Multi-criteria techno-economic optimization of hybrid grid of nanogrids

Abstract

The development of grid of nanogrids that is secure, resilient, sustainable, economical and affordable in an environmentally friendly manner has become a national priority. This paper presents a techno-economic optimal design of grid of nanogrids (GNG) with hybrid energy resources considering uncertainties in the resources and demand. The proposed techno-economic method uses non-dominated sorting genetic algorithm II (NSGA-II) to evaluate the benefit tradeoff of various designs, configurations, and operating modes for GNG. While GNG offer technological advantages, the practical engineering solution is to perform a comprehensive economic assessment of the technological merits. Thus, this paper explores the GNG configuration with higher energy availability and reliability while minimizing size and cost. In the optimization procedure, the benefits of load control and correlation in the distributed renewable energy resources across the GNG are considered to mitigate the requirement of a large energy storage system. The uncertainty in the resources and demand are characterized by a correlated auto-regressive moving average technique.