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CSEE Journal of Power and Energy Systems 2024年第1期10卷 208-221页

作者： jisong Zhu Baike Chen tianyao ji Zhaoxia jing School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China

High-cost generator units are at a cost disadvantage in electricity spot *** study focuses on revenue mechanisms of gas-fired units affected by power market reform in Guangdong province,*** the first time,we compare impacts on market indicators of five settlement mechanisms:feed-in tariff(FiT),location marginal price(LMP),contract for difference(CFD),direct subsidy(DS),and estimated revenue method(ERM).In particular,we design key parameters,including authorized CFD and ERM of two kinds of government authorized contracts based on traditional dispatching patterns to avoid significant profit fluctuations brought by market *** also analyze impact of factors such as climbing performance,seasonal load,and subsidy amount on the overall market and its *** of a case study show to directly subsidize gasfired units will lead higher-cost units to generate more electricity,with a resulting loss of social *** of market prices and provision of unreasonable incentives are fatal disadvantages of this subsidy *** government and policymakers should consider financial means to adjust benefits to reduce production costs and increase social ***,by case analysis,the ERM shows its stable performance in revenue of high-cost units,while we find that authorized CFD is not applicable for gas-fired units whose output is unstable as a marginal unit ***,we suggest government agencies adopt ERM to sign contracts with gas-fired units,to attain a balance between fairness and efficiency.

关键词： Guangdong electricity market high-cost generator unit settlement mechanism subsidy

A Hybrid Signal Processing Method Combining Mathematical Morphology and Walsh Theory for Power Quality Disturbance Detection and Classification

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 584-592页

作者： Zhi Ding tianyao ji Mengshi Li Q.H.Wu School of Electric Power Engineering South China University of Technology(SCUT)Guangzhou 510641China

In this paper, a novel signal processing method combining mathematical morphology (MM) and Walsh theory is proposed, which uses Walsh functions to control the structuring element (SE) and MM operators. Based on the Walsh-MM method, a scheme for power quality disturbances detection and classification is developed, which involves three steps: denoising, feature extraction and morphological clustering. First, various evolution rules of Walsh function are used to generate groups of SEs for the multiscale Walsh-ordered morphological operation, so the original signal can be denoised. Next, the fundamental wave of the denoised signal is suppressed by Hadamard matrix;thus, disturbances can be extracted. Finally, the Walsh power spectrum of the waveform extracted in the previous step is calculated, and the parameters of which are taken by morphological clustering to classify the disturbances. Simulation results reveal the proposed scheme can effectively detect and classify disturbances, and the Walsh-MM method is less affected by noise and only involves simple calculation, which has a potential to be implemented in hardware and more suitable for real-time application.

关键词： Hadamard matrix mathematical morphology morphological clustering power quality disturbance Walsh theory

基于多尺度特征融合与多任务学习框架的非侵入式负荷监测方法

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电网技术 2024年第5期48卷 2074-2083,I0072页

作者：陈嘉伟季天瑶梅广刘紫罡华南理工大学电力学院广东省广州市510641

随着建筑物能源消耗的不断升高,高精度与高泛化能力的非侵入式负荷监测技术的研究具有重大意义。针对当前负荷分解方法存在的问题,提出了一种基于多尺度特征融合与多任务学习框架的非侵入式负荷监测方法。将实例-批归一化网络与U形网络... 详细信息

随着建筑物能源消耗的不断升高,高精度与高泛化能力的非侵入式负荷监测技术的研究具有重大意义。针对当前负荷分解方法存在的问题,提出了一种基于多尺度特征融合与多任务学习框架的非侵入式负荷监测方法。将实例-批归一化网络与U形网络结合,提取总负荷数据的上下文信息,并利用跨越连接实现对不同尺度的细节特征与全局特征的融合。针对多特征特点,引入高效通道注意力网络,使模型聚焦重要特征。引入多任务学习框架与后处理操作,去除输出的假阳性片段,实现对目标电器的精准识别。将所提模型与几种代表性模型在UK-DALE(UK domestic appliance-level electricity)数据集与REDD(reference energy disaggregation data set)上进行对比实验,结果表明,所提模型的性能优于对比模型,具有出色的负荷分解能力与状态识别能力。

关键词：非侵入式负荷监测实例-批归一化网络多尺度特征融合高效通道注意力网络多任务学习

基于数学形态学和沃尔什变换的配电网高阻接地故障检测

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广东电力 2024年第4期37卷 10-23页

作者：梅广季天瑶陈嘉伟丁志华南理工大学电力学院广东广州510641

配电网中高阻接地故障(high impedance grounding fault,HIGF)时常发生,故障一维零序电流信号特征模糊、微弱,极易与励磁涌流、电容器投切信号混淆。为此,提出一种基于相空间重构、数学形态学(mathematical morphology,MM)-沃尔什变换(W... 详细信息

