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Medium- and long-term wind power output time series are required in stochastic programming model for power system planning. Hidden Markov model (HMM) is a common method to generate wind power output time series, which can simultaneously consider the temporal and spatial correlation of multiple wind farms. However, the existing HMM methods use discrete matrix or Gaussian distribution to describe the output distribution of multiple wind farms, which usually leads to a relatively large error in statistical indices between the generated time series and the historical time series. Therefore, this paper proposes a method for generating medium- and long-term correlated output time series of multiple wind farms based on the Gaussians mixture model-Hidden Markov model (GMM-HMM). The discrete state variable in the hidden Markov model is used to describe the meteorological state. The Markov chain between discrete state variables is used to describe the temporal correlation of wind power output. The wind power output vector of multiple wind farms is used as the observation variable, and the mixed Gaussian probability distribution mapping relationship between the state variable and the multidimensional wind power output vector is established. Based on the Monte Carlo sampling method, the multi-wind farm output series satisfying the spatiotemporal correlation of historical output series are generated monthly. In the calculation example, the monthly wind power output series generated by five wind farms in Jilin Province are analyzed. The results show that the main statistical characteristics of the multi-wind power output time series generated by the proposed method are generally superior to those obtained with the traditional wind power output modeling method, which proves the superiority of the proposed method.
Yufei Li; Bo Hu; Tao Niu; Shengpu Gao; Jiahao Yan; Kaigui Xie; Zhouyang Ren. GMM-HMM-based Medium- and Long-term Multi-Wind Farm Correlated Power Output Time Series Generation Method. IEEE Access 2021, 9, 1 -1.
AMA StyleYufei Li, Bo Hu, Tao Niu, Shengpu Gao, Jiahao Yan, Kaigui Xie, Zhouyang Ren. GMM-HMM-based Medium- and Long-term Multi-Wind Farm Correlated Power Output Time Series Generation Method. IEEE Access. 2021; 9 ():1-1.
Chicago/Turabian StyleYufei Li; Bo Hu; Tao Niu; Shengpu Gao; Jiahao Yan; Kaigui Xie; Zhouyang Ren. 2021. "GMM-HMM-based Medium- and Long-term Multi-Wind Farm Correlated Power Output Time Series Generation Method." IEEE Access 9, no. : 1-1.
Hui Li; Zhouyang Ren. A Tidal Resource Evaluation-Based Method for Tidal Current Generation Farm Allocation Considering the Directionality of Tidal Currents. IEEE Transactions on Sustainable Energy 2020, 11, 2631 -2640.
AMA StyleHui Li, Zhouyang Ren. A Tidal Resource Evaluation-Based Method for Tidal Current Generation Farm Allocation Considering the Directionality of Tidal Currents. IEEE Transactions on Sustainable Energy. 2020; 11 (4):2631-2640.
Chicago/Turabian StyleHui Li; Zhouyang Ren. 2020. "A Tidal Resource Evaluation-Based Method for Tidal Current Generation Farm Allocation Considering the Directionality of Tidal Currents." IEEE Transactions on Sustainable Energy 11, no. 4: 2631-2640.
We formulate the Cost-Sensitive Learning to Rank problem of learning to prioritize limited resources to mitigate the most costly outcomes. We develop improved ranking models to solve this problem, as verified by experiments in diverse domains such as forest fire prevention, crime prevention, and preventing storm caused outages in electrical networks.
Ryan McBride; Ke Wang; Zhouyang Ren; Wenyuan Li. Cost-Sensitive Learning to Rank. Proceedings of the AAAI Conference on Artificial Intelligence 2019, 33, 4570 -4577.
AMA StyleRyan McBride, Ke Wang, Zhouyang Ren, Wenyuan Li. Cost-Sensitive Learning to Rank. Proceedings of the AAAI Conference on Artificial Intelligence. 2019; 33 ():4570-4577.
