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

Research on dynamic optimal dispatching strategy of electricheating load in distribution network consideringthe bearing capacity of new energy

随着配电网中新能源渗透率的增加,配电网新能源承载能力受到挑战。电采暖负荷有一定的可调节性,具有参与配电网负荷调度的潜力,如何通过负荷调度提升配电网新能源承载能力具有重要现实意义。文章提出一种考虑新能源承载能力的配电网电采暖负荷动态优化调度策略。首先,构建了蓄热式电采暖负荷的调控模型;然后,以配电网台区新能源承载能力为目标,以配电网负荷波动平抑、配电网稳态安全运行和电采暖负荷用户舒适性为约束,建立了配电网电采暖负荷动态优化调度模型,并提出基于量子遗传算法的求解策略。采用拉丁超立方抽样法生成典型应用场景,进行配电网新能源承载能力调度策略的适用性分析。算例结果表明,所提方法能够充分考虑电采暖负荷的调控潜力,提高配电网新能源的应用水平。

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.