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25-41 

25 

 

 

 

Article 

Techno-economic analysis of a green hydrogen-

firing gas turbine in Malaysia via Monte Carlo 

simulations 
Mohammad Nurizat Rahman* 

 Energy Markets and Strategy, Energy Systems, DNV Technology Centre, 118227 Singapore 

A R T I C L E   I N F O 
 

Article history: 
Received 24 July 2024  
Received in revised form 
04 September 2024 
Accepted 15 October 2024 
 
Keywords:  
Green hydrogen, Gas turbine, Electrolyzer,  
Power generation, Decarbonization, Malaysia 
 
*Corresponding author 
Email address: 
mohammadnurizatrahman@gmail.com 
 
 
DOI: 10.55670/fpll.futech.3.4.4 
 

A B S T R A C T 
 

Based on Malaysia's National Energy Transition Roadmap, hydrogen is 
important to the country's energy transition. However, studies on potential 
green hydrogen applications in Peninsular Malaysia are scarce, particularly in 
gas turbine (GT) co-firing. This gap has shaped discussions around the 
economic and technological aspects of green hydrogen production and co-
firing. Therefore, this paper focuses on the feasibility of green hydrogen co-
firing in one of Malaysia's GTs, with a special emphasis on Peninsular Malaysia, 
the country's primary industrial hub, which houses most of the key GTs. The 
study uses a Monte Carlo model to evaluate the economic and technical factors 
affecting green hydrogen adoption, concentrating on three target years: 2023, 
2030, and 2050, representing different stages of technological deployment and 
market adoption of electrolyzers. Actual GT data is used to calculate future 
green hydrogen demand based on the turbines' technology and the percentage 
of hydrogen co-firing they could accommodate. Scenario I for 2023 showed the 
widest Levelized Cost of Hydrogen (LCOH) distribution, ranging from $3.54 to 
$16.82 per kg, indicating a high level of uncertainty. By 2030, the outlook 
improves significantly, with the conceptual co-firing system potentially 
obtaining an LCOH of $2.68 to $9.43 per kg. Looking ahead to 2050, the study 
predicts a promising future for green hydrogen co-firing, with the LCOH 
potentially dropping to $2.30 to $8.54 per kg, and a mode of $4.64 per kg. 
Sensitivity analysis also reveals shifting key cost drivers. In 2023, early-stage 
investments in electrolyzers are critical, while electricity prices become 
increasingly important in 2030 and 2050. Overall, three key cost drivers have 
been identified as having a significant effect on LCOH: electrolyzer power 
consumption, electricity price, and utilization rate, highlighting the need for 
industry and policymakers to concentrate on these factors when formulating 
new policy instruments for the green hydrogen co-firing initiative in Peninsular 
Malaysia's GTs. 

 

1. Introduction 

Malaysia, a Southeast Asian nation in the process of 
development, is situated along the South China Sea and 
includes parts of both the Malay Peninsula and the island of 
Borneo. It consists of 13 states, 11 of which are located on the 
peninsula, while the remaining two, Sabah and Sarawak, form 
East Malaysia on Borneo. The peninsula shares land borders 
with Thailand and maritime boundaries with Indonesia, 
Singapore, and Vietnam. In contrast, East Malaysia on Borneo 
borders Brunei and Indonesia by land and the Philippines and 
Vietnam by sea. The economic growth of Peninsular Malaysia 
has largely been driven by improvements in electrification, 

supported by various thermal power plants that aid in its 
socioeconomic progress. Recently, Peninsular Malaysia has 
made considerable strides toward establishing a hydrogen-
based economy [1-16]. However, despite positive progress in 
decarbonization, the region faces distinct obstacles due to its 
historical reliance on traditional energy sources, which 
hinders long-term green growth. In 2020, about 85% of the 
country’s electricity was generated from fossil fuels, mainly 
from natural gas as well as sub-bituminous and bituminous 
coal [17, 18]. The rising request for low-cost electrical power 
is driving the expansion of Malaysia’s energy sector [19], 
which is heavily dependent on power plants, which form a 

 

 

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November 2024| Volume 03 | Issue 04 | Pages 25-41 

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mailto:mohammadnurizatrahman@gmail.com
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MN. Rahman /Future Technology                                                                                        November 2024| Volume 03 | Issue 04 | Pages 25-41 

26 

 

considerable part of the power supply. At the same time, the 
Malaysian government has committed to achieving climate 
neutrality by 2050. This puts Peninsular Malaysia, the 
country’s main economic center, at a pivotal point in deciding 
the tactical steps needed for a clean energy transition. To 
meet these challenges, the government introduced the 
National Energy Transition Roadmap (NETR), which sketches 
the country’s plans for managing its energy needs, mitigating 
greenhouse gases (GHG), and advancing energy transition 
efforts. The NETR aims to cut GHGs in the energy sector by 
32% by 2050, compared to 2019 levels, with per capita 
emissions expected to drop to 4.3 metric tons of CO2 
equivalent. These measures set the stage for Malaysia’s 
energy shift, with hydrogen positioned as an essential energy 
carrier for the economy [17]. The country's goals to decrease 
carbon emissions through new technologies have sparked 
discussions regarding the adequacy of its goals for 
implementing electrolysis technologies to foster a domestic 
hydrogen production sector. This has led to widespread 
investigation into sustainable hydrogen and its wide uses in 
industrial processes, sustainable transportation, and 
balancing electricity supply [20, 21].  

