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1 Overview
Due to the complexity of the power system itself, power flow optimization has the characteristics of large scale, many constraints and nonlinearity. By solving the optimal power flow, the goal of optimizing existing resources, reducing power plant consumption cost, reducing power grid line loss, and improving power transmission capacity of power system is finally achieved, which is more economical than traditional power flow calculation. Therefore, the optimal power flow is a subject of concern in the power system, and there are many researches on it.
The history of the formation of the optimization method is relatively short. It mainly uses mathematical means to propose various system optimization methods and schemes, and provides the basis for scientific decision-making for the operation of the power system. The optimal power flow problem requires that the algorithm has a fast convergence speed, and also requires a brief introduction of the algorithm and a small amount of calculation, so that it can be solved by computer. The commonly used methods for solving it include: linear programming method, quadratic programming method, gradient and Newton-like algorithms, interior point method and intelligent method.
2 cases
2.1 Example description
Taking the most economical system fuel as the objective function of the optimal power flow, obtain the optimal power flow calculation of the most economical system fuel for the simplified system shown in Figure 2. The line transmission power boundary, the upper and lower bounds of generator active and reactive power output, and the parameters of the fuel consumption curve are shown in Table 1 and Table 2, respectively. All data are given in per-unit form, the power reference value is 100 MV·A, and the bus voltage upper and lower bounds are 1.1 and 0.9, respectively.
For the above system, in this example, there are 5 nodes in total, and the corresponding state quantities are
2.2 Data
3 Matlab implementation
3.2 Power flow calculation of distribution network (implemented by Python & Matlab)
3.4 Economic dispatch of microgrid (wind, solar, energy storage)