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8th IEEE International Conference on Advanced power system Automation and Protection, APAP 2019

作者： Zhang, Liqiang Cong, Wei Dong, Gang Sun, Yun Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China State Grid Shandong Electric Power Company Jinan China

ISBN: (纸本)9781728117225

The phase information of single-phase electric meter is crucial to improve the level of load management and the quality of modeling. A method for single-phase electric meter phase discrimination based on multiple linear regression (MLR) is proposed. The MLR equation takes the single-phase electric meter voltage as the dependent variable. Meanwhile, it takes the gateway meter voltage, the gateway meter current and the single-phase electric meter current as the independent variables. Each single-phase meter forms a regression equation with the gateway meter A, B and C respectively. The determination coefficients of the three regression equations are calculated. According to the value of the coefficients, the phase of single-phase electric meter is discriminated. An example is given to analyze the proposed method with actual energy meter reading data. The analysis results show that the proposed method has higher accuracy and reliability. © 2019 IEEE.

关键词： Multiple linear regression

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Real-time static voltage stability assessment in large-scale power systems based on spectrum estimation of phasor measurement unit data

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INTERNATIONAL JOURNAL OF ELECTRICAL power & ENERGY systemS 2021年 124卷 106196-106196页

作者： Yang, Fan Ling, Zenan Wei, Mingjie Mi, Tiebin Yang, Haosen Qiu, Robert C. Shanghai Jiao Tong Univ State Energy Smart Grid Res & Dev Ctr Ctr Big Data & Artificial Intelligence Dept Elect Engn Shanghai 200240 Peoples R China Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China

Real-time static voltage stability assessment is crucial to a stressed modern grid. This paper, based on the moment-based spectrum estimation method, proposes a data-driven approach to gain insight into changes of voltage magnitudes via synchronous phasor measurement unit (PMU) data, such that proper actions can be taken against voltage collapse. Built upon random matrix theory, an inverse Jacobian related indicator, i.e., spectrum estimation based stability indicator (SESI), is introduced in this paper to track the motion of the system. After considering the relationship between moments and distributions, this method allows for the regime where the sample size is significantly smaller than the dimensionality. It is adaptive to the real-time static voltage stability assessment in large-scale power systems where the sample size in a sliding window is extremely smaller than the dimensionality of measurement variables, hence delivering a recent status with a low computational cost. In this way, the static voltage stability assessment of a power system with massive amounts of measurement variables can be more sensitively and efficiently implemented. Case studies with the IEEE 118-bus system, the IEEE 300bus system, and a Polish 2383-bus system verify the effectiveness of the proposed approach.

关键词： Static voltage stability assessment Data-driven Wide-area monitoring Spectrum estimation Phasor measurement units

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Socio-inspired democratic political algorithm for optimal PV array reconfiguration to mitigate partial shading

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SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS 2021年 48卷

作者： Yang, Bo Shao, Ruining Zhang, Mengting Ye, Haoyin Liu, Bingqiang Bao, Tongyu Wang, Junting Shu, Hongchun Ren, Yaxing Ye, Hua Kunming Univ Sci & Technol Fac Elect Power Engn Kunming 650500 Peoples R China Elect Power Res Inst Yunnan Power Grid Co Ltd Kunming 650217 Peoples R China Univ Warwick Warwick Mfg Grp Coventry CV4 7AL England Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China

Time-varying environment conditions have significantly influenced operation performance of photovoltaic generation. Partial shading condition is a typical problem which usually increases mismatch losses and reduces output power of photovoltaic array. For large-scale PV power plants, partial shading may affect the efficiency of the entire PV system. To solve this issue, this paper proposes a novel socio-inspired photovoltaic reconfiguration approach, called democratic political algorithm (DPA), which can effectively reduce power losses, improve power generation efficiency and accelerate convergence rate. DPA aims to reconfigure photovoltaic array's electrical connection to minimize malignant impacts from partial shading condition and then obtain higher quality output characteristics. Three case studies are carried out to verify the effectiveness and advantages of DPA, together with a thorough comparison of nine typical meta-heuristic algorithms. Simulation results demonstrate that DPA can enhance output power of photovoltaic array by 21.47% for a 10 x 10 (small) PV array, 21.55% for a 15 x 15 (medium) PV array, and 20.98% for a 20 x 20 (large) PV array compared to total cross tied interconnection scheme.

