Two-stage scheduling model optimization method for integrated energy system

Abstract

The invention discloses a two-stage scheduling model optimization method for an integrated energy system. The method comprises the following steps: S1, constructing a day-ahead economic scheduling model according to the operation cost of system equipment; S2, correcting the operation state of each micro-unit based on the day-ahead economic scheduling model, and constructing a real-time optimization scheduling model; S3, based on the real-time optimization scheduling model, improving a population variation mode by mapping a chaotic crisscross algorithm so as to ensure population diversity and all information of excellent individuals; and S4, constructing a two-stage scheduling optimization solving process based on a CCSO-BOS algorithm. According to the method, a day-ahead scheduling optimization model and a real-time scheduling optimization model of the comprehensive energy system are established on the basis of load prediction and renewable energy processing prediction data. The proposed multi-objective nonlinear optimization problem can be solved, so that renewable energy can be consumed and utilized to the maximum extent. The operation cost of the system is effectively reduced.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of integrated energy, and in particular to a two-stage scheduling model optimization method for an integrated energy system. Background technique [0002] As an important carrier of the Energy Internet, the integrated energy system (Integrated energy system, IES) can efficiently utilize a variety of renewable energy sources, and provide users with various energy application methods such as cold, heat, and electricity, so as to exert the potential of complementary advantages of various energy sources. , can promote the on-site consumption of renewable energy such as solar energy and wind energy, and realize the optimal utilization of resources. Domestic scholars have constructed a variety of comprehensive energy system economic scheduling models. Brainstorm algorithm is a brand-new swarm intelligence optimization algorithm. It mainly simulates the process of human beings to propose c...

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Problems solved by technology

[0005] To this end, the embodiment of the present invention provides a two-stage scheduling model optimization method for integrated energy systems, based on load forecasting and renewable energy processing forecast data, to establish a day-ahead and real-time two-stage scheduling optimization model for integrated energy systems; Solve the problem that the existing technology onl

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