Malaysian researchers such as Zakaria et al. [20] and 
Rahman et al. [1] investigated Malaysia's renewable energy 
(RE) potential, focusing on green hydrogen. Their research 
covered a detailed review of the country's energy landscape 
and the practicality of integrating green hydrogen into the 
existing energy infrastructure. Their research explored the 
feasibility of using the country's natural gas pipeline for 
hydrogen transport, examined the possibility of integrating 
hydrogen into the country's gas turbine (GT) power plants, 
and considered key factors like energy demand, population 
data, energy policies, reliance on traditional energy 
resources, CO2 emissions, and the overall adoption of RE in 
Malaysia. The research also explored hydrogen's role as a RE 
source, covering aspects like hydrogen production 
techniques, storage methods, and green hydrogen-based 
energy generation. While these investigations provided 
insights into hydrogen's potential in Malaysia's RE mix, they 
revealed a considerable gap in quantitative data and techno-
economic analysis required to guide investments in green 
hydrogen. 

Benalcazar et al. [22] studied the potential of green 
hydrogen in Poland. Employing a Monte Carlo simulation, 
they investigated the technical and economic elements that 
might affect the success of Poland's sustainable hydrogen 
policy. The investigation economically examined sustainable 
hydrogen production across various steps of technical 
progress and market growth. A significant result of their 
analysis was the prediction of optimal geographic locations 
for large-scale hydrogen production to minimize costs and 
improve efficiency. Their findings indicated that Poland’s 
LCOH for a 20-MW Proton Exchange Membrane (PEM) 
electrolyzer could vary, with projections for 2050 showing a 
range between €1.95 and €2.03 per kg when using solar 
power and €1.23 to €1.50 per kg when using onshore wind 
power. Reference [23] investigated techno-economic aspects 
of three offshore wind power generation systems, each 
featuring a different hydrogen production method. The 
configurations included distributed, centralized, and onshore 
hydrogen production. The researchers applied different 
methods, such as net present value (NPV) assessments, 
sensitivity analyses, and Monte Carlo simulations to 
determine feasibility. Reference [24] developed a Monte Carlo 
model to assess sustainable geothermal-based hydrogen 

production in the Zilan area in Turkey’s Van province, known 
for its rich geothermal and water resources.  

The model was employed to evaluate the installed 
capacity of an Organic Rankine Cycle (ORC) geothermal 
power plant, identifying Lake Van as a desirable area for 
hydrogen production. Based on the model, the region could 
initially produce 18.6 kg of H2/hr, with potential output rising 
to 28 kg by 2050, indicating strong prospects for sustainable 
hydrogen production. The study also estimated that in 2022, 
the cost to produce one kilogram of hydrogen would be €4.91, 
decreasing significantly to €1.21 per kg by 2050, suggesting 
the growing economic feasibility of geothermal-based 
hydrogen production in the Zilan region. Monte Carlo analysis 
is vital in assessing sustainable hydrogen production's 
economic viability and technical factors, offering crucial 
insights. These studies provide comprehensive information 
about cost efficiency and geographical differences related to 
renewable energy sources and technologies.  

Rahman et al. [1, 25] conducted an in-depth assessment 
of Malaysia’s renewable energy potential for green hydrogen. 
Building on this previous work, the present study focuses on 
quantitative data and performs technical and economic 
analysis of a potential hydrogen application in Malaysia. 
Specifically, this study examines green hydrogen co-firing in a 
gas turbine (GT) in Peninsular Malaysia, the country's main 
industrial hub, home to many significant GT plants. Prior 
research indicates the growing use of hydrogen in power 
generation through gas turbines [26-28]. Additionally, major 
original equipment manufacturers (OEMs) are increasingly 
entering the hydrogen GT market, signaling strong potential 
for the hydrogen economy, as gas turbines remain one of the 
most important power generation technologies globally. 

Increasing gas turbine (GT) fuel flexibility to incorporate 
larger amounts of hydrogen is a critical advancement in 
driving the energy transition toward a hydrogen-centric 
future. For instance, blending 10% hydrogen into the fuel mix 
can decrease CO2 emissions by 2.7%, equivalent to reducing 
1.26 million metric tonnes of CO2 for a 600 MW combined 
cycle gas turbine (CCGT) running at 60% efficiency for 6000 
hours annually [1]. However, due to hydrogen’s high 
reactivity, maintaining flame control to ensure the 
combustion system’s durability while achieving required 
emission standards in GTs remains a major challenge [26-28]. 
It is known that co-firing GTs with unconventional fuels 
introduces risks concerning fuel quality, as GTs built and 
calibrated for specific fuel quality ranges tend to perform best 
within those limits, ensuring both reliability and optimal 
operational efficiency [29]. Despite these challenges, the 
EUTurbines industry group made a commitment in January 
2019 to deploy GTs capable of operating entirely on hydrogen 
by 2030 [1], showing the sector’s dedication to 
decarbonization and the potential for zero-carbon GT 
operations. While green hydrogen is widely seen as a 
promising option for reducing carbon emissions, its global 
expansion is slowed by high electrical power prices and 
capital costs related to electrolytic installations [30-32]. 
Although global research focuses on the economic 
perspective of hydrogen production and co-firing in GTs [33], 
there is a significant lack of studies addressing the future 
costs and feasibility of green hydrogen techniques and co-
firing applications, specifically in Peninsular Malaysia. 
Furthermore, no research, to the author’s knowledge, has yet 
examined the financial and technical uncertainties that 
influence the economics of sustainable hydrogen production 
and its co-firing in the region’s GTs. This paper tries to bridge 
that gap by conducting an in-depth analysis of local technical, 



