A coordinated optimization framework for long-term complementary operation of a large-scale hydro-photovoltaic hybrid system: Nonlinear modeling, multi-objective optimization and robust decision-making

Abstract Hydropower system is a crucial support for the integration of various renewable energy sources. The integration of dispatchable hydropower and non-dispatchable photovoltaic (PV) power is promising to achieve efficient resource use. This paper proposes a coordinated optimization framework for the long-term complementary operation of large-scale hydro-PV hybrid systems. A multi-objective optimization model is established that simultaneously optimizes the economic benefit and operational safety of the hybrid system, i.e., the quantity and quality of the joint power output. The proposed model decouples hydropower and PV power in time scales to maintain calculation accuracy and reduce problem dimensions. A parallel generic front modeling-based multi-objective evolutionary algorithm (GFM-MOEA) is designed to produce a well-converged and well-distributed set of Pareto optimal solutions. Also, we develop a novel robust decision-making model to evaluate, rank and select the Pareto optimal solutions, which allows potential uncertainties in input data to be considered. The proposed framework is applied to the Longyangxia hydro-PV hybrid power system, which is the largest hydro-PV power plant in the world. Several numerical experiments are conducted to examine the hydrological effect on multi-objective optimization as well as the effect of uncertainty levels on robust decision-making. The results show that: (1) a clear competing relationship exists between total generated power and stability of the joint power output; (2) hydropower can compensate for the PV power, mainly when the solar radiation is limited while the abundant water resource is available due to rainfalls; (3) hydrological regimes have significant impacts on the multi-objective optimization results and the complementary effect; (4) the robust decision-making model enhances the reliability of the risk-informed complementary operation strategy by measuring the robustness and uncertainty of the decision.

[1]  Jun Qiu,et al.  Multi-objective optimization for integrated hydro–photovoltaic power system , 2016 .

[2]  Hao Wang,et al.  Deriving operating rules for a large-scale hydro-photovoltaic power system using implicit stochastic optimization , 2018, Journal of Cleaner Production.

[3]  Juan Chen,et al.  Stochastic multi-criteria decision making based on stepwise weight information for real-time reservoir operation , 2020 .

[4]  Li Mo,et al.  Short-term hydro-thermal-wind complementary scheduling considering uncertainty of wind power using an enhanced multi-objective bee colony optimization algorithm , 2016 .

[5]  Fausto A. Canales,et al.  Assessing temporal complementarity between three variable energy sources through correlation and compromise programming , 2019, Energy.

[6]  Risto Lahdelma,et al.  SMAA-2: Stochastic Multicriteria Acceptability Analysis for Group Decision Making , 2001, Oper. Res..

[7]  He Li,et al.  Long-term complementary operation of a large-scale hydro-photovoltaic hybrid power plant using explicit stochastic optimization , 2019, Applied Energy.

[8]  Xiaohui Lei,et al.  Multi-objective optimization scheduling of wind–photovoltaic–hydropower systems considering riverine ecosystem , 2019, Energy Conversion and Management.

[9]  Getachew Bekele,et al.  Feasibility Study of Small Hydro/PV/Wind Hybrid System for off Grid Rural Electrification in Ethiopia , 2012 .

[10]  Ye Tian,et al.  Guiding Evolutionary Multiobjective Optimization With Generic Front Modeling , 2020, IEEE Transactions on Cybernetics.

[11]  Bo Ming,et al.  Optimizing utility-scale photovoltaic power generation for integration into a hydropower reservoir by incorporating long- and short-term operational decisions , 2017 .

[12]  P. Gehrke,et al.  River regulation and fish communities in the Murray-Darling River system, Australia , 1995 .

[13]  Jingwen Zhang,et al.  Hydropower reservoir reoperation to adapt to large-scale photovoltaic power generation , 2019, Energy.

[14]  Lei Cheng,et al.  Optimal daily generation scheduling of large hydro–photovoltaic hybrid power plants , 2018, Energy Conversion and Management.

[15]  In-Beum Lee,et al.  A stochastic optimization approach to the design and operation planning of a hybrid renewable energy system , 2019, Applied Energy.

[16]  William W.-G. Yeh,et al.  Real‐Time Optimal Flood Control Decision Making and Risk Propagation Under Multiple Uncertainties , 2017 .

[17]  Juan Chen,et al.  Short-term stochastic optimization of a hydro-wind-photovoltaic hybrid system under multiple uncertainties , 2020, Energy Conversion and Management.

[18]  John W. Labadie,et al.  Optimal Operation of Multireservoir Systems: State-of-the-Art Review , 2004 .

[19]  Fausto A. Canales,et al.  A review on the complementarity of renewable energy sources: Concept, metrics, application and future research directions , 2019, 1904.01667.

[20]  Hao Wang,et al.  Improved multi-objective model and analysis of the coordinated operation of a hydro-wind-photovoltaic system , 2017 .

[21]  Joseph R. Kasprzyk,et al.  Evolutionary multiobjective optimization in water resources: The past, present, and future , 2012 .

[22]  Wei Hu,et al.  Coordinated optimal operation of hydro–wind–solar integrated systems , 2019, Applied Energy.