Uzair MalikVishal KumarBarjeev Tyagi
A Microgrid (MG) integrates various renewable resources, energy storage systems, and loads to form a single entity. MG permits the integration of environmentally friendly power assets into the existing centralized network. Due to the stochastic nature of renewable sources and load demand, it becomes pretty important to have optimal planning of MG. The running cost incorporated with the capital cost gives a comprehensive MG design. The multi-objective cost optimization function is formulated to minimize the MG system's overall cost and reduce the carbon footprints. It also provides an optimal number of DERs to be used in an MG system. The intermittent nature of renewable sources and load is considered with the random variation based on the beta distribution. The MG planning is carried out in the Roorkee area situated in India. The optimization toolbox in the MATLAB environment is used, which implements two optimizations techniques genetic algorithm (GA) and fmincon. It has been observed that the genetic algorithm gives a better result than the fmincon approach.
Bineeta MukhopadhyayDebapriya Das
Parvaiz Ahmad AhangarShameem Ahmad LoneNeeraj Gupta
Zhongda LuXi YuFengxia XuLiqiu JingXue Cheng
Oday A. AhmedJohn William Grimaldo GuerreroG. EzhilarasanAmit VedShivender SinghAshish SinghI. B. SapaevMuhamad Zahim SujodAhmad AlkhayyatH.P. Allathadka
Li GuoWenjian LiuBingqi JiaoBowen HongChengshan Wang