MN. Rahman /Future Technology                                                                                        November 2024| Volume 03 | Issue 04 | Pages 25-41 

27 

 

financial, and policy or regulatory factors associated with 
green hydrogen production and co-firing applications. 
Additionally, a Monte Carlo simulation analysis is introduced 
to assess the technical and economic feasibility of large-scale 
hydrogen production technologies designed to fulfill the 
hydrogen demand for a key GT in Peninsular Malaysia. The 
research focuses on the importance of solar photovoltaic (PV) 
technology as an essential RE source for sustainable hydrogen 
production in Peninsular Malaysia. Benefiting from its 
equatorial location, the country enjoys favorable solar 
conditions, with an average daily solar irradiance between 
4.21 kWh/m² and 5.56 kWh/m² annually. The maximum 
solar energy is available in August and November, peaking at 
6.8 kWh/m², while December experiences the minimum, 
down to 0.61 kWh/m² [34]. These factors position Malaysia 
as a desirable country for sustainable hydrogen production, 
which could be leveraged for hydrogen co-firing in GTs.  

In this analysis, the LCOH is the key metric employed in 
the probabilistic evaluation of large-scale solar-powered 
electrolyzers and their integration into hydrogen co-firing at 
GT power plants. While interest in green hydrogen's role in 
Malaysia’s energy sector is increasing [35], there is a lack of 
forward-looking investigations specifically focusing on 
Peninsular Malaysia. This limitation has shaped discussions 
on green hydrogen production's economic and technological 
prospects and its co-firing applications in the region. To 
address this gap, this research introduces a Monte Carlo-
based model that estimates the LCOH for different green 
hydrogen co-firing scenarios in a major GT power plant in 
Peninsular Malaysia, considering different stages of market 
development and technological advancement for green 
hydrogen production. Additionally, a sensitivity analysis is 
employed to evaluate the most critical risk factors in large-
scale hydrogen production and co-firing projects. The results 
offer valuable perspective on the projected costs of 
sustainable hydrogen co-firing in Peninsular Malaysia’s GTs, 
further supporting the deployment of the regional hydrogen 
economy. 

2. Materials and methods 

This research presents a detailed model for determining 
the LCOH for on-site hydrogen production systems that utilize 
PEM electrolyzers despite the existence of multiple 
electrolyzer technologies. "In-situ" refers to the PEM 
electrolyzer plant's location within the GT power plant itself. 
This setup necessitates increased land use while eliminating 
transportation costs such as long-distance pipelines or trucks 
for green hydrogen delivery.  

This arrangement can be considered an ideal case, and it 
has also been included in the Directive (EU) 2024/1788, 
which proposes that hydrogen production and consumption 
take place in the same location or as close as possible, 
ensuring stable hydrogen quality for end-use and minimizing 
costs, environmental impact, and hydrogen leaks related to 
transportation [36].  

PEM electrolysis was chosen because of its benefits for 
distributed hydrogen production. These include a compact 
design, high efficiency, and flexibility, making it an ideal 
candidate for integration with existing power plants [37, 38]. 
In contrast to traditional studies that often depend on basic 
sensitivity assessment with single-point or anticipated values 
to forecast the LCOH for emerging or ongoing hydrogen 
technologies, this research adopts a probabilistic method to 
evaluate the influence of techno-economic uncertainties on 
the costs of hydrogen co-firing in Peninsular Malaysia's gas 
turbines. The technical and economic model incorporates a 

Monte Carlo assessment to address uncertainty across 
various input factors when calculating LCOH. The proposed 
methodology is illustrated in Figure 1. 

The computer-based Monte Carlo modeling technique is 
based on selecting inputs randomly from random 
distributions to compute the projected value of a fixed model 
or output function [39, 40]. This method is applied when 
practical experiments are too costly or impractical. The Monte 
Carlo modeling process typically involves the following steps 
[22]: 
• Statistical distributions are determined for model 

parameters influenced by uncertainty or risk factors. 
• A set of N random samples is considered from each random 

distribution and employed as inputs in the deterministic 
model. 

• The model's outcomes are evaluated according to 
the corresponding set of inputs. 

• The outcomes are statistically evaluated, and the 
probability density function is estimated. 

Although the Monte Carlo method has been previously 
applied successfully in research to assess risks in energy 
investments and project cost performance across different 
energy systems [41-44], it has not yet been methodically 
utilized to explore the economic feasibility of hydrogen co-
firing in GTs in Peninsular Malaysia. Considering the 
ambiguities in long-term planning for hydrogen 
infrastructure, this paper introduces a static technical and 
economic model that generates potential outcomes 
employing random samples derived from probability density 
functions. These functions are made from anticipated and 
observed data, following standard practices. Additionally, the 
LCOH is a key metric to assess the economic viability of large-
scale hydrogen co-firing projects in a significant GT power 
plant in Peninsular Malaysia. The LCOH ($/kg) is calculated as 
follows: 

𝐿𝐶𝑂𝐻 =  
𝐼𝑜+∑

𝐼𝑡+𝐶𝑡
(1+𝑟)𝑡

𝑇
𝑡=1

∑
𝐻𝑡

(1+𝑟)𝑡
𝑇
𝑡=1

                                                                           (1) 

Where I represents the initial investment ($), T represents the 
project period (years)- 25 years, C stands for the operating 
costs ($), H indicates the hydrogen demand produced (kg), 
and r represents the discount rate (%).  

