INTRODUCTION

As the world moves towards a greener future, renewable energy resources like solar energy and hydrogen energy are gaining increasing attention. The adaptation and scalability of hydrogen production depends on different factors like available primary resources of energy, hydrogen resources, technologies available for production and environmental impacts on generation [1]. In India, which is one of the fastest-growing economies in the world, renewable energy sources are playing a significant role in reaching India’s rapidly growing energy demand while also reducing its carbon footprint. Solar photovoltaic (PV) technology is rapidly expanding in India and hydrogen is emerging as a promising energy carrier for various sectors such as transportation and industry.

The findings of this study could have significant implications for India’s renewable energy sector, particularly in terms of scaling up solar PV-based green hydrogen generation. India has targeted enterprising limits for renewable energy implementation and green hydrogen could play an important role in meeting these targets while also addressing the country’s energy security and climate change concerns. By better understanding the seasonal variations in green hydrogen generation, policymakers and energy planners in India can make more informed decisions about the optimal deployment of renewable energy resources, ultimately helping to build a cleaner, more sustainable future for the country.

India’s contribution to hydrogen production is still relatively small compared to other countries, but the country has recognized the potential of hydrogen as a clean and sustainable fuel and is taking steps to increase its production.

Currently, most of the hydrogen produced in India is derived from fossil fuels, mainly natural gas. However, India is exploring various pathways to produce green hydrogen using renewable energy resources such as wind and solar. The ministry has set up a Hydrogen Task Force to develop a roadmap for the development of hydrogen technologies in the country. In 2021, India has launched its first mission known as National Hydrogen Mission.

India has also launched several initiatives to promote the use of hydrogen in various sectors. For example, the government has announced plans to introduce hydrogen fuel cell buses in several cities, and is working with industry partners to develop hydrogen-powered locomotives and ships. The country is also exploring the use of hydrogen in the steel and cement industries, which are significant contributors to greenhouse gas emissions.

In addition to green hydrogen, India is also exploring the potential of blue hydrogen, which is produced from natural gas but with carbon capture and storage (CCS) technology to reduce greenhouse gas emissions. Hydrogen production from natural gas requires extra cost for capture, store and utilization of CO2 that is generated during hydrogen production [2]. The country has several natural gas reserves that could be used to produce blue hydrogen, making it a potentially important pathway for hydrogen production in India.

Overall, India’s contribution to hydrogen production is still relatively small, the country has recognized the importance of this clean and sustainable fuel and is taking steps to increase its production and use in various sectors.

In this context, the present study aims to investigate the seasonal variation of solar PV-based green hydrogen generation in a tropical climate region in India. The study location and climate region has been defined and solar irradiance data have been collected for the selected location over a period of time. A model of the green hydrogen generation process has been developed using MATLAB software to simulate the conversion of solar energy into electricity and then into hydrogen through an electrolysis process. The seasonal variations in solar PV-based green hydrogen generation have been analyzed by considering factors such as solar irradiance, temperature, and humidity over the course of a year or multiple years. The study has evaluated the feasibility and effectiveness of solar PV-based green hydrogen generation in the selected location in India, taking into account the potential interests with regard to reduction of GHG emissions and upgrading energy security. Though H2 generation via electrolysis by PV electricity is around 13.6% costlier than conventional electricity, it reduces GHG emission which is a promising alternative to promote low-carbon emission [3]. Apart from generation, storage of hydrogen is also very crucial and challenging. There are several works going on on hydrogen storage. In a recent work Payzullakhanov et al. investigated the potential use of ceramic materials in hydrogen storage [4].

There are few works that have been carried out by different researchers throughout the world focused on PV based hydrogen generation which are mainly based on locations with dry and continental climatic zones. Martinez et al. simulated a PV coupled electrolyzer system in MATLAB with radiation profile of Auckland, New Zealand and found electrolyzer efficiency of 68.49% in summer and 63.32% in winter [5]. Bouaicha et al. developed a simulation set up with storage capacity for hydrogen to give reliable electricity coupled with solar PV [6]. This study has been carried out in America. Few researchers studied the PEM electrolyzer based system in Egypt for the month of March where the electrolyzer has been powered by PV modules [7]. A study was conducted by Sahin where MATLAB/Simulink was developed with PV powered PEM electrolyzer giving hydrogen output of 7.345 mL/min [8]. Tropical climatic regions have four distinct seasons i.e., summer, monsoon, winter and spring. All these seasons have different temperature profiles with different variations of ambient temperature. Apart from that, humidity and rainfall are two important factors to consider. Rainfall has a direct impact on the temperature variation during daytime. Due to random rainfall ambient temperature falls down instantaneously. This affects the performance of the electrolyzer. This study has been focused on such challenging factors and PV-Electrolyzer based green hydrogen production has been simulated by taking the weather parameters of a tropical region in India based on Kolkata.

