Abstract
The proposed study presents a novel probabilistic method for optimal allocation of spinning reserves taking into consideration load, wind and solar forecast errors, inter-zonal spinning reserve trading, and demand response provided by consumers as a single framework. The model considers the system contingencies due to random generator outages as well as the uncertainties caused by load and renewable energy forecast errors. The study utilizes a novel approach to model wind speed and its direction using the bivariate parametric model. The proposed model is applied to the IEEE two-area reliability test system (RTS) to analyze the influence of inter-zonal power generation and demand response (DR) on the adequacy and economic efficiency of energy systems. In addition, the study analyzed the effect of the bivariate wind prediction model on obtained results. The results demonstrate that the presence of inter-zonal capacity in ancillary service markets reduce the total expected energy not supplied (EENS) by 81.66%, while inclusion of a DR program results in an additional 1.76% reduction of EENS. Finally, the proposed bivariate wind prediction model showed a 0.27% reduction in spinning reserve requirements, compared to the univariate model.