The discount factor is assumed to be 8%. The same 8% 
rate is used to calculate the Net Present Value (NPV) of all 
costs, hydrogen produced, and energy generated. Using 10% 
for project evaluation is common practice as it represents a 
fair average of the cost of debt and equity. However, a lower 
rate is applied to projects that involve new and evolving 
technology, such as hydrogen technologies and new energy 
projects. Typically, this ranges from 5 to 10%. The initial 
investment I ($) can be calculated using Eq (2).  

𝐼 = 𝐶𝑃𝑒𝑙 + 𝐿𝐴𝑒𝑙 + 𝑃𝑃𝑒𝑙                                                                     (2) 

where 𝐶𝑃𝑒𝑙 is the capital expenditure (CapEx) for the PEM 
electrolyzer ($), 𝐿𝐴𝑒𝑙  is the CapEx for the land acquisition 
investment cost of the electrolyzer ($/kW) and 𝑃𝑃𝑒𝑙 is the GT 
power plant upgrade cost for hydrogen co-firing ($). 𝐶𝑃𝑒𝑙 is 
calculated based on Eq (3). 



MN. Rahman /Future Technology                                                                                        November 2024| Volume 03 | Issue 04 | Pages 25-41 

28 

 

 

 

 

𝐶𝑃𝑒𝑙 = 𝑃𝑒𝑙 × 𝐼𝑒𝑙                                                (3) 

where 𝑃𝑒𝑙 is the electrolyzer’s rated power (kW) and 𝐼𝑒𝑙 
represents the specific investment cost of the electrolyzer 
($/kW). 
𝑃𝑒𝑙 is calculated based on the hydrogen demand (𝐻) of the GT 
under study at varying co-firing ratios with natural gas. Table 
1 displays the range of 𝐻 based on data gathered from the 
power plant under study, indicating their GT's ability to 
accommodate hydrogen percentage co-firing. The hydrogen 
demand for co-firing is used to calculate the 𝑃𝑒𝑙 using Eq (4). 

𝑃𝑒𝑙 =
𝐻×𝐸𝑒𝑙×𝐶𝐹

𝑢𝑒𝑙
            (4) 

where 𝐸𝑒𝑙 is the electrolyzer's power consumption in 
kWh/kg, 𝐶𝐹 is the assumed annual availability of the GT 
under study, and 𝑢𝑒𝑙 represents the electrolyzer utilization 
rate expressed as a fraction of 1. The 𝑢𝑒𝑙 value range is based 
on the previous study's estimated solar capacity factors in 
Peninsular Malaysia [25]. As stated before, it is considered 
that the PEM electrolyzer is operated by solar power plants.   
Eq (5) shows how 𝐿𝐴𝑒𝑙  is calculated. 

𝐿𝐴𝑒𝑙 = 𝐿 × 𝐽            (5) 

 
 
 
 
 
where 𝐿 is the land size for the electrolyzer (m2) and 𝐽 is the 
specific land price in the region where the GT is located 
($/m2). 𝐿 is calculated via Eq (6). 

𝐿 = 𝐻 × 𝐿𝑠             (6) 

where 𝐿𝑠 is the specific land size for green hydrogen 
production (m2/kg). 
𝑃𝑃𝑒𝑙 is calculated using Eq (7). 

𝑃𝑃𝑒𝑙 = 𝑃𝐺𝑇 ×  𝑃𝑢𝑝𝑔  

where 𝑃𝐺𝑇 is the estimated GT power plant price and 𝑃𝑢𝑝𝑔 is 

the cost of upgrading the GT to co-fire hydrogen, expressed as 
a percentage of 𝑃𝐺𝑇 . 
The annual operating costs (OpEx) involve the cost of 
electricity, water, non-fuel variable operation and 
maintenance, and battery replacement. 

𝐶 = (𝜏 × 𝑃𝑒𝑙 × 𝑢𝑒𝑙 × 𝐶𝑒) + (𝛾 × 𝐻 × 𝐶𝑤) + (𝐶𝑃𝑒𝑙 × 𝜗)           (8) 

where τ represents the total number of hours in a year (h), Ce 
denotes the electricity cost ($/kWh), γ indicates the water 
required to produce each kilogram of hydrogen (L/kg), and 
Cw signifies the water price ($/L). Maintenance expenses are 

Figure 1. A summary of the Monte Carlo approach employed in this study 



MN. Rahman /Future Technology                                                                                        November 2024| Volume 03 | Issue 04 | Pages 25-41 

29 

 

considered constant over the system's lifespan [22] and are 
calculated as a fraction (ϑ) of the capital cost of the 
electrolyzer. Additionally, battery replacement costs are 
accounted for at regular intervals throughout the project's 
duration, with these replacement costs included in the 
operational expenditure (OpEx). The Monte Carlo-based 
model outlined in this section was implemented using 
Microsoft Excel. Simulations were conducted on a desktop 
computer equipped with a 4.7 GHz Intel Core i7-12700H 
processor, featuring six cores and 16 GB of RAM. The results 
generated by this computational tool were verified by 
comparing them with outputs from the H2A: Hydrogen 
Analysis Production Model, a well-regarded tool utilized in 
both academic and industrial settings [45, 46]. A sensitivity 
analysis was performed to improve the Monte Carlo approach 
and to pinpoint the uncertainties affecting the LCOH for the 
green hydrogen co-firing initiative. For this analysis, seven 
input parameters were chosen, corresponding to those 
represented in the probability distribution functions: 
hydrogen demand from the GT, electricity price, power 
consumption of the electrolyzer, utilization rate, water price, 
specific investment cost of the electrolyzer, and battery 
replacement interval. As detailed in Table 1, the sensitivity 
analysis involved systematically varying the values of a single 
parameter within the same ranges as the probability 
distributions. An interview with the original equipment 
manufacturer (OEM) of the GT power plant was conducted to 
ascertain the demand for hydrogen in the GT. This interview 
aimed to assess the GT's capability for hydrogen co-firing and 
to identify any necessary upgrades. The estimated percentage 
range for hydrogen co-firing can be utilized to determine the 
required mass flow range of hydrogen for the GT. According 
to the power plant staff, the GT's estimated annual availability 
is 42%. Scenario assessments were conducted for different 
ranges of specific investment costs associated with 
electrolyzers, as presented in Table 2, which reflects the 
anticipated future cost reductions and market maturity for 
Scenarios I through III. These scenarios projected specific 
investment costs for large-scale PEM electrolyzers across 
various years (2023, 2030, and 2050), utilizing data from 
previous research by Rahman et al. [25]. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

