Driven by the goal of“carbon neutrality”and“emission peak”,effectively controlling system carbon emissions has become significantly important to governments around the world.To this end,a novel two-stage low-carbo...Driven by the goal of“carbon neutrality”and“emission peak”,effectively controlling system carbon emissions has become significantly important to governments around the world.To this end,a novel two-stage low-carbon economic scheduling framework that considers the coordinated optimization of ladder-type carbon trading and integrated demand response(IDR)is proposed in this paper for the integrated energy system(IES),where the first stage determines the energy consumption plan of users by leveraging the price-based electrical-heat IDR.In contrast,the second stage minimizes the system total cost to optimize the outputs of generations with consideration of the uncertainty of renewables.In addition,to fully exploit the system’s emission reduction potential,a carbon trading cost model with segmented CO_(2) emission intervals is built by introducing a reward-penalty ladder-type carbon trading mechanism,and the flexible thermal comfort elasticity of customers is taken into account by putting forward a predicted mean vote index on the load side.The CPLEX optimizer resolves the two-stage model,and the study results on a modified IES situated in North China show the proposed model can effectively reduce carbon emissions and guarantee economical efficiency operation of the system.展开更多
As new power systems and dual carbon policies develop,virtual power plant cluster(VPPC)provides another reliable way to promote the efficient utilization of energy and solve environmental pollution problems.To solve t...As new power systems and dual carbon policies develop,virtual power plant cluster(VPPC)provides another reliable way to promote the efficient utilization of energy and solve environmental pollution problems.To solve the coordinated optimal operation and low-carbon economic operation problem in multi-virtual power plant,a multi-virtual power plant(VPP)electricity-carbon interaction optimal scheduling model considering integrated demand response(IDR)is proposed.Firstly,a multi-VPP electricity-carbon interaction framework is established.The interaction of electric energy and carbon quotas can realize energy complementarity,reduce energy waste and promote low-carbon operation.Secondly,in order to coordinate the multiple types of energy and load in VPPC to further achieve low-carbon operation,the IDR mechanism based on the user comprehensive satisfaction(UCS)of electricity,heat as well as hydrogen is designed,which can effectively maintain the UCS in the cluster within a relatively high range.Finally,the unit output scheme is formulated to minimize the total cost of VPPC and the model is solved using theCPLEX solver.The simulation results showthat the proposed method effectively promotes the coordinated operation among multi-VPP,increases the consumption rate of renewable energy sources and the economics of VPPC and reduces carbon emissions.展开更多
综合需求响应(integrated demand response,IDR)作为区域综合能源系统(regional integrated energy system,RIES)维持供需平衡、实现分布式能源就地消纳的重要途径,已成为当下的研究热点。但现有IDR研究存在3个方面不足:综合能源服务商(...综合需求响应(integrated demand response,IDR)作为区域综合能源系统(regional integrated energy system,RIES)维持供需平衡、实现分布式能源就地消纳的重要途径,已成为当下的研究热点。但现有IDR研究存在3个方面不足:综合能源服务商(integrated energy service provider,IESP)制定激励策略时,未考虑区域内用户的响应疲劳特性;在实施IDR的复杂场景下,未考虑区域IESP间的响应责任交易;忽略响应责任与碳排放责任的耦合关系。为此,首先分析用户响应意愿随响应次数的演化特性,通过引入响应疲劳函数实现对用户响应疲劳特性的有效建模;在此基础上,根据IESP的响应任务类型,设置多个IESP参与IDR的复杂场景。进一步,为实现各IESP参与IDR的经济性与低碳性,在考虑复杂场景下IESP间响应责任交易时的能源转移与碳排放责任转移基础上,建立响应责任-碳排放责任耦合交易机制。最终,采用基于自适应迭代步长的议价方法以确定最优交易价格。通过仿真算例验证所提模型的有效性:考虑用户响应疲劳特性的改进模型使用户的总收益提升27%;所提交易机制不仅使各场景下IESP的总成本分别降低15.8%、9.8%、94.1%,还使典型场景下IESP的碳排放量降低17.8%,提高IESP参与IDR的经济性与低碳性,实现IESP与用户的共赢。展开更多
