Multi-period reactive power optimization method and device for power grid

Abstract

The embodiment of the invention provides a multi-period reactive power optimization method and device for a power grid, and belongs to the technical field of power grid reactive power optimization. The method comprises the steps: calculating an objective function and a constraint condition of a day-ahead plan control stage according to line parameters and operation characteristic parameters, establishing a day-ahead plan control model, calculating an objective function and a constraint condition of an intra-day real-time control stage, and establishing an intra-day real-time control model; performing second-order conic convexity relaxation processing on power flow constraint equations of the day-ahead plan control model and the intra-day real-time control model, and determining a mixed integer second-order conic programming multi-period model; and solving the mixed integer second-order cone programming multi-period model, and determining an optimal control strategy. Due to the fact that the second-order cone relaxation technology is adopted for conducting convex relaxation processing on the alternating current power flow equation in the second-order cone relaxation technology, the non-convex nonlinear problem is converted into a linear equation with a convex feasible region, thereby greatly reducing the solving difficulty. Therefore, a global optimal solution can be rapidly calculated, and the optimal control strategy of the coordinated reactive power control equipment can be obtained.

Description

technical field [0001] The invention relates to the technical field of power grid reactive power optimization, in particular to a multi-period reactive power optimization method and device for a power grid. Background technique [0002] At present, the demand for electricity load continues to grow, and traditional energy sources are in short supply. In this case, a large number of new energy bases on the power supply side generate power and connect to the grid, and renewable energy on the load side participates in power generation extensively and with high density in a distributed manner. However, because its operating characteristics are affected by the environment, the output on both sides of the source and load has obvious randomness, coupled with the uncertainty of load fluctuations, it brings challenges to the operation control of the transmission network, such as voltage fluctuations, network losses and other issues. [0003] In order to stabilize the voltage and redu...

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Problems solved by technology

The mathematical essence of dynamic reactive power optimization is a non-convex nonlinear programming problem. For this type of problem, commonly used optimization algorithms include: particle swarm optimization algorithm, genetic algorithm, tabu search algorithm, immune algorithm, primal dual interior point method, etc. It has advantages, but due to the difficulty of calculation, it is more difficult to find the optimal solution, and it is easy to get the local optimal solution instead of the global optimal solution

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