针对区域综合能源系统(regional integrated e ner gy system,RIES)源荷主体互动少、碳排放强度高、风光消纳能力低以及整体运行效益差等问题,文中提出计及电-气-热价格需求响应的RIES经济低碳运行优化方法。利用电能、天然气、热能共...针对区域综合能源系统(regional integrated e ner gy system,RIES)源荷主体互动少、碳排放强度高、风光消纳能力低以及整体运行效益差等问题,文中提出计及电-气-热价格需求响应的RIES经济低碳运行优化方法。利用电能、天然气、热能共有的商品属性以及多元柔性负荷的可调度价值,建立电-气-热价格需求响应模型,有效增强了价格信号对负荷参与需求响应的激励效应;为充分挖掘系统的低碳潜力,引入阶梯型碳交易,完善实际碳排放模型;以系统运行成本最小为优化目标,研究不同运行方式对系统经济性和低碳性的影响。案例分析结果表明,所构建的运行优化模型采用价格需求响应和阶梯型碳交易协同优化方式,在实现负荷削峰填谷的同时可以兼顾系统运行的经济低碳性与风光消纳能力。展开更多
针对楼宇综合能源系统(residential integrated energy system,RIES)能量管理时未充分考虑影响室温因素及其对负荷建模的影响和刚性捆绑RIES、用户从未全面考虑用户舒适度和用能支出的问题,文中提出冷、热负荷参与阶梯型补贴和电负荷参...针对楼宇综合能源系统(residential integrated energy system,RIES)能量管理时未充分考虑影响室温因素及其对负荷建模的影响和刚性捆绑RIES、用户从未全面考虑用户舒适度和用能支出的问题,文中提出冷、热负荷参与阶梯型补贴和电负荷参与电价型综合需求响应的RIES能量管理优化模型及其求解方法。首先,综合考虑影响室温因素,得到离散化的楼宇热平衡方程,建立楼宇的柔性而非固定的冷、热、电负荷数学模型。其次,建立冷、热负荷参与的阶梯型补贴和电负荷参与的电价型综合需求响应机制。然后,考虑RIES向用户售能的收益、从外部购能的成本和支付用户的补贴费用,构建以最大化RIES运行利润为目标、计及设备和系统运行约束的能量管理优化数学模型,并采用Cplex对线性化后的模型进行求解。最后,通过算例仿真表明:计及综合需求响应的RIES能量管理优化能统筹协调供需两侧资源,提升系统与用户的经济效益。展开更多
随着《碳排放权交易管理办法》的正式实施,加速了碳排放权交易的进度,在此背景下考虑区域综合能源系统(regional integrated energy system,RIES)接入配网后需求响应、可再生资源消纳和碳排放交易成本的影响,提出一种新的配电网规划方...随着《碳排放权交易管理办法》的正式实施,加速了碳排放权交易的进度,在此背景下考虑区域综合能源系统(regional integrated energy system,RIES)接入配网后需求响应、可再生资源消纳和碳排放交易成本的影响,提出一种新的配电网规划方法。首先,对区域综合能源系统结构进行概述,介绍典型区域综合能源系统的构成及特点;其次,将碳交易成本、弃风弃光成本和需求响应引入配电网扩展模型当中,综合考虑系统的碳排放、弃风弃光和需求侧响应对区域综合能源系统的影响,促进系统整体的优化运行。在上述基础上构建考虑区域综合能源系统优化的配网扩展优化双层模型,采用改进粒子群算法(improved particle swarm optimization,IPSO)和预测校正内点法(prediction correction interior point method,PCIP)求解规划层和运行层模型。最后,运用算例系统对构建的模型和方法进行验证。结果表明:配电网扩展规划时,充分考虑区域综合能源系统优化,能够提升可再生能源的消纳,降低整体的扩展规划成本。展开更多
A novel parameter extraction technique suitable f or short channel length lightly-doped-drain (LDD) MOSFET's is proposed which seg ments the total gate bias range,and executes the linear regression in every subs ...A novel parameter extraction technique suitable f or short channel length lightly-doped-drain (LDD) MOSFET's is proposed which seg ments the total gate bias range,and executes the linear regression in every subs ections,yielding the gate bias dependent parameters,such as effective channel le ngth,parasitic resistance,and mobility,etc.This method avoids the gate bias rang e optimization,and retains the accuracy and simplicity of linear regression.The extracted gate bias dependent parameters are implemented in the compact I-V model which has been proposed for deep submicron LDD MOSFET's.The good agreemen ts between simulations and measurements of the devices on 0.18μm CMOS technolo gy indicate the effectivity of this technique.展开更多
This paper proposes a distributed robust optimal dispatch model to enhance information security and interaction among the operators in the regional integrated energy system(RIES).Our model regards the distribution net...This paper proposes a distributed robust optimal dispatch model to enhance information security and interaction among the operators in the regional integrated energy system(RIES).Our model regards the distribution network and each energy hub(EH)as independent operators and employs robust optimization to improve operational security caused by wind and photovoltaic(PV)power output uncertainties,with only deterministic information