The integrated energy system(IES)is an important energy supply method for mitigating the energy crisis.A station-and-network–coordinated planning method for the IES,which considers the integrated demand responses(IDR...The integrated energy system(IES)is an important energy supply method for mitigating the energy crisis.A station-and-network–coordinated planning method for the IES,which considers the integrated demand responses(IDRs)of flexible loads,electric vehicles,and energy storage is proposed in this work.First,based on load substitution at the user side,an energy-station model considering the IDR is established.Then,based on the characteristics of the energy network,a collaborative planning model is established for the energy station and energy network of the IES,considering the comprehensive system investment,operation and maintenance,and clean energy shortage penalty costs,to minimize the total cost.This can help optimize the locations of the power lines and natural gas pipelines and the capacities of the equipment in an energy station.Finally,simulations are performed to demonstrate that the proposed planning method can help delay or reduce the construction of new lines and energy-station equipment,thereby reducing the investment required and improving the planning economics of the IES.展开更多
Hot dry rock(HDR)is rich in reserve,widely distributed,green,low-carbon,and has broad development potential and prospects.In this paper,a distributionally robust optimization(DRO)scheduling model for a regionally inte...Hot dry rock(HDR)is rich in reserve,widely distributed,green,low-carbon,and has broad development potential and prospects.In this paper,a distributionally robust optimization(DRO)scheduling model for a regionally integrated energy system(RIES)considering HDR co-generation is proposed.First,the HDR-enhanced geothermal system(HDR-EGS)is introduced into the RIES.HDR-EGS realizes the thermoelectric decoupling of combined heat and power(CHP)through coordinated operation with the regional power grid and the regional heat grid,which enhances the system wind power(WP)feed-in space.Secondly,peak-hour loads are shifted using price demand response guidance in the context of time-of-day pricing.Finally,the optimization objective is established to minimize the total cost in the RIES scheduling cycle and construct a DRO scheduling model for RIES with HDR-EGS.By simulating a real small-scale RIES,the results show that HDR-EGS can effectively promote WP consumption and reduce the operating cost of the system.展开更多
With the development of renewable energy technologies such as photovoltaics and wind power,it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through the deployment ...With the development of renewable energy technologies such as photovoltaics and wind power,it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through the deployment of energy storage.To solve the problem of the interests of different subjects in the operation of the energy storage power stations(ESS)and the integrated energy multi-microgrid alliance(IEMA),this paper proposes the optimization operation method of the energy storage power station and the IEMA based on the Stackelberg game.In the upper layer,ESS optimizes charging and discharging decisions through a dynamic pricing mechanism.In the lower layer,IEMA optimizes the output of various energy conversion coupled devices within the IEMA,as well as energy interaction and demand response(DR),based on the energy interaction prices provided by ESS.The results demonstrate that the optimization strategy proposed in this paper not only effectively balances the benefits of the IEMA and ESS but also enhances energy consumption rates and reduces IEMA energy costs.展开更多
Integrated energy system optimization scheduling can improve energy efficiency and low carbon economy.This paper studies an electric-gas-heat integrated energy system,including the carbon capture system,energy couplin...Integrated energy system optimization scheduling can improve energy efficiency and low carbon economy.This paper studies an electric-gas-heat integrated energy system,including the carbon capture system,energy coupling equipment,and renewable energy.An energy scheduling strategy based on deep reinforcement learning is proposed to minimize operation cost,carbon emission and enhance the power supply reliability.Firstly,the lowcarbon mathematical model of combined thermal and power unit,carbon capture system and power to gas unit(CCP)is established.Subsequently,we establish a low carbon multi-objective optimization model considering system operation cost,carbon emissions cost,integrated demand response,wind and photovoltaic curtailment,and load shedding costs.Furthermore,considering the intermittency of wind power generation and the flexibility of load demand,the low carbon economic dispatch problem is modeled as a Markov decision process.The twin delayed deep deterministic policy gradient(TD3)algorithm is used to solve the complex scheduling problem.The effectiveness of the proposed method is verified in the simulation case studies.Compared with TD3,SAC,A3C,DDPG and DQN algorithms,the operating cost is reduced by 8.6%,4.3%,6.1%and 8.0%.展开更多
