Affected by the insufficient information of single baseline observation data,the three-stage method assumes the Ground-to-Volume Ratio(GVR)to be zero so as to invert the vegetation height.However,this assumption intro...Affected by the insufficient information of single baseline observation data,the three-stage method assumes the Ground-to-Volume Ratio(GVR)to be zero so as to invert the vegetation height.However,this assumption introduces much biases into the parameter estimates which greatly limits the accuracy of the vegetation height inversion.Multi-baseline observation can provide redundant information and is helpful for the inversion of GVR.Nevertheless,the similar model parameter values in a multi-baseline model often lead to ill-posed problems and reduce the inversion accuracy of conventional algorithm.To this end,we propose a new step-by-step inversion method applied to the multi-baseline observations.Firstly,an adjustment inversion model is constructed by using multi-baseline volume scattering dominant polarization data,and the regularized estimates of model parameters are obtained by regularization method.Then,the reliable estimates of GVR are determined by the MSE(mean square error)analysis of each regularized parameter estimation.Secondly,the estimated GVR is used to extracts the pure volume coherence,and then the vegetation height parameter is inverted from the pure volume coherence by least squares estimation.The experimental results show that the new method can improve the vegetation height inversion result effectively.The inversion accuracy is improved by 26%with respect to the three-stage method and the conventional solution of multi-baseline.All of these have demonstrated the feasibility and effectiveness of the new method.展开更多
依托于聚光型太阳能发电技术的光热电站(concentrating solar power,CSP)可充分应对新能源发电的不确定性,为“双碳”愿景下新型电力系统的转型与建设提供有力保障。然而,CSP电站如何摆脱高昂建设成本的制约,为自身赢得更多可持续发展...依托于聚光型太阳能发电技术的光热电站(concentrating solar power,CSP)可充分应对新能源发电的不确定性,为“双碳”愿景下新型电力系统的转型与建设提供有力保障。然而,CSP电站如何摆脱高昂建设成本的制约,为自身赢得更多可持续发展的机会是亟需解决的关键难题。因此,该文提出了一种考虑电力市场机制的CSP电站子系统容量优化规划方法。首先,围绕借助CSP电站灵活调控特性在运行时间尺度下提升CSP电站自身经济收益这一问题,提出CSP电站以价格制定者这一角色参与电力市场的竞价策略。然后,构建以经济效益最大为目标的CSP电站聚光、储热、发电容量配比双层随机规划模型,并采用离散线性化转换方法将规划模型转化为混合整数线性模型,解决模型重构后非线性模型带来的求解难问题。最后,基于我国西北某地区实际历史数据的算例仿真验证所提优化配比方法的有效性,并分析说明与价格接受者相比电力市场中的议价权能使CSP电站获得更好的市场经济效益。展开更多
随着“双碳”目标的提出,以风电为代表的可再生能源参与电力现货市场已是大势所趋。但由于具有不确定性和波动性,风电在市场中常处于不利地位。风电与具有灵活调节能力的光热电站(Concentrated Solar Power,CSP)联合能够减少实时出力偏...随着“双碳”目标的提出,以风电为代表的可再生能源参与电力现货市场已是大势所趋。但由于具有不确定性和波动性,风电在市场中常处于不利地位。风电与具有灵活调节能力的光热电站(Concentrated Solar Power,CSP)联合能够减少实时出力偏差,进而降低不平衡成本。基于此,本文针对风电—CSP电站联合参与现货市场的运行策略开展研究。首先,对风电—CSP电站联合参与现货市场的机理进行分析,在此基础上,以经济性最优为目标,综合考虑供电收益、冬季供暖收益和不平衡惩罚等因素,提出了考虑冬季供暖的风电—CSP电站联合参与电力现货市场运行策略,并基于Shapley值法对联盟收益进行分配,最后分析了储热容量对联盟收益的影响。算例表明所提联合运行策略能够充分利用CSP电站灵活性,显著提高双方收益,减少弃风损失。展开更多
基金National Natural Science Foundation of China(No.42104025)China Postdoctoral Science Foundation(No.2021M702509)+3 种基金Natural Resources Sciences and Technology Project of Hunan Province(No.2022-07)Surveying and Mapping Basic Research Foundation of Key Laboratory of Geospace Environment and Geodesy,Ministry of Education(No.20-01-04)Natural Science Foundation of Hunan Province(No.2024JJ5144)Open Fund of Hunan International Scientific and Technological Innovation Cooperation Base of Advanced Construction and Maintenance Technology of Highway(Changsha University of Science&Technology,No.kfj190805).
