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Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Zhejiang Electric Power is the property of Zhejiang Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To enhance the accuracy of load identification for multi-energy devices in non-invasive integrated energy systems, a method based on an improved sliding window bilateral CUSUM (cumulative sum), GBSSL (graph semi-supervised learning), and ICapsNet (improved capsule network) was proposed, considering the spatiotemporal coupling characteristics of multi-energy loads. Initially, an adaptive noise value selection method was introduced to enhance the sliding window bilateral CUSUM algorithm, and the improved algorithm was used for event detection, followed by labeling unlabeled samples through GBSSL. Subsequently, on the basis of CapsNet, the similarity and weighted sum calculation methods were improved, the residual block structure convolutional network replaces the original convolutional module, and a polarization self-attention block was introduced into the main capsule module to construct ICapsNet. Finally, different non-invasive load identification methods are used to identify the loads of 10 150 integrated energy load data collected, verifying the superiority of the proposed method. Experimental results show that compared to mainstream noninvasive load identification methods such as BI-GRU, Bagging EL, and DNN, the Precision , Recall, F macro, and BA metrics are improved by an average of 1. 77%, 2. 14%, 1. 94%, and 1. 26%, respectively. The results indicates that the proposed method can accurately identify the loads of multi-energy devices in non-invasive integrated energy systems, with good computational efficiency and versatility. [ABSTRACT FROM AUTHOR]

Integrated Energy System (IES) is of great significance to improve energy efficiency and reduce carbon emissions. Here, a low-carbon optimal scheduling approach is proposed for IES, which considers hydrogen energy utilization and demand response. On the source side, an IES model centering on hydrogen energy utilization is built to optimize the equipment operation flexibility. While on the load side, a demand response model based on Logistic function is built to optimize the load curves thus assist in carbon reduction, which takes into account of the users' energy consumption characteristics. In addition, a tiered carbon trading mechanism is introduced into the optimization model to further explore the carbon reduction potential. Finally, the IES is optimized and scheduled to minimize its total daily operating cost, considering the system's expenditure on energy purchase, operation and maintenance, carbon trading and wind abandonment. Case study shows that the proposed scheduling approach not only achieves peak shaving and valley filling, but also reduces the total operating cost and carbon emission of IES, which verifies its low-carbon and economical characteristics. [ABSTRACT FROM AUTHOR]

Integrated energy system (IES) enables the supply of multiple forms of energy, but the large amount of carbon dioxide it emitted affects the surrounding environment. Here, an optimal scheduling approach based on Twin Delayed Deep Deterministic Policy Gradient (TD3) is proposed for low-carbon economic scheduling of IES. First, taking the minimum operation cost as the objective function, an IES model with multiple complementary energies of electricity, heat and cold is established considering carbon capture technology and power-to-gas technology. Second, a carbon trading mechanism is introduced to stimulate the enthusiasm of energy conservation and emission reduction under optimal scheduling. Then, according to the reinforcement learning framework, the state space, action space and reward function of the optimization model are designed, and the agents in the TD3 algorithm are used to interact with the environment to explore strategies and learn the IES operation strategies. Finally, the historical data are used to train the agents of TD3 algorithm, and the linear programming and particle swarm optimization are compared under different scenarios. The results show that the proposed approach can reduce the IES carbon emission and operating cost, thus realizing the low-carbon economic dispatch of the integrated energy system. [ABSTRACT FROM AUTHOR]