exchanged across boundaries.This paper also adopts the alternating direction method of multipliers(ADMM)algorithm to facilitate secure information interaction among multiple RIES operators,maximizing the benefit for each subject.Furthermore,the traditional ADMM algorithm with fixed step size is modified to be adaptive,addressing issues of redundant interactions caused by suboptimal initial step size settings.A case study validates the effectiveness of the proposed model,demonstrating the superiority of the ADMM algorithm with adaptive step size and the economic benefits of the distributed robust optimal dispatch model over the distributed stochastic optimal dispatch model.展开更多
In the electricity market environment,the regional integrated energy system(RIES)can reduce the total operation cost by participating in electricity market transactions.However,the RIES will face the risk of load and ...In the electricity market environment,the regional integrated energy system(RIES)can reduce the total operation cost by participating in electricity market transactions.However,the RIES will face the risk of load and electricity price uncertainties,which may make its operation cost higher than expected.This paper proposes a method to optimize the operation cost of the RIES in the electricity market environment considering uncertainty.Firstly,based on the operation cost structure of the RIES in the electricity market environment,the energy flow relationship of the RIES is analyzed,and the operation cost model of the RIES is built.Then,the electricity purchase costs of the RIES in the medium-and long-term electricity markets,the spot electricity market,and the retail electricity market are analyzed.Finally,considering the risk of load and electricity price uncertainties,the operation cost optimization model of the RIES is established based on conditional value-at-risk.Then it is solved to obtain the operation cost optimization strategy of the RIES.Verification results show that the proposed operation cost optimization method can reduce the operation cost of high electricity price scenario by optimizing the energy purchase and distribution strategy,constrain the risk of load and electricity price uncertainties,and help balance the risks and benefits.展开更多
To reduce environmental pollution and improve the efficiency of cascaded energy utilization, regional integrated energy system(RIES) has received extensive attention. An accurate multi-energy load prediction is signif...To reduce environmental pollution and improve the efficiency of cascaded energy utilization, regional integrated energy system(RIES) has received extensive attention. An accurate multi-energy load prediction is significant for RIES as it enables stakeholders to make effective decisions for carbon peaking and carbon neutrality goals. To this end, this paper proposes a multivariate two-stage adaptive-stacking prediction(M2ASP) framework. First, a preprocessing module based on ensemble learning is proposed. The input data are preprocessed to provide a reliable database for M2ASP, and highly correlated input variables of multi-energy load prediction are determined. Then, the load prediction results of four predictors are adaptively