@inproceedings{scholars17303,
           title = {Towards Power Grid Stability Index and Line Losses for Optimal Placement using Moth-Flame Optimization},
         journal = {2022 International Conference on Digital Transformation and Intelligence, ICDI 2022 - Proceedings},
       publisher = {Institute of Electrical and Electronics Engineers Inc.},
           pages = {74--80},
            note = {cited By 0; Conference of 2022 International Conference on Digital Transformation and Intelligence, ICDI 2022 ; Conference Date: 1 December 2022 Through 2 December 2022; Conference Code:185994},
             doi = {10.1109/ICDI57181.2022.10007194},
            year = {2022},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146970656&doi=10.1109\%2fICDI57181.2022.10007194&partnerID=40&md5=54e1f13c959ad668546d1d73033ec84c},
        keywords = {Distribution functions; Electric load flow; Electric power system stability, Distribution; Distribution systems; Generation; MFO; Net work; Optimisations; Optimization algorithms; Power; Power grid stability; Stability indices, Electric power distribution},
        abstract = {Forecasting distribution system loads is frequently fraught with uncertainties. Such uncertain-ties impose some undesirable consequences and fluctu-ations on the power working of the system leading to a decrease in the accuracy of the results obtained through system analysis. As a result, probabilistic analysis of the distribution system is extremely important. Hence, this paper presents a new probabilistic load flow approach in the presence of a 24-hour load shifting regime in all periods by applying a normal probability distribution in seven degrees of separation for the loads and employing this distribution function using Forward-backward algorithms based on Moth-Flame Optimization (MOF) aiming to identify the optimal placement and sizing of the Distributed Generation (DG). Our new proposed approach is tested on IEEE IO-bus and 33-bus radial distribution networks. The findings are compared with the conventional approach (i.e., based on deterministic techniques), and it is more efficient with minimum power cost for the user. {\^A}{\copyright} 2022 IEEE.},
          author = {Alqushaibi, A. and Hasan, M. H. and Abdulkadir, S. J. and Muneer, A. and Al-Tashi, Q. and Gamal, M.},
            isbn = {9798350397000}
}