Price forecast valuation for the NYISO electricity market

Following the deregulation of electricity markets in the USA, independent power producers operate as for-profit entities. Their profit depends on the price of electricity and an accurate forecast is critical in making bidding decisions on the electricity and reserve markets or engaging in bilateral contracts. Competing price forecasts have their accuracy expressed in statistical terms but producers need to determine the long-term value of using a given forecast. The purpose of this paper is to address this issue by presenting a method of electricity price forecast valuation which compares forecast models using financial rather than statistical measures.

The objectives of this paper are achieved by mathematical modeling of thermal power plants and price forecast information available to market participants and simulating the operation of a thermal power plant using various price forecasts and perfect information (as a baseline). The operating profit calculated over a long period was used for ranking forecast models.

The framework can be used to estimate the value of a new price forecast as well as to determine if potential gains from developing or acquiring a new forecast will justify the expenses. The results show that an improvement in terms of statistical forecast accuracy measures does not guarantee increased profit.

This paper presents a new method for comparing electricity price forecast models. It can be adapted to various types of thermal power plants that operate on liberalized electricity markets and utilize price-based dynamic economic dispatch models.

This paper presents a simulation-based valuation framework for short-term electricity price. The approach described in this paper can be utilized by independent power producers for different types of generators, operating on deregulated electricity markets.