3. Case Study 

3.1 Renewable energy in Malaysia 
Malaysia possesses various resources that can be 

employed to produce RE. These resources include [82]: 
• Solar irradiation: Malaysia enjoys abundant sunlight, 

making solar energy highly viable [83]. 
• Biomass: Biomass from agricultural, household, and 

industrial waste can be combusted or gasified to produce 
bioenergy [84]. 

• Small-size hydroelectric power: The nation's rivers offer 
opportunities for small-size hydroelectric power 
generation [85]. 

By 2020, Malaysia had deployed a considerable installed 
capacity in RE, totaling 8,450 MW, as demonstrated in Figure 
2. The most important contributor among the different RE 
resources was large hydropower, with 5,692 MW, followed by 
solar PV and bioenergy, with 1,534 MW and 717 MW, 
respectively. The small-size hydropower capacity was 507 
MW. In 2021, Malaysia substantially revised its RE targets to 
achieve 31% and 40% RE capacity by 2025 and 2035, 
respectively, a significant increase from the prior objective of 
20% by 2025 [17].  
The dedication of governmental bodies, including SEDA 
Malaysia and the Energy Commission (EC), operating under 
the Ministry of Natural Resources, Environment, and Climate 
Change (NRECC), is evident through various RE programs and 
initiatives. Examples of these initiatives include the Feed-in 
Tariff scheme (FiT), the Large Scale Solar auction (LSS), Net 
Energy Metering (NEM), and Self-Consumption (SELCO). 

3.2 Important targets for Malaysia's hydrogen economy 
Figure 3 illustrates that Malaysia initiated its hydrogen 

research and deployment attempts in the early 2000s, 
aligning with global advancements in hydrogen technologies 
[15].  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 1. Distributional assumptions for key parameters 

Operating Parameter Unit Distributional Value Reference 
Hydrogen demand from the GT kg/hr PERT (5,750; 8,662; 11,574) OEM 
Electrolyzer power consumption kWh/kg PERT (25.2; 49.2; 83.0) [47-74] 
Utilization rate  PERT (0.13; 0.20; 0.48) [25] 
Electricity price $/kWh PERT (0.045; 0.084; 0.098) [75-76] 
Water price $/l PERT (0.00016; 0.00032; 0.00070) [77] 
Battery replacement interval year  PERT (7; 10; 15) [25] 

 

Table 2. Scenario analysis assumptions 

Operating 
Parameters 

Unit Scenario I (2023) Scenario II (2030) Scenario III (2050) References 

Electrolyzer 
cost 

$/kW 
PERT (500.0; 1164.8; 
2097.6) 

PERT (315.6; 362.0; 403.4) PERT (138.6; 174.5; 210.5) [22] 

 

Table 3. Input parameters 

Operating Parameters Unit Value References 
Specific land size for hydrogen production m2/ton H2 51.0 Internal reference 
GT power plant price $ 550,000,000 Internal reference 
Upgrade cost % 10 Internal reference 
Lower heating value of hydrogen kWh/kg 33.3 [78] 
Replacement cost % of electrolyzer cost 42.0 [79-81] 
Maintenance cost % of electrolyzer cost 5.0 [78] 
Water requirement L/kg H2 9.0 [78] 

 



MN. Rahman /Future Technology                                                                                        November 2024| Volume 03 | Issue 04 | Pages 25-41 

30 

 

 

 

 

 

Recognizing the potential of renewable energy (RE) 
sources like biomass, biogas, municipal waste, solar, and 
hydro, Malaysia integrated RE as the fifth element of its 
energy-mix strategy in 2001 under the National Energy 
Policy. This strategic initiative aimed to leverage Malaysia's 
rich RE resources, targeting a contribution of 5% and 10% to 
the energy mix by 2005 and 2010, respectively. To facilitate 
this transition, the Small Renewable Energy Programme 
(SREP) was established under the direction of the Special  

 

 

 

 

Committee on Renewable Energy (SCORE), reflecting the 
government's commitment to positioning RE as a key energy 
source [86]. During the 8th Malaysia Plan (2001-2005), the 
government acknowledged the significance of hydrogen fuel 
cells as a priority area for R&D, aligning this focus with its RE 
objectives [15]. From 1997 to 2013, the Ministry of Science, 
Technology, and Innovation (MOSTI) allocated RM 40 million 
for hydrogen fuel cell research.  