Chicago/Turabian StyleRyan McBride; Ke Wang; Zhouyang Ren; Wenyuan Li. 2019. "Cost-Sensitive Learning to Rank." Proceedings of the AAAI Conference on Artificial Intelligence 33, no. : 4570-4577.
The existing continuation power flow (CPF) methods, which mainly focus on regional independent systems, are not suitable for multi-area interconnected bulk systems in the electricity market environment. These existing CPF models cannot simulate the control behaviours of active/reactive power exchange among subsystems, and the corresponding CPF algorithms cannot satisfy the requirements of data sharing. This study presents a novel CPF model and its corresponding distributed algorithm for interconnected systems in which the influence of the electricity market is considered. This CPF method has the following unique features: 1) Regarding the bilateral power trading contracts (BPTCs) among regional subsystems, the nonlinear constraint equations of the directional trading active power via the interface are derived, and a multi-balancing machine strategy is introduced for realizing the active power balance of each subsystem. 2) Based on the simulation of the constant-voltage control behaviour of the pilot buses in the regional automatic voltage control (AVC) system, the constant-voltage control behaviour of the boundary buses of the tie-lines is further simulated to realize the reactive power balance among the regional subsystems. 3) According to the characteristics of the proposed CPF model, a novel distributed CPF algorithm based on block matrix computations is presented for realizing the decomposition and coordination calculation of multiple regional subsystems. This distributed algorithm preserves the precision and convergence of integrated CPF algorithms and has an advantage in terms of the calculation speed. The performance of the proposed CPF model and distributed algorithm is demonstrated via case studies and comparative analyses.
Chong Ding; Wei Yan; Zhouyang Ren; Ruifeng Zhao; Wei-Jen Lee; Xinyan Tang. Continuation Power Flow Model for Interconnected Systems Considering the Electricity Market Influence and Its Corresponding Distributed Algorithm. IEEE Access 2019, 7, 75910 -75924.
AMA StyleChong Ding, Wei Yan, Zhouyang Ren, Ruifeng Zhao, Wei-Jen Lee, Xinyan Tang. Continuation Power Flow Model for Interconnected Systems Considering the Electricity Market Influence and Its Corresponding Distributed Algorithm. IEEE Access. 2019; 7 (99):75910-75924.
Chicago/Turabian StyleChong Ding; Wei Yan; Zhouyang Ren; Ruifeng Zhao; Wei-Jen Lee; Xinyan Tang. 2019. "Continuation Power Flow Model for Interconnected Systems Considering the Electricity Market Influence and Its Corresponding Distributed Algorithm." IEEE Access 7, no. 99: 75910-75924.
This paper proposes an alterable weight minimum spanning tree (AW-MST) method to plan electrical collector systems (ECSs) in tidal current generation farms (TCGFs) toward economic objectives. First, a sector-division-based fuzzy c-means (FCM) grouping algorithm is proposed. The tidal current turbines (TCTs) in the TCGF are divided into several sectors by the improved FCM algorithm to relieve the computational burden. Meanwhile, trans-region crossings and overloads of submarine cables can be simultaneously avoided. Second, an ECS planning model is established which fully considers the tidal current velocity (TCV) characteristics and ECS investment and operating costs. Since the variable factors cannot be considered by the common minimum spanning tree algorithms, alterable weights are used in the AW-MST to optimize the variable factors, including power losses and cable types. Finally, the two different TCGFs and the measured TCV datasets collected from North of Orkney, Scotland, were used to verify the effectiveness and adaptability of the proposed method.
Zhouyang Ren; Hui Li; Yang Liu; Yan Xu; Liming Jin; Wenyuan Li; Wenyu Wang. An Alterable Weight Minimum Spanning Tree Method for Electrical Collector System Planning in Tidal Current Generation Farms. IEEE Access 2019, 7, 71585 -71592.
AMA StyleZhouyang Ren, Hui Li, Yang Liu, Yan Xu, Liming Jin, Wenyuan Li, Wenyu Wang. An Alterable Weight Minimum Spanning Tree Method for Electrical Collector System Planning in Tidal Current Generation Farms. IEEE Access. 2019; 7 ():71585-71592.
