Credibility theory based panoramic fuzzy risk analysis of hydropower station operation near the boundary

Abstract Short-term power generation operation is an important content in the hydropower station management. Because of the limitation of forecast accuracy, there is error between the forecasted runoff process and actual runoff process. When the hydropower station operation is near the water level boundaries, such as normal water level or dead water level, this error is likely to bring the risk of water abandoning or output shortage. In order to precisely evaluate the near-boundary operation risk of hydropower station caused by runoff forecasting error, a novel panoramic fuzzy risk analysis model was proposed in this paper by taking the forecasting error as a fuzzy variable. The coupling of hydrological forecasting error and the short-term operation risk of hydropower station based on credibility theory was realized, and the solving process of the model based on fuzzy simulation technology was provided in detail. Different near-boundary operation risks of hydropower station can be analyzed and evaluated by the simulation with different water level combinations in this model. The high-risk area and suggested operation area of Jinxi hydropower station in different near-boundary operation situations were clearly identified in the case study. The intuitive results of this model can provide a strong technical support for the decision-making of the dispatchers when making the power generation plans in the actual production, so that to avoid the occurrence of water abandoning or output shortage of hydropower station, and effectively improve the efficiency of water resources utilization.

[1]  Bo Wang,et al.  Supply Reliability and Generation Cost Analysis Due to Load Forecast Uncertainty in Unit Commitment Problems , 2013, IEEE Transactions on Power Systems.

[2]  Yong Peng,et al.  Optimal operation of cascade hydropower stations using hydrogen as storage medium , 2015 .

[3]  L. Soder,et al.  Multi-Station Equivalents for Short-Term Hydropower Scheduling , 2016, IEEE Transactions on Power Systems.

[4]  Chuntian Cheng,et al.  Applying a Correlation Analysis Method to Long-Term Forecasting of Power Production at Small Hydropower Plants , 2015 .

[5]  Hongwei Lu,et al.  An inexact rough-interval fuzzy linear programming method for generating conjunctive water-allocation strategies to agricultural irrigation systems , 2011 .

[6]  Fan Yang,et al.  Fuzzy arithmetic on LR fuzzy numbers with applications to fuzzy programming , 2015, J. Intell. Fuzzy Syst..

[7]  Shengzhi Huang,et al.  Monthly streamflow prediction using modified EMD-based support vector machine , 2014 .

[8]  Zhong-Zhong Jiang,et al.  A fuzzy matching model with Hurwicz criteria for one-shot multi-attribute exchanges in E-brokerage , 2014, Fuzzy Optim. Decis. Mak..

[9]  M. Majumder,et al.  A comparative study for prediction of direct runoff for a river basin using geomorphological approach and artificial neural networks , 2012, Applied Water Science.

[10]  Liu Xiao.  Dynamic Economic Dispatch for Wind Farms Integrated Power System Based on Credibility Theory , 2011 .

[11]  Yian-Kui Liu,et al.  Expected value of fuzzy variable and fuzzy expected value models , 2002, IEEE Trans. Fuzzy Syst..

[12]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[13]  Jianzhong Zhou,et al.  Credibility theory based dynamic control bound optimization for reservoir flood limited water level , 2015 .

[14]  Mohammad Hossein Fazel Zarandi,et al.  A simulated annealing algorithm for routing problems with fuzzy constrains , 2014, J. Intell. Fuzzy Syst..

[15]  Zhongfu Tan,et al.  A combined external delivery optimization model for wind power and thermal power considering carbon trading and tradable green certificates based on Credibility theory , 2016 .

[16]  Yong He,et al.  Short-Term Power Generation Energy Forecasting Model for Small Hydropower Stations Using GA-SVM , 2014 .

[17]  Davide Luciano De Luca,et al.  Performance assessment of a Bayesian Forecasting System (BFS) for real-time flood forecasting , 2013 .

[18]  Zhiqian Bo,et al.  Risk assessment of cascading failure in power systems based on uncertainty theory , 2011, 2011 IEEE Power and Energy Society General Meeting.

[19]  Li-zi Zhang,et al.  Short-term hydropower optimal scheduling considering the optimization of water time delay , 2014 .

[20]  Li He,et al.  Inexact rough-interval two-stage stochastic programming for conjunctive water allocation problems. , 2009, Journal of environmental management.

[21]  Yifei Sun,et al.  A real-time operation of the Three Gorges Reservoir with flood risk analysis , 2016 .

