考虑主动配电网下多区域综合能源系统间电能交互的优化调度策略

碳达峰碳中和的背景下、主动配电网(active distribution network, ADN)下多主体间能源共享有助于消纳弃风弃光。但随着各微网内风机光伏容量日益增加，每日微网净负荷峰谷趋势变化明显。传统分时电价逐渐很难发挥对微网的削峰填谷作用。提出考虑主动配电网下多主体能源共享调度策略，以主动配电网向下级微网的售电收益减去向主网购电成本所得净收益最大为目标函数，充分考虑下级多微网在电网议价下以微网自身运行成本最低为目标的调度自主性，运用卡罗需-库恩-塔克(Karush-Kuhn-Tucker, KKT)条件将下级多主体电能共享联盟运行成本最低的目标转化为上级目标的约束条件。引入KKT乘子，同时运用大M法对非线性约束进行线性化处理，提高模型求解速度。在MATLAB的Gurobi环境下，对连续的上下层耦合变量乘积进行离散化处理。最后，在IEEE33节点的主动配电网算例中验证所提模型的有效性。

The optimal scheduling strategy of energy mutual economy among multi-regional integrated energy systems under active distribution network is considered

Under the background of carbon peak carbon neutrality, energy sharing among multiple entities in Active Distribution Network (ADN) helps to absorb wind and light. However, the growing wind and photovoltaic capacity within microgrids has resulted in more pronounced daily fluctuations in net load. This has rendered traditional time-of-use electricity pricing less effective in mitigating peak demand and filling valleys in mi-crogrids. To address this issue, this study presents a novel scheduling strategy that takes into account the shared energy among multiple entities within the ADN framework. The objective is to maximize the net income by deducting the electricity purchase cost from the electricity sales revenue generated within the ADN and dis-tributed to sub-level microgrids. Furthermore, the strategy takes into consideration the scheduling autonomy of the sub-level microgrids, which aim to minimize their own operating costs under the pricing policies of the electricity grid. To achieve this optimization, the study transforms the sub-levels'' goal of minimizing operating costs into a constraint on the super-level objective function by employing Karush-Kuhn-Tucker (KKT) multi-pliers. The KKT multipliers are employed along with the big M method to linearize the nonlinear constraints, thereby improving the computational efficiency of the model. Additionally, the continuous coupled variables between the upper and lower levels are discretized in the Matlab Gurobi environment. The effectiveness of the proposed scheduling strategy is evaluated through a case study carried out on an active distribution network implemented in the IEEE 33-node system. This analysis demonstrates the practical feasibility and benefits of the model for optimizing energy distribution within the ADN framework.