Abstract

Recently, fast uptake of renewable energy sources (RES) in the world has introduced new difficulties and challenges; one of the most important challenges is providing economic energy with high efficiency and good quality. To reach this goal, many traditional and smart algorithms have been proposed and demonstrated their feasibility in obtaining the optimal solution. Therefore, this paper introduces an improved version of Bonobo Optimizer (BO) based on a quasi-oppositional method to solve the problem of designing a hybrid microgrid system including RES (photovoltaic (PV) panels, wind turbines (WT), and batteries) with diesel generators. A comparison between traditional BO, the Quasi-Oppositional BO (QOBO), and other optimization techniques called Harris Hawks Optimization (HHO), Artificial Electric Field Algorithm (AEFA) and Invasive Weed Optimization (IWO) is carried out to check the efficiency of the proposed QOBO. The QOBO is applied to a stand-alone hybrid microgrid system located in Aswan, Egypt. The results show the effectiveness of the QOBO algorithm to solve the optimal economic design problem for hybrid microgrid power systems.

Highlights

  • Despite the steady increase in electric power production, it is still below the required level, due to the increase in load demand caused by the population increase as well as the increased use of technology in the residential, industrial and agricultural fields

  • The objective function in the optimization model is the minimization for the Net Present Cost (NPC) which is the pillar factor considered for any project design; it is counted as a sum of all components costs including the capital (C), operation and maintenance (OM) and replacement costs (R), considering the fuel cost of the diesel FCdg, taking into account the interest rate, inflation rate (δ), and escalation rate (μ) and the predefined project lifetime (N)

  • The optimal sizing is based on the objective functions introduced in (9) and the parameters of optimization are: (i) the area of PV system, (ii) the area swept by the wind turbines (WT), (iii) the rated power of diesel generator, (iv) the nominal capacity of the battery, (v) the consumption of the biomass fuel

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Summary

Introduction

Despite the steady increase in electric power production, it is still below the required level, due to the increase in load demand caused by the population increase as well as the increased use of technology in the residential, industrial and agricultural fields. In order to invest in RES to optimize electrical energy production and raise the efficiency of the systems, many studies in the world recommend combining different technologies to form hybrid renewable energy systems (HRES) [4,5]. These sources complement each other, support the national grid, and reduce the use of traditional power plants depending on fossil fuels that release greenhouse gases and pollute the environment [6].

Mathematical Description of the Proposed Hybrid System Components
Wind Energy System
Biomass System
Diesel System
BESS System
Net Present Cost
PV and WT Costs
Diesel Generator Costs
Levelized Cost of Energy
Renewable Energy Fraction
Availability Index
Bonobo Optimizer
Bonobo Selection Using Fission–Fusion Strategy
Creation of New Bonobo
Parameter Updating
Three Leaders
Quasi-Oppositional
Case Study
Results
Validation of QOBO Algorithm
Combinations of the Studied System Components
Sensitivity
Conclusions

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