A real-time operation strategy optimization method and system for an integrated energy system

Abstract

The invention discloses a real-time operation strategy optimization method and system for an integrated energy system, and the method comprises the following steps: building a multi-element load joint prediction model based on an improved pulse neural network, and obtaining an electric prediction load, a cold prediction load, and a heat prediction load; establishing a multi-dimensional comprehensive energy system evaluation system; taking an electric prediction load, a cold prediction load and a hot prediction load as load requirements, determining an optimization objective function according to a multi-dimensional comprehensive energy system evaluation system, and optimizing hourly output of each unit in the comprehensive energy system and solving by using a two-stage cooperation coevolution algorithm to obtain a real-time operation strategy of the comprehensive energy system; according to the invention, multiple optimization methods are used for collaborative optimization, so that the optimal operation strategy of the integrated energy system can be obtained more quickly and accurately.

Description

technical field [0001] The invention belongs to the technical field of operation strategy optimization of an integrated energy system, and in particular relates to a method and system for optimizing a real-time operation strategy of an integrated energy system. Background technique [0002] As an important component of the new generation energy system, the integrated energy system integrates various forms of energy supply, energy conversion and energy storage equipment, realizes the coupling of different types of energy in different links such as source, network, and load, and utilizes energy in cascades, thus Improve energy efficiency. [0003] A good and reliable operation strategy is the key to ensure the overall efficiency and performance of the integrated energy system. Since the electricity, cooling, and heat loads change over time and the changes are asynchronous, the integrated energy system should not adopt a single operation strategy. The operation strategy should ...

AI Technical Summary

Problems solved by technology

Therefore, accurate load forecasting is the primary prerequisite for optimizing the operation strategy of an integrated energy system. Most of the existing single load forecasting methods are based on traditional machine learning algorithms and deep learning algorithms. Traditional machine learning algorithms are highly efficient, and deep learning The prediction accuracy of the algorithm is higher, and the current prediction method is difficult to balance efficiency and accuracy

In addition, a single load forecasting method cannot cope with the complex coupling relationship between different types of loads

[0004] In the optimization of the operation strategy of the integrated energy system, the objective function and optimization method are important factors affecting the optimization of the operation strategy. The current objective function is more concerned with the economic and environmental benefits of the system, and there are fewer objective functions based on reliability, and it is difficult to balance them. Rapidity

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