Optimal planning DG and BES units in distribution system considering uncertainty of power generation and time-varying load

Global environmental problems associated with traditional energy generation have led to a rapid increase in the use of renewable energy sources (RES) in power systems. The integration of renewable energy technologies is commercially available nowadays, and the most common of such RES technology is photovoltaic (PV). This paper proposes an application of hybrid teaching-learning and artificial bee colony (TLABC) technique for determining the optimal allocation of PV based distributed generation (DG) and battery energy storage (BES) units in the distribution system (DS) with the aim of minimizing the total power losses. Besides, some potential nodes identified by the power loss sensitivity factor (PLSF). Thereupon TLABC is applied to determine the location of the DG and its size from the candidate nodes. The beta probability distribution function (PDF) is employed to characterize the randomness of solar radiation. High penetration of RES can lead to a high level of risk in DS stability. To maintain system stability, BES is considered to smooth out the fluctuations and improve supply continuity. The benefits of using BES is mainly dependent on operational strategies related to PV and storage in DS. The performance of the developed approach is tested on the 69 node and 118 node DSs and compared with the differential evolution (DE) algorithm, genetic algorithm (GA), for a fair comparison. Besides, the developed approach compared with other methods in literature which are solved the same problem. The results show how practical is the developed approach compared with other techniques.