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A model for hydrogen production and storage during deep peak-shaving (less than 30% of rated capacity) was established by coupling a gas turbine combined cycle (GTCC) unit with a solid oxide electrolysis cell (SOEC), demonstrating the feasibility of efficiently matching electrothermal resources within the system to accommodate renewable energy. Machine learning was used to predict GTCC variable-load power output, heat recovery boiler models were used to calculate steam parameters, and SOEC thermochemical models were applied to determine hydrogen production electricity and heat consumption. Results show that SOEC electrolysis voltage and hydrogen production can quickly respond to changes in input electrical energy, with the thermal inertia temperature difference of hydrogen production stabilizing at 25~27 ℃. When the peak shaving depth (the ratio of accommodated renewable energy to rated capacity) increased from 50% to 100%, the overall efficiency of the energy storage peak shaving system rose from 47.8% to 55.3%. Using GTCC-SOEC to accommodate renewable energy reduced the total energy consumption of hydrogen production from 6.7 kJ/m³ to 5.8 kJ/m³, with a reduction of 13.4%. SOEC hydrogen production heat consumption is about 80% of the electricity consumption, and the efficiency of the coupled hydrogen production system is only approximately 3.15%～3.34% lower than the efficiency of GTCC standalone peak-shaving power generation. For every 1% increase in peak shaving depth, hydrogen production increases by about 0.1 t/h, and CO2 emissions from natural gas combustion decrease by 0.64 t/h. Considering storage costs and weather impacts, when the unit operates for 8 hours per day, as the peak periods for wind and solar generation increase from 0 to 1.5 hours, the hydrogen blending volume ratio increases to 30%, and the average efficiency of the hydrogen storage-release cycle increases from the baseline 56.7% to 62.5%; When the daily online duration of renewable energy reaches 2.5 hours, the average efficiency within the cycle can reach 67.1%. When the ratio of peak-shaving subsidy to electricity price is less than 0.2, the cost-to-output ratio initially decreases and then increases with the ratio of stored to grid electricity. When the subsidy-to-electricity price ratio is greater than 0.2, the cost-to-output ratio continuously increases with the stored-to-grid electricity ratio.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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