Title: A coordinated and optimised scheduling method for integrated energy systems based on improved genetic algorithm

Authors: Yuanliang Zhang; Bin Guo; Liyu Huang; Yin Zheng

Addresses: Measurement Center of Guangzhou Power Supply, Bureau of Guangdong Power Grid, Guangzhou, 511495, China ' Measurement Center of Guangzhou Power Supply, Bureau of Guangdong Power Grid, Guangzhou, 511495, China ' Measurement Center of Guangzhou Power Supply, Bureau of Guangdong Power Grid, Guangzhou, 511495, China ' Measurement Center of Guangzhou Power Supply, Bureau of Guangdong Power Grid, Guangzhou, 511495, China

Abstract: A coordinated and optimised scheduling method for integrated energy systems based on improved genetic algorithm is proposed in order to improve the energy output efficiency of integrated energy systems. The multi-objective and multi-time dynamic loading model for an integrated energy system is constructed, and the power flow equation for the multi-energy network of electricity, gas and heat is established. The objective function for the coordinated scheduling model of the integrated energy system is designed by introducing the improved genetic algorithm, and the configuration parameters of the objective function are optimised by improving the crossover, variation and the rules of its own cold and heat conversion, so as to realise the coordinated and optimised scheduling of the integrated energy system and get the final scheduling model. The test results show that the proposed method can improve the balance of energy output and the energy efficiency of the system and shorten the convergence time.

Keywords: improved genetic algorithm; comprehensive energy; system coordination; optimise scheduling; power flow equation for multi energy network.

DOI: 10.1504/IJETP.2023.134163

International Journal of Energy Technology and Policy, 2023 Vol.18 No.3/4/5, pp.195 - 207

Received: 27 Apr 2023
Accepted: 03 Jul 2023
Published online: 12 Oct 2023 *

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