Determining reserve requirements in systems with significant stochastic generation capacity using copulas

The large-scale integration of stochastic generation requires additional operating reserves to cope with the uncertainty in power system operation, due to the large forecast error with existing methodologies. Previous research shows that allocating power reserves dynamically according to conditional distribution of power forecast error would benefit the generation scheduling in day-ahead electricity market. Therefore, this paper applies the empirical copula model to estimate the dynamic operating reserves, via formulating the joint probability distribution of forecast errors for multiple wind farms and photovoltaic (PV) plants. Simulation results demonstrate that the proposed probabilistic method can facilitate more accurate scheduling of dynamic reserves for stochastic generation, in the electricity market with large shares of wind and solar power.