Optimized Demand-Side Day-Ahead Generation Scheduling Model for a Wind-Photovoltaic-Energy Storage Hydrogen Production System

Abstract

This paper proposed an optimized day-ahead generation model involving hydrogen-load demand-side response, with an aim to make the operation of an integrated wind-photovoltaic-energy storage hydrogen production system more cost-efficient. Considering the time-of-use electricity pricing plan, demand for hydrogen load, and the intermittency of renewable energy, the model has the ambition to achieve minimum daily cost of operating a hydrogen production system. The model is power-balanced, fit for energy storage devices, and developed through adaptive simulated annealing particle swarm optimization. Analysis results showed that the proposed optimized scheduling model helped avoid the significant purchase of electric power at peak times and reduced the cost of running the hydrogen production system, ensuring that the daily hydrogen energy produced could meet the daily demand for the gas load. This justified how the model and its algorithm were correctly and efficiently applied.