基于新能源承载能力的配电网电采暖负荷动态优化调度策略研究OACSTPCD

With the increasing penetration rate of new energy in the distribution network,the bearing capacity of new energy in the distribution network is facing challenges;The electric heating load has a certain degree of adjustability and has the potential to participate in the load dispatch of the distribution network.How to improve the new energy bearing capacity of the distribution network through load dispatch has important practical significance.The article proposes a dynamic optimization scheduling strategy for electric heating loads in distribution networks that considers the bearing capacity of new energy.Firstly,a regulation model for the load of thermal storage electric heating was constructed;Then,with the goal of bearing capacity of new energy in the distribution network substation area,and with the constraints of smoothing load fluctuations,stable and safe operation of the distribution network,and user comfort of the heating load,a dynamic optimization scheduling model for the heating load of the distribution network was established,and a solution strategy based on quantum genetic algorithm was proposed.The Latin hypercube sampling method is used to generate typical application scenarios for the applicability analysis of dispatching strategies for the new energy bearing capacity of distribution networks.The calculation results show that the proposed method can fully consider the potential for regulating the electric heating load and improve the application level of new energy in the distribution network.