An LMP forecasting method considering the transmission loss and the correlation among stochastic wind power outputs

The global environmental concern has promoted the installed capacity of renewable energy to explode. The uncertainty of the growing renewable energy poses a risk of incorrect forecasting of clearing prices and misled strategies to participants in the deregulated power markets. However, the transmission loss and the correlation among integrated wind power outputs are ignored in the existing research. To improve the forecasting accuracy, this paper presents a Markov Chain Monte Carlo method for stochastic LMP considering the correlation among wind power outputs and transmission loss. The expectation of an LMP with a given precision can be obtained from the proposed method. The case study verifies the validity of the proposed method, demonstrating that the squared Euclidean distance of the selected Archimedean Copula function is limited to 9.3143. Additionally, given the same convergence criteria, the sampling times are reduced by an order of magnitude compared to the Acceptance-Rejection sampling method.