Abstract
Wind power generation is uncertain and intermittent accentuating variability. Currently in many power systems worldwide, the total generation-load unbalance caused by mismatch between forecast and actual wind power output is handled by automatic governor control and real-time 5-minute balancing markets, which are operated by the independent system operators for maintaining reliable operation of power systems. Mechanisms such as automatic governor control and real-time 5-minute balancing markets are in place to correct the mismatch between the load forecast and the actual load. They are not designed to address increased uncertainty and variability introduced by large-scale wind power or solar power generation expected in the future. Thus, large-scale wind power generation with increased uncertainty and intermittency causing variability poses a techno-economic challenge of sourcing least cost load balancing services (reserve).
Highlights
Modern power system researchers focus on a wide range of challenges related to technology, as well as economics, environment and policy
An intraday (
We propose the use of binomial trees to model potential variation of wind energy output from the forecasted value
Summary
Modern power system researchers focus on a wide range of challenges related to technology, as well as economics, environment and policy. Rapid technological advancements such as variable speed wind generators, larger turbine sizes, lower wind speed operation capability, developments in offshore turbines, etc., have propelled the significant growth of wind electricity generation recorded in the past decade (Fig. 1.1). In this chapter we introduce the concept of historic volatility of wind energy inspired by the Black-Scholes mathematical model This approach provides us the ability to estimate wind energy forecast error by using the historic values of recorded energy for each wind farm comparing with forecasts. This chapter reports on a method for wind producers to buy reserve from reserve providers to mitigate the uncertainty using the Black-Scholes mathematical model for pricing the options and for estimating the amount of possible errors in wind energy forecast for a future time span. This research integrates the network security constraints into the whole framework of reserve trades via our proposed option market
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