Abstract
Developing offshore wind power—one of the most promising renewable energy sources—is considered to be an effective measure by China to promote energy transformation and achieve carbon neutrality. The integration of offshore wind with energy storage facilities can improve wind energy opportunities and mitigate the disharmony between energy generation and supply. This study develops a mathematical model to optimise a high capacity offshore wind-pumped-storage hybrid power system with Non-dominant Sorting Genetic Algorithm with Elite Strategy (NSGA-Ⅱ). We optimised various objects and compared the results. The results showed that the positive effects of increased electricity sales revenue could not always balance the negative effects of increased investments after configuring energy storage. Moreover, the simulation of the pumping state, discharging state, and state of charge (SOC) examined the system performance. The annual energy distribution analysed quantitively the reservoirs utilisation frequency and energy utilisation efficiency, which revealed the effect of design variables on pumping and discharging operation. Additionally, the effects of system stability constraints and load demand levels on the economic benefits, system performance, and CO2 emission reduction were compared and analysed. The adaptability of the optimal configurations to high load demand was tested. Finally, the sensitivity analysis provided clear guidance on external financial parameters for subsidy backslope.
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