Lakshmi G V Naga, Jayalaxmi A, Veeramsetty Venkataramana
Department of Electrical Engineering, University College of Engineering Osmania University, Hyderabad, India.
Department of Electrical and Electronics Engineering, JNTU Hyderabad, Hyderabad, India.
Electr Eng (Berl). 2023;105(2):965-977. doi: 10.1007/s00202-022-01709-y. Epub 2022 Dec 24.
The optimal location of distributed generation (DG) is a critical challenge for distribution firms in order to keep the distribution network running smoothly. The optimal placement of DG units is an optimization challenge in which the objective function is to maximize distribution firms' financial benefit owing to reduced active power losses and emissions in the network. Bus voltage limits and feeder thermal limits are considered as constraints. To overcome the problem of trapping the solution toward the local optimal point and to achieve strong local and global searching capabilities, a new hybrid Jaya-Red Deer optimizer is proposed as an optimization approach in this study to determine the best placement and size of distributed generating units. In the MATLAB environment, the suggested method is implemented on IEEE 15 and PG & E 69 bus distribution systems and validated with Red Deer Optimizer, Dragonfly Algorithm, Genetic Algorithm, Particle Swarm Optimization, Jaya Algorithm and Black Widow Optimizer. Based on the simulation results, distribution firms may operate their networks with the greatest financial advantage by properly positioning and sizing their DG units.
为使配电网平稳运行，分布式发电（DG）的最佳选址是配电公司面临的一项关键挑战。DG装置的最佳布局是一个优化难题，其目标函数是通过减少网络中的有功功率损耗和排放来最大化配电公司的经济效益。母线电压限制和馈线热限制被视为约束条件。为克服将解陷入局部最优解的问题并实现强大的局部和全局搜索能力，本研究提出一种新的混合Jaya-马鹿优化器作为一种优化方法，以确定分布式发电单元的最佳布局和规模。在MATLAB环境中，该方法在IEEE 15和PG&E 69节点配电系统上实现，并与马鹿优化器、蜻蜓算法、遗传算法、粒子群优化算法、Jaya算法和黑寡妇优化器进行了验证。基于仿真结果，配电公司可以通过合理定位和确定DG装置的规模，以最大的经济效益运营其网络。