A robust low-carbon economic optimal scheduling method that considers source-load uncertainty and hydrogen energy utilization is developed.The proposed method overcomes the challenge of source-load random fluctuations...A robust low-carbon economic optimal scheduling method that considers source-load uncertainty and hydrogen energy utilization is developed.The proposed method overcomes the challenge of source-load random fluctuations in integrated energy systems(IESs)in the operation scheduling problem of integrated energy production units(IEPUs).First,to solve the problem of inaccurate prediction of renewable energy output,an improved robust kernel density estimation method is proposed to construct a data-driven uncertainty output set of renewable energy sources statistically and build a typical scenario of load uncertainty using stochastic scenario reduction.Subsequently,to resolve the problem of insufficient utilization of hydrogen energy in existing IEPUs,a robust low-carbon economic optimal scheduling model of the source-load interaction of an IES with a hydrogen energy system is established.The system considers the further utilization of energy using hydrogen energy coupling equipment(such as hydrogen storage devices and fuel cells)and the comprehensive demand response of load-side schedulable resources.The simulation results show that the proposed robust stochastic optimization model driven by data can effectively reduce carbon dioxide emissions,improve the source-load interaction of the IES,realize the efficient use of hydrogen energy,and improve system robustness.展开更多
This paper collects and synthesizes the technical requirements, implementation, and validation methods for quasi-steady agent-based simulations of interconnectionscale models with particular attention to the integrati...This paper collects and synthesizes the technical requirements, implementation, and validation methods for quasi-steady agent-based simulations of interconnectionscale models with particular attention to the integration of renewable generation and controllable loads. Approaches for modeling aggregated controllable loads are presented and placed in the same control and economic modeling framework as generation resources for interconnection planning studies. Model performance is examined with system parameters that are typical for an interconnection approximately the size of the Western Electricity Coordinating Council(WECC) and a control area about 1/100 the size of the system. These results are used to demonstrate and validate the methods presented.展开更多
在我国“双碳”背景下,建立综合能源系统(integrated energy system,IES)已经成为实现“碳达峰”、“碳中和”目标,加快能源结构转型的重要举措,而综合需求响应(integrated demand response,IDR)是综合能源系统减少碳排放、缓解供需双...在我国“双碳”背景下,建立综合能源系统(integrated energy system,IES)已经成为实现“碳达峰”、“碳中和”目标,加快能源结构转型的重要举措,而综合需求响应(integrated demand response,IDR)是综合能源系统减少碳排放、缓解供需双侧不平衡的有效途径。然而,现有关于IDR的研究大多仅考虑其经济效益,未考虑其环境效益,忽略了需求侧用户对不同时段激励价格的比价行为以及不同用户的差异化响应特性。该文提出了基于碳排放因子的IDR碳排放折算模型,并将碳排放成本加入综合能源系统服务商(integrated energy system provider,IESP)的目标函数中;通过建立激励交叉弹性耦合矩阵对用户的比价行为进行了有效建模以提升模型的精确性;同时计及用户的差异化响应特性,通过制定差异化的激励策略以充分挖掘用户的响应潜力。所提模型被建立为一个IESP-用户双层优化模型,并将该模型转化为了一个单层的凸优化模型以实现高效地求解。最后通过仿真算例验证了模型的有效性,不仅减少了碳排放量,同时降低了IESP的响应成本并提升了用户的舒适度,实现了多方共赢。展开更多
为挖掘需求侧资源响应潜力,文中提出一种计及多重需求响应的综合能源系统(integrated energy system,IES)多时间尺度低碳调度策略。首先,考虑到需求侧资源在不同时间尺度下的响应差异性,建立计及价格型和激励型的多重综合需求响应(integ...为挖掘需求侧资源响应潜力,文中提出一种计及多重需求响应的综合能源系统(integrated energy system,IES)多时间尺度低碳调度策略。首先,考虑到需求侧资源在不同时间尺度下的响应差异性,建立计及价格型和激励型的多重综合需求响应(integrated demand response,IDR)模型。然后,为减少源、荷预测误差对IES运行的影响,分别构建日前低碳经济调度模型和日内双时间尺度滚动优化平抑模型。最后,算例仿真设置不同场景进行对比分析。结果表明,相比传统IDR,多重IDR能有效挖掘用户响应潜力,提升系统经济性。此外,计及多重IDR的多时间尺度调度策略能有效缓解源、荷误差带来的功率波动并降低系统碳排放量,实现IES低碳、经济和稳定运行。展开更多
为解决电力系统中电源侧和负荷侧的不确定性对电网调度计划的影响,针对电源侧,考虑风电与光伏出力的不确定性,分别建立风电与光伏的概率密度函数模型,通过拉丁超立方采样方法生成场景并进行缩减,从而得出风电与光伏出力区间;针对负荷侧...为解决电力系统中电源侧和负荷侧的不确定性对电网调度计划的影响,针对电源侧,考虑风电与光伏出力的不确定性,分别建立风电与光伏的概率密度函数模型,通过拉丁超立方采样方法生成场景并进行缩减,从而得出风电与光伏出力区间;针对负荷侧,考虑柔性负荷对电网消峰填谷的作用,提出基于智能小区的综合需求响应两阶段鲁棒优化模型。在日前阶段,以电网系统运行成本和碳交易成本最小为优化目标,考虑源荷的不确定性,基于价格需求响应模型,从而确定日前调度方案。在日内阶段,基于日前阶段优化结果,以智能小区运行成本和碳交易成本最小为优化目标,建立两阶段鲁棒优化模型,通过列约束生成(column-and-constraint generation,C&CG)算法将目标函数进行转换,采用Karush-Kuhn-Tucker条件和Big-M约束方法将max-min形式优化问题转化为混合整数线性规划(mixed integer linear programming,MILP)模型。最终,通过算例验证了所提模型的正确性以及算法的有效性。展开更多
基金supported by the State Grid Shandong Electric Power Company Economic and Technical Research Institute Project(SGSDJY00GPJS2100135).