combined in the first stage of M2ASP to enhance generalization ability. Predictor hyper-parameters and intermediate data sets of M2ASP are trained with a metaheuristic method named collaborative atomic chaotic search(CACS) to achieve the adaptive staking of M2ASP. Finally, a prediction correction of the peak load consumption period is conducted in the second stage of M2ASP. The case studies indicate that the proposed framework has higher prediction accuracy, generalization ability, and stability than other benchmark prediction models.展开更多
储能设备可以实现负荷的跨时段平移,在综合能源系统的经济稳定运行中能够起到重要作用。但当下储能投建费用较高,难以大规模应用。而通过优化用户侧可控负荷,可达到类似储能设备平移负荷的效果。从电能、热能2个角度出发,提出了利用用...储能设备可以实现负荷的跨时段平移,在综合能源系统的经济稳定运行中能够起到重要作用。但当下储能投建费用较高,难以大规模应用。而通过优化用户侧可控负荷,可达到类似储能设备平移负荷的效果。从电能、热能2个角度出发,提出了利用用户侧虚拟储能的区域综合能源系统(regional integrated energy system,RIES)优化调度策略。首先基于电动汽车充电管理方法和楼宇蓄热特性,对电、热虚拟储能(virtual energy storage,VES)系统进行建模;进而将虚拟储能系统集成到考虑天气不确定性的区域综合能源系统调度模型中,该模型以降低能源系统日运行费用为优化目标,合理安排电动汽车充电并在温度舒适度范围内对建筑物室温进行调节,实现虚拟储能系统的充放能管理;最后以夏季系统用能场景为例,对优化模型进行仿真实证。仿真结果表明,虚拟储能设备可以起到负荷平移效果,削减储能配置容量。应用虚拟储能系统的区域综合能源系统优化调度模型可以在满足能源需求和温度舒适度的前提下降低系统日运行成本,提升系统运行稳定性。展开更多
为兼顾区域综合能源系统(regional integrated energy system,RIES)中能耗成本、污染排放、风电消纳等多个调度目标,建立了考虑综合需求响应的RIES多目标优化模型。首先,对含电转气、储能系统、热电联产机组等设备的RIES建模,并在区域...为兼顾区域综合能源系统(regional integrated energy system,RIES)中能耗成本、污染排放、风电消纳等多个调度目标,建立了考虑综合需求响应的RIES多目标优化模型。首先,对含电转气、储能系统、热电联产机组等设备的RIES建模,并在区域内引入了具体考虑削减负荷、转移负荷和替代负荷的综合需求响应,旨在削减系统负荷峰谷差。然后,分别建立了以系统用能成本、弃风功率和污染物治理成本最小的目标函数,采用多目标优化方法——以模糊加权规划遍历权值求解帕累托前沿,再根据证据推理决策方法寻找最优调度策略。最后基于典型算例研究,结果表明了所提多目标优化算法能有效在多个调度目标间做出权衡,考虑综合需求响应的RIES在总能耗、环境友好和风电消纳等方面更具优势。展开更多
针对可再生能源发电的消纳以及冷热电负荷需求不匹配问题,文章在原有区域综合能源系统(regional integrated energy system,RIES)的基础上,引入电转气(power to gas,P2G)技术,同时结合综合能源系统内不同种类可平移负荷的用能特性,建立...针对可再生能源发电的消纳以及冷热电负荷需求不匹配问题,文章在原有区域综合能源系统(regional integrated energy system,RIES)的基础上,引入电转气(power to gas,P2G)技术,同时结合综合能源系统内不同种类可平移负荷的用能特性,建立了各类可平移负荷模型,对冷热电负荷平移,利用内点法求解可平移负荷模型,建立涵盖经济、能源及环境等多方面的多目标系统运行优化模型,采用粒子群优化算法获得Pareto非劣解集,并利用模糊理论获得折中解。在算例中设置多种场景,仿真分析考虑负荷平移和电转气技术的区域综合能源系统在降低系统运行成本、削峰填谷等方面的优势,从而验证所搭建模型的有效性。展开更多
文摘针对区域综合能源系统(regional integrated e ner gy system,RIES)源荷主体互动少、碳排放强度高、风光消纳能力低以及整体运行效益差等问题,文中提出计及电-气-热价格需求响应的RIES经济低碳运行优化方法。利用电能、天然气、热能共有的商品属性以及多元柔性负荷的可调度价值,建立电-气-热价格需求响应模型,有效增强了价格信号对负荷参与需求响应的激励效应;为充分挖掘系统的低碳潜力,引入阶梯型碳交易,完善实际碳排放模型;以系统运行成本最小为优化目标,研究不同运行方式对系统经济性和低碳性的影响。案例分析结果表明,所构建的运行优化模型采用价格需求响应和阶梯型碳交易协同优化方式,在实现负荷削峰填谷的同时可以兼顾系统运行的经济低碳性与风光消纳能力。
文摘针对楼宇综合能源系统(residential integrated energy system,RIES)能量管理时未充分考虑影响室温因素及其对负荷建模的影响和刚性捆绑RIES、用户从未全面考虑用户舒适度和用能支出的问题,文中提出冷、热负荷参与阶梯型补贴和电负荷参与电价型综合需求响应的RIES能量管理优化模型及其求解方法。首先,综合考虑影响室温因素,得到离散化的楼宇热平衡方程,建立楼宇的柔性而非固定的冷、热、电负荷数学模型。其次,建立冷、热负荷参与的阶梯型补贴和电负荷参与的电价型综合需求响应机制。然后,考虑RIES向用户售能的收益、从外部购能的成本和支付用户的补贴费用,构建以最大化RIES运行利润为目标、计及设备和系统运行约束的能量管理优化数学模型,并采用Cplex对线性化后的模型进行求解。最后,通过算例仿真表明:计及综合需求响应的RIES能量管理优化能统筹协调供需两侧资源,提升系统与用户的经济效益。
文摘A novel parameter extraction technique suitable f or short channel length lightly-doped-drain (LDD) MOSFET's is proposed which seg ments the total gate bias range,and executes the linear regression in every subs ections,yielding the gate bias dependent parameters,such as effective channel le ngth,parasitic resistance,and mobility,etc.This method avoids the gate bias rang e optimization,and retains the accuracy and simplicity of linear regression.The extracted gate bias dependent parameters are implemented in the compact I-V model which has been proposed for deep submicron LDD MOSFET's.The good agreemen ts between simulations and measurements of the devices on 0.18μm CMOS technolo gy indicate the effectivity of this technique.
