Cost Optimization of Power Generation Systems Using Bat Algorithm for Remote Health Facilities

摘要

Power problems in hospitals are much more frequent compared to other hi-tech industries. Even a small interruption in power can damage costly medical equipment's causing millions in revenue loss. Many medical facilities have their own power generation systems consisting of individual generators. However Nano grid is emerging as a popular mechanism to counter power outages from grids and maintain power quality. They are also emerging as a popular technique for maintaining power in remote locations. Nano-grids replicate a large centralized electricity grid model at a smaller scale in remote locations where grid connectivity may be impossible. Nano-grids are being successfully used in remote hilly areas with renewable energy sources. To design renewable energy system effectively the appropriate amount of renewable energy resources and their capability should be based on long term load requirements and designed with minimum cost. Optimal sizing is NP-Hard because of the dynamic state of power production in renewable sources. In this work, the optimal sizing problem is solved using the BAT algorithm with a novel cost function. Extensive simulations show BAT algorithm is effective to solve the optimal sizing problem with improved results compared to Genetic Algorithm.