Capacity optimization configuration of live gas storage system in independent power systems

Abstract

As the energy demand and the continuous improvement of environmental performance continuous grow, the use of Independent Power Systems (IPS) is becoming increasingly common. Energy storage facilities not only achieve reliable power supply through IPS, but also face the problem of how to achieve more efficient and energy-saving. Therefore, this paper chose to establish a charged gas storage system (GSS for short here) of an independent power system to establish the mathematical model of the GSS through the Linear programming model, including the energy balance equation of the GSS and the load balance equation of the power system. It then used genetic algorithm (GA) to optimize the capacity of the GSS and obtained the optimal capacity configuration plan. In the simulation experiment analysis of a live GSS in view of GA for capacity optimization configuration, the live GSS proposed in this paper outperformed traditional GSS and battery GSS in terms of performance, power load, energy conversion, and capacity configuration. In terms of power load, the six indexes of regulation capacity, response speed, stability, discharge efficiency, power density and energy storage capacity are compared. Among them, the system capacity designed in this paper is 90, 83, 97, 83 and 90 % respectively, which are much higher than the other two. Among them, the six dimensional power load capacity was outstanding, and the energy conversion efficiency was also around 80 %. The capacity configuration was distributed between 85 and 94. This article proposed a design scheme for an electrified GSS based on GA for capacity optimization configuration, which can better meet the needs of independent power systems and improve their reliability and stability.

Keywords

• Independent power system
• Electrified GSS
• Capacity-optimized configuration
• Genetic algorithm
• Optimal configuration