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| 1 | Statistical scenarios forecasting method for wind power ramp events using modified neural networks显示文摘Wind power ramp events increasingly affect the integration of wind power and cause more and more problems to the safety of power grid operation in recent years.Several forecasting techniques for wind power ramp events have been reported.In this paper,the statistical scenarios forecasting method is proposed for wind power ramp event probabilistic forecasting based on the probability generating model.Multi-objective fitness functions are established considering cumulative density functions and higher order moment autocorrelation functions with respect to the consistency of distribution and timing characteristics,respectively.Parameters of probability generating model are calculated by the iterative optimization using the modified genetic algorithm with multi-objective fitness functions.A number of statistical scenarios captured bands are generated accordingly.Eventually,ramp event probability characteristics are detected from scenarios captured bands to evaluate the ramp event forecasting method.A wind plant of Bonneville Power Administration with actual wind power data is selected for calculation and statistical analysis.It is shown that statistical results with multi-objective functions are more accurate than the results with single objective functions.Moreover,the statistical scenarios forecasting method can accurately estimate the characteristics of wind power ramp events.The results verify that the proposed method can guide the generation method of statistical scenarios and forecasting models for ramp events. | Mingjian CUI Deping KE Di GAN Yuanzhang SUN | 2015 | Journal of Modern Power Systems and Clean Energy2015，3，3： | 13 |
| 2 | A multi-state model for wind farms considering operational outage probability显示文摘As one of the most important renewable energy resources,wind power has drawn much attention in recent years.The stochastic characteristics of wind speed lead to generation output uncertainties of wind energy conversion system(WECS)and affect power system reliability,especially at high wind power penetration levels.Therefore,a more comprehensive analysis toward WECS as well as an appropriate reliability assessment model are essential for maintaining the reliable operation of power systems.In this paper,the impact of wind turbine outage probability on system reliability is firstly developed by considering the following factors:running time,operating environment,operating conditions,and wind speed fluctuations.A multistate model for wind farms is also established.Numerical results illustrate that the proposed model can be well applied to power system reliability assessment as well as solving a series of reliability-centered decision-making problems of power system scheduling and maintenance arrangements. | Lin CHENG Manjun LIU Yuanzhang SUN Yi DING | 2013 | Journal of Modern Power Systems and Clean Energy2013，1，2： | 8 |
| 3 | A Day-ahead Economic Dispatch Method Considering Extreme Scenarios Based on Wind Power Uncertainty显示文摘As the intermittency of wind power is a growing concern in the day-ahead economic dispatch,this paper proposes a day-ahead economic dispatch method considering extreme scenarios of wind power by using an uncertainty set.The uncertainty set inspired by robust optimization is used to describe wind power intermittency in this paper.Four extreme scenarios based on the uncertainty set are formulated to represent the worst cases of wind power fluctuation.An economic dispatch method considering the costs of both load shedding and wind curtailment is proposed.The economic dispatch model can be easily solved by a quadratic programming method owing to the introduction of four extreme scenarios and the uncertainty set of wind power.Simulation is done using the IEEE 30-bus system and the results verify the effectiveness of the proposed method. | Jian Xu Bao Wang Yuanzhang Sun Qi Xu Ji Liu Huiqiu Cao Haiyan Jiang Ruobing Lei Mengjun Shen | 2019 | CSEE Journal of Power and Energy Systems2019，5，2： | 5 |
| 4 | Load Shedding and Restoration for Intentional Island with Renewable Distributed Generation显示文摘Due to the high penetration of renewable distributed generation(RDG),many issues have become conspicuous during the intentional island operation such as the power mismatch of load shedding during the transition process and the power imbalance during the restoration process.In this paper,a phase measurement unit(PMU)based online load shedding strategy and a conservation voltage reduction(CVR)based multi-period restoration strategy are proposed for the intentional island with RDG.The proposed load shedding strategy,which is driven by the blackout event,consists of the load shedding optimization and correction table.Before the occurrence of the large-scale blackout,the load shedding optimization is solved periodically to obtain the optimal load shedding plan,which meets the dynamic and steady constraints.When the blackout occurs,the correction table updated in real time based on the PMU data is used to modify the load shedding plan to eliminate the power mismatch caused by the fluctuation of RDG.After the system transits to the intentional island seamlessly,multi-period restoration plans are generated to optimize the restoration performance while maintaining power balance until the main grid is repaired.Besides,CVR technology is implemented to restore more loads by regulating load demand.The proposed load shedding optimization and restoration optimization are linearized to mixed-integer quadratic constraint programming(MIQCP)models.The effectiveness of the proposed strategies is verified with the modified IEEE 33-node system on the real-time digital simulation(RTDS)platform. | Jian Xu Boyu Xie Siyang Liao Zhiyong Yuan Deping Ke Yuanzhang Sun Xiong Li Xiaotao Peng | 2021 | Journal of Modern Power Systems and Clean Energy2021，9，3： | 2 |