The design process of integrated energy system will face the uncertainty of renewable energy generation and energy demand, and the risk of sub-optimal decision will be introduced when the deterministic method is used for design. In this paper, an efficient planning and optimization model for integrated energy systems considering dual source-load uncertainty was proposed. A large set of primitive stochastic scenarios was first generated using Monte Carlo simulation, and the primitive stochastic yearly scenarios were doubly reduced to typical years and typical days in order to ensure that the stochastic planning model was solvable, taking into account the uncertainty of the boundary conditions. Secondly, to confirm the validity of the scenarios obtained based on the reduced scenarios, this paper tests the validity of the stochastic planning model by substituting the stochastic planning scenarios into the original set of stochastic scenarios for production simulation using an integrated energy system in an industrial park as a case study. The results show that the typical day boundary fully considers the uncertainty of the original design boundary, and can ensure the solution of the stochastic programming model. Compared with the deterministic optimization model, the stochastic optimization model produces a more conservative scheme with less allocation of renewable energy and more dependence on conventional energy and power grid. At the same time, the results of production simulation show that the stochastic programming method has more advantages in economy, and the equal annual cost of the planning scheme is 2. 02% lower than that of the deterministic planning scheme. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Guangdong University of Technology is the property of Journal of Guangdong University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Engineering for Thermal Energy & Power / Reneng Dongli Gongcheng is the property of Journal of Engineering for Thermal Energy & Power and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

针对风电、光伏等新能源分布式发电系统（distributed generator，DG）受环境因素变化导致出力不确定、现有碳交易模型交易价格固定导致减碳成本增多的问题，提出基于DG不确定仿射模型的综合能源系统低碳优化规划方法。首先，根据环境条件建立基于矩阵形式仿射算法的DG出力模型，降低DG出力不确定性对综合能源系统优化规划的影响。其次，将碳排放量作为惩罚措施引入综合能源系统优化规划中，改进传统碳交易模型，降低综合能源系统碳排放量。然后，基于差分进化粒子群优化算法，对建立的综合能源系统低碳规划模型求解，避免算法在寻优过程陷入局部最优。最后，在IEEE 33节点系统上的仿真结果表明，所提规划方法比传统随机优化和区间优化规划方法分别降低了8.68%和2.93%的总投资成本，比传统固定碳交易价格模型降低了6.28%的碳排放量。

由于用户级综合能源系统（integrated energy system，IES）的多元负荷序列之间复杂的耦合关系及易受外部因素影响等原因，综合能源系统多元负荷的精准预测面临很大困难。为此，提出一种基于Spearman相关性分析阈值寻优（threshold optimization，TO）和变分模态分解结合长短期记忆网络（variational mode decomposition based long short-term memory network，VMD-LSTM）的多元负荷预测方法。首先，使用斯皮尔曼等级（Spearman rank，SR）相关系数定量计算多元负荷间以及负荷与其他气候因素间的相关关系并通过循环寻优确定最优相关阈值，然后采用VMD算法将以最优阈值筛选出的负荷特征序列分解成更简单、平稳、有规律性的本征模态函数（intrinsic mode function，IMF）后与最优气象特征一起输入LSTM模型进行负荷预测。通过某用户级IES的实际数据对所提方法的有效性进行了验证，结果表明，所提方法能有效提高IES的多元负荷预测精度。

The Regional Integrated Energy System (RIES) represents a crucial technological strategy for future energy solutions, with an emphasis on regional integration as a key developmental direction. The substantial integration of renewable energy and the diversification of load types introduce multifaceted uncertainties that significantly impact the operation of the electrical grid. In response to these issues, this paper presents an optimized RIES model that incorporates multiple uncertainties. multi-energy coupling, and Integrated Demand Response (IDR). The proposed RIES optimization model encompasses renewable energy sources. coupling devices. energy storage units, and both electrical and thermal loads. This model undergoes a comparative analysis of the mathematical characteristics of source and load uncertainties. To address these uncertainties, Robust Optimization (RO) is applied to new energy source variability, while Stochastic Optimization (SO) was utilized for load uncertainty characterization. The model was then empirically validated using actual RIES data. Research findings indicated that the application of RO and SO methods for modeling source and load uncertainties enhances robustness and economic efficiency. The RIES model, considering these uncertainties, effectively reduces the disparity between peak and valley loads, decreases the pressure on equipment supply, and guarantees collaborative optimization of the system's operations, thereby improving both the reliability and economic viability of the system. [ABSTRACT FROM AUTHOR]

