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学者姓名：邵振国
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Abstract ：
针对现有谐波责任划分方法未考虑不同谐波严重程度下责任所造成的实际影响差异,提出一种考虑谐波严重程度的长时间尺度谐波责任划分方法.考虑谐波数值分布与变化趋势两方面因素划分工况,并计算各工况综合权重量化谐波严重程度;基于典型相关性分析原理筛选长时间尺度数据,并根据谐波责任定义式估算谐波责任;结合上述综合权重获取长时间尺度综合谐波责任划分指标;采用仿真算例与实测数据进行验证,与传统方法相比,所提方法可反映各谐波源在长时间尺度下不同次数谐波造成的累计影响,更适用于谐波精准治理与公平奖惩工作.
Keyword ：
工况划分 工况划分 谐波严重程度 谐波严重程度 谐波变化趋势 谐波变化趋势 谐波责任划分 谐波责任划分 长时间尺度 长时间尺度
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| GB/T 7714 | 张逸 , 郭俊煜 , 邵振国 . 考虑谐波严重程度的长时间尺度谐波责任划分方法 [J]. | 电力自动化设备 , 2024 , 44 (1) : 126-133 . |
| MLA | 张逸 等. "考虑谐波严重程度的长时间尺度谐波责任划分方法" . | 电力自动化设备 44 . 1 (2024) : 126-133 . |
| APA | 张逸 , 郭俊煜 , 邵振国 . 考虑谐波严重程度的长时间尺度谐波责任划分方法 . | 电力自动化设备 , 2024 , 44 (1) , 126-133 . |
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随着不确定性可再生能源大规模并网，电网频率特性日益复杂。传统火电机组具有响应时间长、无法准确跟踪指令等问题，亟须利用储能提高火电机组参与自动发电控制（automatic generation control,AGC）调频时的调节性能。首先，针对调频考核规则，建立调频性能指标数学模型，并考虑火储系统出力特性，结合改进层次分析法校正调频子指标权重系数，以此构建以调频性能最优为目标的第一阶段优化模型；在此基础上，为了减少储能荷电状态（state of charge,SOC）越限和深度充放情况，以储能SOC偏差最小为目标构建第二阶段优化模型。仿真验证表明：所提的两阶段调频方法能够提高火储联合系统的调频性能和调频收益，同时有效减少储能深度充放情况和工作寿命损耗，提高储能辅助调频服务的可持续性。
Keyword ：
两阶段调频 两阶段调频 储能 储能 改进层次分析法 改进层次分析法 自动发电控制 自动发电控制 调频辅助服务 调频辅助服务
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| GB/T 7714 | 王益斌 , 陈飞雄 , 邵振国 et al. 基于权重系数校正的火储两阶段联合调频方法 [J]. | 中国电力 , 2024 , 57 (03) : 83-94 . |
| MLA | 王益斌 et al. "基于权重系数校正的火储两阶段联合调频方法" . | 中国电力 57 . 03 (2024) : 83-94 . |
| APA | 王益斌 , 陈飞雄 , 邵振国 , 张抒凌 , 张伟骏 , 李智诚 . 基于权重系数校正的火储两阶段联合调频方法 . | 中国电力 , 2024 , 57 (03) , 83-94 . |
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仿射潮流算法是求解新型电力系统状态量分布特征的重要手段。针对现有仿射潮流算法保守度较高、算法效率较低且需要选择合适的迭代初始值等不足之处，该文提出一种基于全纯嵌入的不确定性仿射潮流计算方法。首先，构建电力系统节点电压和功率仿射模型，并建立系统仿射潮流方程。在此基础上，将嵌入因子引入到仿射潮流方程中，构造具有泰勒级数形式的全纯嵌入仿射潮流模型；接着，将仿射潮流求解问题转换为泰勒幂级数系数的求解问题，获取状态量初始解及递推关系，计算不确定性潮流的仿射解。最后，算例验证所提算法具有保守性低、计算效率高和量化分析分布式电源出力对电压影响等优势。
Keyword ：
不确定性 不确定性 仿射潮流 仿射潮流 全纯嵌入 全纯嵌入 区间潮流 区间潮流
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| GB/T 7714 | 邵振国 , 李壹民 , 颜熙颖 et al. 基于全纯嵌入的电力系统不确定性仿射潮流方法 [J]. | 中国电机工程学报 , 2024 , 44 (01) : 105-117 . |
| MLA | 邵振国 et al. "基于全纯嵌入的电力系统不确定性仿射潮流方法" . | 中国电机工程学报 44 . 01 (2024) : 105-117 . |
| APA | 邵振国 , 李壹民 , 颜熙颖 , 何松涛 , 陈飞雄 . 基于全纯嵌入的电力系统不确定性仿射潮流方法 . | 中国电机工程学报 , 2024 , 44 (01) , 105-117 . |
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Abstract ：
微机继电保护作为电网安稳运行的关键环节，需要符合新工科背景和工程教育专业认证人才培养要求的教学方法。为此提出一种融合STEM与OBE理念的“微机继电保护”案例教学法，对“微机继电保护”复杂理论体系进行了模块化研究，并以工程案例为载体阐明微机继电保护运行机理，实现教学主体由教师向学生的转变。实践证明，所提方法能够有效提高教学效率，确保工程能力产出，有助于“微机继电保护”课程建设。
Keyword ：
多教育理念融合 多教育理念融合 微机继电保护 微机继电保护 模块化案例教学 模块化案例教学
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| GB/T 7714 | 陈飞雄 , 蔡明杰 , 邵振国 et al. 融合STEM与OBE理念的“微机继电保护”案例教学 [J]. | 电气电子教学学报 , 2024 , 46 (01) : 9-15 . |
