需求响应激励下耦合电转气、碳捕集设备的综合能源系统优化OA北大核心CSTPCD
Optimization of Integrated Energy System Coupled with Power-to-Gas and Carbon Capture and Storage Equipment under Demand Response Incentive
为了充分调动用户侧柔性负荷资源,发挥氢能的低碳特性,本文提出了一种需求响应激励下耦合两阶段电转气和碳捕集设备的综合能源系统优化方法.首先,构建两阶段电转气、碳捕集、氢燃料电池和储氢罐等设备组成的氢基综合能源系统.其次,结合负荷能源转换间耦合关系与调节特性,引入阶梯型需求响应激励机制并对补偿基价、区间长度、价格增长率 3 个参数进行自适应优化.最后,设置多种场景,用多目标灰狼算法对系统的供能侧、需求侧和阶梯型需求响应激励机制进行优化求解.结果表明,基于此方法系统运行的总成本和CO2 排放量都有所降低.
In order to fully mobilize user-side flexible load resources and take advantage of the low-carbon characteristics of hydrogen energy,this paper proposes an integrated energy system optimization method coupled with two-stage power-to-gas and carbon capture and storage(CCS)equipment under demand response incentive.Firstly,a hydrogen-based integrated energy system consisting of two-stage power-to-gas,CCS,hydrogen fuel cells,and hydrogen storage tanks is constructed.Secondly,combined with the conversion coupling relationship between load and energy,and the flexibility characteristics,the stepped demand response incentive mechanism is introduced,and adaptive optimization is conducted for three parameters including compensation base price,interval length and price growth rate.Finally,multiple scenarios are set up,and the multi-objective gray wolf algorithm is used to optimally solve the the supply-side,demand-side,and stepped demand response incentive mechanism of the system.The results show that the total cost of the system operation and CO2 emissions are reduced with the proposed method.
高月芬;员成博;孔凡鹏;王雪松
华北电力大学能源动力与机械工程学院,河北保定 071003||华北电力大学河北省低碳高效发电技术重点实验室,河北保定 071003
综合能源系统柔性负荷阶梯型需求响应激励机制电转气多目标灰狼算法
integrated energy systemflexible loadstepped demand response incentivespower-to-gasmulti-objective grey wolf algorithm
《中国电力》 2024 (004)
32-41 / 10
国家自然科学基金资助项目(52276007). This work is supported by National Natural Science Foundation of China(No.52276007).
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