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Energy, Electrical and power Engineering (CEEPE), International Conference on

作者： Shihang Song Li Zhang Zhiqiang Qi Haibo Wang Yuxi Wang Xinyan Su Guanting Chen Fukun Wang Key Laboratory of Power System Intelligent Dispatch and Control Shandong University Jinan China State Grid Shandong Electric Power Company Jinan China

As the proportion of renewable energy connected to grid increases continuously, the volatility and uncertainty of its output affect the safe operation of the power system, so it is necessary to adjust the trading mechanism of electricity market. As a high-quality flexible resource, energy storage becomes an important means to deal with the challenge caused by renewable energy. How to improve the mechanism of electricity market to better play the role of energy storage is worthy of in-depth research. This paper proposes a trading adjustment mechanism for energy storage in electricity market based on the fluctuation degree of equivalent net load, and establishes a joint market model of energy market and frequency regulation market including storage power station. The example simulation shows that the trading adjustment mechanism proposed in this paper can effectively enhance the role of energy storage, and has a good effect on improving the fluctuation degree of net load and reducing system operating costs.

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A High-Efficiency Method to Determine Parameters of High Impedance Arc Fault Models

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IEEE TRANSACTIONS ON power DELIVERY 2022年第2期37卷 1203-1214页

作者： Wei, Mingjie Shi, Fang Zhang, Hengxu Yang, Fan Chen, Weijiang Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China Shanghai Jiao Tong Univ Dept Elect Engn Shanghai 200240 Peoples R China State Grid Corp China Beijing 10003 Peoples R China

Numerical modeling of the high impedance arc fault (HIAF) is essential to supplementing the deficiency of real-world fault cases and extending the fault scenarios. Setting parameters of the model correctly is the basis to reproduce practical fault waveforms. According to the literature, the parameters of HIAF models are mostly determined manually and subjectively. The existing automatic methods of parameter determination are mostly used in the modeling of other types of arcs (such as DC arcs and circuit breaker arcs), which do not consider the connections with power networks. It will be time-consuming if directly applying these methods to the HIAF model with the connection of a power network. In this paper, after introducing the unique requirements in simulating the nonlinearity of HIAFs, a high-efficiency parameter determination method is proposed for HIAF models. The method is realized by interfacing the optimizer programmed in Python with the HIAF model and power network established in PSCAD. In this process, a combination of pulse controllers is designed and certain configurations are proposed, so that the parameter determination procedure can be significantly simplified. Case studies show that, by combining the proposed high-efficiency method with our previously proposed DIST-C HIAF model, fitting accuracy and efficiency can be guaranteed at the same time. The time for parameter determination of a HIAF model is only within minutes, decreasing hundreds of times and independent of the length of desired waveforms.

关键词： Impedance Circuit faults Surface impedance Ionization Resistance Nonlinear distortion Integrated circuit modeling Arc model high impedance arc fault parameter determination high-efficiency

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Prediction and Preventive control Scheme for Wind and PV power Ramp Events

Prediction and Preventive Control Scheme for Wind and PV Pow...

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IEEE International Conference on power and power and Renewable Energy (ICPRE)

作者： Yifei Zhai Zengwei Wang Kunpeng Zhang Huan Ma Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China Power Grid Technology Center State Grid Shandong Electric Power Research Institute Jinan China

ISBN: (数字)9798350377460

ISBN: (纸本)9798350377477

As the large scale integration of photovoltaic and wind power into the grid increases, renewable energy ramp events have become a potential threat to the secure operation of the power grid. To effectively address renewable energy power ramp events, this paper proposes a prediction and preventive control scheme. First, a rolling warning approach is achieved by the long short-term memory network and fuzzy logic, which provides warning levels and guides decision-making for preventive control. Second, a two-stage optimization scheduling model is proposed, including a day-ahead and an intra-day sub-model. The two-stage scheduling model comprehensively considers power support from interconnectors and preventive control costs. Simulation results demonstrate that the proposed scheme can provide adaptive preventive control strategies for power ramp events with varying risk levels, thereby enhancing the utilization of renewable energy and improving the security of power system.

关键词： Photovoltaic systems Renewable energy sources Adaptation models Costs Simulation Decision making power system stability Wind power generation Wind forecasting Transient analysis

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Multitime Scale Active and Reactive power Coordinated Optimal dispatch in Active Distribution Network Considering Multiple Correlation of Renewable Energy Sources

Multitime Scale Active and Reactive Power Coordinated Optima...