 

Figure 2. RE installed capacity as of 2020 

Figure 3. Key milestones toward Malaysia's hydrogen economy 



MN. Rahman /Future Technology                                                                                        November 2024| Volume 03 | Issue 04 | Pages 25-41 

31 

 

In July 2006, the Fuel Cell Institute, later known as the 
Institute of Fuel Cell (IFC-UKM), was established at Universiti 
Kebangsaan Malaysia (UKM) [87]. This institute marked the 
commencement of Malaysia's exploration into fuel cells and 
hydrogen energy, beginning with the construction of the 
nation’s first PEM fuel cell [16]. In 2009, the Institute of 
Hydrogen Economy (IHE) was established at Universiti 
Teknologi Malaysia (UTM) [88]. The Fuel Cell Research Group 
was created in 1996 with an RM 2 million grant, which was 
subsequently augmented by an RM 15 million grant from 
MOSTI's Intensification of Research in Priority Areas (IRPA) 
Programme. As Malaysia progressed, the 9th Malaysia Plan 
prioritized hydrogen development through various policies, 
initiatives, and strategic roadmaps. The National Renewable 
Energy (RE) Policy and Action Plan laid the groundwork for 
the Fuel Cells and Hydrogen Roadmaps (2005-2030), 
focusing on hydrogen production from renewable resources 
and establishing networks to support hydrogen fuel cell 
vehicles [15]. The hydropower-rich state of Sarawak also 
introduced its own hydrogen energy roadmap to utilize its 
hydropower potential [21]. During Phase 2, which covered 
the 10th and 11th Malaysia Plans, legislative and financial 
interventions were implemented to promote commercial-
scale hydrogen projects [15]. In September 2011, the 
Sustainable Energy Development Authority Malaysia (SEDA 
Malaysia) was created to manage the Feed-in Tariff (FiT) 
system under the Renewable Energy Act of 2011 [89]. The FiT 
mechanism encouraged the public and industrial sectors to 
produce electricity from RE sources, such as solar and wind, 
and sell surplus energy to the National Grid [90]. The revised 
target under the RE Act aimed for 985 MW, or 5.5% of the 
energy mix, by 2015. By 2020, Malaysia sought to generate 
11% of its electricity from renewable sources, amounting to 
2,080 MW [15]. In 2010, the Green Technology Financing 
Scheme (GTFS) was launched to support green investments 
by making financing more accessible [91]. As of December 
2017, GTFS had 28 Participating Financial Institutions (PFIs) 
funding 319 projects worth RM 3.638 billion. This initiative 
created 4,909 jobs and helped cut CO2 emissions by 3,784 
million tonnes annually. To further promote green 
technology, the Malaysian Green Technology and Climate 
Change Centre (MGTC) was tasked with managing Green 
Investment Tax Allowances (GITA) [92] and Green Income 
Tax Exemption (GITE) [93] to support the adoption of green 
technology.As Malaysia's hydrogen economy framework 
evolves, industry leaders are increasingly focusing on 
renewable energy commercialization. For instance, Sarawak 
Energy Berhad (SEB) set up Southeast Asia's first integrated 
hydrogen production facility using electrolysis, which 
includes a refueling station, and introduced hydrogen-
powered vehicles as part of a demonstration project [1]. 
Meanwhile, NanoMalaysia Berhad (NMB) is advancing 
hydrogen production on-site and developing hydrogen 
hybrid energy storage systems within the Energy and 
Environment sector. By 2020, solar energy had gained 
significant traction, with 1,162 out of the 1,178 approved 
renewable energy projects in the government's database 
being solar-related, reflecting its affordability [15]. 

3.3 National Energy Transition Roadmap (NETR) 
As of 2020, Malaysia's total primary energy supply 

(TPES) was largely driven by four main sources. Natural gas 
was the largest contributor at 42.4%, followed by crude oil 
and petroleum products at 27.3%, and coal at 26.4%. 
Renewable energy sources, mainly hydropower, solar, and 
biofuels, provided only 3.9% of the total [18]. Consequently, 

the government has set a more ambitious renewable energy 
(RE) target, raising the goal from 40% by 2035 to 70% by 
2050. The Malaysian government recently unveiled the 
National Energy Transition Roadmap (NETR) to achieve the 
70% RE capacity by 2050 [17]. The NETR outlines six key 
levers for the energy transition, with hydrogen being a critical 
focus. This lever aims to enhance hydrogen’s viability and 
competitiveness through regulatory frameworks and 
innovation, alongside forging long-term agreements with 
importing nations. The main hydrogen-related initiatives 
under this plan include: 
• Developing standards and regulations for low-carbon 

hydrogen. 
• Expanding domestic green electrolyzer production 

capacity. 
• Reducing the levelized cost of hydrogen (LCOH) to improve 

the economics of hydrogen hubs. 
• Boosting demand for low-carbon hydrogen by pursuing 

bilateral agreements with key importing countries, 
promoting value chain development, and securing long-
term green hydrogen commitments. 

The NETR's focus on LCOH as a central program aligns with 
Malaysia's research into estimating LCOH for 2023, 2030, and 
2050, supporting the country's net-zero carbon emission 
target. 

