针对含光伏(photovoltaic,PV)、电动汽车(electric vehicle,EV)及家庭电器负荷的智能社区,以车入户(vehicle to home,V2H)的形式将EV纳入家庭需求响应框架,利用EV的双向输能特性并考虑EV充/放电带来的电池容量退化成本,协同PV、电网的...针对含光伏(photovoltaic,PV)、电动汽车(electric vehicle,EV)及家庭电器负荷的智能社区,以车入户(vehicle to home,V2H)的形式将EV纳入家庭需求响应框架,利用EV的双向输能特性并考虑EV充/放电带来的电池容量退化成本,协同PV、电网的实时电价和用户需求的可容忍时延,基于Lyapunov优化理论提出随机环境下V2H用户的EV充/放电调度策略和每户家庭的负荷响应策略,最小化家庭用户的长期平均购电成本。并提出一种智能社区在线能量交易方案,旨在最小化智能社区总的购电成本、最大限度提高社区能源利用率。理论分析和仿真结果表明,所提算法无需实时电价、PV出力、用户负荷需求的先验概率信息,仅基于当前系统状态就可使优化目标趋于最优值,实现家庭用户的能量调度和家庭用户之间的能量共享,减少家庭购电成本,提高用户之间能量交易的灵活性。展开更多
在智能电网环境下,提出了一种家庭能源管理系统框架和优化调度算法。根据室外温度预测值、可再生能源功率输出预测值、日前电价信号和用户偏好,算法对可调度用电负载、电动汽车、储能系统的运行进行优化调度从而最小化用户用电费用。算...在智能电网环境下,提出了一种家庭能源管理系统框架和优化调度算法。根据室外温度预测值、可再生能源功率输出预测值、日前电价信号和用户偏好,算法对可调度用电负载、电动汽车、储能系统的运行进行优化调度从而最小化用户用电费用。算法考虑了电动汽车在高电价时段通过V2H(vehicle to home,V2H)功能向负载供电的情形,采用情景分析法处理室外温度和可再生能源功率输出预测的不确定性。通过仿真实验验证了算法性能,结果表明与只对负载或家庭能源管理系统部分组成部件进行优化调度的算法相比,所提算法显著降低了用电费用。展开更多
The hydrothermal reaction of NH 4VO 3, CoCl 2·6H 2O, o-phen and H 2O gave a novel two-dimensional layered polyoxovanadate, [Co(o-phen)]V 2O 6·H 2O, which was constructed from {V 2O 6} chains linked by Co(o-p...The hydrothermal reaction of NH 4VO 3, CoCl 2·6H 2O, o-phen and H 2O gave a novel two-dimensional layered polyoxovanadate, [Co(o-phen)]V 2O 6·H 2O, which was constructed from {V 2O 6} chains linked by Co(o-phen) complex fragments. [Co(o-phen)]V 2O 6·H 2O was characterized by IR, TG and single-crystal X-ray diffraction. It crystallizes in monoclinic space group P2(1)/c with a= 0.785 2(9) nm, b=2.118 3(2) nm, c=0.946 3(11) nm, β=112.827(2)°, V=0.145 1(3) nm3, D c=2.074 g/cm3, Z=4, R 1=0.038 8, wR 2=0.094 1.展开更多
A novel compound Ni(phen)(H2O)(V2O6) has been hydrothermally synthesized and structurally determined to be a two-dimensional compound, which contains {V2O6}n2n- chains interconnected by nickel(II) complexes via oxygen...A novel compound Ni(phen)(H2O)(V2O6) has been hydrothermally synthesized and structurally determined to be a two-dimensional compound, which contains {V2O6}n2n- chains interconnected by nickel(II) complexes via oxygen atoms. The crystallographic data measured by single-crystal X-ray diffraction analysis are as follows: C12H10N2NiO7V2, Mr=454.81, monoclinic, space group P21 / c, a=0.784 6(3), b=2.103 6(8), c=0.942 3(4) nm, β=112.872(5)°, V=1.433 0(10) nm3, Z=4, Dc=2.104 Mg·m-3, μ(Mo Kα)=2.615 mm-1, F(000)=904, T=298(2) K, 4 480 reflections collected, 2 470 independent (Rint=0.032 2), the final R=0.058 4 and wR2=0.145 7 for 2 303 observed reflections with I>2σ(I). CCDC: 192520.展开更多
文摘针对含光伏(photovoltaic,PV)、电动汽车(electric vehicle,EV)及家庭电器负荷的智能社区,以车入户(vehicle to home,V2H)的形式将EV纳入家庭需求响应框架,利用EV的双向输能特性并考虑EV充/放电带来的电池容量退化成本,协同PV、电网的实时电价和用户需求的可容忍时延,基于Lyapunov优化理论提出随机环境下V2H用户的EV充/放电调度策略和每户家庭的负荷响应策略,最小化家庭用户的长期平均购电成本。并提出一种智能社区在线能量交易方案,旨在最小化智能社区总的购电成本、最大限度提高社区能源利用率。理论分析和仿真结果表明,所提算法无需实时电价、PV出力、用户负荷需求的先验概率信息,仅基于当前系统状态就可使优化目标趋于最优值,实现家庭用户的能量调度和家庭用户之间的能量共享,减少家庭购电成本,提高用户之间能量交易的灵活性。
文摘在智能电网环境下,提出了一种家庭能源管理系统框架和优化调度算法。根据室外温度预测值、可再生能源功率输出预测值、日前电价信号和用户偏好,算法对可调度用电负载、电动汽车、储能系统的运行进行优化调度从而最小化用户用电费用。算法考虑了电动汽车在高电价时段通过V2H(vehicle to home,V2H)功能向负载供电的情形,采用情景分析法处理室外温度和可再生能源功率输出预测的不确定性。通过仿真实验验证了算法性能,结果表明与只对负载或家庭能源管理系统部分组成部件进行优化调度的算法相比,所提算法显著降低了用电费用。
文摘The hydrothermal reaction of NH 4VO 3, CoCl 2·6H 2O, o-phen and H 2O gave a novel two-dimensional layered polyoxovanadate, [Co(o-phen)]V 2O 6·H 2O, which was constructed from {V 2O 6} chains linked by Co(o-phen) complex fragments. [Co(o-phen)]V 2O 6·H 2O was characterized by IR, TG and single-crystal X-ray diffraction. It crystallizes in monoclinic space group P2(1)/c with a= 0.785 2(9) nm, b=2.118 3(2) nm, c=0.946 3(11) nm, β=112.827(2)°, V=0.145 1(3) nm3, D c=2.074 g/cm3, Z=4, R 1=0.038 8, wR 2=0.094 1.
文摘A novel compound Ni(phen)(H2O)(V2O6) has been hydrothermally synthesized and structurally determined to be a two-dimensional compound, which contains {V2O6}n2n- chains interconnected by nickel(II) complexes via oxygen atoms. The crystallographic data measured by single-crystal X-ray diffraction analysis are as follows: C12H10N2NiO7V2, Mr=454.81, monoclinic, space group P21 / c, a=0.784 6(3), b=2.103 6(8), c=0.942 3(4) nm, β=112.872(5)°, V=1.433 0(10) nm3, Z=4, Dc=2.104 Mg·m-3, μ(Mo Kα)=2.615 mm-1, F(000)=904, T=298(2) K, 4 480 reflections collected, 2 470 independent (Rint=0.032 2), the final R=0.058 4 and wR2=0.145 7 for 2 303 observed reflections with I>2σ(I). CCDC: 192520.
