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

作者： Jiao, Min Li, Peng Yang, Ming Han, Longxiao Wang, Qiushi Yu, Yixiao Li, Menglin Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan Peoples R China

ISBN: (纸本)9798350339345

With the continuous expansion of wind power generation, wind power curtailment is becoming increasingly serious. In order to improve wind power accommodation capacity, more flexibility resources that can be utilized by electrical power system (EPS) need to be identified. This paper proposed a decentralized coordinated robust dispatch model of multi-area integrated electricity and heating system (IEHS), considering the dynamic characteristics of district heating network (DHN) and flexibility from interconnected IEHS transferred though tie-line. Meanwhile, the risk of wind power accommodation is also considered to balance the operational costs and risk costs. The alternating direction multiplier method (ADMM) is applied to solve the coordinated robust dispatch of multi-area IEHS. The results of the case studies show that the proposed model can optimize the allocation of power generation and flexibility resources in multi-area interconnected system, realize multi-area interconnected system flexibility sharing and effectively reducing operating costs.

关键词： Integrated electricity and heating system dynamic haracteristics coordinated dispatch decentralized multi-area interconnected system

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Carbon Cost Pass-through Analysis Considering Renewable Energy Consumption 4

Carbon Cost Pass-through Analysis Considering Renewable Ener...

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4th International Conference on Smart power and Internet Energy systems (SPIES)

作者： Su, Xinyan Zhang, Li Wang, Hao Wang, Yuxi Song, Shihang Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan Peoples R China

ISBN: (纸本)9781665489577

The establishment of carbon allowances and carbon market has changed the competitiveness of thermal-generating units in the energy market and produced carbon cost passing through to electricity prices. With the increase in the proportion of renewable energy connected to the grid, thermal units have a strong performance in the ancillary service market due to their good regulation characteristics. For this situation, this paper establishes the carbon cost pass-through rate calculation model based on simulating energy market transactions which used the energy-reserve joint optimization model to consider the participation of thermal units in the energy market and reserve market under the condition of a high proportion of renewable energy connected to the grid. A 10-unit system is taken as an example to verify the effectiveness of the improved carbon cost pass-through analysis, and analyze the impact of changes in wind power integration on carbon cost pass-through.

关键词： carbon cost pass-through renewable energy energy-reserve joint optimization Least Squares regression

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A power supply restoration method of distribution network based on NSGA-II algorithm 3

A power supply restoration method of distribution network ba...

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3rd International Academic Exchange Conference on Science and Technology Innovation, IAECST 2021

作者： Zhou, Fengyuan Gao, Zhanjun Mu, Jinshuang Zong, Peng Ministry of Education Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Jinan China

ISBN: (纸本)9781665402675

With the rapid development of today's economy and society, people put forward higher requirements for power quality. In the process of distribution network operation, if there is a fault, it will produce immeasurable loss. It is necessary to restore the power supply in the non-fault power outage area in time. Therefore, it is particularly important to restore the power supply of distribution network quickly and efficiently. This paper considers factors such as load recovery, switching operation times and network loss. Based on the mathematical model of distribution network restoration and reconstruction, a genetic algorithm for distribution network power supply restoration and reconstruction is proposed. Combined with the characteristics of distribution network, the crossover rate and mutation rate suitable for distribution network are selected to improve the efficiency of the algorithm and make it quickly converge to the global optimal solution. Finally, the feasibility of distribution network is verified by an example. © 2021 IEEE.

关键词： Genetic algorithms

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Black Start Scheme of Wind-storage Combined system Based on Virtual Synchronous Generator control 2

Black Start Scheme of Wind-storage Combined System Based on ...

