Auxiliary Decision Method for Power Dispatching Based on Flexible Super-Capacitors and Proximal Policy Optimization Algorithm

Abstract

To reduce power waste and improve the operational safety of renewable energy grids, this study proposes an auxiliary decision-making method for power dispatching based on flexible super-capacitors and proximal policy optimization algorithms. The results demonstrated that the impedance of Mn&Ni-based composite electrodes was small, about $118~\Omega $ , and when the current density was 1A/g, the constant current charging and discharging time could reach 128 seconds, with a specific capacitance of 39F/g. In addition, when the power density of the capacitor was 8500W/kg, the energy density could reach up to 125Wh/kg. As for the auxiliary decision-making model for power dispatching, the reward value of the proximal policy optimization algorithm began to converge after approximately 50,000 iterations, at which point its reward value was approximately 257. The reward value of the one-step scheduling strategy gradually stabilized at around 1.0 after the number of scheduling steps reached 560,000. When the energy output rate of renewable energy units was high, the consumption rate of renewable energy was 90.1%. The above results indicate that the power scheduling method combining flexible super-capacitors and proximal policy optimization algorithms can effectively achieve the storage of electricity and improve the consumption rate of renewable energy.

Keywords

• Flexible super-capacitors
• composite materials
• proximal policy optimization
• power dispatch
• assisting decision-making