[22]  Baoding Liu,et al.  Standby redundancy optimization problems with fuzzy lifetimes , 2005, Comput. Ind. Eng..

[23]  Gordon H. Huang,et al.  Inexact two-stage stochastic credibility constrained programming for water quality management , 2013 .

[24]  Shenglian Guo,et al.  Estimation of reservoir flood control operation risks with considering inflow forecasting errors , 2014, Stochastic Environmental Research and Risk Assessment.

[25]  Chuntian Cheng,et al.  Daily Reservoir Runoff Forecasting Method Using Artificial Neural Network Based on Quantum-behaved Particle Swarm Optimization , 2015 .

[26]  Chu Zhang,et al.  A hybrid model based on synchronous optimisation for multi-step short-term wind speed forecasting , 2018 .

[27]  Liu Yuan,et al.  Benefit and Risk Balance Optimization for Stochastic Hydropower Scheduling , 2016, Water Resources Management.

[28]  N. Zmijewski,et al.  Hydrograph variances over different timescales in hydropower production networks , 2016 .

[29]  Liping Wang,et al.  Research and Application of Multidimensional Dynamic Programming in Cascade Reservoirs Based on Multilayer Nested Structure , 2015 .

[30]  Xiaoxia Huang,et al.  Chance-constrained programming models for capital budgeting with NPV as fuzzy parameters , 2007 .

[31]  Wenyuan Li,et al.  Power System Operation Risk Assessment Using Credibility Theory , 2008, IEEE Transactions on Power Systems.

[32]  Xi Chen,et al.  Two-stage credibility-constrained programming with Hurwicz criterion (TCP-CH) for planning water resources management , 2014, Eng. Appl. Artif. Intell..

[33]  Baoding Liu,et al.  Theory and Practice of Uncertain Programming , 2003, Studies in Fuzziness and Soft Computing.

[34]  Denis Dartus,et al.  Modelling errors calculation adapted to rainfall - Runoff model user expectations and discharge data uncertainties , 2017, Environ. Model. Softw..

[35]  Ali Fares,et al.  Rainfall-runoff modeling in a flashy tropical watershed using the distributed HL-RDHM model , 2014 .

[36]  Marco Franchini,et al.  Case Study: Improving Real-Time Stage Forecasting Muskingum Model by Incorporating the Rating Curve Model , 2011 .

[37]  P. Breil,et al.  Description and evaluation of a surface runoff susceptibility mapping method , 2016 .

[38]  Andrzej M. J. Skulimowski,et al.  Universal Intelligence, Creativity, and Trust in Emerging Global Expert Systems , 2013, ICAISC.

[39]  Zhong-Zhong Jiang,et al.  Fuzzy Multiobjective Modeling and Optimization for One-Shot Multiattribute Exchanges With Indivisible Demand , 2016, IEEE Transactions on Fuzzy Systems.

[40]  Li Mo,et al.  Short-term hydro generation scheduling of Xiluodu and Xiangjiaba cascade hydropower stations using improved binary-real coded bee colony optimization algorithm , 2015 .

[41]  Zhong-Zhong Jiang,et al.  A Multi-objective Matching Approach for One-Shot Multi-attribute Exchanges Under a Fuzzy Environment , 2015, Int. J. Fuzzy Syst..

[42]  Ting Zhou,et al.  Operating Rules Derivation of Jinsha Reservoirs System with Parameter Calibrated Support Vector Regression , 2014, Water Resources Management.

[43]  Xiaoxia Huang,et al.  Credibility-based chance-constrained integer programming models for capital budgeting with fuzzy parameters , 2006, Inf. Sci..

[44]  Sampath Sundaram,et al.  Credibility hypothesis testing of expectation of fuzzy normal distribution , 2014, J. Intell. Fuzzy Syst..

[45]  Yong Peng,et al.  Risk analysis of dynamic control of reservoir limited water level by considering flood forecast error , 2011 .

[46]  Vijay P. Singh,et al.  Entropy-based derivation of generalized distributions for hydrometeorological frequency analysis , 2018 .

[47]  Ruey-Hsun Liang,et al.  A Fuzzy-Optimization Approach for Generation Scheduling With Wind and Solar Energy Systems , 2007, IEEE Transactions on Power Systems.

[48]  Dug Hun Hong.  Renewal reward process for $$T$$T-related fuzzy random variables on $$(\mathbb {R}^{p}, \mathbb {R}^{q})$$(Rp,Rq) , 2014, Fuzzy Optim. Decis. Mak..