Hybrid Wind and Solar Systems Optimization

Badr, M. A.

doi:10.5772/intechopen.89136

Cited by 2 publications

(1 citation statement)

References 20 publications

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“…The load demand and loss probability are used to calculate the optimal size of the battery storage system's capacity, which is a vital part of energy exportation. Numerous optimisation techniques are used to design and operate hybrid renewable energy systems, including linear programming, genetic algorithms, particle swarm optimisation, and ant colony optimisation [6]. Recycling sensitivity analysis is proposed in [7] in order to ascertain the effects of ambiguities in the hybrid system.…”

Section: Introductionmentioning

confidence: 99%

Design analysis of hybrid solar-wind renewable energy systems using water strider optimization

2024

Phys. Scr.

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Hybrid energy systems (HES) have the potential to reduce global warming and provide an affordable alternative to provide electricity access to remote regions. This paper proposes an optimal design of HES using water strider optimisation (WSO) with multi-objective parameters. A selection of appropriate components, sizing, radius index, pitch control, and battery bank size for a HES system is optimised with the WSO algorithm. The objective is to provide cost-efficient, dependable, and alternative energy optimisation in various load demand conditions. The designed parameters, including a battery bank of 2.5 kWh to 800 kWh, a solar photovoltaic (PV) array size of 50 kW to 300 kW in terms of load demand, a 2-axis tracking PV system with an area of 12 m2, and a wind turbine (WT) with a swept area of 22 m2 and a hub height of 12.3 m, make up an optimized HES. The single-family energy demand in India is the topic of this study, with a lifespan of 20 to 30 years.

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Section: Introductionmentioning

confidence: 99%

Design analysis of hybrid solar-wind renewable energy systems using water strider optimization

2024

Phys. Scr.

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Sizing and Design of a PV-Wind-Fuel Cell Storage System Integrated into a Grid Considering the Uncertainty of Load Demand Using the Marine Predators Algorithm

et al. 2022

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In this paper, the utility grid is integrated with hybrid photovoltaic (PV)/wind/fuel cells to overcome the unavailability of the grid and the single implementation of renewable energy. The main purpose of this study is smart management of hydrogen storage tanks and power exchange between the hybrid renewable energy and the grid to minimize the total cost of the hybrid system and load uncertainties. PV and wind act as the main renewable energy sources, whereas fuel cells act as auxiliary sources designed to compensate for power variations and to ensure continuous power flow to the load. The grid is considered a backup system that works when hybrid renewable energy and fuel cells are unavailable. In this study, the optimal size of the components of the hybrid energy system is introduced using two methods: the marine predators’ algorithm (MPA) and the seagull optimization algorithm (SOA). The optimal sizing problem is also run accounting for the uncertainty in load demand. The results obtained from the proposed optimization are given with and without uncertainty in load demand. The simulation results of the hybrid system without uncertainty demonstrate the superiority of the MPA compared with SOA. However, in the case of load uncertainty, the simulation results (the uncertainty) are given using the MPA optimization technique with +5%, +10%, and +15% uncertainty in load, which showed that the net present cost and purchase energy are increased with uncertainty.

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Hybrid Wind and Solar Systems Optimization

Cited by 2 publications

References 20 publications

Design analysis of hybrid solar-wind renewable energy systems using water strider optimization

Design analysis of hybrid solar-wind renewable energy systems using water strider optimization

Sizing and Design of a PV-Wind-Fuel Cell Storage System Integrated into a Grid Considering the Uncertainty of Load Demand Using the Marine Predators Algorithm

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