| 5 | Active Power Correction Strategies Based on Deep Reinforcement Learning Part I:A Simulation-driven Solution for Robustness显示文摘Employing the novel Deep Reinforcement Learning approach,this paper addresses the active power corrective control in modern power systems.Seeking to minimize the joint effect engendered by operation cost and blackout penalty,this correction strategy focuses on evaluating the robustness and adaptability aspects of the control agent.In Part I of this paper,where robustness is the primary focus,the agent is developed to handle unexpected incidents and guide the stable operation of power grids A Simulation-driven Graph Attention Reinforcement Learning method is proposed to perform robust active power corrective control.The aim of the graph attention networks is to determine the representation of power system states considering the topological features.Monte Carlo tree search is adopted to select the best suitable action set out of the large action space,including generator redispatch and topology control actions.Finally,driven by simulation,a guided training mechanism along with a long-short-term action deployment strategy are designed to help the agent better evaluate the action set while training and to operate more stably when deployed.The efficacy of the proposed method has been demonstrated in the“2020 I earning to Run a Power Network.Neurips Track 1”global competition and the associated cases.Part II of this paper deals with the adaptability case,where the agent is equipped to better adapt to a grid that has an increasing share of renewable energies through the years. | Peidong Xu Jiajun Duan Jun Zhang Yangzhou Pei Di Shi Zhiwei Wang Xuzhu Dong Yuanzhang Sun | 2022 | CSEE Journal of Power and Energy Systems2022，8，4： | 2 |
| 6 | Nonlinear decentralized robust governor control for hydroturbine-generator sets in multi-machine power systems显示文摘 | Lu Qiang Sun Yusong Sun Yuanzhang | 2004 | International Journal of Electrical Power & Energy Systems2004，26，5： | 1 |
| 7 | Based on the optimal combination weights can quality grey comprehensive evaluation method显示文摘 | Shenyang Wu Peng Xiao Tao Shi commuter Mao Xun sun Yuanzhang | 2012 | Automation of electric power systems2012，10，： | 1 |
| 8 | Nonlinear decentralized robust governor control for hydroturbine generator systems显示文摘 | Lu Qiang Sun Yusong Sun Yuanzhang | 2004 | Electrical sets in multi-machine power Power and Energy Systems2004，26，5： | 1 |
| 9 | A practical method to improve phasor and power measurement accuracy of DFT algorithm显示文摘 | Wang Maohai Sun Yuanzhang | 2006 | IEEE Transactions on Power Delivery2006，21，3： | 1 |
| 10 | A novel state selection technique for power system reliability evaluation 显示文摘 | Haitao Liu Yuanzhang Sun etc | 2008 | Electric Power Systems Research2008，78，6： | 1 |
| 11 | A practical, precise method for frequency tracking and phasor estimation显示文摘 | Wang Maohai Sun Yuanzhang | 2004 | IEEE Transactions on Power Delivery2004，19，4： | 1 |
| 12 | A practical, precise method for frequency tracking and phasor estimation 显示文摘 | Maohai Wang Yuanzhang Sun | 2004 | IEEE Transactions on Power Delivery2004，19，4： | 1 |
| 13 | Online short-term reliability evaluation using fast sorting technique显示文摘 | Liu Haitao Sun Yuanzhang Cheng Lin | 2008 | IET Generation Transmission & Distribution2008，2，1： | 1 |
| 14 | Demand-side Management Based on Model Predictive Control in Distribution Network for Smoothing Distributed Photovoltaic Power Fluctuations显示文摘With the rapid increase of distributed photovoltaic(PV) power integrating into the distribution network(DN), the critical issues such as PV power curtailment and low equipment utilization rate have been caused by PV power fluctuations. DN has less controllable equipment to manage the PV power fluctuation. To smooth the power fluctuations and further improve the utilization of PV, the regulation ability from the demandside needs to be excavated. This study presents a continuous control method of the feeder load power in a DN based on the voltage regulation to respond to the rapid fluctuation of the PV power output. PV power fluctuations will be directly reflected in the point of common coupling(PCC), and the power fluctuation rate of PCCs is an important standard of PV curtailment.Thus, a demand-side management strategy based on model predictive control(MPC) to mitigate the PCC power fluctuation is proposed. In pre-scheduling, the intraday optimization model is established to solve the reference power of PCC. In real-time control, the pre-scheduling results and MPC are used for the rolling optimization to control the feeder load demand. Finally,the data from the field measurements in Guangzhou, China are used to verify the effectiveness of the proposed strategy in smoothing fluctuations of the distributed PV power. | Jian Xu Haobo Fu Siyang Liao Boyu Xie Deping Ke Yuanzhang Sun Xiong Li Xiaotao Peng | 2022 | Journal of Modern Power Systems and Clean Energy2022，10，5： | 1 |
| 15 | Decentralized Nonlinear Optimal Excitation Control显示文摘 | Qiang Lu Yuanzhang Sun Zhen Xu | 1996 | IEEE Trans on Power Systems1996，11，4： | 1 |
| 16 | On-line short-term reliability evaluation using fast sortingtechnique显示文摘 | Liu Haitao Sun Yuanzhang Cheng Lin | 2008 | IET Generation Transmission&Dis-tribution2008，2，1： | 1 |
| 17 | A practical method to improve phasor and power measurement accuracy of DFr algorithm显示文摘 | Wang Maohai Sun Yuanzhang | 2006 | IEEE Transactions on Power Delivery2006，21，3： | 1 |
| 18 | A practical, precise method for frequency tracking and phasor estimation显示文摘 | Wang Maohai Sun Yuanzhang | 2004 | IEEE Transactions on Power Delivery2004，19，4： | 1 |
| 19 | A practical method to improve phasor and power measurement accuracy of DFT algorithm 显示文摘 | WANG MAOHAI SUN YUANZHANG | 2006 | IEEE Transactions on Power Delivery2006，21，3： | 1 |
| 20 | Method for assessing grid frequency deviation due to wind power fluctuation based on time-frequency transformation显示文摘 | Lin Jin Sun Yuanzhang Poul sorensen | 2012 | IEEE Transactions on Energy Conversion2012，3，1： | 1 |
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