Two-stage optimization scheduling method supporting source-network-load-storage multivariate ubiquitous coordination

Abstract

The invention relates to a two-stage optimization scheduling method supporting source network load storage multivariate ubiquitous coordination. The method comprises the following steps: 1, a day-ahead stage: predicting next-day data according to historical data and a load uncertainty model considering demand side management; 2, taking low-carbon economy as a target, considering a deep peak regulation working condition and a normal operation working condition of the thermal power generating unit, carrying out random sampling by utilizing a Monte Carlo method, and solving a day-ahead low-carboneconomy scheduling model by utilizing a hybrid bat algorithm to obtain a low-carbon economy scheduling model; 3, in the intra-day stage, according to the ultra-short-term prediction values of the wind power plant and the photovoltaic power station and the intra-day system load considering the day-ahead price demand response, based on an intra-day thermal power generating unit correction model andan intra-day low-carbon economic dispatching model, determining the unit start-stop combination and the price and price type demand response quantity of each time period; and solving and adjusting the day-ahead scheduling plan by using a hybrid bat algorithm. The low-carbon economic dispatching of the power system is realized, the local optimum in a high-dimensional condition is effectively avoided, and the global optimal solution is quickly obtained.

Description

technical field [0001] The invention relates to the technical field of electric power system and automation thereof, in particular to the low-carbon economic dispatching of the electric power system, and in particular to a two-stage optimal dispatching method supporting multi-element ubiquitous coordination of source-network-load-storage. Background technique [0002] With the vigorous promotion of the construction of the strong smart grid and the ubiquitous power Internet of Things, a high proportion of renewable energy is connected to the grid, and artificial intelligence, sensors, and advanced communication technologies obtain comprehensive new energy, energy storage, and load data for application. Optimal scheduling of power systems. Facing the smart grid with high penetration rate of new energy, it is very urgent to make full use of source-load-storage data to solve the problem of low-carbon economic dispatch of wind power, photovoltaic power generation, thermal power, ...

AI Technical Summary

Problems solved by technology

The continuous penetration of new energy has brought great difficulties to the peak regulation of the power grid. Thermal power units are often in the state of deep peak regulation and frequent slope climbing, which has a great impact on the operation of the entire system.

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