Enhancing the economic efficiency of wind-photovoltaic‑hydrogen complementary power systems via optimizing capacity allocation

Daohong Wei, Mengwei He, Jingjing Zhang, Dong Liu, Md Apel Mahmud

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Renewable energy generation has emerged as an important strategy in achieving dual carbon. However, the inherent randomness and uncontrollability of major new energy resources present significant challenges for the safe and stable operation of power system. Advanced energy storage technologies are essential to enhance the stability of grid-connected power system incorporating wind and solar energy resources. Reasonable allocation of wind power, photovoltaic (PV), and energy storage capacity is the key to ensuring the economy and reliability of power system. To achieve this goal, a mathematical model of the wind-photovoltaic‑hydrogen complementary power system (WPHCPS) is established to achieve economical and reliable system operation. A control algorithm based on the composite grey wolf optimization (GWO) and particle swarm optimization (PSO) is proposed for the maximum power point tracking (MPPT) of PV system as well as capacity allocation of WPHCPS. Finally, a case demonstrating the optimal capacity configuration scheme is quantitatively analyzed, where the load shortage rate and abandonment rate of wind and solar power are considered. The quantified results show that the optimal operating scene is 50 wind turbines, 2521 PV arrays, 25 batteries, 30 electrolytic cells, 38 hydrogen storage tanks, and 54 hydrogen fuel cells, with the total revenue 232,895.9 CNY. The wind and solar abandonment rate and load interruption rate are 0.36 % and 0.21 %, respectively. The methods and results obtained provide a reference for improving the consumption and stability of the complementary power system and achieving sustainable utilization of clean energy.

Original languageEnglish
Article number114531
Number of pages20
JournalJournal of Energy Storage
Volume104
Issue numberPart B
Early online date15 Nov 2024
DOIs
Publication statusPublished - 20 Dec 2024

Keywords

  • Grey wolf and particle swarm optimization combination algorithms
  • Hydrogen storage
  • MPPT
  • Optimal capacity allocation
  • Wind-photovoltaic‑hydrogen complementary power system

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