generator to incur a small loss for a few hours than to pay the additional startup cost that would be necessitated after shutting down briefly. According to the overall market-clearing operations, and as indicated in Figure 1, the price of energy will be above the CC's marginal cost for 21 hours. Thus, the CC will earn an income of $181 per megawatt-day, taking into account the different prices in each hour and the possible marginal losses from operating in those few hours when marginal cost exceeds the PX