The park-level integrated energy system(PIES)is essential for achieving carbon neutrality by managing multi-energy supply and demand while enhancing renewable energy integration.However,current carbon trading mechanis...The park-level integrated energy system(PIES)is essential for achieving carbon neutrality by managing multi-energy supply and demand while enhancing renewable energy integration.However,current carbon trading mechanisms lack sufficient incentives for emission reductions,and traditional optimization algorithms often face challenges with convergence and local optima in complex PIES scheduling.To address these issues,this paper introduces a low-carbon dispatch strategy that combines a reward-penalty tiered carbon trading model with P2G-CCS integration,hydrogen utilization,and the Secretary Bird Optimization Algorithm(SBOA).Key innovations include:(1)A dynamic reward-penalty carbon trading mechanism with coefficients(μ=0.2,λ=0.15),which reduces carbon trading costs by 47.2%(from$694.06 to$366.32)compared to traditional tiered models,incentivizing voluntary emission reductions.(2)The integration of P2G-CCS coupling,which lowers natural gas consumption by 41.9%(from$4117.20 to$2389.23)and enhances CO_(2) recycling efficiency,addressing the limitations of standalone P2G or CCS technologies.(3)TheSBOA algorithm,which outperforms traditionalmethods(e.g.,PSO,GWO)in convergence speed and global search capability,avoiding local optima and achieving 24.39%faster convergence on CEC2005 benchmark functions.(4)A four-energy PIES framework incorporating electricity,heat,gas,and hydrogen,where hydrogen fuel cells and CHP systems improve demand response flexibility,reducing gas-related emissions by 42.1%and generating$13.14 in demand response revenue.Case studies across five scenarios demonstrate the strategy’s effectiveness:total operational costs decrease by 14.7%(from$7354.64 to$6272.59),carbon emissions drop by 49.9%(from 5294.94 to 2653.39kg),andrenewable energyutilizationincreases by24.39%(from4.82%to8.17%).These results affirmthemodel’s ability to reconcile economic and environmental goals,providing a scalable approach for low-carbon transitions in industrial parks.展开更多
在“双碳”背景下,园区中的电动汽车(Electric Vehicle,EV)运行须要在有序充放电的基础上考虑碳排放因素,从而更好地服务于园区低碳化能量管理。文章提出了一种考虑EV低碳充放电响应的园区能量优化管理方法,以充分发挥EV低碳特性,进一...在“双碳”背景下,园区中的电动汽车(Electric Vehicle,EV)运行须要在有序充放电的基础上考虑碳排放因素,从而更好地服务于园区低碳化能量管理。文章提出了一种考虑EV低碳充放电响应的园区能量优化管理方法,以充分发挥EV低碳特性,进一步降低碳排放。首先,基于碳排放流理论提出了EV单位电能含碳率(Carbon Rate per Unit of Electricity,CRUE)的概念,用于构建EV的碳排放流模型;然后,提出了EV低碳充放电响应模型,建立了个性化的EV充放电定价机制;最后,提出了基于个性化充放电电价和充电站动态碳排放因子引导的EV低碳充放电决策模型。算例分析结果表明,文章提出的能量管理方法可以激励EV用户提高车-网互动积极性,在提高园区经济效益的同时,还可以降低11%的系统碳排放量。展开更多
针对“双碳”目标下园区综合能源系统(Park-level integrated energy system,PIES)与充电站(Charging station,CS)协同调度中利益协调不足、碳配额机制应用不充分的问题,提出一种双层优化模型,弥补现有研究对CS独立运营经济诉求的忽视,...针对“双碳”目标下园区综合能源系统(Park-level integrated energy system,PIES)与充电站(Charging station,CS)协同调度中利益协调不足、碳配额机制应用不充分的问题,提出一种双层优化模型,弥补现有研究对CS独立运营经济诉求的忽视,并挖掘电动汽车碳配额交易在多主体场景下的潜力。上层以PIES运行成本最小化为目标,结合可再生能源出力与负荷供需关系设计灵活定价机制;下层以CS收益最大化为目标,构建电动汽车(Electric vehicle,EV)碳配额核算与交易模型,通过出售多余配额提升收益。模型中引入序列运算理论处理可再生能源与负荷不确定性,将机会约束规划转化为混合整数线性规划问题,并利用CPLEX求解。仿真结果显示,灵活定价机制与碳配额交易协同作用下,园区运行成本降低6.92%,充电站收益提高76.49%,验证了EV碳配额交易在平衡多主体利益、提升系统经济性与环境效益中的有效性。展开更多
基金funded by State Grid Beijing Electric Power Company Technology Project,grant number 520210230004.
文摘The park-level integrated energy system(PIES)is essential for achieving carbon neutrality by managing multi-energy supply and demand while enhancing renewable energy integration.However,current carbon trading mechanisms lack sufficient incentives for emission reductions,and traditional optimization algorithms often face challenges with convergence and local optima in complex PIES scheduling.To address these issues,this paper introduces a low-carbon dispatch strategy that combines a reward-penalty tiered carbon trading model with P2G-CCS integration,hydrogen utilization,and the Secretary Bird Optimization Algorithm(SBOA).Key innovations include:(1)A dynamic reward-penalty carbon trading mechanism with coefficients(μ=0.2,λ=0.15),which reduces carbon trading costs by 47.2%(from$694.06 to$366.32)compared to traditional tiered models,incentivizing voluntary emission reductions.(2)The integration of P2G-CCS coupling,which lowers natural gas consumption by 41.9%(from$4117.20 to$2389.23)and enhances CO_(2) recycling efficiency,addressing the limitations of standalone P2G or CCS technologies.(3)TheSBOA algorithm,which outperforms traditionalmethods(e.g.,PSO,GWO)in convergence speed and global search capability,avoiding local optima and achieving 24.39%faster convergence on CEC2005 benchmark functions.(4)A four-energy PIES framework incorporating electricity,heat,gas,and hydrogen,where hydrogen fuel cells and CHP systems improve demand response flexibility,reducing gas-related emissions by 42.1%and generating$13.14 in demand response revenue.Case studies across five scenarios demonstrate the strategy’s effectiveness:total operational costs decrease by 14.7%(from$7354.64 to$6272.59),carbon emissions drop by 49.9%(from 5294.94 to 2653.39kg),andrenewable energyutilizationincreases by24.39%(from4.82%to8.17%).These results affirmthemodel’s ability to reconcile economic and environmental goals,providing a scalable approach for low-carbon transitions in industrial parks.
文摘在“双碳”背景下,园区中的电动汽车(Electric Vehicle,EV)运行须要在有序充放电的基础上考虑碳排放因素,从而更好地服务于园区低碳化能量管理。文章提出了一种考虑EV低碳充放电响应的园区能量优化管理方法,以充分发挥EV低碳特性,进一步降低碳排放。首先,基于碳排放流理论提出了EV单位电能含碳率(Carbon Rate per Unit of Electricity,CRUE)的概念,用于构建EV的碳排放流模型;然后,提出了EV低碳充放电响应模型,建立了个性化的EV充放电定价机制;最后,提出了基于个性化充放电电价和充电站动态碳排放因子引导的EV低碳充放电决策模型。算例分析结果表明,文章提出的能量管理方法可以激励EV用户提高车-网互动积极性,在提高园区经济效益的同时,还可以降低11%的系统碳排放量。
