This paper applies double-uncertainty optimization theory to the operation of AC/DC hybrid microgrids to deal with uncertainties caused by a high proportion of intermittent energy sources.A fuzzy stochastic expectatio...This paper applies double-uncertainty optimization theory to the operation of AC/DC hybrid microgrids to deal with uncertainties caused by a high proportion of intermittent energy sources.A fuzzy stochastic expectation economic model for day-ahead scheduling based on uncertain optimization theory is proposed to minimize the operational costs of hybrid AC/DC microgrids.The fuzzy stochastic alternating direction multiplier method is proposed to solve the double-uncertainty optimization problem.A real-time intra-day unbalanced power adjustment model is established to minimize real-time adjustment costs.Through comparative analysis of deterministic optimization,stochastic optimization and fuzzy stochastic optimization of day-ahead scheduling and real-time adjustment,the validity of fuzzy stochastic optimization based on a fuzzy stochastic expectation model is proved.展开更多
基金supported by the National Natural Science Foundation of China(No.51577068)Science&Technology Foundation of SGCC(No.520201150012)
文摘This paper applies double-uncertainty optimization theory to the operation of AC/DC hybrid microgrids to deal with uncertainties caused by a high proportion of intermittent energy sources.A fuzzy stochastic expectation economic model for day-ahead scheduling based on uncertain optimization theory is proposed to minimize the operational costs of hybrid AC/DC microgrids.The fuzzy stochastic alternating direction multiplier method is proposed to solve the double-uncertainty optimization problem.A real-time intra-day unbalanced power adjustment model is established to minimize real-time adjustment costs.Through comparative analysis of deterministic optimization,stochastic optimization and fuzzy stochastic optimization of day-ahead scheduling and real-time adjustment,the validity of fuzzy stochastic optimization based on a fuzzy stochastic expectation model is proved.
