Optimal Reactive Power Dispatch with Renewable Energy Sources Using Improved Neural Network Algorithm

In this study, an improved neural network algorithm (INNA) is developed for solving the stochastic optimal reactive power dispatch (ORPD) framework considering uncertainty factors related to loading demand, solar and wind energies. The ORPD aims to optimize active power loss of the network while assuring system constraints. Various well-suited probability distribution functions are performed to simulate uncertainties of loading demand and renewable energy sources (RESs). A scenario-based approach is applied to handle stochastic ORPD by solving numerous representative scenarios. The adapted IEEE 30-bus network is used to validate the developed INNA. From the achieved results, INNA has improved the results compared to its original version. Hence, the INNA is very effective in solving stochastic ORPD problems.