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2020 IEEE/IAS Industrial and Commercial power system Asia, I and CPS Asia 2020

作者： Ma, Changhui Wang, Liang Gai, Chenhao Yang, Dong Zhang, Pengfei Zhang, Hengxu Li, Changgang Electric Power Research Institute State Grid Shandong Electric Power Company Jinan Shandong China Dispatch and Control Center State Grid Shandong Electrical Power Company Jinan Shandong China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan Shandong China State Grid International Development Limited Beijing China

ISBN: (纸本)9781728143033

For hours-ahead assessment of power systems with a high penetration level of renewable generation, a large number of uncertain scenarios should be checked to ensure the frequency security of the system after the severe power disturbance following HVDC blocking. In this situation, the full time-domain simulation is unsuitable as a result of the heavy calculation burden. To fulfill the quick assessment of the frequency security, the online frequency security assessment framework based on deep learning is proposed in this paper. The Deep Belief Network (DBN) method is used to establish the framework. The sample generation method is researched to generate representative samples for the purposed of higher assessment accuracy. A large-scale AC-DC interconnected power grid is adopted to verify the validity of the proposed assessment method. © 2020 IEEE.

关键词： Time domain analysis

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Reliability Evaluation of Distribution Grid Considering Flexible Grid Connection of Distributed Photovoltaic

Reliability Evaluation of Distribution Grid Considering Flex...

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作者： Zecheng Li Yanying Sun Chen Feng State Grid Ningxia Electric Power Research Institute School of Mechanical Electronic and Information Engineering China University of Mining and Technology (Beijing) The Key Laboratory of Power System Intelligent Dispatch and Control Shandong University

Aiming at the problem that the flexible access of distributed photovoltaics to the distribution network affects its reliability,this paper establishes a model of the distributed photovoltaic output probability based on the typical output characteristics of distributed photovoltaics ***,the power grid risk assessment indicators are determined to facilitate the quantification of distribution network risks,including voltage over-limit,power over-limit,and load loss risk ***,a distribution network model containing distributed photovoltaic grid-connected is established on the MATlab simulation platform,and the risk assessment of the distribution network containing distributed photovoltaic grid-connected is carried out.

关键词： distributed photovoltaic voltage limit power limit loss of load risk assessment

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Energy Storage Involved in Eliminating Intermittent Two-Stage Robust Optimal dispatching

Energy Storage Involved in Eliminating Intermittent Two-Stag...

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IEEE/IAS Industrial and Commercial power system Asia (I&CPS Asia)

作者： Yiran Ma Xueshan Han Ming Yang Bincheng Zhao Key Laboratory of Power System Intelligent Dispatch and Control Shandong University Jinan China

ISBN: (数字)9781728143033

ISBN: (纸本)9781728143040

As renewable energy increasingly connecting into the power grids, the regulation capacity of automatic power generation control (AGC) is gradually decreasing, which is urgent to cooperate with active equipment such as energy storage. In current, dispatch decision-making methods often ignore the intermittent effects of renewable energy. Energy storage can take advantage of its fast regulation rate to better cope with the intermittency of renewable energy based on AGC unit dispatching. Therefore, this paper proposes a two-stage robust optimization dispatching model in which energy storage participates in eliminating intermittency of renewable energy, and abstracts the track of energy storage and AGC units in control as a process between any two moments. This model can make full use of the rapid adjustment capability of energy storage and makes up for the lack of response speed of the AGC unit, improves its climbing ability to release the unit's adjustment potential, and responds to the intermittent problems of renewable energy power generation. The model is solved by column and constraint generation algorithm (C & CG). The example shows that the model is more robust than the model that does not consider energy storage participates in eliminating intermittent effect and has obvious advantages in economy and efficiency.

关键词： Energy storage Industrial power systems Asia Conferences dispatching Robustness

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An Improved Variable Step Size P&O MPPT Algorithm Based on Constant Voltage and K Division Technology 3

An Improved Variable Step Size P&O MPPT Algorithm Based on C...

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Joint 2019 International Conference on Ubiquitous power Internet of Things, UPIOT 2019 and 2019 3rd International Symposium on Green Energy and Smart Grid, SGESG 2019

作者： ZHANG Peng SUI Huibin KONG Hongmei Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University

In the literature, various techniques have been proposed to achieve the maximum output power of photovoltaic cells, but the fixed step size perturbation and observation and incremental conductance algorithm can't enhance effectively the peculiarity of the PV system, due to their slow tracking speed, big power loss and limited accuracy. An improved variable step size perturbation and observation MPPT algorithm based on the K division method is proposed. The symbol of dp/du before and after the disturbance is judged, if the two adjacent samples have the same symbol, the disturbance step size remains unchanged. On the contrary, the disturbance step size will be divided by K and become the new disturbance step size until achieving the maximum output power. The simulation establish on MATlab/Simulink reveals that the method has fast response speed, high accuracy, low power loss, and can locate the new maximum power point quickly when environmental conditions change.