| MLA | 陈飞雄 et al. "融合STEM与OBE理念的“微机继电保护”案例教学" . | 电气电子教学学报 46 . 01 (2024) : 9-15 . |
| APA | 陈飞雄 , 蔡明杰 , 邵振国 , 洪翠 , 张宁 . 融合STEM与OBE理念的“微机继电保护”案例教学 . | 电气电子教学学报 , 2024 , 46 (01) , 9-15 . |
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The affine arithmetic is an important tool for solving the uncertain power flow problem. The traditional affine power flow method has the disadvantages of over-conservative, low efficiency and high requirement of the iterative initial values. To deal with these issues, an affine power flow algorithm for the power system based on holomorphic embedding method is proposed in this paper. First, the nodal voltage and power affine models of the power system are developed, and the affine power flow equations are established. On this basis, the embedding factor is introduced into the affine power flow equations and a holomorphic embedded affine model with Taylor series form is developed. What’s more, the affine power flow solution problem is converted into a solution problem with Taylor power series coefficients. Thus, the germ solution and the recurrence relations of the status variables are obtained, and the affine values of the uncertain power flow are computed. Finally, several numerical results are presented and discussed, demonstrating that the proposed algorithm has the advantages of low conservativeness, high computational efficiency and the ability to analyze the impact of distributed generation on voltage quantificational. © 2024 Chinese Society for Electrical Engineering. All rights reserved.
Keyword ：
Computational efficiency Computational efficiency Electric load flow Electric load flow Embeddings Embeddings Iterative methods Iterative methods Taylor series Taylor series
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| GB/T 7714 | Shao, Zhenguo , Li, Yimin , Yan, Xiying et al. Affine Power Flow Algorithm for Power System Based on Holomorphic Embedding Method [J]. | Proceedings of the Chinese Society of Electrical Engineering , 2024 , 44 (1) : 105-116 . |
| MLA | Shao, Zhenguo et al. "Affine Power Flow Algorithm for Power System Based on Holomorphic Embedding Method" . | Proceedings of the Chinese Society of Electrical Engineering 44 . 1 (2024) : 105-116 . |
| APA | Shao, Zhenguo , Li, Yimin , Yan, Xiying , He, Songtao , Chen, Feixiong . Affine Power Flow Algorithm for Power System Based on Holomorphic Embedding Method . | Proceedings of the Chinese Society of Electrical Engineering , 2024 , 44 (1) , 105-116 . |
