Optimal incorporation of solar and wind DGs along with seasonal loads using teaching-learning based optimization

Renewable energy attracts more attention every day, because they are non-polluting and lasting. Recently, a significant number of renewable energy generating units (DGs) that are based on intermittent generation patterns are being added to the distribution network, in addition to the growing need for load, environmental threats are As well as reach the minimum. An appropriate combination of distributed disposable generation in distribution networks is important to guarantee the operational benefits of network quality. In this paper, the optimal location of solar sources and wind sources in a distribution network, taking into account seasonal loads and atmospheric changes has been made. Modeling has been made due to uncertainty in solar beam and wind speed. For better stability and improvement of power quality, we consider constraints on the voltage and current flow of transmission lines and the problem of optimizing the location of resources with these constraints has become a multi-objective optimization problem. To solve the problem, the optimization method teaching-learning based optimization (TLBO) has been used. The proposed method has been tested and tested on a standard 30-bus network. According to simulation results, the proposed method has had satisfactory and promising results.