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2nd Asia Conference on Electrical, power and Computer Engineering, EPCE 2023

作者： Wang, Hao Wang, Hongtao Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China

ISBN: (纸本)9798350310818

With a high proportion of wind power generations connected to the grid, wind power generation is expected to be a black-start source. This paper proposed a black start scheme based on virtual synchronous generator (VSG) control for wind-storage combined system. The energy storage inverter was transformed into a VSG with the secondary frequency regulation ability by improved frequency synchronous control (IFSC), and a conventional VSG controller was designed for the rotor side inverter of doubly fed induction generator. And a control mode switching device was designed for the energy storage in order to maintain the grid stability after black start. This paper built the model of wind-storage combined system on the Matlab/Simulink for black start simulation. The simulation results show that the maximum frequency deviation is 68.75% lower than the conventional control when the ancillary machines of wind turbines were restored. What's more, the maximum frequency deviation shall not exceed 0.12%, and the maximum voltage deviation shall not exceed 8% during the black start process and the controllers can realize no-error frequency adjustment. Finally, control mode switching device can smoothly switch IFSC to VSG. Thus, the effectiveness of the proposed black start scheme and controllers are verified. © 2023 IEEE.

关键词： controllers

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Cascading Failures Assessment with High Penetration of DFIG Based Wind Turbines

Cascading Failures Assessment with High Penetration of DFIG ...

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2021 IEEE Sustainable power and Energy Conference, iSPEC 2021

作者： Liu, Tianhao Zhu, Yuanzhen Sun, Runjia Liu, Yutian Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan China

ISBN: (纸本)9781665414395

An assessment method of cascading failure is proposed to acquire high-risk cascading failures chains under high penetration of renewable energy power system. At first, a dynamic simulation model considering the controller of DFIG is established, and the simplified LVRT model is proposed for the DFIG response model. Then, a risk index is defined for the depth first tree search method used in searching proceeding. Finally, a searching method for cascading failure based on dynamic simulation and power flow is presented, which can simulate the interactive between DFIG and grid failure. The effectiveness of the method proposed to search high-risk cascading failures chains under high penetration of renewable energy is verified by the simulations concerning the modified New England test system. © 2021 IEEE.

关键词： Electric load flow

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Solar power Ramp Event Forewarning With Limited Historical Observations

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2019年第6期55卷 5621-5630页

作者： Zhu, Wenli Zhang, Li Yang, Ming Wang, Bo Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250000 Shandong Peoples R China China Elect Power Res Inst Grade Key Lab Operat & Control Renewable Energy & Beijing 100192 Peoples R China

Timely and accurate forewarning of solar power ramp events (SPREs) is crucial for a power system operation. In this article, a novel forewarning method for SPREs is proposed based on credal network (CN) and imprecise Dirichlet model (IDM). A new expression of SPRE is proposed, which focuses on the power change caused by meteorological fluctuation. Considering that the single-valued probability may not provide convincing results in case of insufficient ramp event records, probability interval is adopted to reflect the ambiguous correlation between SPREs and meteorological conditions. The meteorological evidences are mapped to ramp events by a CN to enhance the sensitivity of SPRE identification. The structure of the CN is established by the learning algorithm with respect to the relations between SPRE and meteorological conditions, as well as different meteorological conditions. Furthermore, an extended IDM is developed to estimate the interval-valued parameters in the CN. Then, a credal classifier is established to output the ramp forewarning result. The effectiveness of the proposed method is verified through case studies, and obvious improvement on the accuracy of ramp forewarning can be seen.

关键词： Conditional probability credal classification credal network (CN) forecast model imprecise Dirichlet model (IDM) imprecise probability ramp detection ramp forewarning ramp rate solar power ramp event (SPRE)

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A Wind Speed Correction Method Based on Modified Hidden Markov Model for Enhancing Wind power Forecast

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2022年第1期58卷 656-666页

作者： Li, Menglin Yang, Ming Yu, Yixiao Lee, Wei-Jen Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China Univ Texas Arlington Arlington TX 76019 USA

Short-term wind power forecast (WPF) depends highly on the wind speed forecast (WSF), which is the prime contributor to the forecasting error. To achieve more accurate WPF results, this article proposes a wind speed correction method to improve the WSF result obtained by using the weather research and forecasting (WRF) model. First, the WRF model is constructed to forecast the wind speed, and its performance is analyzed. Second, a novel hidden Markov model (HMM) is developed to explore both the temporal autocorrelation of WSF error and the nonlinear correlation between the WSF result and the error. In the model, the fuzzy C-means cluster is introduced to properly divide the hidden state space of HMM and the emission probability of HMM is improved as continuous by the kernel density estimation (KDE) to make full use of the observation information. The proposed HMM model is better at wind speed correction through modification. Third, the HMM is solved by the Viterbi algorithm and the minimum mean-square error regulation to correct the predicted wind speed. Finally, the deterministic and probabilistic WPF results are obtained by using another KDE model, the proposed method is demonstrated to be superior to the benchmarks in case studies.