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传统基于谐波状态估计的谐波源定位方法需要专门的同步相量量测装置，工程应用受到限制。为此，基于电能质量监测装置所采集的非同步量测数据，提出了基于特征集重构与多标签分类模型的谐波源定位方法。利用监测数据的充分统计量来挖掘量测时段的谐波信息，同时利用标签特定特征学习算法重构特征集，从而消除冗余特征以及无关特征对于谐波源定位精度的影响；提出基于邻接矩阵以及灵敏度分析的测点配置方法，结合电路网络拓扑信息实现测点的优化配置；提出基于改进极限学习机的谐波源定位方法，该方法以重构特征集为输入，建立多标签分类模型，实现谐波源定位。通过仿真与算例分析，验证了所提方法的可行性及有效性。
Keyword ：
极限学习机 极限学习机 标签特定特征学习算法 标签特定特征学习算法 电能质量 电能质量 谐波源定位 谐波源定位 非同步谐波监测数据 非同步谐波监测数据
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| GB/T 7714 | 邵振国 , 林潇 , 张嫣 et al. 基于特征集重构与多标签分类模型的谐波源定位方法 [J]. | 电力自动化设备 , 2024 , 44 (02) : 147-154 . |
| MLA | 邵振国 et al. "基于特征集重构与多标签分类模型的谐波源定位方法" . | 电力自动化设备 44 . 02 (2024) : 147-154 . |
| APA | 邵振国 , 林潇 , 张嫣 , 陈飞雄 , 林洪洲 . 基于特征集重构与多标签分类模型的谐波源定位方法 . | 电力自动化设备 , 2024 , 44 (02) , 147-154 . |
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Abstract ：
围绕综合能源系统的能流计算问题，从网络模型及求解、不确定性能流分析方法 2个层面综述了各类能流计算方法。首先，在综合能源系统网络特性建模方面，讨论了偏微分方程模型、动态特性模型和稳态特性模型及其求解方法。其次，归纳了应对系统外部输入不确定性的概率和区间2类传统能流分析方法，以及概率-区间混合不确定性能流分析方法。最后，从工程应用角度分析当前综合能源系统能流计算的难点与热点，进而对其发展方向进行展望。
Keyword ：
不确定性分析方法 不确定性分析方法 概率-区间方法 概率-区间方法 综合能源系统 综合能源系统 网络特性模型 网络特性模型 能流计算 能流计算
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| GB/T 7714 | 陈飞雄 , 颜熙颖 , 邵振国 et al. 综合能源系统建模与能流计算方法研究综述 [J]. | 高电压技术 , 2024 , 50 (04) : 1376-1391 . |
| MLA | 陈飞雄 et al. "综合能源系统建模与能流计算方法研究综述" . | 高电压技术 50 . 04 (2024) : 1376-1391 . |
| APA | 陈飞雄 , 颜熙颖 , 邵振国 , 李壹民 , 郑翔昊 , 张河 . 综合能源系统建模与能流计算方法研究综述 . | 高电压技术 , 2024 , 50 (04) , 1376-1391 . |
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Grid-connected voltage source converters (VSCs) have been broadly applied in modern power system. However, instability issues may be triggered by the integration of grid-connected VSCs, jeopardising the operation of the power grid. Conventional stability analysis methods can be utilised to derive system stability margins under nominal conditions. Whereas grid-connected VSCs inevitably operate under multiparameter uncertainty, which may result in overly optimistic or even incorrect estimations of stability margins, thereby posing potential risks to system operation. To address this issue, an interval small-signal stability analysis approach is proposed to investigate the system stability under multiparameter uncertainty. First, the interval state-space model of the grid-connected VSC system is constructed based on interval symbolic linearisation. Furthermore, the interval eigenvalue decomposition is introduced to calculate the interval eigenvalue distribution of the interval state-space model. Eventually, the upper bounds of the real part of the dominant interval eigenvalues are utilised for deriving interval stable parameter regions. Results of Monte Carlo analysis and time-domain simulations of the grid-connected VSC system are utilised to verify the effectiveness of the proposed interval stability analysis method.