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作者： Chen, Shuai Wang, Chengfu Zhang, Zhenwei Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education School of Electrical Engineering Shandong University Jinan China

To improve the adaptability for renewable energy sources (RES), a multitime scale optimal dispatch method, which considers the multiple correlations of RES, is proposed in the active distribution network (ADN). The proposed method includes a multiple correlation model of RES and a scheduling framework. The multiple correlation model of RES is formulated by t Copula function, Sklar's theorem, and conditional distribution of multivariate t distribution. The multiple correlation model can estimate the forecast error of the future period according to the historical data and the latest prediction. The scheduling framework further employs the revised forecast to coordinate the fast/slow-response regulation resources in the ADN under three timescales. In the day-Ahead stage, the operation state of slow-response resources is optimized and determined. In the intraday stage, the output of the fast-response resource, which is transferred to the real-Time stage as reference trajectory, is optimized based on the short-Term prediction. In the real-Time stage, the stochastic model predictive control is adopted to adjust the output of fast-response resources based on ultra-short-Term prediction and reference trajectory. Case analyses indicate that the proposed method can effectively reduce the voltage fluctuation, promote the utilization of demand-side resources, and improve the system economic performance by introducing the multiple correlation model. © 1972-2012 IEEE.

关键词： Stochastic systems

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Multi-level Voltage Coordination Optimization Strategy of Distribution Network Considering Multiple Devices

Multi-level Voltage Coordination Optimization Strategy of Di...

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IEEE Asia power and Energy Engineering Conference (APEEC)

作者： Caishuai Liang Mingqiang Wang Fengbin Sun Xia Zhang Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China Luyuan Electric Group Co. LTD Jinan China

ISBN: (数字)9798350373479

ISBN: (纸本)9798350373486

The presence of wind power, photovoltaic, and other distributed energy sources within the distribution network. The power quality of the distribution network degrades as the proportion of distributed energy increases. To address the uncertainty introduced by the integration of distributed energy, it is essential to coordinate and optimize the multi-voltage levels within the distribution network. Currently, most studies focus on achieving voltage control in the distribution network by minimizing either network loss or voltage fluctuation, often limiting consideration to a single voltage stage. Minimizing network loss can enhance the overall operational cost efficiency of the distribution network, but it has a limited impact on suppressing voltage fluctuation. Hence, this paper initially establishes a two-layer voltage control model for the distribution network through priority target programming. The first layer employs the minimum voltage deviation as the objective function to meet the 10-0.38 kV voltage control requirements. The second layer minimizes the total operational cost of the distribution network, incorporating network loss costs as the objective function to meet economic operational requirements. The programming is subsequently implemented in GAMS. Lastly, the effectiveness of the proposed model is validated using the IEEE-33 node system.

关键词： Costs Voltage fluctuations Fluctuations Uncertainty Distribution networks Transforms Programming

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Topology Identification for Distribution systems Based on Bayesian Nonparametric Model and Gaussian Mixture Ensemble Kalman Filter

Topology Identification for Distribution Systems Based on Ba...

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power and Electrical Engineering (ACPEE), 5th Asia Conference on

作者： Tingting Zhang Wen Zhang School of Control Science and Engineering Shandong University Jinan China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education School of Electrical Engineering Shandong University Jinan China

ISBN: (数字)9798350309638

ISBN: (纸本)9798350309645

To ensure the secure and reliable operation of active distribution systems (ADSs), it is essential to efficiently and accurately identify their time-varying topology. This paper proposes an estimation-based topology identification (TI) method for ADSs considering topology changes. The TI problem is formulated by a forecasting-aided estimation model, which is depicted by a discrete-time switching state-space model. The topology change process is described by a Bayesian nonparametric model that allows TI with limited knowledge of topology libraries. Then the Gaussian mixture ensemble Kalman filter (GM-EnKF) is employed to carry out the TI, where the underlying probability density is approximated by using Gaussian mixture model. In this case, the proposed method become capable of handling the unavoidable non-Gaussian noises in realistic distribution systems. Test results on various ADSs validates the effectiveness of the proposed GM-EnKF-based TI method on accurate and efficient topology identification.

关键词： Noise Estimation Termination of employment Switches Predictive models Topology Bayes methods

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Performance Improvement of a Three-Phase Interleaved DC-DC Converter Without Requiring Antisaturation control for Postfault Conditions

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IEEE TRANSACTIONS ON power ELECTRONICS 2021年第7期36卷 7378-7383页

作者： Rahimi, Tohid Ding, Lei Faraji, Rasoul Kheshti, Mostafa Pou, Josep Shandong Univ Jinan Sch Elect Engn Key Lab Power Syst Intelligent Dispatch & Control Jinan 250100 Peoples R China Nanyang Technol Univ Singapore 639798 Singapore

Employing interleaved techniques in dc-dc converters provide fault-tolerant capability to the faulted switches of the converter. In the case of one-phase failure, the other phases can continue operating. However, in interleaved topologies, if the output power is maintained at the desired constant value for postfault conditions, there is a saturation risk of inductors. In this letter, a postfault reconfiguration process for the three-phase interleaved dc-dc converter is proposed, which guarantees the operation of the inductor without saturation risk after power switch failures. The reconfiguration steps do not require isolating the inductor of the corresponding faulty phase. Experimental results of the presented converter verify the operation of the inductor without saturation and the effectiveness of the proposed strategy.

