A flower pollination optimization algorithm for an off-grid PV-Fuel cell hybrid renewable system

Samy, Mohamed; Barakat, Shimaa; Ramadan, Haïtham Saad Mohamed

doi:10.1016/j.ijhydene.2018.05.127

Cited by 204 publications

(46 citation statements)

References 29 publications

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“…The methods employed in the reviewed literature (cf. Table 5) range from simple energy balancing calculations (e. g. [71,100,105]) to simulations (e. g. [80,95,103]), metaheuristics (e. g. genetic algorithm [70], discrete harmony search [89], artificial bee swarm optimization [90,91] or flower pollination algorithm [114]), mixedinteger linear optimizations (e. g. [31]) and multi-objective optimizations (e. g. [113]). When investigating the methods, it is striking that in most cases only simplified calculations are carried out.…”

Section: Methodologies and Modelsmentioning

confidence: 99%

“…This country classification is based on the gross national income per capita [387]. [51,92,136], Cameroon [96,127], Egypt [114], Ghana [27,29], India [30,34,[46][47][48]59,60,73,74,78,82,88,94,102,107,108,110,115,116,131,133], Indonesia [33,121], Nigeria [28,137,139], Pakistan [72,76,111] [41,58], Austria [118], Canada [39,40,106,123,145], Croatia [52,80,117], Denmark [53,...…”

Section: Spatial Resolution and Locationmentioning

confidence: 99%

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Reviewing energy system modelling of decentralized energy autonomy

Weinand

Scheller

McKenna

2020

Energy

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Research attention on decentralized autonomous energy systems has increased exponentially in the past three decades, as demonstrated by the absolute number of publications and the share of these studies in the corpus of energy system modelling literature. This paper shows the status quo and future modelling needs for research on local autonomous energy systems. A total of 359 studies are roughly investigated, of which a subset of 123 in detail. The studies are assessed with respect to the characteristics of their methodology and applications, in order to derive common trends and insights. Most case studies apply to middle-income countries and only focus on the supply of electricity in the residential sector. Furthermore, many of the studies are comparable regarding objectives and applied methods. Local energy autonomy is associated with high costs, leading to levelized costs of electricity of 0.41 $/kWh on average. By analysing the studies, many improvements for future studies could be identified: the studies lack an analysis of the impact of autonomous energy systems on surrounding energy systems. In addition, the robust design of autonomous energy systems requires higher time resolutions and extreme conditions. Future research should also develop methodologies to consider local stakeholders and their preferences for energy systems.

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Section: Methodologies and Modelsmentioning

confidence: 99%

Section: Spatial Resolution and Locationmentioning

confidence: 99%

Reviewing energy system modelling of decentralized energy autonomy

Weinand

Scheller

McKenna

2020

Energy

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“…[15], energy management strategy with optimal design of PV/WT/FC installed in Iran has been presented via flower pollination algorithm (FPA) to minimize the net present cost (NPC) while in Ref. [16], FPA has been employed to optimize PV/FC system. In Refs.…”

Section: Introductionmentioning

confidence: 99%

Recent Approach Based Social Spider Optimizer for Optimal Sizing of Hybrid PV/Wind/Battery/Diesel Integrated Microgrid in Aljouf Region

2020

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This paper develops a recent methodology based on social spider optimizer (SSO) to determine the optimal sizing of a hybrid renewable energy sources (RESs) integrated microgrid (MG). It comprises photovoltaic (PV), wind turbine (WT), battery, diesel generator (DG), and inverter. The cost of energy (COE) is proposed as fitness function. The objective of the proposed SSO is to determine three design variables which are number of PV panels, number of WT, and number of battery autonomy days such that COE is minimized. Additionally, an energy management strategy is presented. Loss of power supply probability (LPSP) is considered to confirm the reliability of operation. The selection of SSO is due to its simplicity in construction and requiring less controlling parameters. The proposed MG is installed in a remote area at Aljouf region in the northern of Kingdom of Saudi Arabia. Annual data of irradiance, wind speed, and temperature are recorded. The SSO results are compared to Harris Hawks optimizer (HHO), Grey Wolf Optimizer (GWO), Multi-Verse Optimizer (MVO), Antlion Optimizer (ALO), and Whale Optimization Algorithm (WOA). The results obtained show that the proposed approach provides the best optimal configuration of hybrid RESs compared to HHO, GWO, MVO, ALO and WOA with COE of 0.1349 $/kWh and LPSP of 0.01714. Moreover, sensitivity analysis with sizing different topologies of MG including PV/Battery/DG, WT/Battery/DG, and PV/WT/ Battery/DG is presented. The best COEs are obtained via SSO achieving 0.2180 $/kWh for the first topology and 0.2161$/kWh for the second architecture. Furthermore, sensitivity analysis is also presented to investigate the effect of design variables on COE. The experimental results confirm the superiority of the proposed approach in designing reliable and costless microgrid. INDEX TERMS Optimal sizing of hybrid RESs, microgrid, social spider optimization.

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“…(8) Eventuality of the aforesaid approach is conducted on the standard IEEE 33 and IEEE 69 bus power system. a second-order cone programming model [19] Cuckoo search algorithm [20] The Flower Pollination Algorithm (FPA) [21] biogeography-based optimization algorithm [22] PSO algorithm [23] Multi-objective ant lion optimizer [24] Breeder genetic algorithm (BGA). The organization of the remainder of the current article is as the following, Load and uncertainty modeling discusses in part II.…”

Section: Introductionmentioning

confidence: 99%

Optimal Allocation of Hybrid Renewable Energy System by Multi-Objective Water Cycle Algorithm

et al. 2019

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This article offers a multi-objective framework for an optimal mix of different types of distributed energy resources (DERs) under different load models. Many renewable and non-renewable energy resources like photovoltaic system (PV), micro-turbine (MT), fuel cell (FC), and wind turbine system (WT) are incorporated in a grid-connected hybrid power system to supply energy demand. The main aim of this article is to maximize environmental, technical, and economic benefits by minimizing various objective functions such as the annual cost, power loss and greenhouse gas emission subject to different power system constraints and uncertainty of renewable energy sources. For each load model, optimum DER size and its corresponding location are calculated. To test the feasibility and validation of the multi-objective water cycle algorithm (MOWCA) is conducted on the IEEE-33 bus and IEEE-69 bus network. The concept of Pareto-optimality is applied to generate trilateral surface of non-dominant Pareto-optimal set followed by a fuzzy decision-making mechanism to obtain the final compromise solution. Multi-objective non-dominated sorting genetic (NSGA-III) algorithm is also implemented and the simulation results between two algorithms are compared with each other. The achieved simulation results evidence the better performance of MOWCA comparing with the NSGA-III algorithm and at different load models, the determined DER locations and size are always righteous for enhancement of the distribution power system performance parameters.

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A flower pollination optimization algorithm for an off-grid PV-Fuel cell hybrid renewable system

Cited by 204 publications

References 29 publications

Reviewing energy system modelling of decentralized energy autonomy

Reviewing energy system modelling of decentralized energy autonomy

Recent Approach Based Social Spider Optimizer for Optimal Sizing of Hybrid PV/Wind/Battery/Diesel Integrated Microgrid in Aljouf Region

Optimal Allocation of Hybrid Renewable Energy System by Multi-Objective Water Cycle Algorithm

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