Bi-objective optimization of a standalone hybrid PV–Wind–battery system generation in a remote area in Tunisia

Belouda, Malek; Hajjaji, Mohamed Ali; Sliti, Hamdi; Mami, Abdelkader

doi:10.1016/j.segan.2018.09.005

Cited by 65 publications

(25 citation statements)

References 30 publications

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“…In Equations (23) and (25), S l new is only accepted if it provides a better TAC value based on the fitness function. Finally, the optimization process of TLBO continues until some termination criterion is met.…”

Section: Tlbomentioning

confidence: 99%

“…Meta-heuristic algorithms with hybridized schemes and other optimization methodologies are widely adopted for energy management [16][17][18][19] and the unit sizing problem [20][21][22][23][24][25][26][27][28][29]. The Jaya optimization scheme was used for the optimal sizing of HRESs to minimize TAC [20,21].…”

Section: Introductionmentioning

confidence: 99%

“…The PV-WT-battery system achieved the best results in terms of TAC as compared to PV-battery and WT-battery systems. The authors in [23] used an evolutionary multi-objective, non-dominated sorting GA (NSGA-II) to find an optimum sizing of the PV-WT-battery system for a remote area, located in Tunisia. Similarly, NSGA-II with re-ranking based GA operators was proposed for a PV-WT-diesel-battery system [24].…”

Section: Introductionmentioning

confidence: 99%

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Enhanced Evolutionary Sizing Algorithms for Optimal Sizing of a Stand-Alone PV-WT-Battery Hybrid System

et al. 2019

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An increase in the world’s population results in high energy demand, which is mostly fulfilled by consuming fossil fuels (FFs). By nature, FFs are scarce, depleted, and non-eco-friendly. Renewable energy sources (RESs) photovoltaics (PVs) and wind turbines (WTs) are emerging alternatives to the FFs. The integration of an energy storage system with these sources provides promising and economical results to satisfy the user’s load in a stand-alone environment. Due to the intermittent nature of RESs, their optimal sizing is a vital challenge when considering cost and reliability parameters. In this paper, three meta-heuristic algorithms: teaching-learning based optimization (TLBO), enhanced differential evolution (EDE), and the salp swarm algorithm (SSA), along with two hybrid schemes (TLBO + EDE and TLBO + SSA) called enhanced evolutionary sizing algorithms (EESAs) are proposed for solving the unit sizing problem of hybrid RESs in a stand-alone environment. The objective of this work is to minimize the user’s total annual cost (TAC). The reliability is considered via the maximum allowable loss of power supply probability ( L P S P m a x ) concept. The simulation results reveal that EESAs provide better results in terms of TAC minimization as compared to other algorithms at four L P S P m a x values of 0%, 0.5%, 1%, and 3%, respectively, for a PV-WT-battery hybrid system. Further, the PV-WT-battery hybrid system is found as the most economical scenario when it is compared to PV-battery and WT-battery systems.

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Section: Tlbomentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Enhanced Evolutionary Sizing Algorithms for Optimal Sizing of a Stand-Alone PV-WT-Battery Hybrid System

et al. 2019

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“…There are several computational methods to evaluate the behavior of renewable systems, depending on the environmental conditions of the study site [2][3][4][5][6][7][8][9]. References [10][11][12][13][14][15][16][17][18][19] explain the analysis of the performance and sizing optimization in renewable hybrid systems composed of photovoltaic (PV) and wind energy (WT). Some studies use computational tools such as HOMER and Matlab to find an optimal model through objective functions.…”

Section: Introductionmentioning

confidence: 99%

Optimal energy management strategies to reduce diesel consumption for a hybrid off-grid system

Arévalo-Cordero

Benavides

Espinoza

et al. 2020

redin

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Although climate change is a reality, many off-grid communities continue to use diesel generators for electricity supply. This document presents a strategy to reduce diesel consumption in an out-of-grid system formed by renewable sources (PV-HKT-WT-DG). Three energy dispatch strategies have been proposed to verify the impact on diesel consumption and generator operating hours. In addition, different energy storage technologies (acid lead, lithium-ion, vanadium redox flow, pump storage and supercapacitor) have been considered. The HOMER software has been used to calculate the optimal size of the systems through technical-economic indicators. The results show that it is possible to reduce diesel consumption progressively; however, the cost of energy increases. On the other hand, when using lithium-ion batteries under charge cycle control, the penetration of the diesel generator has been greatly reduced without affecting the cost of the system. Finally, sensitivity analyzes have shown that when demand increases, diesel consumption does not increase significantly by using redox vanadium flow batteries, whereas the diesel generator operating hours decrease significantly in all systems.

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“…The hybrid system that is most researched is the combination of photovoltaic and wind energy. The reference [16], explains the sizing of the hybrid system composed of (PV-Wind) in a remote area of Tunisia obtaining the results of sizing optimization, and other isolated systems [17]- [26].…”

Section: Introductionmentioning

confidence: 99%

Optimization of an Off-Grid Hybrid System Using Lithium Ion Batteries

Cordero¹,

García²,

Jurado³

2020

ACTA POLYTECH HUNG

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Distributed generation represents an optimal solution for energy problems in remote sites, where access to energy distribution companies is difficult. This article therefore presents the modeling and optimization of an electric power system based on hybrid renewable energy (photovoltaic/hydrokinetic/diesel), combined with a Lithium Ion battery storage system. The analysis is performed using two methods. The first is a computational model based on mathematical equations using the Simulink Design Optimization (SDO) tool in Matlab. The second is a simulation of the hybrid system using the HOMER Software. The results show that the highest annual energy contribution corresponds to the hydrokinetic generation system (78.87%), the photovoltaic generation with a percentage of 19.59% and the penetration of the diesel generator is the lowest with 1.53%. In addition, the Nelder-Mead algorithm (SDO) shows a lower number of diesel generator starts, increasing the capacity of the batteries.

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Bi-objective optimization of a standalone hybrid PV–Wind–battery system generation in a remote area in Tunisia

Cited by 65 publications

References 30 publications

Enhanced Evolutionary Sizing Algorithms for Optimal Sizing of a Stand-Alone PV-WT-Battery Hybrid System

Enhanced Evolutionary Sizing Algorithms for Optimal Sizing of a Stand-Alone PV-WT-Battery Hybrid System

Optimal energy management strategies to reduce diesel consumption for a hybrid off-grid system

Optimization of an Off-Grid Hybrid System Using Lithium Ion Batteries

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