METHODOLOGY

In this study, a simscape model of green hydrogen generation has been developed and the study was carried out by taking Kolkata as the location of study. Kolkata is situated in the eastern part of India and has tropical climatic conditions. All the weather data of Kolkata like solar irradiation, temperature, humidity and rainfall have been considered in this study. The step-by-step process undertaken is described in the following Fig. 1. The data are collected on a monthly average daily basis for all the months of a year. Radiation profile of Kolkata has been taken from the meteorological department of India and summarized in Fig. 2. Input energy, output energy, energy efficiency of each component in the study have been evaluated and analyzed. All the simulated data and analysis of the results obtained are reflected in the result and discussion section.

Fig. 1.
figure 1

Flowchart of the study.

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Fig. 2.
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Radiation profile of Kolkata [9].

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The weather data collected from the meteorological departmental site has been collected and solar radiation data has been sorted for input in PV panels. To convert the solar radiation data to compatible radiation profiles suited for the PV module component, average peak value for each month has been calculated and accordingly solar profile for each month has been generated as primary input in the PV-Electrolyzer set. Then the DC electricity generated as per radiation data given to the PV module is fed to a DC/DC converter. The purpose of the DC/DC converter is to regulate the voltage and current levels of the DC electricity coming from the PV panels and keep it within the range of input current and voltage levels of the electrolyzer. Ambient temperature, humidity and rainfall have been considered during the generation of H2 from electrolyzer and as a result, H2 generation rate in kg/h has been found as primary result.

The output results have been evaluated on an annual basis and seasonal variation of green hydrogen production has been noted and explained.

DESIGN

The basic blocks of this study consist of Solar Array, DC/DC converter unit, Electrolysis unit and Scopes. The electrolyser consists of a continuously suppliable water tank. The produced hydrogen in the electrolyzer has been stored in a tank which was modeled as a fixed temperature gas chamber. The block diagram of the design has been reflected in the following Fig. 3.

Fig. 3.
figure 3

Block diagram of the system.

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COMPONENTS

(I) Solar Array: There are different types of PV module models available in MATLAB [10]. Out of which a suitable model has been taken according to the matching of the PV-Electrolyzer system. The photovoltaic array is based on the light generated current equation having module area of 625 m2,

$$\begin{gathered} J = {{J}_{0}}\left\{ {\exp \left[ {q{{\left( {V - {\text{AJ}}{{{\text{R}}}_{{\text{s}}}}} \right)} \mathord{\left/ {\vphantom {{\left( {V - {\text{AJ}}{{{\text{R}}}_{{\text{s}}}}} \right)} {{{k}_{{\text{B}}}}T}}} \right. \kern-0em} {{{k}_{{\text{B}}}}T}}} \right] - 1} \right\} \\ + \,\,(V - {\text{AJ}}{{{\text{R}}}_{{\text{s}}}}){{R}_{{\text{p}}}} - {{J}_{{{\text{ph}}}}}. \\ \end{gathered} $$
(1)

(II) DC/DC Converter: The DC/DC converter used here is buck converter to step down the PV generated voltage to favorable input voltage for electrolyzer. Generally, electrolyzers have input voltage between 1.8–2 V.

(III) Electrolyzer: The electrolyzer used for simulation is electrolyzer block present in simscape and the details of the input and output ports has been discussed in Tables 1 and 2, correspondingly.

Table 1.   Input ports of the electrolyzer [11]
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Table 2. Output ports of the electrolyzer [11]
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As a whole, 110 electrolyzer cells and 6 electrodes have been used in this study.

(IV) Hydrogen Tank: A dynamic module of the hydrogen tank has been designed with the following equation,

$${{P}_{{\text{b}}}} - {{P}_{{{\text{bi}}}}} = {{Z\left( {{{N}_{{{{{\text{H}}}_{{\text{2}}}}}}}R{{T}_{{\text{b}}}}} \right)} \mathord{\left/ {\vphantom {{Z\left( {{{N}_{{{{{\text{H}}}_{{\text{2}}}}}}}R{{T}_{{\text{b}}}}} \right)} {{{M}_{{{{{\text{H}}}_{{\text{2}}}}}}}{{V}_{{\text{b}}}}}}} \right. \kern-0em} {{{M}_{{{{{\text{H}}}_{{\text{2}}}}}}}{{V}_{{\text{b}}}}}},$$
(2)

where,

Pb: Pressure of the tank in Pascal

Pbi: Initial pressure of the storage tank in Pascal

R: Universal gas constant (J/kmol K)

Tb: Operating temperature in K

Vb: Volume of the tank in m3

T: Temperature in K and

Z: Compressibility factor defined by a function of pressure as shown in the following equation,

$$Z = {{P{{V}_{{\text{m}}}}} \mathord{\left/ {\vphantom {{P{{V}_{{\text{m}}}}} {RT}}} \right. \kern-0em} {RT}}.$$
(3)

The volume of the tank was taken as 27 m3 and temperature of the tank was maintained at 273.15 K.

