要求:
不要机译的,译文流畅
IN electricity market designs such as the one implemented in California, there often exist multiple markets for selling and buying electric power. These markets typically include forward energy markets, ancillary services (AS) markets, and real-time energy markets. While the overall transaction volume of the ancillary services markets is smaller than that of the energy markets, the revenue from selling ancillary services can yield significant profit potential or cost reduction. A mature pool-based electricity market offers participants the choice (and certain obligation) to participate in the ancillary services markets besides the energy markets. To determine the best portfolio strategy for selling electricity into these markets, market participants need to jointly optimize (or, co-optimize) the allocation of electricity generation capacity dedicated to each market incorporating both price and operational uncertainties in the energy and ancillary services markets. There has been a large amount of research on the co-optimization problem of selling electricity into multiple markets given deterministic price forecasts. However, much less literature is available on such a problem subject to stochastic prices as well as random service requests on the committed ancillary services capacity. This paper attempts to address this disparity by providing a stochastic co-optimization framework for optimizing the operations of a hydro-electric generator. The framework can be extended to other applications such as optimal bidding of generation capacity in multiple electricity markets facing price and operational uncertainties.
While the electricity contracts, ancillary services and real-time markets are similar in the sense that their transactions are all completed through auctions, they differ in the types of products offered for trading. Unlike the forward and real-time (instantaneous delivery) energy markets which are for firm energy delivery, the ancillary services market is a forward market for capacity with obligation to deliver energy only when called in real-time. The need for ancillary services as a form of reserve capacity comes from the fact that it is impossible to forecast system demand exactly and then purchase electricity for all the customers ahead of time. Although the real-time energy market is also available for load/generation balancing due to errors in forecasts (or strategic bidding), it is very difficult to predict how much capacity would show up in real-time since there are no forward obligations by the participants.