(185w) The Optimization of Integrated Energy System Under Uncertainty Based on Genetic Algorithm

The integrated energy system is a multi-energy flow coupling system which includes the energy production, transportation, distribution, conversion and storage processes. It has greatly improved the efficiency since the system achieves cascade utilization of energy. The cold, heat and electricity can be transformed into each other in the system for the peak load shifting. In order to solve the increasingly serious resources and environmental problems, many countries regard the integrated energy system as the future development strategy. However, the design of the integrated energy system are quite complex because of the obvious volatility and uncertainty of the renewable energy and energy load.

In this work, the mathematical model of integrated energy system was established which included wind power generation, solar power generation and energy storage technology. According to the energy demand characteristics and the renewable energy resources conditions, the uncertain parameters of the model were presented based on historical data. In this paper, a database which contains various device parameters such as the price and equipment efficiency was set up, concerning the current development status of related energy equipment. Furthermore, an corresponding equations were also given to describe the relationship between equipment capacity and these parameters. Moreover, the genetic algorithm was improved to optimize the system design parameters based on the uncertain parameters. Finally, the optimized design of the integrated energy system was obtained which contains the system composition and equipment parameters