Abstract
There is an increasing need to understand the impact of high-penetration wind power on various aspects of power system operation. This study presents a methodology to evaluate the impact of market price volatility on intermittent wind power. The proposed methodology first considers the uncertainty of wind power using a probabilistic distribution of wind speed in combination with the rated speed–MW curve. The correlation among different wind power plants is also modelled. With these statistical models, a Monte Carlo simulation (MCS) approach can be used to assess the probabilistic distribution of the price signals, that is, the probabilistic locational marginal pricing (LMP) distribution. Since the computational effort of MCS is intensive, a lookup table is proposed as preprocessing to greatly simplify the MCS. The proposed approach is tested with the PJM 5-bus system and the IEEE 118-bus system. Rules of thumb are drawn regarding the probabilistically calculated LMP and the correlation coefficients.
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