@article{scholars18586,
            year = {2023},
             doi = {10.3390/math11092079},
          number = {9},
            note = {cited By 2},
          volume = {11},
         journal = {Mathematics},
           title = {An Enhanced Multi-Objective Optimizer for Stochastic Generation Optimization in Islanded Renewable Energy Microgrids},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85159212645&doi=10.3390\%2fmath11092079&partnerID=40&md5=9f298dbb932d02c04ee03487fdcd188b},
        abstract = {A microgrid is an autonomous electrical system that consists of renewable energy and efficiently achieves power balance in a network. The complexity in the distribution network arises due to the intermittent nature of renewable generation units and varying power. One of the important objectives of a microgrid is to perform energy management based on situational awareness and solve an optimization problem. This paper proposes an enhanced multi-objective multi-verse optimizer algorithm (MOMVO) for stochastic generation power optimization in a renewable energy-based islanded microgrid framework. The proposed algorithm is utilized for optimum power scheduling among various available generation sources to minimize the microgrid{\^a}??s generation costs and power losses. The performance of MOMVO is assessed on a 6-unit and 10-unit test system. Simulation results show that the proposed algorithm outperforms other metaheuristic algorithms for multi-objective optimization. {\^A}{\copyright} 2023 by the authors.},
          author = {Lakhina, U. and Badruddin, N. and Elamvazuthi, I. and Jangra, A. and Huy, T. H. B. and Guerrero, J. M.}
}