GOALI: Collaborative Research - A Systems Approach to Modeling Real-Time Market Prices of Electricity

本研究的目的是确定合适的方法，发现在放松管制的市场中的实时电价的统计分布。它将采用一种自下而上的系统方法，通过生产成本模型来代表市场。该模型的组成部分将是发电机的容量、可靠性和成本特性，包括市场、燃料价格、需求和影响它的气象影响。作为第一近似值，每小时的价格将等同于用于供应每小时需求的最后一台发电机组的边际成本。最初的努力将集中在通过生产成本模型从市场供求双方的现有信息中找到每小时边际单位的统计分布。然而，经验数据表明，当供给接近需求时，在寡头垄断市场下，现货价格超过边际生产成本。这一现象将使用不同的经济模型在随机框架下的生产成本表示的市场。 试图在建模的整个统计分布要求，与发电机停机和时序负荷的随机过程占。该项目将开发适用于大型系统的近似分析程序，并将使用蒙特卡罗模拟评估这些近似值的准确性。将通过将这些模型预测的结果与历史数据进行比较来验证计算结果。

The purpose of this research project is to determine suitable approaches for finding the statistical distributions of real-time electricity prices in a deregulated market. It will use a bottoms-up systems based approach in which the market is represented via a production-costing model. The components of this model will be the capacity, reliability, and cost characteristics of the generators that comprise the market, fuel prices, demand, and the meteorological influences that affect it. As a first approximation, the price at every hour will be equated to the marginal cost of the last generating unit used to supply each hour's demand. The initial effort will concentrate on finding the statistical distribution of the marginal unit at each hour via the production-costing model from the available information on the supply and demand sides of the market. Empirical data suggest, however, that when the supply approaches demand and under an oligopoly market, the spot price exceeds the marginal cost of production. This phenomenon will be investigated using different economic models under a stochastic framework based on a production-costing representation of the market. Attempts at modeling the entire statistical distributions require that the stochastic processes associated with the generator outages and chronological load are accounted for. The project will develop approximate analytical procedures that are applicable to large systems and will evaluate the accuracy of these approximations using Monte Carlo simulation. The computations will be validated by comparing the results predicted by these models with historical data.