SIMULATION

The simulation set up has been developed in the MATLAB/Simulink platform and all the components have been tested separately before final run. The weather data has been collected from the Indian Meteorological Department and used as input reference for this study. The study was conducted for 5 h on a daily basis from 10 AM to 3 PM and hourly hydrogen generation in kg/h as primary output.

RESULTS AND DISCUSSION

This study evaluated the annual variation of green hydrogen generation on a monthly basis and carried out the system losses and overall efficiency. The following Table 3 represents different system parameters along with monthly variations. Variations of monthly generations, electrolyzer efficiency and system efficiency has been carried out by converting all the energy parameters into a single energy unit kWh. The results are plotted in the following Figs. 4–9.

Table 3.  Monthly average daily energy parameters of the PV module-electrolyzer system
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Fig. 4.
figure 4

Monthly variation of hydrogen production rate.

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Fig. 5.
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Monthly variation of energy consumed and energy generated by the electrolyzer.

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Fig. 6.
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Variation of efficiency of the PV modules.

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Fig. 7.
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Variation of energy loss in DC/DC converter.

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Fig. 8.
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Variation of electrolyzer efficiency on monthly basis.

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Fig. 9.
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Variation of system efficiency on monthly basis.

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Result shows different parameters related to green hydrogen production. From Fig. 4 it has been observed that the hydrogen production rate is highest in the month of March with 1.18 kg/h and lowest in the month of July with 0.8 kg/h. There is approximately 32.2% reduction on the hydrogen production rate between March and July. Figure 6 suggests PV module efficiency is highest in the month of July with 18.3% whereas, lowest in the month of March with 16.84%. The efficiency is lowest in March due to higher ambient temperature. In July, ambient temperature varies between 25–32°C due to the monsoon season which is favorable for solar cell operation but the difference in highest and lowest panel efficiency is not much significant. Although PV panel efficiency is highest in July but from Fig. 7 it is clear that for DC/DC converter it is lowest. This is due to different contact and cabling loss in the monsoon month. Figure 5 gives an annual pattern on energy consumption and energy output from the electrolyzer. The highest electrolyzer efficiency is 66.06% for the month of March and lowest is 59.11% for the month of July. The average temperature during daytime in Kolkata for the month of March is 34°C with only 2 rain days. This phenomenon helps the electrolyzer to operate at higher efficiency as it was operated near to optimum operating temperature (35°C) with a steady temperature profile due to very low precipitation. Whereas, for July the average daytime temperature is 29°C with 19 rainy days. This high precipitation results in rapid temperature fluctuation. Due to continuous rainfall, ambient temperature may fall abruptly which affects the performance of the electrolyzer. For smooth operation of the electrolyzer, a steady temperature profile must be maintained. But in this case for the month of July the fluctuation of temperature reduced the efficiency of the electrolyzer. Figrues 8 and 9 depict that both electrolyzer efficiency and overall system efficiency followed almost the same monthly pattern. Though PV panel efficiency followed a completely different pattern from the electrolyzer efficiency but similarity in monthly variation of efficiencies for electrolyzer and overall system efficiency is due to very small monthly variations in efficiencies in case of PV panels. This small variation is not significant enough to make an impact on overall system efficiency.

CONCLUSIONS

This study has been focused on the hydrogen generation dependent on the weather parameters like solar irradiation, temperature, humidity and rainfall. For a tropical region like Kolkata, weather conditions notably change from summer to monsoon to winter seasons. Though the PV panel efficiency is better during the monsoon seasons due to favorable temperature conditions but overall electricity generation is quite low. The overcast condition during monsoon seasons reduced the clearness index results in less penetration of solar radiation on the PV panel. Significant temperature fluctuation happened due to rainfall during the daytime of monsoon seasons. This fluctuation affects the performance of the electrolyzer. The results like PV panel efficiency, Electrolyzer efficiency and System efficiency coming from the simulation are well in the range of practical results evaluated by different researchers. Monthly average Efficiency of PV panels was around 17.4% which is in between the practical range of efficiency for mono-Si PV panels of 16–20% [12]. The monthly average efficiency of the electrolyzer was found to be 62.5% which is well in the range of efficiency found in PEM electrolyzers. Generally, PEM electrolyzers have energy efficiencies between 60–80% [13]. Thus, the results are close to the practical results found by different researchers across the globe which gives the indication of accuracy and validation of the study.

NOMENCLATURE

AC

alternating current

CCS

carbon capture and storage

CO2

carbon-di-oxide

DC

direct current

GHG

greenhouse gas

mono C-Si

multi-crystalline silicon

GHI

global horizontal irradiance

H2

hydrogen gas

kWh

kilo-watt hour

PEM

proton exchange membrane

PV

photovoltaic