Hybrid renewable energy-based distribution system for seasonal load variations

In recent scenario, there is abundant availability of renewable energy resources to satisfy the significant increase in residential, industrial, and commercial demand. This paper presents a novel framework to determine the preeminent size of renewable distributed generators (RDGs) by optimizing the system components such as area required for solar-photovoltaic modules, swept area occupied by wind turbine blades, and area used by fuel cell. A microgrid with hybrid RDG (h-RDG) is integrated in distribution system to minimize the distribution loss, substation energy requirement, and improve the voltage level of the load. The power loss minimization is formulated as a nonlinear problem and optimized by the proposed Hybrid Nelder Mead-Particle Swarm Optimization algorithm. The microgrid location is identified by voltage stability index to improve the stability of system. Further, the system is analyzed for energy flow in different seasonal loading conditions with mixture of residential, industrial, and commercial load. The effective performance of the proposed technique is applied to standard 12-bus, 69-bus, and a practical Tamil Nadu (TN) 84-bus radial distribution system (RDS) for different hybrid combinations of h-RDG in microgrid. The result proves that the proposed method provides a simple and efficient tool for optimal and flexible use of h-RDG in microgrid under different climatic changes by simultaneously reducing distribution energy loss and improving voltage profile.