关键词： Photovoltaic array Partial shading condition Reconfiguration Democratic political algorithm

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Multi-level interactive unit commitment of regional power system

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INTERNATIONAL JOURNAL OF ELECTRICAL power & ENERGY systemS 2021年 125卷 106464-106464页

作者： Ji, Xingquan Zhang, Yumin Han, Xueshan Ye, Pingfeng Xu, Bo Yu, Yongjin Shandong Univ Sci & Technol Coll Elect Engn & Automat Qingdao 266590 Peoples R China Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China State Grid Energy Res Inst Co Beijing 102209 Peoples R China

Distributed energy resource (DER) including wind power, solar energy and energy storage system (ESS) are connected to the active distribution network (ADN) in various combination ways, which makes the distribution network have interaction. As a bridge connecting the transmission grid (TG) and micro grid (MG), ADN breaks the traditional operation pattern of TG + ADN + MG. Considering the physical connections and shared information among TG, ADN and MG, this paper proposes a decentralized and parallel analytical target cascading (ATC) algorithm for interactive unit commitment (UC) implementation in regional power systems. To explore the synergistic ability of the TG + ADN + MG coping with uncertainties of DER, i.e., wind power, the primary and secondary frequency regulation of TG are implemented to cope with uncertainties. Furthermore, the distributional uncertainty of wind power is well modeled by data driven, which is proposed in our previous work (Zhang et al., 2019) [1]. Both the startup/shutdown variables of the thermal units and the variables in TG + ADN + MG are integrated into the multi-level interactive UC model to optimize simultaneously, thus realizing the optimal goal of the whole network, resources complementary and optimal allocation of power system. An improved 6-bus system is used to test the proposed model, the numerical results show that the proposed decentralized algorithm is a fully parallelized procedure. And it also demonstrates the parallel implementation significantly enhances computations efficiency of the ATC algorithm.

关键词： Analytical target cascading algorithm Distributed parallel computing Primary and secondary frequency regulation Unit commitment

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Wind power Probabilistic Forecasting Based on Wind Correction Using Weather Research and Forecasting Model

Wind Power Probabilistic Forecasting Based on Wind Correctio...

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IEEE Student Conference on Electric Machines and systems

作者： Menglin Li Ming Yang Yixiao Yu Peng Li Zhiyuan Si Jiajun Yang Key Laboratory of Power System Intelligent Dispatch and Control Shandong University Jinan China Electric Power Research Institute of State Grid Shaanxi Electric Power Corporation Xi’an China

ISBN: (数字)9781728156224

ISBN: (纸本)9781728156231

This paper proposes a wind power probabilistic forecasting (WPPF) method by correcting the wind forecasting (WF) obtained from the weather research and forecasting (WRF) simulation. Short term wind power forecasting highly depends on the numerical weather prediction (NWP), wind forecasting especially, which contributes the most error of the predicted wind power. This method is based on the WRF, it first analyzes the performance on wind forecasting and the relationship between the predicted wind and the observed one. Second, the Hidden Markov Model (HMM) ameliorated by the Gaussian mixture model (GMM) is introduced to extract the association of the predicted wind and forecasting error and the inner temporal ship of error itself, and makes correction on the raw wind forecasting. Finally, the spare Bayesian learning (SBL) is used to generate the wind power probabilistic prediction. Case study demonstrates the proposed method significantly enhances wind forecasting accuracy and lead to a better WPPF.

关键词： Hidden Markov models Wind power generation Predictive models Probabilistic logic Forecasting Wind forecasting Marine vehicles

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Design of Micro Dynamic Simulation system for power system with Wind power and VSC-HVDC

Design of Micro Dynamic Simulation System for Power System w...

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IEEE Conference on Energy Internet and Energy system Integration (EI2)

作者： Leshu Sun Hengxu Zhang Yongji Cao Changgang Li Qi Guo Yihua Zhu Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education Shandong University Jinan China Electric Power Research Institute China Southern Power Grid Guangzhou China

ISBN: (数字)9781728196060

ISBN: (纸本)9781728196077

The excessive use of fossil energy has huge impacts on environment. The energy revolution with optimized energy structure has been advocated. At this background, the main development direction of energy structure is to increase the proportion of renewable energy to the grid. The two main kinds of power system analysis methods is digital simulation relying on electromagnetic or electromechanical transient software and the dynamic simulation composed by physical elements. Traditional dynamic system can only meet the requirement of AC transmission system simulation and is difficult to be expanded with new elements. In this paper, a micro dynamic simulation system is designed according to the similarity theorem. Moreover, the wind power module and VSC-HVDC module are added to meet the requirement of simulating future power systems. In addition, an experimental system based on DSP and FPGA is designed to monitor and control different dynamic elements.

关键词： Analytical models power system dynamics Wind power generation Data models systems simulation Integrated circuit modeling Transient analysis

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Event-Driven Fast Frequency Response for Large Active power Disturbances

Event-Driven Fast Frequency Response for Large Active Power ...

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IEEE Conference on Energy Internet and Energy system Integration (EI2)

作者： Yongji Cao Hengxu Zhang Changgang Li Leshu Sun Qi Guo Yihua Zhu Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education Shandong University Jinan China Electric Power Research Institute China Southern Power Grid Guangzhou China

ISBN: (数字)9781728196060

ISBN: (纸本)9781728196077

With the rapid development of renewable energy sources, the equivalent inertia of power systems is decreasing, which leads to more drastic dynamic frequency response. This paper proposes an event-driven fast frequency response (EFFR) approach to counter frequency decline after large power disturbances. Based on the data from the wide area measurement systems, a centralized control framework is established to perform the EFFR. Then, the reference power for EFFR can be determined promptly via monitoring active power deficits. Considering the control costs and power reserves, a utility index is created to quantify the priority of each unit to participate in EFFR, on which the reference power is distributed. Furthermore, a recovery strategy is designed to restore the normal operation states of units when the power system enters the quasi-steady state. According to a droop slope, units exit the EFFR mode in sequence, of which the distributed reference power decreases gradually. A case study is presented to validate the feasibility and effectiveness of the proposed approach.