关键词： Inductors Topology Inductance Fuses Fault tolerant systems Switching frequency DC-DC power converters DC-DC converters postfault reconfiguration saturation of inductors

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Short-Term Load Prediction of EV Charging Station Based on LSTM Recursion

Short-Term Load Prediction of EV Charging Station Based on L...

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power Science and Technology (ICPST), IEEE International Conference on

作者： Ziyu Xu Kuan Cao Yutian Liu Chunyi Wang Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China Development Planning Department State Grid Shandong Electric Power Company Jinan China

ISBN: (数字)9798350349030

ISBN: (纸本)9798350349047

With the rapidly increasing market share of electric vehicles (EV) in recent years, the randomness and uncertainty of EV charging load have posed challenges to the operation of distribution networks. To improve accuracy in load prediction of EV charging station, a short-term load prediction method based on the long short-term memory (LSTM) recursive neural network is proposed in the paper. First, the Canopy-based K-means clustering algorithm is improved to divide the similarly daily load sets of EV charging station. Then, the characteristic information of load days, such as meteorological data, is processed to obtain the typical feature vector of each load set. Next, the bidirectional long short-term memory (BiLSTM) models corresponding to each load set are trained based on the sliding window principle and phase space reconstruction. By calculating the Euclidean distance of the feature vectors between the predicted day and each load set, the most suitable pre-trained BiLSTM model is selected to predict the charging station load. Finally, simulation results demonstrate that the proposed method can effectively improve the load prediction accuracy.

关键词： Recurrent neural networks Accuracy Uncertainty Simulation Predictive models Feature extraction Electric vehicle charging

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Dynamic Economic dispatch Considering Transmission-Distribution Coordination and Automatic Regulation Effect

Dynamic Economic Dispatch Considering Transmission-Distribut...

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作者： Wang, Mingqiang Wu, Yuqian Yang, Ming Wang, Mengxia Jing, Linguo Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan250002 China State Grid Tangshan Power Supply Company Tangshan063000 China State Grid Binzhou Power Supply Company Binzhou256600 China

With the rapid increase of renewable energy sources, the variability and uncertainty in power systems are significantly increased, and the power system operation is facing more and more challenges. In the traditional dynamic economic dispatch (DED) of transmission systems, the frequency and voltage regulation effects are not actively utilized. In addition, the transmission systems and distribution systems are optimized separately;the transmission-distribution coordination effect is not considered. In this article, a new DED is proposed. The optimal scheduling results are obtained by making a balance between operating cost and reliability cost. Both the automatic regulation effect and transmission-distribution coordination effect are explored and exploited in terms of the equivalent reserve, which can reduce the reserve provided by generating units, and can further enhance the security and economics of power system operation. The validity and effectiveness of the proposed model are illustrated by case studies. © 1972-2012 IEEE.

关键词： Scheduling

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A Multi-Criteria Approach for Evaluating Voltage Regulation Characteristics Facilitating Flexible Operations of Fossil-Fueled power Generators

A Multi-Criteria Approach for Evaluating Voltage Regulation ...

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IEEE General Meeting power& Energy Society

作者： Nuo Xu Xiaodong Chu Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education Shandong University Jinan P. R. China

Conventional fossil-fueled power generators are one of flexibility options to accommodate the ever increasing penetration of fluctuating renewable energy whereas their capability constraints are not negligible. A multi-criteria approach is proposed in this paper for evaluating voltage regulation characteristics of fossil-fueled power generators to facilitate their flexible operations. First, an evaluation index system is established accounting for three vital criteria including steady-state performance, dynamic performance, and transient performance of the excitation system. Second, Bayesian BWM and CRITIC methods are used to determine respectively each index’s subjective and objective weights in which the game theory is leveraged to obtain the combined weights. Finally, PROMETHEE II is exploited to rank candidate generators based on the preference functions. The proposed multi-criteria approach is tested on an example system to verify its feasibility and effectiveness. The generator with balanced performance in all aspects prevails in the evaluation of the voltage regulation characteristics.

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