The endless problem of energy supplies are always floating on the surface. As a result, there are a daily improvement to optimize power generators, networks and system configuration. Renewable distributed generators (RDG) are in the heart of these developments. The size of RDG is increasing daily so, it must be optimized to maximize benefits and eliminate drawbacks. Optimization algorithms are one of the fast growing techniques. In this study the Manta Ray Foraging optimization algorithm (MRFO) is applied to minimize power losses through sizing and allocation of DG type I integrated into radial distribution network (RDN). The proposed technique was tested on three different networks, IEEE 33, 69 and 85 test systems. Also, three cases were assumed to evaluate the effectiveness of MRFO algorithm. The results were compared to recent applied techniques.

能源供应的无尽问题总是浮在水面。结果，每天都有改进以优化发电机，网络和系统配置。可再生分布式发电机（RDG）是这些发展的核心。RDG的大小每天都在增加，因此必须对其进行优化以最大化收益并消除弊端。优化算法是快速增长的技术之一。在这项研究中，应用了蝠ta觅食优化算法（MRFO），以通过对集成到径向配电网（RDN）中的I型DG的大小和分配进行最小化。所提出的技术已在三种不同的网络上进行了测试，即IEEE 33、69和85测试系统。此外，假设三种情况来评估MRFO算法的有效性。