Optimal scheduling of HIES considering green certificate-carbon trading and flexible output of heat and power
|更新时间:2025-10-16
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Optimal scheduling of HIES considering green certificate-carbon trading and flexible output of heat and power
Vol. 44, Issue 3, Pages: 86-96(2025)
作者机构:
贵州大学电气工程学院,贵州,贵阳,550025
作者简介:
基金信息:
DOI:
CLC:TK9;TM7
Published:2025
稿件说明:
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FAN Shuaizhi. Optimal scheduling of HIES considering green certificate-carbon trading and flexible output of heat and power[J]. 2025, 44(3): 86-96.
DOI:
FAN Shuaizhi. Optimal scheduling of HIES considering green certificate-carbon trading and flexible output of heat and power[J]. 2025, 44(3): 86-96.DOI:
Optimal scheduling of HIES considering green certificate-carbon trading and flexible output of heat and power
摘要
为提升综合能源系统的低碳性与经济性,充分挖掘灵活需求,提出一种基于绿证-碳交易和热电灵活输出的含氢综合能源系统(hydrogen-containing integrated energy system
To improve the low-carbon efficiency and economy of the integrated energy system
while fully utilizing demand-side flexibility
a hydrogen-containing integrated energy system (HIES) based on green certificate-carbon trading and flexible output of heat and power is proposed. Firstly
the traditional combined heat and power (CHP) is coupled with organic Rankine cycle (ORC) and electric boiler (EB) to allow flexible operation
enabling the power generated by gas turbine (GT) to be supplied simultaneously to the power grid and EB. The heat energy released is simultaneously used for ORC and EB
alleviating the constraints of thermoelectric coupling. Secondly
a green certificate-carbon trading model is constructed by integrating green certificate trading with tiered carbon emission trading
which reduces the system's carbon emissions and improves the consumption of renewable energy. The influence of the green certificate unit price and the renewable energy quota coefficient on the system's optimal scheduling is analyzed. Additionally
the model includes electrolyzers and hydrogen fuel cells
fully considering the diversified utilization of hydrogen energy
thereby improving the system's low-carbon efficiency. Lastly
a day-ahead optimal scheduling model is constructed with the goal of minimizing the total cost of the system. The results demonstrate that this strategy can enhance renewable energy consumption while reducing carbon emissions and total system costs.