• Environmental and Resource Economics Review
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• v.13 no.3
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• pp.417-440
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• 2004

For the behavior of the wholesale spot price, a regime switching model with time-varying transition probabilities was estimated using the data from the PJM (Pennsylvania-New Jersey-Maryland) market. By including the temperature as an explanatory variable in the transition probability equations, the threshold effect of changing regime is clearly enhanced. And hence the predictability of the price spikes was improved. This means that the model showed a very clear threshold effect, with a low probability of switching for low loads and low temperatures and a high probability for high loads and high temperatures. And temperature showed a clearer threshold effect than load does. This implies that weather-related contracts may help to hedge against the risk in the cost of buying electricity during a summer.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.255-263
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• 2003

A multi-agent system designed to represent newly deregulated electricity markets in the USA is aimed at testing the capability of the multi-agent model to replicate the observed price behavior in the wholesale market and developing a smart business intelligence which quickly searches the optimum offer strategy responding to the change in market environments. Simulation results show that the optimum offer strategy is to withhold expensive generating units and submit relatively low offers when demand is low, regardless of firm size; the optimum offer strategy during a period of high demand is either to withhold capacity or speculate for a large firm, while it is to be a price taker a small firm: all in all, the offer pattern observed in the market is close to the optimum strategy. From the firm's perspective, the demand-side participation as well as the intense competition dramatically reduces the chance of high excess profit.