考虑低碳和柔性负荷的有源配电网混合整数二阶锥规划

Mixed-Integer Second-Order Cone Programming for Active Distribution Networks Considering Low-Carbon and Flexible Loads

在配电网低碳化背景下,提出了考虑碳排放和柔性负荷的有源配电网混合整数二阶锥规划模型,目标是在满足网络运行约束和CO_(2)排放上限的前提下,给出总成本最小的投资策略。考虑新能源、负荷和能源价格的不确定性,提出了基于k均值的场景聚类方法。模型的决策变量为更换过载线路、投建新能源和储能装置,以及投建稳压器和电容器组等电压控制设备,并考虑了多项式形式的电压相关型的柔性负荷、网络重构以及碳排放额约束。针对规划模型的非凸非线性特征,采用虚拟需求法将网络重构建模为混合整数线性规划形式,并提出了一种基于泰勒展开的改进二阶锥松弛方法,以解决柔性负荷模型给传统二阶锥松弛带来的难题。通过69节点系统对该模型进行测试,结果表明,所提模型不仅总规划成本较低,而且有助于减少碳排放。

In the context of low-carbon distribution network, this paper proposes a mixed-integer second-order cone programming model for active distribution networks considering carbon emissions and flexible loads, with the investment strategy with minimum total cost. Considering the uncertainty of renewable energy, load and energy price, a scenario clustering method based on K-means is proposed. The decision variables of the model are the replacement of overloaded lines, the construction of new energy and energy storage devices, and the construction of voltage control equipment such as voltage regulators and capacitor banks. The polynomial voltage-dependent flexible loads, network reconfiguration and carbon emission constraints are considered. Aiming at the non-convex nonlinear characteristics of the planning model, the virtual demand method is used to model the network reconstruction as a mixed integer linear programming form, and an improved second-order cone relaxation method based on Taylor expansion is proposed to solve the problem of traditional second-order cone relaxation caused by flexible load model. The model is tested with a 69-node system, and the results show that the proposed model not only has a lower overall planning cost, but also helps reduce carbon emissions.