Chicago/Turabian StyleZhouyang Ren; Hui Li; Yang Liu; Yan Xu; Liming Jin; Wenyuan Li; Wenyu Wang. 2019. "An Alterable Weight Minimum Spanning Tree Method for Electrical Collector System Planning in Tidal Current Generation Farms." IEEE Access 7, no. : 71585-71592.
Existing continuation power flow (CPF) models mainly focus on the regional independent systems, which are not suitable for multi-area AC/DC interconnected systems because the market trading behaviors and security control for power allocation of tie-lines are ignored. This study presents a novel CPF model and its decoupling algorithm for multi-area AC/DC interconnected systems incorporating a voltage source converter (VSC)-based multi-terminal direct current (MTDC) network. This CPF model includes the following unique features: (1) In view of the bilateral power trading contracts among regional subsystems, the nonlinear constraint equations of directional trading active power via interface are derived, and the multi-balancing machine strategy is introduced to realize the active power balance of each subsystem. (2) An accurate simulation method for the security control behaviors of the power allocation in tie-lines is proposed, which includes a specific selection strategy for automatic generation control units and a generation re-dispatch strategy. These two strategies work together to prevent the serious overload in tie-lines during load growth and improve the voltage stability margin of the interconnected bulk systems. (3) The switching characteristic of reactive power control behaviors of VSC stations is simulated in the CPF calculation. In the end, a novel decoupling CPF algorithm based on bi-directional iteration is presented to realize the decomposition and coordination calculation. This decoupling algorithm preserves the precision and convergence of integrated CPF algorithms, and it has an apparent advantage on the calculation speed. Furthermore, this decoupling algorithm also can easily reflects the effects of the control mode changes of VSC stations to the voltage stability margin of AC system. Case studies and comparative analysis on the IEEE two-area RTS-96 system indicate the effectiveness and validity of the proposed CPF model and corresponding decoupling algorithm.
Wei Yan; Chong Ding; Zhouyang Ren; Wei-Jen Lee. A Continuation Power Flow Model of Multi-Area AC/DC Interconnected Bulk Systems Incorporating Voltage Source Converter-Based Multi-Terminal DC Networks and Its Decoupling Algorithm. Energies 2019, 12, 733 .
AMA StyleWei Yan, Chong Ding, Zhouyang Ren, Wei-Jen Lee. A Continuation Power Flow Model of Multi-Area AC/DC Interconnected Bulk Systems Incorporating Voltage Source Converter-Based Multi-Terminal DC Networks and Its Decoupling Algorithm. Energies. 2019; 12 (4):733.
Chicago/Turabian StyleWei Yan; Chong Ding; Zhouyang Ren; Wei-Jen Lee. 2019. "A Continuation Power Flow Model of Multi-Area AC/DC Interconnected Bulk Systems Incorporating Voltage Source Converter-Based Multi-Terminal DC Networks and Its Decoupling Algorithm." Energies 12, no. 4: 733.
Based on a sequential Monte–Carlo simulation technique, a reliability evaluation method and several indices are proposed for tidal current farm integrated generation systems in this paper. A tidal current velocity model is first developed to capture the chronology and randomness of tidal current velocity by combining a fuzzy equivalent matrix-based clustering approach with a nonparametric probabilistic modeling technique. The single and multiple wake effects between tidal current turbines in a tidal current farm are quantitatively represented using an analytical wake model. Second, a power output model for a tidal current farm (TCF) is proposed, incorporating the characteristics of tidal current velocity, wake effects and turbine failures. A sequential Monte–Carlo simulation-based reliability evaluation method, as well as several reliability evaluation indices are proposed to quantify the impacts of TCF integration and wake effects on the reliability level of generation systems. The historical tidal current velocity data collected from a site located in FL, USA, and the popular reliability test system known as RBTS with an additional TCF were used to verify the accuracy and effectiveness of the proposed method. The impacts of tidal power integration and the relative distances between turbines in TCF on generation systems’ reliability were also studied.
