Hydrogen production horizon using solar energy in Biskra, Algeria

Saadi, Aïcha; Becherif, Mohamed; Ramadan, Haïtham Saad Mohamed

doi:10.1016/j.ijhydene.2016.08.224

Cited by 48 publications

(13 citation statements)

References 34 publications

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“…Ozcan et al 20 presented an analysis and performance assessment for the study of the solarpowered Mg-Cl cycle of hydrogen production using energy and exergy methods. Dagdougui et al 23 proposed a geographic information system (GIS)-based decision-making methodology for the selection of the most suitable locations for installing renewable hydrogen production systems through solar and wind energies. Rezaeishouroki et al 21 prioritized 13 cities of Fars Province in Iran to implement the wind energy system for the production of renewable hydrogen.…”

Section: Literature Reviewmentioning

confidence: 99%

“…22 The study showed that developments of improved processes for hydrogen production via solar resource are likely to continue in order to reach competitive hydrogen production costs. Dagdougui et al 23 proposed a geographic information system (GIS)-based decision-making methodology for the selection of the most suitable locations for installing renewable hydrogen production systems through solar and wind energies.…”

Section: Figurementioning

confidence: 99%

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Investigation of solar energy utilization for production of hydrogen and sustainable chemical fertilizer: A case study

Mostafaeipour

Sedeh

2019

Int J Energy Res

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Summary Renewable energies play a vital role in the economic and social development and progress of many countries. As one of the most significant sources of renewable energy, solar energy has been used due to its availability in many regions. Generating electricity for hydrogen production is one of the applications of solar energy. In petrochemical complexes, hydrogen is often used for producing fertilizers, especially urea fertilizers. The present study aims at investigating five major Iranian petrochemical complexes in terms of their suitability for the construction of a solar plant to produce electrolysis‐based green chemical fertilizers. To this end, a multicriteria decision‐making model is proposed, which includes the fuzzy analytic hierarchy process (AHP) and extended TODIM method of multicriteria decision making (including crisp, interval, and fuzzy numbers). The present research investigates 10 criteria for prioritizing petrochemical complexes, classified into four general categories, namely, climatic, geographic, environmental, and probability of natural disaster occurrence categories. Having calculated the weight of the criteria using the fuzzy AHP method, the alternatives are prioritized using the extended TODIM method. The methods of simple additive weighting (SAW), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and VIKOR were then used for validation of the results. Results showed that the Shiraz Petrochemical Complex has the highest priority and Khorasan Petrochemical Complex has the lowest priority for producing green fertilizer via solar energy–assisted water electrolysis. By using the solar system, Shiraz Petrochemical Complex can emit over 1900 tons less pollutants in the environment per day and provides up to 8% of its annual total production through clean energy.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Figurementioning

confidence: 99%

Investigation of solar energy utilization for production of hydrogen and sustainable chemical fertilizer: A case study

Mostafaeipour

Sedeh

2019

Int J Energy Res

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“…This makes it possible to produce a maximum of energy. The PV modules are oriented south (azimuth 0 • ) and inclined 34.8 • relative to the horizontal, which is the optimum tilt angle in that location, as demonstrated in [50]. The parameters of the PV panel are listed in Table 1, whereas the P-V and I-V characteristics of the overall PV system in different climate conditions are given in Figure 5.…”

Section: Modeling Of Solar Pv Modulementioning

confidence: 99%

Real-Time Implementation of High Performance Control Scheme for Grid-Tied PV System for Power Quality Enhancement Based on MPPC-SVM Optimized by PSO Algorithm