3.4 Green hydrogen production from solar photovoltaic 
As the energy sector is the largest contributor to 

greenhouse gas (GHG) emissions in Peninsular Malaysia [66], 
one potential solution for decarbonizing the region's energy 
systems is the implementation of power-to-gas-to-power 
technology, which can support long-term economic 
transformation [94]. This approach highlights two crucial 
areas in the hydrogen industry: the production of green 
hydrogen [95] and its application in power generation 
through hydrogen co-firing [96]. Malaysia's abundant solar 
resources, along with their substantial capacity, underscore 
the nation's significant potential for solar photovoltaic (PV) 
power generation. This favorable environment positions 
Malaysia to leverage its solar energy resources to further 
develop its renewable energy sector and achieve its ambitious 
RE targets. Figure 4 illustrates the potential of Malaysia's RE 
resources in terms of equivalent power generation capacity. 
The country has an impressive total RE potential of 288.9 GW, 
with solar PV making up 269 GW, or 93.1% of the total. Solar 
PV stands as the leading contributor to Malaysia's RE 
capacity, offering the greatest potential for power generation 
among all renewable sources in the country. 
Peninsular Malaysia's proximity to the equator grants it 
abundant solar resources, as shown in Figure 5, making it an 
excellent location for utilizing solar energy in green hydrogen 
production. Solar installations are strategically dispersed 
throughout different regions of the country. This widespread 
adoption of solar power not only supports Malaysia's 
renewable energy (RE) objectives but also enhances its 
potential for sustained green hydrogen production, 
strengthening the nation's commitment to a cleaner and more 
sustainable energy future. Figure 4 outlines the solar 
photovoltaic (PV) potential across three key solar 
technologies: rooftop solar, floating solar, and ground-
mounted solar [15].  
• Ground-mounted solar on unused land: This category 

consists of installations on flat, unzoned land that excludes 
water bodies, forests, agricultural zones, and mountainous 
areas. With an estimated potential of 210 GW, ground-
mounted solar installations on unused land represent 



MN. Rahman /Future Technology                                                                                        November 2024| Volume 03 | Issue 04 | Pages 25-41 

32 

 

Malaysia's largest solar resource, driven by the availability 
of vast suitable land areas. 

• Floating solar PV: Malaysia has an estimated potential of 
16.6 GW for floating solar PV installations. These 
installations are located on water bodies at 17 major 
hydroelectric plants and 62 reservoir dams, covering a 
surface area of about 2,944 km² [15]. 

• Rooftop solar PV: Peninsular Malaysia leads in rooftop 
solar PV potential with 37.4 GW, largely due to its high level 
of urbanization. Sarawak and Sabah, in comparison, have 
rooftop solar PV potentials of 2.6 GW and 2.2 GW, 
respectively. These installations are located on residential, 
commercial, and industrial rooftops, taking advantage of 
existing infrastructure [97]. 

 

 

Figure 4. RE potential in Malaysia 

 

 
Figure 5. Solar irradiance level in Peninsular Malaysia [98] 

Although Malaysia's energy system remains highly 
dependent on natural gas and coal, its renewable energy (RE) 
capacity has grown gradually in recent years. Nevertheless, 
the intermittent and non-dispatchable characteristics of 
renewables, particularly solar PV, which has lower capacity 
factors than thermal power plants, meant that renewable 
electricity generation (excluding hydropower) only reached 
3,285 GWh in 2020, accounting for just 1.92% of the total 
electricity output [18]. Figure 6 shows the progress of 
electricity generation from different technologies in Malaysia 
since 2015. The Malaysian government’s latest Hydrogen 
Economy and Technology Roadmap (HETR) demonstrates 
the country’s commitment to achieving a 31% RE capacity 
share by 2025. To meet this goal, a plan was initiated in 2021 
to develop 1,178 MW of new RE capacity in Peninsular 
Malaysia, with 1,098 MW coming from solar PV installations, 

reflecting a positive outlook for green hydrogen production 
via solar PV in the coming years [15]. For potential future 
hydrogen production incentives, such as tax credits, the 
production process itself is critical in reducing GHG 
emissions. While the combustion of hydrogen in GTs 
produces nearly zero GHG emissions (assuming 100% 
hydrogen firing), the emissions from hydrogen production 
vary greatly depending on the method used. Green hydrogen, 
which is produced using RE sources such as solar PV, has the 
lowest GHG emissions and thus is the most viable option for 
Malaysia's long-term hydrogen economy policies. Solar PV, 
given Malaysia's favorable solar conditions, has significant 
potential to support large-scale green hydrogen production, 
making it a critical enabler for the country's transition to a 
hydrogen economy. To deliver meaningful climate benefits 
and GHG reductions, hydrogen co-firing in GTs must maintain 
a low GHG profile throughout the production process. This 
ensures that the environmental benefits of hydrogen 
combustion are not offset by emissions during production, 
which aligns with broader climate goals and supports 
potential incentives for green hydrogen development. 

 
Figure 6. Electricity generation mix in Malaysia 

3.5 Regulatory framework of hydrogen firing in GTs 
The terms "regulation" and "policy" are frequently used 

synonymously, but they serve distinct functions. A policy is a 
set of guidelines or principles established by an organization 
or government to guide decisions and actions. For example, 
Malaysia's NETR is a key policy guiding the country's energy 
transition efforts, with hydrogen use in the energy sector 
identified as a potential catalyst for these efforts. Policies 
provide a broad framework for decision-making and outline 
the path to achieving specific objectives. They are typically 
aspirational and have no legal ramifications if not followed. In 
contrast, regulations are specific rules or laws enacted by 
governing bodies to ensure that policies or laws are followed. 
Regulations specify how broad policy principles should be 
implemented and are legally binding. Noncompliance with 
regulations may result in penalties or other legal 
consequences. For example, environmental regulations may 
limit factory emissions to protect air quality. At the time of 
writing, Malaysia did not have a regulatory framework in 
place for hydrogen-powered GTs. Thus, examining global 
regulatory frameworks can help outline potential regulatory 
scenarios for hydrogen-powered GTs in Malaysia, as well as 
provide insight into the technology's prospects. 