基金supported in part by the National Natural Science Foundation of China(No.52107085)the Natural Science Foundation of Jiangsu Province(No.BK20210367)。
文摘This paper proposes a distributed robust optimal dispatch model to enhance information security and interaction among the operators in the regional integrated energy system(RIES).Our model regards the distribution network and each energy hub(EH)as independent operators and employs robust optimization to improve operational security caused by wind and photovoltaic(PV)power output uncertainties,with only deterministic information exchanged across boundaries.This paper also adopts the alternating direction method of multipliers(ADMM)algorithm to facilitate secure information interaction among multiple RIES operators,maximizing the benefit for each subject.Furthermore,the traditional ADMM algorithm with fixed step size is modified to be adaptive,addressing issues of redundant interactions caused by suboptimal initial step size settings.A case study validates the effectiveness of the proposed model,demonstrating the superiority of the ADMM algorithm with adaptive step size and the economic benefits of the distributed robust optimal dispatch model over the distributed stochastic optimal dispatch model.
基金supported in part by the Research Project of Digital Grid Research Institute,China Southern Power Grid(No.YTYZW20010)in part by the Research and Development Program Project in Key Areas of Guangdong Province(No.2021B0101230003)in part by the National Natural Science Foundation of China(No.51907031)。
文摘In the electricity market environment,the regional integrated energy system(RIES)can reduce the total operation cost by participating in electricity market transactions.However,the RIES will face the risk of load and electricity price uncertainties,which may make its operation cost higher than expected.This paper proposes a method to optimize the operation cost of the RIES in the electricity market environment considering uncertainty.Firstly,based on the operation cost structure of the RIES in the electricity market environment,the energy flow relationship of the RIES is analyzed,and the operation cost model of the RIES is built.Then,the electricity purchase costs of the RIES in the medium-and long-term electricity markets,the spot electricity market,and the retail electricity market are analyzed.Finally,considering the risk of load and electricity price uncertainties,the operation cost optimization model of the RIES is established based on conditional value-at-risk.Then it is solved to obtain the operation cost optimization strategy of the RIES.Verification results show that the proposed operation cost optimization method can reduce the operation cost of high electricity price scenario by optimizing the energy purchase and distribution strategy,constrain the risk of load and electricity price uncertainties,and help balance the risks and benefits.