文摘Driven by the goal of“carbon neutrality”and“emission peak”,effectively controlling system carbon emissions has become significantly important to governments around the world.To this end,a novel two-stage low-carbon economic scheduling framework that considers the coordinated optimization of ladder-type carbon trading and integrated demand response(IDR)is proposed in this paper for the integrated energy system(IES),where the first stage determines the energy consumption plan of users by leveraging the price-based electrical-heat IDR.In contrast,the second stage minimizes the system total cost to optimize the outputs of generations with consideration of the uncertainty of renewables.In addition,to fully exploit the system’s emission reduction potential,a carbon trading cost model with segmented CO_(2) emission intervals is built by introducing a reward-penalty ladder-type carbon trading mechanism,and the flexible thermal comfort elasticity of customers is taken into account by putting forward a predicted mean vote index on the load side.The CPLEX optimizer resolves the two-stage model,and the study results on a modified IES situated in North China show the proposed model can effectively reduce carbon emissions and guarantee economical efficiency operation of the system.
基金supported by the National Natural Science Foundation of China (NSFC) (Grant No.52107107).
文摘As new power systems and dual carbon policies develop,virtual power plant cluster(VPPC)provides another reliable way to promote the efficient utilization of energy and solve environmental pollution problems.To solve the coordinated optimal operation and low-carbon economic operation problem in multi-virtual power plant,a multi-virtual power plant(VPP)electricity-carbon interaction optimal scheduling model considering integrated demand response(IDR)is proposed.Firstly,a multi-VPP electricity-carbon interaction framework is established.The interaction of electric energy and carbon quotas can realize energy complementarity,reduce energy waste and promote low-carbon operation.Secondly,in order to coordinate the multiple types of energy and load in VPPC to further achieve low-carbon operation,the IDR mechanism based on the user comprehensive satisfaction(UCS)of electricity,heat as well as hydrogen is designed,which can effectively maintain the UCS in the cluster within a relatively high range.Finally,the unit output scheme is formulated to minimize the total cost of VPPC and the model is solved using theCPLEX solver.The simulation results showthat the proposed method effectively promotes the coordinated operation among multi-VPP,increases the consumption rate of renewable energy sources and the economics of VPPC and reduces carbon emissions.
文摘综合需求响应(integrated demand response,IDR)作为区域综合能源系统(regional integrated energy system,RIES)维持供需平衡、实现分布式能源就地消纳的重要途径,已成为当下的研究热点。但现有IDR研究存在3个方面不足:综合能源服务商(integrated energy service provider,IESP)制定激励策略时,未考虑区域内用户的响应疲劳特性;在实施IDR的复杂场景下,未考虑区域IESP间的响应责任交易;忽略响应责任与碳排放责任的耦合关系。为此,首先分析用户响应意愿随响应次数的演化特性,通过引入响应疲劳函数实现对用户响应疲劳特性的有效建模;在此基础上,根据IESP的响应任务类型,设置多个IESP参与IDR的复杂场景。进一步,为实现各IESP参与IDR的经济性与低碳性,在考虑复杂场景下IESP间响应责任交易时的能源转移与碳排放责任转移基础上,建立响应责任-碳排放责任耦合交易机制。最终,采用基于自适应迭代步长的议价方法以确定最优交易价格。通过仿真算例验证所提模型的有效性:考虑用户响应疲劳特性的改进模型使用户的总收益提升27%;所提交易机制不仅使各场景下IESP的总成本分别降低15.8%、9.8%、94.1%,还使典型场景下IESP的碳排放量降低17.8%,提高IESP参与IDR的经济性与低碳性,实现IESP与用户的共赢。
基金supported in part by the National Key R&D Program of China(2018YFB0905000)the Science and Technology Project of the State Grid Corporation of China(SGTJDK00DWJS1800232)
文摘The integrated energy system(IES)is an important energy supply method for mitigating the energy crisis.A station-and-network–coordinated planning method for the IES,which considers the integrated demand responses(IDRs)of flexible loads,electric vehicles,and energy storage is proposed in this work.First,based on load substitution at the user side,an energy-station model considering the IDR is established.Then,based on the characteristics of the energy network,a collaborative planning model is established for the energy station and energy network of the IES,considering the comprehensive system investment,operation and maintenance,and clean energy shortage penalty costs,to minimize the total cost.This can help optimize the locations of the power lines and natural gas pipelines and the capacities of the equipment in an energy station.Finally,simulations are performed to demonstrate that the proposed planning method can help delay or reduce the construction of new lines and energy-station equipment,thereby reducing the investment required and improving the planning economics of the IES.
