英语翻译要求：不要机译的,译文流畅 IN electricity market designs such as the

英语翻译
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.

在诸如美国加利福尼亚州的电力市场格局中,通常会有诸多买卖电力的市场.这些市场常常包括储备能源市场,辅助服务市场以及实时能源市场.虽然辅助服务的交易量比不上能源市场,但辅助服务的收入状况却可能对利润和成本构成重大影响.在发展成熟的存在多种能源选择的电力市场中,市场参与方可在除了正常的能源供应之外参与辅助服务（或承担某种参与辅助服务的义务）.为确定最佳的电力供应组合战略方案,参与者们必须根据能源和辅助服务的价格以及运营变动状况共同确定最有的电力分配方案.由于最优的电力分配方案最终取决于定价因素,因确保在各市场中优化配置电力需要做大量的研究调查工作.然而,关于如何利用固定的辅助服务设施来应对价格变动和随即电力需求的问题的研究文献相当缺乏,本文试图通过构建一种可行的的共同优化框架来解决此不平衡,由此来优化水电发电设备的最优运行.本框架对于解决存在价格及运营不确定因素的多来源电力市场中最优发电配置也可适用.尽管电力供应合同,附属服务和实时市场都是通过拍卖来完成交易的,但是就它们各自所提供的交易产品来说又存在区别.储备能源和实时能源（即时送达的能源）是为了实现稳定的电力供应,但附属服务却属远期能源市场,即只有在收到送电要求之后才去输送电力.辅助服务作为储备能力的一种形式的存在是因为无法准确预测系统需求而提前为所有客户购买电力.虽然实时能源市场因为预测失误（或战略竞标误差）,但是由于参与者并没有在未来某个时点供应电力的约束,因此预测未来实时的电力需求相当困难.