配电网中高阻接地故障(high impedance grounding fault,HIGF)时常发生,故障一维零序电流信号特征模糊、微弱,极易与励磁涌流、电容器投切信号混淆。为此,提出一种基于相空间重构、数学形态学(mathematical morphology,MM)-沃尔什变换(Walsh transform,WT)的HIGF识别方法。首先,使用联合参数选取算法确定延迟时间和嵌入维数,利用坐标重构法对仿真零序电流信号进行相空间重构,获得重构轨迹图,以发掘在一维空间无法观测到的特征;然后,使用MM对重构图像进行去噪以及边缘特征提取;接着,采用MM-WT算法提取重构图像特征;最后,计算提取的图像特征的脉冲因子和对称因子,实现对HIGF和其他扰动事件的识别。在PSCAD/EMTDC和RSCAD/RTDS上进行仿真实验,结果验证了所提算法的可靠性和可行性。

关键词：配电网高阻接地故障相空间重构数学形态学沃尔什变换

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Impact of Long-Term Transactions on Strategic Bidding in the Electricity Market

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CSEE Journal of Power and Energy Systems 2023年第6期9卷 2090-2098页

作者： tianyao ji Yueyong Yang Zhaoxia jing School of Electric Power Engineering South China University of TechnologyGuangzhouChina

Power producers'profits are determined by the market price in the electricity market and therefore they will adopt certain strategies in market transactions to achieve higher *** an electricity spot market that adopts uniform pricing,power producers with considerable generation capacity are able to exercise their market power,given that the market concentration is relatively high at the beginning of market *** has been proved that an effective bidding strategy can increase the market clearing prices,so as to increase the profits of the power ***,the introduction of long-term transactions may mitigate the impact of producers'market power,as a great amount of long-term volume is settled at the long-term contract price,which is determined in advance and is less fluctuating than the spot *** forms of long-term transactions,the fixed volume contract and the varied volume contract,are studied in this *** studies are conducted on a multi-agent platform,where both the long-term and spot transactions of power producers are included,and the total profits of a power producer with or without long-term transactions are analyzed to demonstrate their ***,the results clearly show that long-term transactions can effectively prevent power producers from exercising market power.

关键词： Electricity market long-term transaction spot transaction strategic bidding

基于分区和滑动时间窗策略的配电网线路参数辨识

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智慧电力 2024年第3期52卷 117-124页

作者：李晨涛欧颖雅季天瑶张禄亮华南理工大学电力学院广东广州510006

针对配电网线路参数辨识困难、不精确的问题,提出了一种基于分区和滑动时间窗策略的配电网线路参数辨识的方法。首先,使用线性解耦潮流模型最小二乘回归得到线路初始辨识参数。然后,将配电网分成若干个区域,并采用滑动时间窗策略,在每... 详细信息

针对配电网线路参数辨识困难、不精确的问题,提出了一种基于分区和滑动时间窗策略的配电网线路参数辨识的方法。首先,使用线性解耦潮流模型最小二乘回归得到线路初始辨识参数。然后,将配电网分成若干个区域,并采用滑动时间窗策略,在每个时间窗中对每个区域内的线路参数通过高斯-牛顿法进行精确辨识。最后,对所有时间窗内的辨识结果进行离群值检测,综合各个时间窗的辨识结果得到最终的辨识值。所提方法提高了线路参数的辨识精度,并且可以避免精确辨识时选取到坏数据导致辨识结果偏离真实值。

关键词：配电网线路参数辨识网络分区滑动时间窗数据驱动

基于多层级条件风险价值的高渗透可再生能源电力系统低碳运行联合优化

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电网与清洁能源 2024年第2期40卷 37-46页

作者：沈佳程李梦诗季天瑶林镇佳华南理工大学电力学院广东广州510006

在双碳目标下,风电渗透率增加给新型电力系统的安稳运行带来挑战,而条件风险价值法(Conditional Value-at-Risk,CVaR)可对风电的随机风险进行分类量化评估,以用于系统调度运行。根据CVaR提出了改进的多层级条件风险价值法(Multi-layer C... 详细信息

在双碳目标下,风电渗透率增加给新型电力系统的安稳运行带来挑战,而条件风险价值法(Conditional Value-at-Risk,CVaR)可对风电的随机风险进行分类量化评估,以用于系统调度运行。根据CVaR提出了改进的多层级条件风险价值法(Multi-layer Conditional Value-at-Risk,MCVaR),并建立了基于MCVaR的高渗透可再生能源电力系统低碳运行联合优化模型。仿真算例结果表明,MCVaR相较于CVaR能够显著降低系统的弃风与切负荷量,同时系统的极端损失下降了49.45%。所提方法能够在满足系统可控风险约束的前提下,实现运行经济效益与低碳环保收益的综合最优化。