Krama

Zellouma²,

Rabhi

et al. 2018

Energies

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This paper proposes a high performance control scheme for a double function grid-tied double-stage PV system. It is based on model predictive power control with space vector modulation. This strategy uses a discrete model of the system based on the time domain to generate the average voltage vector at each sampling period, with the aim of canceling the errors between the estimated active and reactive power values and their references. Also, it imposes a sinusoidal waveform of the current at the grid side, which allows active power filtering without a harmonic currents identification phase. The latter attempts to reduce the size and cost of the system as well as providing better performance. In addition, it can be implemented in a low-cost control platform due to its simplicity. A double-stage PV system is selected due to its flexibility in control, unlike single-stage strategies. Sliding mode control-based particle swarm optimization (PSO) is used to track the maximum power of the PV system. It offers high accuracy and good robustness. Concerning DC bus voltage of the inverter, the anti-windup PI controller is tuned offline using the particle swarm optimization algorithm to deliver optimal performance in DC bus voltage regulation. The overall system has been designed and validated in an experimental prototype; the obtained results in different phases demonstrate the higher performance and the better efficiency of the proposed system in terms of power quality enhancement and PV power injection.Energies 2018, 11, 3516 2 of 26 and in the center of a big city [6], because sunlight is available almost everywhere. Photovoltaic electricity can be produced as close as possible to its place of consumption in a decentralized way [7], directly to the user, which makes it accessible to a large part of the world's population.Much research and development are conducted about the critical elements of photovoltaic energy; starting with energy generation [6], conversion, then injection into the network [8], as well as energy management [9]. The key problem with photovoltaic energy generation is the difficulty of achieving the highest energy yield for PV panels. The voltage of a PV panel strongly depends on the connected load due to the non-linear behavior of the PV cell [10]. Therefore, various Maximum Power Point Tracking (MPPT) algorithms have been established to allow panels operate in optimal conditions, and thus, to track the maximum power point [6,11]. Among these algorithms are "Perturbation & Observation (P&O)" [12] and "incremental conductance (InCon)" [13] which are the most used due to the simplicity of their implementation. However, the abovementioned methods are constrained by the amplitude of the injected perturbations, which determines the importance of the oscillations around the Maximum power point (MPP) as well as the convergence time. To overcome this problem, several algorithms have been developed based on techniques derived from artificial intelligence such as Fuzzy Logic [14], Neural Network [15], Neuro-Fuz...

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“…As mentioned before, the electrolyser cells are connected in series, therefore, same amount of current is flowing through each cell, given by equation (14). The voltage characteristics of considered electrolyser, as presented in [33], can be found by equation (15).…”

Section: Alkaline Electrolysermentioning

confidence: 99%

“…However, they are intermittent in nature, with non-uniform availability during diurnal period and zero availability during nocturnal period. To be used as steady power source, sustainable energy storage is needed and hydrogen production provide a long term and reliable solution for solar energy systems [15]. Electrolytic hydrogen production from water can work in a closed loop as the electricity can be produced back in fuel cell with water production, assuming no loss.…”

Section: Introductionmentioning

confidence: 99%

Optimization Strategy of Sustainable Concentrated Photovoltaic Thermal (CPVT) System for Cooling

Burhan

Shahzad

2018

Energy, Environment, and Sustainability

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Renewable energy resources are susceptible to intermittent power supply and their standalone operation has prime importance for steady power supply. Solar energy resources have high global availability and potential among all energy sources. Most of areas with high solar energy potential have either dry hot or tropical climate. A major portion of primary energy supply for such area is utilized in their cooling energy needs. In this chapter, a sustainable approach for cooling needs has been proposed using solar energy based highly efficient concentrated photovoltaic (CPV). A combined cooling system, based upon mechanical vapour compression (MVC) and adsorption chillers have been considered. The MVC chiller utilizes the produced electricity by the third generation multi-junction solar cells (MJC). However, adsorption chiller is operated with thermal energy recovered from the cooling of CPV system, which also increases the system efficiency as high as 71%. To handle intermittency, hydrogen production is used primary energy storage system, along with the hot water storage. The complete system configuration is then optimized for standalone operation with optimum components size and minimum cost, using microgenetic algorithm according to proposed optimization strategy.

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Hydrogen production horizon using solar energy in Biskra, Algeria

Cited by 48 publications

References 34 publications

Investigation of solar energy utilization for production of hydrogen and sustainable chemical fertilizer: A case study

Investigation of solar energy utilization for production of hydrogen and sustainable chemical fertilizer: A case study

Real-Time Implementation of High Performance Control Scheme for Grid-Tied PV System for Power Quality Enhancement Based on MPPC-SVM Optimized by PSO Algorithm

Optimization Strategy of Sustainable Concentrated Photovoltaic Thermal (CPVT) System for Cooling

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