Benefit and Risk Balance Optimization for Stochastic Hydropower Scheduling

Limited by inflow forecasting methods, the forecasting results are so unreliable that we have to take their uncertainty and risk into account when incorporating stochastic inflow into reservoir operation. Especially in the electricity market, punishment often happens when the hydropower station does not perform as planned. Therefore, focusing on the risk of power generation, a benefit and risk balance optimization model (BRM) which takes stochastic inflow as the major risk factor is proposed for stochastic hydropower scheduling. The mean-variance theory is firstly introduced into the optimal dispatching of hydropower station, and a variational risk coefficient is employed to give service to managers’ subjective preferences. Then, the multi-period stochastic inflow is simulated by multi-layer scenario tree. Moreover, a specific scenario reduction and reconstruction method is put forward to reduce branches and computing time accordingly. Finally, the proposed model is applied to the Three Gorges Reservoir (TGR) in China for constructing a weekly generation scheduling in falling stage. Compared to deterministic dynamic programming (DDP) and stochastic dynamic programming (SDP), BRM achieves more satisfactory performance. Moreover, the tradeoffs for risk-averse decision makers are discussed, and an efficient curve about benefit and risk is formed to help make decision.

[1]  Taher Niknam,et al.  Scenario-based dynamic economic emission dispatch considering load and wind power uncertainties , 2013 .

[2]  Steffi Naumann,et al.  Short-Term Reservoir Optimization for Flood Mitigation under Meteorological and Hydrological Forecast Uncertainty , 2015, Water Resources Management.

[3]  Haralambos V. Vasiliadis,et al.  Bayesian stochastic optimization of reservoir operation using uncertain forecasts , 1992 .

[4]  Jinwen Wang,et al.  A new stochastic control approach to multireservoir operation problems with uncertain forecasts , 2010 .

[5]  Kwok-wing Chau,et al.  Operation challenges for fast-growing China ’ s hydropower systems and realization of energy saving and emission reduction , 2012 .

[6]  Felix F. Wu,et al.  Managing Price Risk in a Multimarket Environment , 2006 .

[7]  Ming Zhang,et al.  Application of Minimum Reward Risk Model in Reservoir Generation Scheduling , 2016, Water Resources Management.

[8]  Yixin Ni,et al.  Supplier Asset Allocation in a Pool-Based Electricity Market , 2007, IEEE Transactions on Power Systems.

[9]  Chuntian Cheng,et al.  Operation challenges for fast-growing China's hydropower systems and respondence to energy saving and emission reduction , 2012 .

[10]  Shi-Mei Choong,et al.  State-of-the-Art for Modelling Reservoir Inflows and Management Optimization , 2015, Water Resources Management.

[11]  Ebrahim Farjah,et al.  An efficient scenario-based and fuzzy self-adaptive learning particle swarm optimization approach for dynamic economic emission dispatch considering load and wind power uncertainties , 2013 .

[12]  Arthur L. Stoecker,et al.  Nonlinear Reservoir Optimization Model with Stochastic Inflows: Case Study of Lake Tenkiller , 2015 .

[13]  Jery R. Stedinger,et al.  Reservoir optimization using sampling SDP with ensemble streamflow prediction (ESP) forecasts , 2001 .

[14]  Franco Romerio,et al.  Long-term Uncertainty of Hydropower Revenue Due to Climate Change and Electricity Prices , 2016, Water Resources Management.

[15]  Manfred Gilli,et al.  Climate Change Impacts on Hydropower Management , 2013, Water Resources Management.

[16]  Jord Jurriaan Warmink,et al.  Identification and Quantification of Uncertainties in a Hydrodynamic River Model Using Expert Opinions , 2011 .

[17]  Bin Xu,et al.  Risk analysis for the downstream control section in the real-time flood control operation of a reservoir , 2015, Stochastic Environmental Research and Risk Assessment.

[18]  Liping Wang,et al.  Self-Optimization Simulation Model of Short-Term Cascaded Hydroelectric System Dispatching Based on the Daily Load Curve , 2013, Water Resources Management.

[19]  Chunlong Li,et al.  Long-term generation scheduling of Xiluodu and Xiangjiaba cascade hydro plants considering monthly streamflow forecasting error , 2015 .

[20]  J. Stedinger,et al.  Sampling stochastic dynamic programming applied to reservoir operation , 1990 .

[21]  Pan Liu,et al.  A two-stage method of quantitative flood risk analysis for reservoir real-time operation using ensemble-based hydrologic forecasts , 2014, Stochastic Environmental Research and Risk Assessment.

[22]  J. Stedinger,et al.  Developments in Stochastic Dynamic Programming for Reservoir Operation Optimization , 2013 .

[23]  Chen-Ching Liu,et al.  Risk assessment in energy trading , 2003 .

[24]  Werner Römisch,et al.  Scenario Reduction Algorithms in Stochastic Programming , 2003, Comput. Optim. Appl..

[25]  Ximing Cai,et al.  Effect of streamflow forecast uncertainty on real-time reservoir operation , 2010 .

[26]  Dapeng Yu,et al.  Modelling the anthropogenic impacts on fluvial flood risks in a coastal mega-city: A scenario-based case study in Shanghai, China , 2015 .

[27]  Bruno Merz,et al.  A Probabilistic Modelling System for Assessing Flood Risks , 2006 .

[28]  Werner Römisch,et al.  Scenario tree reduction for multistage stochastic programs , 2009, Comput. Manag. Sci..

[29]  Ahmed El-Shafie,et al.  Reservoir Optimization in Water Resources: a Review , 2014, Water Resources Management.

[30]  Xiaohui Yuan,et al.  Optimal self-scheduling of hydro producer in the electricity market , 2010 .

[31]  Miguel A. Mariño,et al.  Mathematical Models of Inter-plant Economical Operation of a Cascade Hydropower System in Electricity Market , 2009 .

[32]  Jianshi Zhao,et al.  Joint and respective effects of long- and short-term forecast uncertainties on reservoir operations , 2014 .

[33]  Li Liang.  Discussion on the short-term weekly optimal scheduling of cascade hydropower stations , 2009 .

[34]  Guohe Huang,et al.  A PCM-based stochastic hydrological model for uncertainty quantification in watershed systems , 2015, Stochastic Environmental Research and Risk Assessment.

[35]  A. Abur,et al.  Total transfer capability computation for multi-area power systems , 2006, IEEE Transactions on Power Systems.

[36]  Jan H. Kwakkel,et al.  Dealing with Uncertainties in Fresh Water Supply: Experiences in the Netherlands , 2015, Water Resources Management.

[37]  O. Bozorg Haddad,et al.  Real-Time Operation of Reservoir System by Genetic Programming , 2012, Water Resources Management.