Distributionally Robust Optimization Collaborative Planning Method for Transmission Network External Channel and Energy Storage with High Proportion of Renewable Energy
In response to the significant challenges posed by strong randomness,centralized,and high-capacity integration of wind and photovoltaic power to the safe operation of the transmission network and the consumption of new energy,this paper considers the uncertainty and time correlation of wind and photovoltaic output,and proposes a distributionally robust optimization(DRO)collaborative planning method for the external transmission channels and energy storage in the transmission network with a high proportion of renewable energy.Firstly,the planning of the external transmission channels and energy storage are jointly used as decision variables and the surplus renewable energy resources are sent out through the external transmission channels.Secondly,the functions of energy storage for peak shaving,valley filling and suppressing the random fluctuations of new energy are used to promote the full consumption of renewable energy.Then,using techniques such as second-order cone convex relaxation and Taylor series expansion,the original mixed integer non-convex nonlinear programming model is transformed into a mixed integer convex programming model to achieve efficient solution.Finally,an improved IEEE 39 bus transmission system is taken as a case study to verify the validity of the proposed model and method.
high proportion of renewable energytransmission network planningcollaborative planningdistributionally robust optimizationtime correlation
万方数据
维普