关键词： An Improved Variable Step Size P&O MPPT Algorithm Based on Constant Voltage and K Division Technology

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New Cycle-based Formulation, Cost Function, and Heuristics for DC OPF Based controlled Islanding

arXiv

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arXiv 2023年

作者： Tyuryukanov, Ilya Popov, Marjan Bos, Jorrit A. van der Meijden, Mart A.M.M. Terzija, Vladimir Delft University of Technology Delft2628CD Netherlands Siemens Energy AG Freyeslebenstr. 1 Erlangen91058 Germany TenneT TSO B.V. Utrechtseweg 310 Arnhem6812AR Netherlands Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education School of Electrical Engineering Shandong University Jinan250061 China

This paper presents a new formulation for intentional controlled islanding (ICI) of power transmission grids based on mixed-integer linear programming (MILP) DC optimal power flow (OPF) model. We highlight several deficiencies of the most well-known formulation for this problem and propose new enhancements for their improvement. In particular, we propose a new alternative optimization objective that may be more suitable for ICI than the minimization of load shedding, a new set of island connectivity constraints, and a new set of constraints for DC OPF with switching, and a new MILP heuristic to find initial feasible solutions for ICI. It is shown that the proposed improvements help to reduce the final optimality gaps as compared to the benchmark model on several test instances. © 2023, CC BY.

关键词： Integer programming

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PV Prediction based on PSO-GS-SVM Hybrid Model 3

PV Prediction based on PSO-GS-SVM Hybrid Model

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Joint 2019 International Conference on Ubiquitous power Internet of Things, UPIOT 2019 and 2019 3rd International Symposium on Green Energy and Smart Grid, SGESG 2019

作者： KONG Hongmei SUI Huibin ZHANG Peng Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University

Photovoltaic power generation is affected by many factors, with volatility and intermittent characteristics. Large-scale photovoltaic access to the power grid poses great challenges to the safety and stability of power systems. Therefore, accurate prediction of photovoltaic power generation helps dispatchers adjust scheduling schedules in a timely manner, effectively reducing the adverse impact of photovoltaic power generation access on the power grid. This paper proposes a hybrid PV power prediction model based on PSO-GS-SVM. The particle swarm optimization(PSO) method is used to optimize the large step size of the support vector machine(SVM), and the parameter optimization range is obtained. GridSearch Method(GS) refined parameters optimization of PSO-SVM, and obtained PSO-GS-SVM hybrid model. The model is used to train and predict the normalized and dimensional sunny and non-clear working conditions data sets, and compared with BP neural network, SVM and PSO-SVM models. The results show that the PSO-GS-SVM hybrid model has better generalization ability and higher fitting effect.

关键词： PV Prediction based on PSO-GS-SVM Hybrid Model Hybrid

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A Hybrid Photovoltaic power Prediction Model Based on Multi-source Data Fusion and Deep Learning

A Hybrid Photovoltaic Power Prediction Model Based on Multi-...

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IEEE Student Conference on Electric Machines and systems

作者： Zhiyuan Si Ming Yang Yixiao Yu Tingting Ding Menglin Li Key Laboratory of Power System Intelligent Dispatch and Control Shandong University Jinan China

ISBN: (数字)9781728156224

ISBN: (纸本)9781728156231

With the rapid development of the world economy, environmental and energy problems have become increasingly prominent. This fact motivates the exploitation of renewable energy, such as solar power. Solar photovoltaic (PV) power has been integrated into modern smart grids on a large scale. Accurate photovoltaic prediction is the key to ensure the stable operation of the power grid. The single prediction model is difficult to be universal due to the limitations of the model. Therefore, this paper proposes a hybrid ultra-short-term photovoltaic power prediction model based on multi-source data fusion and deep learning. First, the satellite cloud images, historical power sequences, and numerical weather prediction (NWP) data are fused. Then, the photovoltaic power prediction models are established by using appropriate deep learning methods (convolutional neural networks (CNN), long-short term memory (LSTM) networks, and Extreme Gradient Boosting (XGBoost)) according to different data. Finally, the three models are combined to get the final prediction result. The results show that the proposed method in this paper has better forecasting performance than other single models.