Keyword ：
power convertors power convertors power system interconnection power system interconnection power system stability power system stability
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| GB/T 7714 | Ouyang, Fuxin , Shao, Zhenguo , Jiang, Changxu et al. Interval analysis of the small-signal stability of grid-connected voltage-source converter system considering multiparameter uncertainty [J]. | IET ENERGY SYSTEMS INTEGRATION , 2024 , 6 (2) : 144-161 . |
| MLA | Ouyang, Fuxin et al. "Interval analysis of the small-signal stability of grid-connected voltage-source converter system considering multiparameter uncertainty" . | IET ENERGY SYSTEMS INTEGRATION 6 . 2 (2024) : 144-161 . |
| APA | Ouyang, Fuxin , Shao, Zhenguo , Jiang, Changxu , Zhang, Yan , Chen, Feixiong . Interval analysis of the small-signal stability of grid-connected voltage-source converter system considering multiparameter uncertainty . | IET ENERGY SYSTEMS INTEGRATION , 2024 , 6 (2) , 144-161 . |
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Most of the existing electric vehicle (EV) charging navigation methods do not simultaneously take into account the electric vehicle charging destination optimization and path planning. Moreover, they are unable to provide online real-time decision-making under a variety of uncertain factors. To address these problems, this paper first establishes a bilevel stochastic optimization model for EV charging navigation considering various uncertainties, and then proposes an EV charging navigation method based on the hierarchical enhanced deep Q network (HEDQN) to solve the above stochastic optimization model in real-time. The proposed HEDQN contains two enhanced deep Q networks, which are utilized to optimize the charging destination and charging route path of EVs, respectively. Finally, the proposed method is simulated and validated in two urban transportation networks. The simulation results demonstrate that compared with the Dijkstra shortest path algorithm, single-layer deep reinforcement learning algorithm, and traditional hierarchical deep reinforcement learning algorithm, the proposed HEDQN algorithm can effectively reduce the total charging cost of electric vehicles and realize online realtime charging navigation of electric vehicles, that shows excellent generalization ability and scalability.
Keyword ：
Charging navigation Charging navigation Destination optimization Destination optimization Electric vehicle Electric vehicle Hierarchical reinforcement learning Hierarchical reinforcement learning Route planning Route planning
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| GB/T 7714 | Jiang, Changxu , Zhou, Longcan , Zheng, J. H. et al. Electric vehicle charging navigation strategy in coupled smart grid and transportation network: A hierarchical reinforcement learning approach [J]. | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS , 2024 , 157 . |
| MLA | Jiang, Changxu et al. "Electric vehicle charging navigation strategy in coupled smart grid and transportation network: A hierarchical reinforcement learning approach" . | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 157 (2024) . |
| APA | Jiang, Changxu , Zhou, Longcan , Zheng, J. H. , Shao, Zhenguo . Electric vehicle charging navigation strategy in coupled smart grid and transportation network: A hierarchical reinforcement learning approach . | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS , 2024 , 157 . |
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Conventional harmonic source location methods based on harmonic state estimation require phasor measurement units，therefore their engineering applications are limited. Aiming at this problem，a harmonic source location method based on feature set reconstruction and multi-label classification model is proposed based on asynchronous measurement data collected by power quality monitoring devices. The sufficient statistics of the monitoring data is used to mine the harmonic information of the measurement period. Meanwhile，a label-specific feature learning algorithm is used to reconstruct the feature set，so as to eliminate the influence of redundant and irrelevant features on the accuracy of harmonic sources location. Then a configuration method of measurement devices is proposed based on the adjacency matrix and sensitivity analysis，which uses circuit network topology information to achieve measurement device configuration. An improved extreme learning machine based harmonic source location method is proposed，which uses the reconstructed feature set as input and establishes a multi-label classification model to achieve harmonic source location. The feasibility and effectiveness of the proposed method are verified by simulation and arithmetic cases. © 2024 Electric Power Automation Equipment Press. All rights reserved.
Keyword ：
Classification (of information) Classification (of information) Harmonic analysis Harmonic analysis Knowledge acquisition Knowledge acquisition Learning algorithms Learning algorithms Location Location Machine learning Machine learning Network topology Network topology Phasor measurement units Phasor measurement units Power quality Power quality Sensitivity analysis Sensitivity analysis
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| GB/T 7714 | Shao, Zhenguo , Lin, Xiao , Zhang, Yan et al. Harmonic source location method based on feature set reconstruction and multi-label classification model [J]. | Electric Power Automation Equipment , 2024 , 44 (2) : 147-154 . |
| MLA | Shao, Zhenguo et al. "Harmonic source location method based on feature set reconstruction and multi-label classification model" . | Electric Power Automation Equipment 44 . 2 (2024) : 147-154 . |
| APA | Shao, Zhenguo , Lin, Xiao , Zhang, Yan , Chen, Feixiong , Lin, Hongzhou . Harmonic source location method based on feature set reconstruction and multi-label classification model . | Electric Power Automation Equipment , 2024 , 44 (2) , 147-154 . |
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