Multi-target unit combination intelligent optimization system based on power g state identification

Abstract

The invention belongs to the technical field of power system control and relates to a multi-target unit combination intelligent optimization system based on power network state identification. The multi-target unit combination intelligent optimization system is an intelligent dynamic modeling model formed by an optimization calculation module and a power network parameter acquisition module, optimization calculation is related to awaiting distribution amount introduction and distribution result derivation, the power network parameter acquisition module is connected with an energy control system, and the energy control system supplies data to the power network parameter acquisition module. The multi-target unit combination intelligent optimization system based on power network state identification is an improvement of the traditional unit combination optimization mode, automatically identifies a power network real-time operation state by utilizing a knowledge base system and is automatically configured with a multi-target optimization unit combination model according to a certain regulation based on the power network operation state. Starting from power dispatch reality, the invention converts various target optimization problems to optimization sequencing problems based on different regulations of each unit in a feasible range, thereby conveniently dispatching results of observation, explanation and evaluation optimization calculation of decision making persons.

Description

technical field [0001] The present invention belongs to the technical field of electric power system control, and in particular relates to a multi-objective unit combination intelligent optimization system based on power grid state recognition, specifically improving the existing unit combination optimization mode, using the knowledge base system to operate the power grid in real time The state is automatically identified, and according to the operating state of the power grid, the corresponding multi-objective optimization unit combination model is automatically configured according to certain rules. Background technique [0002] With the reform of the power system and power dispatching model, the optimization goal of power economic dispatch has gone through several different stages: [0003] Under the traditional dispatching mode, the power grid and the power plant are not separated, and they are the main body of common interests. The main goal of dispatching optimization ...

AI Technical Summary

Problems solved by technology

[0013] The preset optimization model is a compromise model that considers various operating states of the power grid. This model can satisfy various optimization objectives to a certain extent, but it cannot fully achieve optimization for any single objective; multi-objective optimization The model is not to consider the more optimization objectives, the more constraints, and the more complex the model, the better. An overly complex model will not only reduce the correctness and credibility of the model, but also cause a decrease in solution accuracy, an increase in calculation time, and data loss. Reduced storage space and transmission efficiency

[0014] 2) The optimization model is static and cannot meet the needs of intelligent dispatching of the power grid

[0015] Power grid operation data is dynamically changing, and the importance of multiple optimization objectives is also changing in different power grid states. In the above process, the requirements for intelligent grid dispatching management continue to increase, and it is objectively necessary to achieve a specific one under different operating states. Or the optimization of several objectives, the optimization model is a preset, static model, which cannot meet the demand for dynamic adjustment of the model due to real-time changes in the power grid state, and the existing unit combination mode cannot meet the requirements of intelligent dispatching

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