计及发电量不确定性的风电场配储容量优化OA

The wind power industry generally uses the comprehensive reduction coefficient to estimate power generation,but this approach is overly simplistic for the distribution and storage decision.The determination of energy storage capacity for a wind farm should not only prioritize high economic benefits but also control the risk to deal with different working conditions.In order to quantitatively evaluate the impact of exceedance probability on the energy storage capacity configuration and economy of wind farms,this paper takes a wind farm in Shanxi as a case study,employs Monte Carlo simulation to develop a normal probability distribution model for reduction factors and calculates the exceedance probability of the wind farm's power generation.Subsequently,the research optimizes the energy storage capacity by taking the power generation as a variable and aiming to maximize the net profit of the wind storage system.The findings indicate that the power generation forecasts for the same wind power project vary significantly across different exceedance probabilities,leading to divergent optimal energy storage capacities based on these varying power generation outcomes.Consequently,decision-makers must account for uncertainty risks in the allocation and storage strategies to enhance the overall economic viability of the wind storage project.The incorporation of exceedance probability enhances the flexibility and precision of decision-making in wind power projects,thereby facilitating the effective allocation of reserves for such initiatives.