Abstract
Renewable energy resources are deemed a potential energy production source due to their cost efficiency and harmless reaction to the environment, unlike non-renewable energy resources. However, they often fail to meet energy requirements in unfavorable weather conditions. The concept of Hybrid renewable energy resources addresses this issue by integrating both renewable and non-renewable energy resources to meet the required energy load. In this paper, an intelligent cost optimization algorithm is proposed to maximize the use of renewable energy resources and minimum utilization of non-renewable energy resources to meet the energy requirement for a nanogrid infrastructure. An actual data set comprising information about the load and demand of utility grids is used to evaluate the performance of the proposed nanogrid energy management system. The objective function is formulated to manage the nanogrid operation and implemented using a variant of Particle Swarm Optimization (PSO) named recurrent PSO (rPSO). Firstly, rPSO algorithm minimizes the installation cost for nanogrid. Thereafter, the proposed NEMS ensures cost efficiency for the post-installation period by providing a daily operational plan and optimizing renewable resources. State-of-the-art optimization models, including Genetic Algorithm (GA), bat and different Mathematical Programming Language (AMPL) solvers, are used to evaluate the model. The study's outcomes suggest that the proposed work significantly reduces the use of diesel generators and fosters the use of renewable energy resources and beneficiates the eco-friendly environment.
Highlights
Most of the central power generators rely upon conventional means of energy to produce electricity
This study presents a novel nanogrid Energy Management System (NEMS) that provides an optimal solution using recursive particle swarm optimization (PSO)
Due to several inherited advantages, nanogrids have become a major source of electricity for energy consumers across the globe
Summary
Most of the central power generators rely upon conventional means of energy to produce electricity These resources encompass oil, natural gas, coal, and nuclear energy, collectively termed fossil-fuel-based solutions that generate around 80% of the world’s energy [1]. Natural resources such as solar, wind, and hydrothermal hold a great potential to meet ever-increasing electricity requirements without harming the environment Due to their high dependence upon weather stochasticity, these renewable energy resources often fail to produce an adequate amount of energy [3,4]. Most of the contemporary state-of-the-art focuses on reducing the static cost of nanogrid installation and overlooks post-installation factors like daily maintenance and operational plan Considering these factors while designing nanogrid structures has a high probability of significantly reducing cost for efficient energy management systems. The rPSO results in minimum cost, including installation, maintenance, and operational cost
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