虚拟电厂优化调度测算数据

为了优化虚拟电厂的运算量，提高虚拟电厂的调度控制时效性，利用虚拟电厂优化调度测算模型可以快速对复杂的数据进行过滤处理，减少优化运算量。基于优化调度测算模型可以科学的规划调度计划，提高虚拟电厂的调度控制时效性。算法规则包括以下几个方面：1、建立起三个目标函数：（1）最小功率偏差：，为功率偏差，Pi为第i个供电设备的输出功率，Pj为第j个用电设备的消耗功率，n1为供电设备数量，n2为用电设备数量；（2）最小线损：，L为线损，n3为输电线路数量，Cij是连接输电线路i和输电线路j的电导，Ui是输电线路i的电压，Uj是输电线路j的电压，θij为输电线路i和输电线路j的电压相角差；（3）最小运行成本：，F为总成本，F1为供电设备正常运行成本，F2为可中断负荷的投切成本，F3为火电厂运行的污染成本；2、对建立好的目标函数进行加权处理并整合，得到加权后的综合目标函数Z=0.5△P+0.3L+0.2F，综合目标函数Z为最终优化计算函数，用以优化虚拟电厂的运算量；3、优化过程：选定综合目标函数中权重最大的参数变量，并以选定的参数变量为基础对综合目标函数归一化处理，得到综合目标函数的最优解，例如以功率偏差△P为权重最大的参数变量时，就以功率偏差△P为基础对综合目标函数Z进行归一化处理，最终得到最优解，提高虚拟电厂的调度控制时效性。

To optimize the computational load of virtual power plants (VPPs) and improve the timeliness of their scheduling and control, the optimal scheduling calculation model for virtual power plants can rapidly filter complex data and reduce the volume of optimization calculations. Additionally, the model can scientifically formulate scheduling plans to further enhance the timeliness of VPP scheduling and control. The algorithm rules are as follows:
1. Establish three objective functions:
(1) Minimum power deviation: ΔP, where ΔP represents the power deviation, Pi denotes the output power of the i-th power supply device, Pj denotes the consumption power of the j-th power consumption device, n1 is the number of power supply devices, and n2 is the number of power consumption devices;
(2) Minimum line loss: L, where L represents the line loss, n3 is the number of transmission lines, Cij is the conductance connecting transmission line i and transmission line j, Ui is the voltage of transmission line i, Uj is the voltage of transmission line j, and θij is the voltage phase angle difference between transmission line i and transmission line j;
(3) Minimum operating cost: F, where F represents the total cost, F1 is the normal operating cost of power supply equipment, F2 is the switching cost of interruptible loads, and F3 is the pollution emission cost of thermal power plant operation;
2. Perform weighted processing and integration on the established objective functions to obtain the weighted comprehensive objective function Z = 0.5ΔP + 0.3L + 0.2F. The comprehensive objective function Z serves as the final optimization calculation function to optimize the computational load of virtual power plants;
3. Optimization process: Select the parameter variable with the largest weight in the comprehensive objective function, and normalize the comprehensive objective function based on the selected parameter variable to obtain the optimal solution of the comprehensive objective function. For example, when the power deviation ΔP is the parameter variable with the largest weight, normalize the comprehensive objective function Z based on ΔP to finally derive the optimal solution, thereby improving the timeliness of VPP scheduling and control.