Zhouyang Ren; Hui Li; Wenyuan Li; XueQian Zhao; Yihao Sun; Te Li; Fan Jiang. Reliability Evaluation of Tidal Current Farm Integrated Generation Systems Considering Wake Effects. IEEE Access 2018, 6, 52616 -52624.
AMA StyleZhouyang Ren, Hui Li, Wenyuan Li, XueQian Zhao, Yihao Sun, Te Li, Fan Jiang. Reliability Evaluation of Tidal Current Farm Integrated Generation Systems Considering Wake Effects. IEEE Access. 2018; 6 ():52616-52624.
Chicago/Turabian StyleZhouyang Ren; Hui Li; Wenyuan Li; XueQian Zhao; Yihao Sun; Te Li; Fan Jiang. 2018. "Reliability Evaluation of Tidal Current Farm Integrated Generation Systems Considering Wake Effects." IEEE Access 6, no. : 52616-52624.
This paper proposes a bi-level programming model for the planning of tidal current farms (TCFs). The micro-siting strategy of tidal current turbines (TCTs) and the collector system planning scheme are coordinated to achieve a better balance of energy yields, TCF capital investment and power systems economic operation using the proposed method. The power output of the TCF is modeled considering the characteristics of tidal current velocity and wake effects. A coordinated planning model consisting of one upper-level model and two lower-level models is developed to maximize comprehensive profit. Not only the investment and maintenance costs of TCTs and submarine cables, but also the operation cost of the collector system and the impact of the TCF integration on the operation of power systems are all taken into account to ensure the long-term benefits of both TCF owners and power systems. An efficient solution for the proposed planning model is developed by combining a genetic algorithm with a mixed integer programming. The effectiveness and adaptability of the proposed method are demonstrated using the measured data of tidal current velocity with distinct characteristics and the IEEE 30- and 118- bus test systems.
Zhouyang Ren; Yuanmeng Wang; Hui Li; Xuan Liu; Yunfeng Wen; Wenyuan Li. A Coordinated Planning Method for Micrositing of Tidal Current Turbines and Collector System Optimization in Tidal Current Farms. IEEE Transactions on Power Systems 2018, 34, 292 -302.
AMA StyleZhouyang Ren, Yuanmeng Wang, Hui Li, Xuan Liu, Yunfeng Wen, Wenyuan Li. A Coordinated Planning Method for Micrositing of Tidal Current Turbines and Collector System Optimization in Tidal Current Farms. IEEE Transactions on Power Systems. 2018; 34 (1):292-302.
Chicago/Turabian StyleZhouyang Ren; Yuanmeng Wang; Hui Li; Xuan Liu; Yunfeng Wen; Wenyuan Li. 2018. "A Coordinated Planning Method for Micrositing of Tidal Current Turbines and Collector System Optimization in Tidal Current Farms." IEEE Transactions on Power Systems 34, no. 1: 292-302.
This paper proposes a bi-level programming-based optimization method to determine the sizing of tidal current farm (TCF) and the arrangement of tidal current turbines reaching the minimized comprehensive generation cost of tidal power. Not only the characteristics of tidal current velocity and wake effects but also the economic costs and environmental benefits brought by TCF integration are all incorporated in the proposed method. The method includes a power output model of TCF that can capture the characteristics of tidal current velocity and turbine wake effects, and a bi-level optimization model that takes into account the penalty costs of greenhouse gas emissions, the operation costs of power system, and the investment cost of tidal current turbines. The bi-level model is solved using a genetic algorithm and a quadratic programming technique. The effectiveness and adaptability of the proposed method are demonstrated using the measured data of tidal current velocity and the IEEE 30-bus test system.
Yi Dai; Zhouyang Ren; Ke Wang; Wenyuan Li; Zhenwen Li; Wei Yan. Optimal Sizing and Arrangement of Tidal Current Farm. IEEE Transactions on Sustainable Energy 2017, 9, 168 -177.
