Abstract
Electric distribution systems face many issues, such as power outages, high power losses,
voltage sags, and low voltage stability, which are caused by the intermittent nature of renewable
power generation and the large changes in load demand. To deal with these issues, a distribution
system has been designed using both short- and long-term energy storage systems such as superconducting
magnetic energy storage (SMES) and pumped-hydro energy storage (PHES). The aim
of this paper is to propose a metaheuristic-based optimization method to find the optimal size of a
hybrid solar PV-biogas generator with SMES-PHES in the distribution system and conduct a financial
analysis. This method is based on an efficient algorithm called the “enhanced whale optimization”
algorithm (EWOA), along with the proposed objective functions and constraints of the system. The
EWOA is employed to reduce the hybrid system’s life cycle cost (LCC) and improve its reliability,
both of which serve as performance indicators for the distribution system. The proposed method for
sizing a grid-connected hybrid solar PV-biogas generator with SMES-PHES is compared with other
metaheuristic optimization techniques, including the African vulture optimization algorithm (AVOA),
grey wolf optimization algorithm (GWO), and water cycle algorithm (WCA). The numerical results
of the EWOA show that the combination of a hybrid solar PV-biogas generator with SMES-PHES can
successfully reduce the LCC and increase reliability, making the distribution system work better.