关键词： Hidden Markov models Wind forecasting Forecasting Predictive models Wind speed Mathematical models Wind power generation Hidden markov model (HMM) kernel density estimation (KDE) weather research and forecasting (WRF) model wind power forecast (WPF) wind speed correction

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Short- Term Load Forecast Based on Feature Reconstruction and Bidirectional LSTM

Short- Term Load Forecast Based on Feature Reconstruction an...

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

作者： Zheng, Xudong Yang, Ming Yu, Yixiao Li, Menglin Wang, Chuanqi Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan Peoples R China

ISBN: (纸本)9798350339345

Short term load forecasting is a guarantee for the safe, stable, and economic operation of the power system. With the large-scale integration of distributed new energy, load fluctuations increase, and the input feature data dimension increases during forecasting. Therefore, it is particularly important to screen and process input features reasonably when using deep neural networks for prediction. In response to the varying degrees of influence of various feature factors at different time points, this paper proposes a feature screening and input feature reconstruction method based on the maximum information coefficient of MIC, which achieves feature impact analysis, screening, and input feature reconstruction at sampling point granularity. The BI-LSTM neural network with stronger information mining ability is introduced to achieve high-precision short-term load forecasting. The results show that using the proposed input feature reconstruction strategy and assigning input feature weights according to the degree of influence significantly improves the prediction accuracy of deep neural networks. The method proposed in this paper has good adaptability to load fluctuations..

关键词： short-term load forecasting Maximum information coefficient Feature reconstruction Bidirectional LSTM

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On-line Discrimination Method of Current Transformer's Polarity Using Line No-load Closing Impulse Current 8

On-line Discrimination Method of Current Transformer's Polar...

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

作者： Zhang, Yunqi Cong, Wei Hu, Liangliang Zhang, Liqiang Shangdong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China

ISBN: (纸本)9781728117225

An on-line method using no-load closing impulse current of the line to discriminate CT's polarity is proposed in this paper. No-load closing model for the single-phase transmission line is established firstly, and the mathematical relationship between electrical quantities and line parameters during closing process is described by differential equations. Line parameters such as the inductance or resistance are regarded as unknown quantities, and the characteristics of their values are analyzed when solving the differential equations under different CT polarities. Then the calculation values are normalized. In order to quantify the distribution characteristics of normalized equivalent values, define the forward and backward coefficients. According to the ratio of these two coefficients, namely recognition coefficient, CT's polarity in single-phase system can be discriminated. On this basis, CTs' polarities in three-phase system can be discriminated by different phase-mode transformations with specific matrixes. Finally, the effectiveness of the method is verified by simulation. © 2019 IEEE.

关键词： Electric instrument transformers

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An inrush current identification scheme for converter transformer based on magnetization curve model matching 3

An inrush current identification scheme for converter transf...

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3rd International Conference on Mechanical, Electronics, and Electrical and Automation control, METMS 2023

作者： Liu, Shiming Zhang, Chao Zeng, Qiqi Zhao, Wenchen Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China

ISBN: (纸本)9781510666689

Influenced by the complex environment on the AC/DC hybrid power system, converter transformer is susceptible to inrush current or DC bias interference, resulting in false blocking of differential protection during internal fault. In order to distinguish inrush current and internal fault accurately, this paper proposes an inrush current identification scheme for converter transformers based on the flux-current characteristic model matching method. Firstly, the magnetization curve model is selected to fit the nonlinear magnetization characteristics of the transformer, and a model matching scheme based on voltage comparison is designed. Then the model matching degree index (referred to as matching per unit value M in this paper) is constructed to quantitatively describe the model matching degree, and the inrush current identification criterion based on the model matching degree M is proposed. Finally, the action reliability of the proposed identification criterion is verified by simulation experiments. © 2023 SPIE.

关键词： DC transformers

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