基金King Saud University for funding this research through the Researchers Supporting Program Number(RSPD2024R704),King Saud University,Riyadh,Saudi Arabia.
文摘Hot dry rock(HDR)is rich in reserve,widely distributed,green,low-carbon,and has broad development potential and prospects.In this paper,a distributionally robust optimization(DRO)scheduling model for a regionally integrated energy system(RIES)considering HDR co-generation is proposed.First,the HDR-enhanced geothermal system(HDR-EGS)is introduced into the RIES.HDR-EGS realizes the thermoelectric decoupling of combined heat and power(CHP)through coordinated operation with the regional power grid and the regional heat grid,which enhances the system wind power(WP)feed-in space.Secondly,peak-hour loads are shifted using price demand response guidance in the context of time-of-day pricing.Finally,the optimization objective is established to minimize the total cost in the RIES scheduling cycle and construct a DRO scheduling model for RIES with HDR-EGS.By simulating a real small-scale RIES,the results show that HDR-EGS can effectively promote WP consumption and reduce the operating cost of the system.
基金supported by the Guangxi Science and Technology Major Special Project (Project Number GUIKEAA22067079-1).
文摘With the development of renewable energy technologies such as photovoltaics and wind power,it has become a research hotspot to improve the consumption rate of new energy and reduce energy costs through the deployment of energy storage.To solve the problem of the interests of different subjects in the operation of the energy storage power stations(ESS)and the integrated energy multi-microgrid alliance(IEMA),this paper proposes the optimization operation method of the energy storage power station and the IEMA based on the Stackelberg game.In the upper layer,ESS optimizes charging and discharging decisions through a dynamic pricing mechanism.In the lower layer,IEMA optimizes the output of various energy conversion coupled devices within the IEMA,as well as energy interaction and demand response(DR),based on the energy interaction prices provided by ESS.The results demonstrate that the optimization strategy proposed in this paper not only effectively balances the benefits of the IEMA and ESS but also enhances energy consumption rates and reduces IEMA energy costs.
基金supported in part by the Scientific Research Fund of Liaoning Provincial Education Department under Grant LQGD2019005in part by the Doctoral Start-up Foundation of Liaoning Province under Grant 2020-BS-141.
文摘Integrated energy system optimization scheduling can improve energy efficiency and low carbon economy.This paper studies an electric-gas-heat integrated energy system,including the carbon capture system,energy coupling equipment,and renewable energy.An energy scheduling strategy based on deep reinforcement learning is proposed to minimize operation cost,carbon emission and enhance the power supply reliability.Firstly,the lowcarbon mathematical model of combined thermal and power unit,carbon capture system and power to gas unit(CCP)is established.Subsequently,we establish a low carbon multi-objective optimization model considering system operation cost,carbon emissions cost,integrated demand response,wind and photovoltaic curtailment,and load shedding costs.Furthermore,considering the intermittency of wind power generation and the flexibility of load demand,the low carbon economic dispatch problem is modeled as a Markov decision process.The twin delayed deep deterministic policy gradient(TD3)algorithm is used to solve the complex scheduling problem.The effectiveness of the proposed method is verified in the simulation case studies.Compared with TD3,SAC,A3C,DDPG and DQN algorithms,the operating cost is reduced by 8.6%,4.3%,6.1%and 8.0%.
基金supported by the National Key Research and Development Project of China(2018YFE0122200).