关键词：条件风险价值低碳运行可再生能源备用优化

基于Attention和残差网络的非侵入式负荷监测

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电测与仪表 2024年第6期61卷 173-180页

作者：何健明李梦诗张禄亮季天瑶华南理工大学广州510006

非侵入式负荷监测(non-intrusive load monitoring,NILM)可以从家庭电能表的总功率读数,估算出各用电器的功率。由于对于同一类用电器,其状态种类、各状态持续时长、各状态的功率波形都不同,这使得基于特征工程和聚类的模型的泛化能力不... 详细信息

非侵入式负荷监测(non-intrusive load monitoring,NILM)可以从家庭电能表的总功率读数,估算出各用电器的功率。由于对于同一类用电器,其状态种类、各状态持续时长、各状态的功率波形都不同,这使得基于特征工程和聚类的模型的泛化能力不强;回归模型的分解功率难以迅速跟踪真实功率。针对这些问题,文中将回归问题转化为在序列每个时刻的多分类问题,并提出基于Attention和残差网络的非侵入式负荷监测模型。该模型基于具有编码器和解码器的seq2seq框架,首先通过嵌入矩阵将高维稀疏one-hot向量映射为低维稠密向量;在编码部分,通过双向GRU从前后两个方向提取序列信息,引入Attention机制计算序列中当前时刻最重要的信息,引入残差连接学习残差部分输入输出之间的差异;在解码部分,用回归层组合BiGRU解码结果,取经过softmax函数处理的最大概率功率类别作为结果。该模型在选取REFIT数据集中表现良好,其中测试集与训练集完全独立,表明训练好的模型可以直接应用在新的住宅用户中。

关键词：非侵入式负荷监测深度学习 BiGRU 残差网络注意力机制

Fault Identification in Power Network Based on Deep Reinforcement Learning

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CSEE Journal of Power and Energy Systems 2022年第3期8卷 721-731页

作者： Mengshi Li Huanming Zhang tianyao ji Q.H.Wu School of Electric Power Engineering South China University of TechnologyGuangzhou510641China

With the integration of alternative energy and renewables,the issue of stability and resilience of the power network has received considerable *** basic necessity for fault diagnosis and isolation is fault identification and *** conventional intelligent fault identification method needs supervision,manual labelling of characteristics,and requires large amounts of labelled *** enhance the ability of intelligent methods and get rid of the dependence on a large amount of labelled data,a novel fault identification method based on deep reinforcement learning(DRL),which has not received enough attention in the field of fault identification,is investigated in this *** proposed method uses different faults as parameters of the model to expand the scope of fault *** addition,the DRL algorithm can intelligently modify the fault parameters according to the observations obtained from the power network environment,rather than requiring manual and mechanical tuning of *** methodology was tested on the IEEE 14 bus for several scenarios and the performance of the proposed method was compared with that of population-based optimization methods and supervised learning *** obtained results have confirmed the feasibility and effectiveness of the proposed method.

关键词： Artificial intelligence deep Q network deep reinforcement learning fault diagnosis fault identification parameter identification power network

Stochastic Economic Dispatch Considering the Dependence of Multiple Wind Farms Using Multivariate Gaussian Kernel Copula

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CSEE Journal of Power and Energy Systems 2022年第5期8卷 1352-1362页

作者： Yantai Lin tianyao ji Yuzi jiang Q.H.Wu School of Electric Power Engineering South China University of TechnologyGuangzhou 510641China

Wind farms usually cluster in areas with abundant wind ***,spatial dependence of wind speeds among nearby wind farms should be taken into account when modeling a power system with large-scale wind power *** paper proposes a novel non-parametric copula method,multivariate Gaussian kernel copula(MGKC),to describe the dependence structure of wind speeds among multiple wind *** speed scenarios considering the dependence among different wind farms are sampled from the MGKC by the quasi-Monte Carlo(QMC)method,so as to solve the stochastic economic dispatch(SED)problem,for which an improved meanvariance(MV)model is established,which targets at minimizing the expectation and risk of fuel cost *** this model,confidence interval is applied in the wind speed to obtain more practical dispatch solutions by excluding extreme scenarios,for which the quantile-copula is proposed to construct the confidence interval *** studies are carried out on a modified IEEE 30-bus power system with wind farms integrated in two areas,and the results prove the superiority of the MGKC in formulating the dependence among different wind farms and the superiority of the improved MV model based on quantilecopula in determining a better dispatch solution.

关键词： Multivariate Gaussian kernel copula Quasi-Monte Carlo Quantile-copula stochastic economic dispatch