Copyright of Integrated Intelligent Energy is the property of Editorial Department of Integrated Intelligent Energy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Power Generation Technology is the property of Power Generation Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Power Generation Technology is the property of Power Generation Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Telecommunications Science is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the process of low-carbon construction of integrated energy systems, the analysis of the system's low-carbon level and the determination of factors influencing the system's low-carbon development potential are considered to be a challenge. Therefore, a comprehensive low-carbon assessment method for integrated energy systems based on the hybrid variable-rights theory was proposed. Firstly, the current development of smart grid was taken into account, and a low-carbon integrated assessment system including carbon capture and demand response technologies was also proposed. Pearson coefficients were utilized to conduct correlation analysis of the indicators within the system. The weights of the indicators were updated using a subjective and objective combination assignment method improved by the hybrid variable weight principle, taking into consideration the ranking of the multi-dimensional indicator state values. Secondly, a technique for order preference by similarity to ideal solution(TOPSIS) model based on hybrid variable weights was established to comprehensively assess the influencing factors of the system's low-carbon level and low-carbon development potential, providing a more scientific and objective basis for seeking carbon reduction paths and achieving the construction of the system's decarbonization. Finally, the data of the integrated energy system in the northern region of Xinjiang were selected for arithmetic analysis to verify the correctness of the proposed method. [ABSTRACT FROM AUTHOR]

Copyright of Electric Power Engineering Technology is the property of Editorial Department of Electric Power Engineering Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Nanchang University (Engineering & Technology) is the property of Nanchang University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

“双碳”目标和能源转型的大背景下，区域综合能源系统内部耦合关系不断丰富，对于碳排放的管理不断严格，考虑互联协同的分布式能源站低碳规划问题亟待解决。为此，首先讨论了互联协同分布式能源站空间性能参数矩阵；然后计及负荷-能源站的管线建设以及环境成本、能源站-能源站的互联管线长度、各个分布式能源站规划容量等关键因素，提出了一种考虑互联协同的分布式能源站低碳多目标选址规划模型；最后，讨论了负荷不确定性对分布式能源站选址规划的影响，并且基于基准负荷确定性场景，在某城市实际算例中验证并讨论了考虑低碳需求前后各个分布式能源站的选址结果对比。

Copyright of Journal of Chongqing University of Technology (Natural Science) is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Integrated Intelligent Energy is the property of Editorial Department of Integrated Intelligent Energy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Zhejiang Electric Power is the property of Zhejiang Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Drive is the property of Electric Drive Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Under the background of carbon peak carbon neutrality, energy sharing among multiple entities in active distribution network (ADN) helps to absorb wind and light. However, the growing wind and photovoltaic capacity within microgrids has resulted in more pronounced daily fluctuations in net load. This has rendered traditional time-of-use electricity pricing less effective in mitigating peak demand and filling valleys in microgrids. To address this issue, a scheduling strategy considering the shared energy among multiple entities in the context of an active distribution network was proposed in this paper. The objective was to maximize the net income by deducting the electricity purchase cost from the electricity sales revenue generated within the ADN and distributed to sublevel microgrids. Furthermore, the strategy takes into consideration the scheduling autonomy of the sub-level microgrids, which aim to minimize their own operating costs under the pricing policies of the electricity grid. To achieve this optimization, the sub-levels' goal of minimizing operating costs was transformed into a constraint on the super-level objective function by employing Karush-KuhnTucker (KKT) multipliers, as done in the study. The KKT multipliers were employed along with the big M method to linearize the nonlinear constraints, thereby improving the computational efficiency of the model. Additionally, the continuous coupled variables between the upper and lower levels were discretized in the MATLAB Gurobi environment. The effectiveness of the proposed scheduling strategy was evaluated through a case study carried out on an active distribution network implemented in the IEEE 33-node system. This analysis demonstrates the practical feasibility and benefits of the model for optimizing energy distribution within the ADN framework. [ABSTRACT FROM AUTHOR]

Copyright of Integrated Intelligent Energy is the property of Editorial Department of Integrated Intelligent Energy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Integrated Intelligent Energy is the property of Editorial Department of Integrated Intelligent Energy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Integrated Intelligent Energy is the property of Editorial Department of Integrated Intelligent Energy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Integrated Intelligent Energy is the property of Editorial Department of Integrated Intelligent Energy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Integrated Intelligent Energy is the property of Editorial Department of Integrated Intelligent Energy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power is the property of Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)