A comparative optimization of a trigeneration system with an innovative integration of solar Heliostat towers and Hydrogen production unit

Izadi, Ali; Ahmadi, Pouria; Mousavi, Shadi Bashiri; Fakhari, Iman

doi:10.1016/j.seta.2021.101522

Cited by 19 publications

(5 citation statements)

References 43 publications

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“…After simulation of the system, the lowest cost rate, minimum CO 2 emissions, least power from the grid, and highest O 2 production is computed through the optimization method. CO 2 and cost rate are calculated based on Equations (1) , (2) , respectively [ 31 ].

Where

and

stand for gained power from renewable energies and the grid (kWh) and

and

describe the life cycle CO 2 production of each kWh energy from renewable energies and the grid [ 32 ].…”

Section: System Descriptionmentioning

confidence: 99%

Design, and optimization of COVID-19 hospital wards to produce Oxygen and electricity through solar PV panels with hydrogen storage systems by neural network-genetic algorithm

Izadi

Shahafve

Ahmadi

et al. 2023

Energy

Self Cite

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Where

and

stand for gained power from renewable energies and the grid (kWh) and

and

describe the life cycle CO 2 production of each kWh energy from renewable energies and the grid [ 32 ].…”

Section: System Descriptionmentioning

confidence: 99%

Design, and optimization of COVID-19 hospital wards to produce Oxygen and electricity through solar PV panels with hydrogen storage systems by neural network-genetic algorithm

Izadi

Shahafve

Ahmadi

et al. 2023

Energy

Self Cite

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“…Since one of the optimization parameters in this system is the price of solar‐PV panels and wind turbines, Equation () was used to convert the purchasing price of these components to the cost 27

\dot{Z} = \frac{Z \times CRF \times Φ}{3600 \times N} .

In this equation,

\dot{Z}

is the cost, Z represents the price of the component,

Φ

is the maintenance factor (1.06), N denotes the annual working hours of the system (8000 hours), CRF is the capital recovery factor, which is determined by Equation ().

CRF = \frac{i {((), 1 goodbreak+ i)}^{italicny}}{{((), 1 goodbreak+ i)}^{italicny} + 1},

where

i

is the interest rate (0.12) and

ny

is the number of working years of the component (15 years).…”

Section: Simulationmentioning

confidence: 99%

“…25 Since one of the optimization parameters in this system is the price of solar-PV panels and wind turbines, Equation (1) was used to convert the purchasing price of these components to the cost. 27…”

Section: Trnsysmentioning

confidence: 99%

Artificial neural network‐based Sobol algorithm for multi‐objective optimization of renewable energy supply in buildings: A transient approach

Musharavati

2022

Intl J of Energy Research

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The need to increase the share of renewable energy supply in buildings has been a subject of concern for many authors. Renewable energies can offset building electrical and thermal energy loads, thus reducing constrains on national grid networks. The aim of this paper is to construct, model and optimize a hybrid renewable energy supply system under transient conditions. The supply system consists of solar-PV panels and vertical axis wind turbines, while batteries are used for energy storage. TRNSYS software is used to model the energy demand of an office building that operates under the average standard building as specified in EnergyPlus software. In order to determine the optimal size of the energy supply system an Artificial Neural Network (ANN) combined with a Sobol algorithm are employed. Two objective functions are developed to: (a) minimize the cost of purchasing solar-PV panels and wind turbines, and (b) minimize the electricity required from the national grid network. The simulation and optimization results show that the best condition is achieved with 461 panels and one vertical axis wind turbine. At this best condition, the amount of electricity required from the national grid network is 5.

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“…Fossil fuels such as coal, oil, and natural gas have been the primary sources of energy and they have driven rapid economic growth and spurred social development. However, due to their limited reserves around the world and the fact that they mainly produce carbon dioxide as a byproduct, issues related to energy shortages and climate change will seriously impact people's quality of life while also constraining economic and social development [1]. Therefore, researching and developing new types of clean energy as soon as possible is an inevitable trend for future energy structure transformation.…”

Section: Introductionmentioning

confidence: 99%

Research on Capacity Configuration of Wind Solar Off-grid Hydrogen Production System

Chang,

Xian,

Mao

et al. 2023

Preprint

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This paper mainly studies the configuration issues of the wind solar off-grid hydrogen production system. The system consists of a WT, PV array, energy storage batteries, an alkaline electrolyser, and a proton exchange membrane (PEM) electrolyser. The addition of PEM electrolyzer aims to reduce wind and solar power curtailment and improve the energy utilization efficiency of the system.Firstly, the study establishes simplified mathematical models for each device, designs a powerflow strategy, and develops an economically optimal objective function. The model is solved using the optimized sparrow optimization algorithm to obtain the system configuration and other important indicators such as annual energy output power and H2 production.For a scenario with a 1 MW WT and a 1 MW PV panel hydrogen production, the system configuration is determined as follows: EES with a capacity of 244 kWh, alkaline electrolyser with a power of 863 kW, PEM electrolyser with a power of 198 kW, and hydrogen storage tank capacity of 3060 kg. The energy utilization efficiency is 51% and the investment cost is approximately 2.38 million$.

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A comparative optimization of a trigeneration system with an innovative integration of solar Heliostat towers and Hydrogen production unit

Cited by 19 publications

References 43 publications

Design, and optimization of COVID-19 hospital wards to produce Oxygen and electricity through solar PV panels with hydrogen storage systems by neural network-genetic algorithm

Design, and optimization of COVID-19 hospital wards to produce Oxygen and electricity through solar PV panels with hydrogen storage systems by neural network-genetic algorithm

Artificial neural network‐based Sobol algorithm for multi‐objective optimization of renewable energy supply in buildings: A transient approach

Research on Capacity Configuration of Wind Solar Off-grid Hydrogen Production System

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