基金supported in part by Science and Technology Project of the Headquarters of State Grid Corporation of China (No. 5100-202155018A-0-0-00)the National Natural Science Foundation of China (No. 51807134)+1 种基金the State Key Laboratory of Power System and Generation Equipment (No. SKLD21KM10)the Natural Science and Engineering Research Council of Canada (NSERC)(No. RGPIN-2018-06724)。
文摘To reduce environmental pollution and improve the efficiency of cascaded energy utilization, regional integrated energy system(RIES) has received extensive attention. An accurate multi-energy load prediction is significant for RIES as it enables stakeholders to make effective decisions for carbon peaking and carbon neutrality goals. To this end, this paper proposes a multivariate two-stage adaptive-stacking prediction(M2ASP) framework. First, a preprocessing module based on ensemble learning is proposed. The input data are preprocessed to provide a reliable database for M2ASP, and highly correlated input variables of multi-energy load prediction are determined. Then, the load prediction results of four predictors are adaptively combined in the first stage of M2ASP to enhance generalization ability. Predictor hyper-parameters and intermediate data sets of M2ASP are trained with a metaheuristic method named collaborative atomic chaotic search(CACS) to achieve the adaptive staking of M2ASP. Finally, a prediction correction of the peak load consumption period is conducted in the second stage of M2ASP. The case studies indicate that the proposed framework has higher prediction accuracy, generalization ability, and stability than other benchmark prediction models.
文摘储能设备可以实现负荷的跨时段平移,在综合能源系统的经济稳定运行中能够起到重要作用。但当下储能投建费用较高,难以大规模应用。而通过优化用户侧可控负荷,可达到类似储能设备平移负荷的效果。从电能、热能2个角度出发,提出了利用用户侧虚拟储能的区域综合能源系统(regional integrated energy system,RIES)优化调度策略。首先基于电动汽车充电管理方法和楼宇蓄热特性,对电、热虚拟储能(virtual energy storage,VES)系统进行建模;进而将虚拟储能系统集成到考虑天气不确定性的区域综合能源系统调度模型中,该模型以降低能源系统日运行费用为优化目标,合理安排电动汽车充电并在温度舒适度范围内对建筑物室温进行调节,实现虚拟储能系统的充放能管理;最后以夏季系统用能场景为例,对优化模型进行仿真实证。仿真结果表明,虚拟储能设备可以起到负荷平移效果,削减储能配置容量。应用虚拟储能系统的区域综合能源系统优化调度模型可以在满足能源需求和温度舒适度的前提下降低系统日运行成本,提升系统运行稳定性。
文摘为兼顾区域综合能源系统(regional integrated energy system,RIES)中能耗成本、污染排放、风电消纳等多个调度目标,建立了考虑综合需求响应的RIES多目标优化模型。首先,对含电转气、储能系统、热电联产机组等设备的RIES建模,并在区域内引入了具体考虑削减负荷、转移负荷和替代负荷的综合需求响应,旨在削减系统负荷峰谷差。然后,分别建立了以系统用能成本、弃风功率和污染物治理成本最小的目标函数,采用多目标优化方法——以模糊加权规划遍历权值求解帕累托前沿,再根据证据推理决策方法寻找最优调度策略。最后基于典型算例研究,结果表明了所提多目标优化算法能有效在多个调度目标间做出权衡,考虑综合需求响应的RIES在总能耗、环境友好和风电消纳等方面更具优势。
文摘针对可再生能源发电的消纳以及冷热电负荷需求不匹配问题,文章在原有区域综合能源系统(regional integrated energy system,RIES)的基础上,引入电转气(power to gas,P2G)技术,同时结合综合能源系统内不同种类可平移负荷的用能特性,建立了各类可平移负荷模型,对冷热电负荷平移,利用内点法求解可平移负荷模型,建立涵盖经济、能源及环境等多方面的多目标系统运行优化模型,采用粒子群优化算法获得Pareto非劣解集,并利用模糊理论获得折中解。在算例中设置多种场景,仿真分析考虑负荷平移和电转气技术的区域综合能源系统在降低系统运行成本、削峰填谷等方面的优势,从而验证所搭建模型的有效性。