AMA StyleYi Dai, Zhouyang Ren, Ke Wang, Wenyuan Li, Zhenwen Li, Wei Yan. Optimal Sizing and Arrangement of Tidal Current Farm. IEEE Transactions on Sustainable Energy. 2017; 9 (1):168-177.
Chicago/Turabian StyleYi Dai; Zhouyang Ren; Ke Wang; Wenyuan Li; Zhenwen Li; Wei Yan. 2017. "Optimal Sizing and Arrangement of Tidal Current Farm." IEEE Transactions on Sustainable Energy 9, no. 1: 168-177.
A probabilistic power flow analysis method for power systems with tidal power sources is presented in this paper. The regularity of tidal power is modeled using a k-means clustering technique and the randomness of tidal power is modeled using a nonparametric kernel density estimation method. A stochastic sampling method is also developed to generate random samples of tidal power time series for Monte Carlo based probabilistic power flow analysis. The influence of tidal current generation on power flows is then evaluated and quantified considering both the regularity and randomness of tidal power. The measured tidal current speed data of two different locations in Florida and Alaska states, USA and the IEEE 57-bus standard test system are used to verify the correctness and effectiveness of the presented probabilistic power flow analysis method.
Zhouyang Ren; Ke Wang; Wenyuan Li; Liming Jin; Yi Dai. Probabilistic Power Flow Analysis of Power Systems Incorporating Tidal Current Generation. IEEE Transactions on Sustainable Energy 2017, 8, 1195 -1203.
AMA StyleZhouyang Ren, Ke Wang, Wenyuan Li, Liming Jin, Yi Dai. Probabilistic Power Flow Analysis of Power Systems Incorporating Tidal Current Generation. IEEE Transactions on Sustainable Energy. 2017; 8 (3):1195-1203.
Chicago/Turabian StyleZhouyang Ren; Ke Wang; Wenyuan Li; Liming Jin; Yi Dai. 2017. "Probabilistic Power Flow Analysis of Power Systems Incorporating Tidal Current Generation." IEEE Transactions on Sustainable Energy 8, no. 3: 1195-1203.
Wei Cui; Wei Yan; Wei-Jen Lee; Xia Zhao; Zhouyang Ren; Cong Wang. A Two-stage Stochastic Programming Model for Optimal Reactive Power Dispatch with High Penetration Level of Wind Generation. Journal of Electrical Engineering & Technology 2017, 12, 53 -63.
AMA StyleWei Cui, Wei Yan, Wei-Jen Lee, Xia Zhao, Zhouyang Ren, Cong Wang. A Two-stage Stochastic Programming Model for Optimal Reactive Power Dispatch with High Penetration Level of Wind Generation. Journal of Electrical Engineering & Technology. 2017; 12 (1):53-63.
Chicago/Turabian StyleWei Cui; Wei Yan; Wei-Jen Lee; Xia Zhao; Zhouyang Ren; Cong Wang. 2017. "A Two-stage Stochastic Programming Model for Optimal Reactive Power Dispatch with High Penetration Level of Wind Generation." Journal of Electrical Engineering & Technology 12, no. 1: 53-63.
Zhouyang Ren; Wei Yan; Xia Zhao; XueQian Zhao; Juan Yu. Probabilistic Power Flow Studies Incorporating Correlations of PV Generation for Distribution Networks. Journal of Electrical Engineering & Technology 2014, 9, 461 -470.
AMA StyleZhouyang Ren, Wei Yan, Xia Zhao, XueQian Zhao, Juan Yu. Probabilistic Power Flow Studies Incorporating Correlations of PV Generation for Distribution Networks. Journal of Electrical Engineering & Technology. 2014; 9 (2):461-470.
Chicago/Turabian StyleZhouyang Ren; Wei Yan; Xia Zhao; XueQian Zhao; Juan Yu. 2014. "Probabilistic Power Flow Studies Incorporating Correlations of PV Generation for Distribution Networks." Journal of Electrical Engineering & Technology 9, no. 2: 461-470.