文摘Affected by the insufficient information of single baseline observation data,the three-stage method assumes the Ground-to-Volume Ratio(GVR)to be zero so as to invert the vegetation height.However,this assumption introduces much biases into the parameter estimates which greatly limits the accuracy of the vegetation height inversion.Multi-baseline observation can provide redundant information and is helpful for the inversion of GVR.Nevertheless,the similar model parameter values in a multi-baseline model often lead to ill-posed problems and reduce the inversion accuracy of conventional algorithm.To this end,we propose a new step-by-step inversion method applied to the multi-baseline observations.Firstly,an adjustment inversion model is constructed by using multi-baseline volume scattering dominant polarization data,and the regularized estimates of model parameters are obtained by regularization method.Then,the reliable estimates of GVR are determined by the MSE(mean square error)analysis of each regularized parameter estimation.Secondly,the estimated GVR is used to extracts the pure volume coherence,and then the vegetation height parameter is inverted from the pure volume coherence by least squares estimation.The experimental results show that the new method can improve the vegetation height inversion result effectively.The inversion accuracy is improved by 26%with respect to the three-stage method and the conventional solution of multi-baseline.All of these have demonstrated the feasibility and effectiveness of the new method.
文摘依托于聚光型太阳能发电技术的光热电站(concentrating solar power,CSP)可充分应对新能源发电的不确定性,为“双碳”愿景下新型电力系统的转型与建设提供有力保障。然而,CSP电站如何摆脱高昂建设成本的制约,为自身赢得更多可持续发展的机会是亟需解决的关键难题。因此,该文提出了一种考虑电力市场机制的CSP电站子系统容量优化规划方法。首先,围绕借助CSP电站灵活调控特性在运行时间尺度下提升CSP电站自身经济收益这一问题,提出CSP电站以价格制定者这一角色参与电力市场的竞价策略。然后,构建以经济效益最大为目标的CSP电站聚光、储热、发电容量配比双层随机规划模型,并采用离散线性化转换方法将规划模型转化为混合整数线性模型,解决模型重构后非线性模型带来的求解难问题。最后,基于我国西北某地区实际历史数据的算例仿真验证所提优化配比方法的有效性,并分析说明与价格接受者相比电力市场中的议价权能使CSP电站获得更好的市场经济效益。
文摘随着“双碳”目标的提出,以风电为代表的可再生能源参与电力现货市场已是大势所趋。但由于具有不确定性和波动性,风电在市场中常处于不利地位。风电与具有灵活调节能力的光热电站(Concentrated Solar Power,CSP)联合能够减少实时出力偏差,进而降低不平衡成本。基于此,本文针对风电—CSP电站联合参与现货市场的运行策略开展研究。首先,对风电—CSP电站联合参与现货市场的机理进行分析,在此基础上,以经济性最优为目标,综合考虑供电收益、冬季供暖收益和不平衡惩罚等因素,提出了考虑冬季供暖的风电—CSP电站联合参与电力现货市场运行策略,并基于Shapley值法对联盟收益进行分配,最后分析了储热容量对联盟收益的影响。算例表明所提联合运行策略能够充分利用CSP电站灵活性,显著提高双方收益,减少弃风损失。