关键词： Stability criteria power system stability Frequency response Indexes Monitoring Frequency control Centralized control

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A deep reinforcement learning method for managing wind farm uncertainties through energy storage system control and external reserve purchasing

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INTERNATIONAL JOURNAL OF ELECTRICAL power & ENERGY systemS 2020年 119卷 105928-000页

作者： Yang, J. J. Yang, M. Wang, M. X. Du, P. J. Yu, Y. X. Shandong Univ Minist Educ Key Lab Power Intelligent Dispatch & Control Jinan 250061 Peoples R China State Grid Shaanxi Elect Power Res Inst Xian 710054 Peoples R China

In deregulated environment, the wind power producers (WPPs) will face the challenge of how to increase their revenues under uncertainties of wind generation and electricity price. This paper proposes a method based on deep reinforcement learning (DRL) to address this issue. A data-driven controller that directly maps the input observations, i.e., the forecasted wind generation and electricity price, to the control actions of the wind farm, i.e., the charge/discharge schedule of the relevant energy storage system (ESS) and the reserve purchase schedule, is trained according to the method. By the well-trained controller, the influence of the uncertainties of wind power and electricity price on the revenue can be automatically involved and an expected optimal decision can be obtained. Furthermore, a targeted DRL algorithm, i.e., the Rainbow algorithm, is implemented to improve the effectiveness of the controller. Especially, the algorithm can overcome the limitation of the conventional reinforcement learning algorithms that the input states must be discrete, and thus the validity of the control strategy can be significantly improved. Simulation results illustrate that the proposed method can effectively cope with the uncertainties and bring high revenues to the WPPs.

关键词： Deep reinforcement learning Energy storage system Optimal controller Rainbow Reserve Wind power producer

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Influence Analysis of Thermal States on Dynamic Frequency Response for power systems with High Renewables

Influence Analysis of Thermal States on Dynamic Frequency Re...

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Sustainable power and Energy Conference (iSPEC)

作者： Yongji Cao Hengxu Zhang Changgang Li Leshu Sun Chen Li Hao Qin Qi Guo Yihua Zhu Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education Shandong University Jinan China State Key Laboratory of HVDC Electric Power Research Institute National Energy Power Grid Technology R&D Centre Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China

ISBN: (数字)9781728191645

ISBN: (纸本)9781728191652

As thermal generators are substituted by renewables, the power reserves are decreasing and the influence of boiler thermal states on frequency dynamics becomes more severe. The variations of thermal states can aggravate dynamic frequency response, especially for power systems with high renewables. However, the system frequency response (SFR) model has been widely adopted, but in which the thermal states are neglected. This paper analyzes the influence of thermal states on dynamic frequency response quantitatively. The modified SFR models are built by extending the boiler models with different simplification degrees. Then, from the view of the response amplitude and time, the quantitative indices are established to measure the response trajectories of modified SFR models. And the characteristics of frequency dynamics and the statistic indices of data sequences are utilized to analyze the influences of thermal states and assess the performances of modified SFR models. According to the results of comparative analysis, the neglect of thermal states incurs more optimistic frequency dynamics and impairs the frequency stability of power systems with high renewables. Additionally, the accuracy of the SFR model can be enhanced even with the most simplified boiler model.

关键词： Analytical models power system dynamics power system stability Boilers Frequency response Thermal analysis Thermal stability

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Research on DC Microgrid Protection Based on Improved Dual-Slope Current Differential Protection

Research on DC Microgrid Protection Based on Improved Dual-S...

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IEEE Student Conference on Electric Machines and systems

作者： Mingyang Wang Qing Chen Liuyang Chen Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong Ministry of Education Shandong Ministry of Education Shandong University Jinan China

ISBN: (数字)9781728156224

ISBN: (纸本)9781728156231

This paper presents a fault detection method based on an improved dual-slope current differential protection. Traditional current differential protection needs to consider both the action sensitivity in the case of internal faults and the protection reliability in case of external faults. The braking coefficient cannot be set too low, so the sensitivity to internal high-impedance faults is low. For this reason, this paper improves the traditional current differential protection. On the basis of the dual-slope current differential protection method, it adds a judgment delay time with inverse time characteristics. Without changing the original performance of the differential protection, it increases its sensitivity to internal high-impedance faults improves the power supply capacity of the system.

关键词： Sensitivity power supplies Fault detection Microgrids Fault location Reliability Faces

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