文摘A robust low-carbon economic optimal scheduling method that considers source-load uncertainty and hydrogen energy utilization is developed.The proposed method overcomes the challenge of source-load random fluctuations in integrated energy systems(IESs)in the operation scheduling problem of integrated energy production units(IEPUs).First,to solve the problem of inaccurate prediction of renewable energy output,an improved robust kernel density estimation method is proposed to construct a data-driven uncertainty output set of renewable energy sources statistically and build a typical scenario of load uncertainty using stochastic scenario reduction.Subsequently,to resolve the problem of insufficient utilization of hydrogen energy in existing IEPUs,a robust low-carbon economic optimal scheduling model of the source-load interaction of an IES with a hydrogen energy system is established.The system considers the further utilization of energy using hydrogen energy coupling equipment(such as hydrogen storage devices and fuel cells)and the comprehensive demand response of load-side schedulable resources.The simulation results show that the proposed robust stochastic optimization model driven by data can effectively reduce carbon dioxide emissions,improve the source-load interaction of the IES,realize the efficient use of hydrogen energy,and improve system robustness.
文摘This paper collects and synthesizes the technical requirements, implementation, and validation methods for quasi-steady agent-based simulations of interconnectionscale models with particular attention to the integration of renewable generation and controllable loads. Approaches for modeling aggregated controllable loads are presented and placed in the same control and economic modeling framework as generation resources for interconnection planning studies. Model performance is examined with system parameters that are typical for an interconnection approximately the size of the Western Electricity Coordinating Council(WECC) and a control area about 1/100 the size of the system. These results are used to demonstrate and validate the methods presented.
文摘在我国“双碳”背景下,建立综合能源系统(integrated energy system,IES)已经成为实现“碳达峰”、“碳中和”目标,加快能源结构转型的重要举措,而综合需求响应(integrated demand response,IDR)是综合能源系统减少碳排放、缓解供需双侧不平衡的有效途径。然而,现有关于IDR的研究大多仅考虑其经济效益,未考虑其环境效益,忽略了需求侧用户对不同时段激励价格的比价行为以及不同用户的差异化响应特性。该文提出了基于碳排放因子的IDR碳排放折算模型,并将碳排放成本加入综合能源系统服务商(integrated energy system provider,IESP)的目标函数中;通过建立激励交叉弹性耦合矩阵对用户的比价行为进行了有效建模以提升模型的精确性;同时计及用户的差异化响应特性,通过制定差异化的激励策略以充分挖掘用户的响应潜力。所提模型被建立为一个IESP-用户双层优化模型,并将该模型转化为了一个单层的凸优化模型以实现高效地求解。最后通过仿真算例验证了模型的有效性,不仅减少了碳排放量,同时降低了IESP的响应成本并提升了用户的舒适度,实现了多方共赢。
文摘为挖掘需求侧资源响应潜力,文中提出一种计及多重需求响应的综合能源系统(integrated energy system,IES)多时间尺度低碳调度策略。首先,考虑到需求侧资源在不同时间尺度下的响应差异性,建立计及价格型和激励型的多重综合需求响应(integrated demand response,IDR)模型。然后,为减少源、荷预测误差对IES运行的影响,分别构建日前低碳经济调度模型和日内双时间尺度滚动优化平抑模型。最后,算例仿真设置不同场景进行对比分析。结果表明,相比传统IDR,多重IDR能有效挖掘用户响应潜力,提升系统经济性。此外,计及多重IDR的多时间尺度调度策略能有效缓解源、荷误差带来的功率波动并降低系统碳排放量,实现IES低碳、经济和稳定运行。
文摘为解决电力系统中电源侧和负荷侧的不确定性对电网调度计划的影响,针对电源侧,考虑风电与光伏出力的不确定性,分别建立风电与光伏的概率密度函数模型,通过拉丁超立方采样方法生成场景并进行缩减,从而得出风电与光伏出力区间;针对负荷侧,考虑柔性负荷对电网消峰填谷的作用,提出基于智能小区的综合需求响应两阶段鲁棒优化模型。在日前阶段,以电网系统运行成本和碳交易成本最小为优化目标,考虑源荷的不确定性,基于价格需求响应模型,从而确定日前调度方案。在日内阶段,基于日前阶段优化结果,以智能小区运行成本和碳交易成本最小为优化目标,建立两阶段鲁棒优化模型,通过列约束生成(column-and-constraint generation,C&CG)算法将目标函数进行转换,采用Karush-Kuhn-Tucker条件和Big-M约束方法将max-min形式优化问题转化为混合整数线性规划(mixed integer linear programming,MILP)模型。最终,通过算例验证了所提模型的正确性以及算法的有效性。