Abstract:

To achieve the goals of carbon peaking and carbon neutrality,we must lower the hydrogen production cost, expand the application of electric energy,alleviate the fluctuations of new energy and facilitate the local consumption of renewable energy. One of the key technologies to solve these problems is to realize hydrogen production powered by local wind and solar power. To optimize the comprehensive benefit of a wind-solar-hydrogen energy system and reduce wind and solar power curtailment loss and the loss of suppliers caused by interrupted load, a return maximization model for the system is established. The model has taken the system's investment, operation and maintenance costs, costs and profits of hydrogen selling,oxygen selling, electric power selling and purchasing,as well as the penalty for wind and solar power curtailment and interrupted load into consideration. The upper limit of the electric energy purchased by or sell to the main network is considered in the penalty function of wind and solar power curtailment and interrupted load, to avoid the imbalance of the system caused by the over-limit power. Introducing adaptive inertia weight into the designed adaptive particle swarm optimization algorithm can effectively avoid the algorithm from falling into the local optimal solution in seeking the optimal capacity allocation scheme of the model. The simulation results show that the optimal scheme can minimize the wind and solar power curtailment ratios and load interruption in a typical month, and effectively improve the comprehensive benefit of the system.

Key words: carbon neutrality, wind-solar-hydrogen system, renewable energy, wind and solar power curtailment, hydrogen production, microgrid, load interruption, capacity allocation, adaptive particle swarm algorithm