Research on Short-term Optimization for Integrated Hydro-PV Power System Based on Genetic Algorithm

The combination of hydropower and PV power could make full use of the advantages of water and solar energy, which forms the integrated hydro-PV system. In this paper, a short-term optimization approach for integrated hydro-PV system is proposed, which involves the prediction model of PV power and GA-based multi-objective optimization model of the integrated system. To this aim, the short-term PV power output under three types of weather is firstly predicted by hourly solar radiation and module temperature using the nonlinear multiple regression (NMR) model. The objective functions with respect to maximum power output of the integrated system and minimum variation between complementary and original power, and the constraints are derived according to the calculating principles of hydropower. Based on the optimization model consisting of objective functions and constraints, genetic algorithm (GA) method is applied in the modelling of the optimization problem to obtain the optimal solution of the operation and scheduling of the integrated system. The optimal solutions showed that the integrated system could achieve good complementarity between hydropower and PV in time scale using the GA optimization method. Copyright 2018 Elsevier Ltd. All rights reserved.