Optimal power flow for an integrated wind-solar-hydro-thermal power system considering uncertainty of wind speed and solar radiation

This paper proposes two solution methods with the help of metaheuristic algorithms to reduce the electricity generation costs of power plants in an IEEE 30-node transmission power network. The first solution method considers the whole system simultaneously whereas the second method optimizes the generation of hydropower plants (HPs) in the first stage and deals with other remaining plants and parameters of the transmission power network in the second stage. The integrated system is comprised of thermal power plants, HPs, wind power plants and photovoltaic power plants (PVPs) considering the certainty and uncertainty of solar radiation and wind speed. In addition, the placement of a PVP is, respectively, tried at node 30 and node 3 based on loss sensitivity factor (LSF). The results from an effective Cuckoo search algorithm (ECSA) for the two solution methods indicate that the second solution method is much more effective than the first one. In addition, three other metaheuristics including equilibrium optimizer, Cuckoo search algorithm and Marine predators algorithm are also applied for the second solution method. The comparisons of result reveal that ECSA is more effective than these methods and the operation cost of the system can be minimized by ECSA. On the other hand, results from uncertainty and certainty of wind and solar also indicate that node 30 with higher LSF is more suitable than node 3 with lower LSF to place the PVP. As a result, it concludes that the second solution method and ECSA should be integrated to solve OPF for the integrated wind-solar-hydro-thermal power system.