关键词： Photovoltaic systems Deep learning Satellites Predictive models Data models Hybrid power systems Numerical models

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Rolling dispatch framework of integrated electricity-gas system considering power-to-gas facilities and natural gas network dynamics: Modelling and case studies

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INTERNATIONAL JOURNAL OF ELECTRICAL power & ENERGY systemS 2023年第1期152卷

作者： Gao, Han Li, Zhengshuo Wang, Cheng Chen, Sheng Fan, Miao Sun, Hongbin Shandong Univ Sch Elect Engn Jinan 250061 Peoples R China Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China North China Elect Power Univ Sch Elect & Elect Engn Beijing 102206 Peoples R China Hohai Univ Dept Elect Engn & Energy Nanjing 210098 Peoples R China Siemens Ind Inc Schenectady NY 12305 USA Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

Rolling dispatch strategy is widely used in power systems to handle the uncertainty and volatility of renewable energy. Meanwhile, flexible gas-fired units and emerging power-to-gas (P2G) facilities integrate the power system and natural gas system as an integrated electricity-gas system (IEGS). Hence, rolling dispatch should be applied to the whole IEGS. This paper designs the rolling dispatch framework in the IEGS and proposes the partial-differential-equations-involved (PDEs) mathematical models that accurately formulate the natural gas network dynamics and the operation properties of P2G facilities to retain the facticity of the IEGS in the rolling dispatch process (e.g., the linepack characteristics of natural gas networks and the physical limits of the P2G facilities). The impact of uncertain wind power on the IEGS operation is also considered. In order to reduce the computational burdens, this paper employs a combination of implicit difference method and the technique of linearization to transform the original rolling dispatch model with PDEs and chance constraints into mixed integer linear programming which is solvable by off-the-shelf solvers. The results of the case studies demon-strate that the proposed rolling dispatch strategy promotes renewable energy accommodation, enhances the flexibility, security, and efficiency of the IEGS, and mitigates the impact of renewable energy's uncertainty and volatility on the IEGS.

关键词： Integrated electricity-gas system Natural gas network dynamics power-to-gas facilities Intraday rolling dispatch Partial differential equations

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Quantitative Evaluation of Available Capacity of Series Battery Pack Based on Monte Carlo Simulation

Quantitative Evaluation of Available Capacity of Series Batt...

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2020 Asia Energy and Electrical Engineering Symposium

作者： Shi, Miaoyan Shi, Xiaohan Li, Zeyu Zhao, Yawen Ren, Shijie Ding, Lianlian Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan Peoples R China Shandong Goldencell Elect Technol Co Ltd Zaozhuang Peoples R China

ISBN: (纸本)9781728167824

To obtain high-power and large-capacity, power battery system for EVs or energy storage battery system for power grid usually takes the pack form that connects hundreds or even thousands of cells in a series-parallel structure. Therefore, the inconsistency between cells becomes a key factor that affects the performance of the battery pack. To evaluate this impact, this paper propose a quantitative evaluation method from the statistical analysis by considering the impact of the cells' inconsistency on the battery pack performance as a stochastic process. Firstly, the available capacity is taken as the indicator of battery pack's performance and its probability distribution features is derived based on the probability distribution of cells' capacity, SOC and internal resistance. Then, the probability distribution function of available capacity and its numerical characteristics including expectation and variance are calculated based on Monte Carlo simulation in the case that the cells' parameters follow the normal distribution. The results of the theoretical analysis and the simulating calculation show that the available capacity of the battery pack follows Burr distribution with significant skewness and the expectation of pack's available capacity loss is in direct proportion to the variance of cells' parameters and is proportional to the power function of cells' number when cells' parameters are normally distributed.

关键词： lithium-ion battery inconsistency the Monte Carlo quantitative analysis capacity

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Dynamic Economic dispatching Considering Time-Coupling Spinning Reserve Response Risk with High Penetration of Wind power

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ENERGIES 2022年第21期15卷 7831-7831页

作者： Pei, Younan Han, Xueshan Ye, Pingfeng Zhang, Yumin Zhang, Lihong Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Peoples R China Shandong Univ Sci & Technol Coll Energy Storage Technol Qingdao 266590 Peoples R China Shandong Univ Sci & Technol Coll Elect Engn & Automat Qingdao 266590 Peoples R China

Aiming at the problem that the current dynamic economic dispatch (DED) fails to consider the response risk of spinning reserve caused by the fluctuation and uncertainty of wind power, we work out a DED problem considering time-coupling spinning reserve response risk while the stochasticity and variability arising from RESs are taken into consideration. The developed framwork unified the response risk of reserve caused by forced shutdown of the unit into the response risk caused by time coupling. The expected customer interruption cost (ECOST) and the expected abandoned wind cost considering this reserve response risk are added to the objective function. While seeking the minimum objective function, the system is automatically configured with suitable reserve to ensure the consistency of the system's response risk in each period. An improved multi-universe parallel quantum genetic algorithm was used to solve the model. Numerical examples and analysis prove the effectiveness and feasibility of the proposed method.

关键词： dynamic economic dispatch multi-universe parallel quantum genetic algorithm power system response risk spinning reserve

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