In the United States, the Environmental Protection 
Agency (EPA) actively regulates GHG emissions from power 
plants, including those that use hydrogen-fired GTs. The 
EPA's regulatory efforts are part of a larger initiative under 
the Clean Air Act (CAA) to reduce the environmental impact 
of fossil fuel combustion and promote cleaner energy sources. 
The New Source Performance Standards (NSPS) for GHG 
emissions from new, modified, and reconstructed fossil fuel-



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33 

 

fired electric generating units (EGUs) are an important 
benchmark. These standards aim to reduce CO2 emissions. 
The updated NSPS for GHG emissions, which was finalized in 
April 2024, sets strict CO2 limits for new gas-fired combustion 
turbines. However, the EPA declined to finalize its proposed 
plan to include low-GHG hydrogen co-firing as the "Best 
System of Emission Reduction" (BSER) for new and 
reconstructed base load and intermediate load turbines, 
citing uncertainties in the evaluation criteria. After reviewing 
public comments and conducting additional analysis, the EPA 
concluded that the uncertainties made it difficult to 
determine whether low-GHG hydrogen co-firing is the best 
system for reducing emissions at this time. Nonetheless, 
under CAA section 111, the EPA establishes performance 
standards without requiring the use of specific technologies, 
which means that sources may continue to co-fire hydrogen 
to meet the performance standards. Despite this, the Inflation 
Reduction Act (IRA) strongly encourages the use of low-GHG 
technologies in the power sector by providing tax credits, loan 
guarantees, and public investment programs [99]. The IRA 
includes provisions to promote Carbon Capture, Utilization, 
and Storage (CCUS) as well as clean hydrogen production, 
which can aid in the integration of coal and natural gas into a 
low-GHG electricity grid.  

The European Union (EU) is implementing hydrogen-
related regulations through key directives aimed at 
encouraging hydrogen production, distribution, and usage. 
One such directive, the Renewable Energy Directive (RED II), 
establishes binding targets for renewable energy and 
encourages the use of renewable hydrogen. RED II specifically 
establishes targets for renewable fuels of non-biological 
origin (RFNBOs), which are produced from renewable energy 
sources such as wind or solar but are not derived from 
biological materials. Hydrogen, for example, is produced 
through electrolysis using renewable electricity. By 2030, 
RFNBOs must account for at least 42% of all hydrogen used in 
industrial applications, whether for final energy consumption 
or non-energy purposes. By 2035, this target will have risen 
to 60%. The term "final energy purposes" refers to hydrogen's 
direct use as a fuel in energy production, such as power 
generation or industrial processes, which supports the future 
of hydrogen-powered GTs. Furthermore, the EU's Hydrogen 
and Decarbonized Gas Market Package seeks to establish a 
competitive, integrated hydrogen market [100]. This package 
includes measures to ensure non-discriminatory access to 
hydrogen infrastructure, cross-border trade, and common 
standards for hydrogen quality and safety. It also addresses 
issues like blending hydrogen with natural gas and building 
dedicated hydrogen pipelines. Although the regulatory 
framework related to hydrogen-fired GTs is still in its early 
stages and is not as stringent or comprehensive as for other 
technologies, the emerging trend emphasizes the importance 
of green/renewable hydrogen for clean energy production. 
This highlights the need for techno-economic studies on 
green hydrogen co-firing in Peninsular Malaysia’s GTs to 
support future energy prospects. 

3.6 Techno-economic evaluation of local green hydrogen 
production and co-firing 
The study aims to analyze three distinct scenarios, each 

focusing on evaluating the economic feasibility of producing 
green hydrogen in Peninsular Malaysia at various stages of 
technological advancement and market acceptance. The 
hydrogen produced in these scenarios is then considered for 
use in co-firing at one of Peninsular Malaysia’s gas turbines 
(GTs). Table 2 outlines the differing electrolyzer costs, 

highlighting anticipated cost reductions and market maturity 
for Scenarios I-III. As green hydrogen production in 
Peninsular Malaysia is still in its nascent phase, and with no 
commercial hydrogen co-firing GTs in operation, the levelized 
cost of hydrogen (LCOH) at both the national and local levels 
is subject to numerous independent variables, each with its 
own uncertainty. To address these uncertainties, the study 
employs a Monte Carlo simulation, using probability 
distributions—specifically beta-PERT distributions—due to 
their ability to be estimated with limited data and their 
inclusion of three key parameters: minimum value (lower 
bound), maximum value (upper bound), and most likely value 
(mode). Table 1 illustrates the types of distributions and 
parameters utilized in this study. Estimates were compiled 
from various public sources, including academic articles, 
government publications, and international organizations, 
alongside interactions with the gas turbine (GT) power plant 
being examined. For instance, information regarding 
electrolyzer technologies was sourced from IRENA, IEA, 
Bloomberg, Deloitte, and others, while data on ground-
mounted solar PV technologies were obtained from multiple 
sources, such as IRENA, NREL, and Bloomberg NEF. Many of 
these data sources span the years 2017 to 2023, ensuring that 
the study reflects a contemporary perspective on the 
economics of green hydrogen production in Peninsular 
Malaysia. Additionally, water costs for hydrogen production 
were estimated using historical datasets, considering that 
each state in Peninsular Malaysia has its own water pricing 
system established by the state government. This thorough 
approach, incorporating probability distributions and 
information from a range of reliable sources, facilitates a 
comprehensive analysis of the economic factors surrounding 
green hydrogen production and co-firing in the region while 
addressing the uncertainties inherent in these early-stage 
endeavors. 

4. Results and discussions 

This section provides an overview of the findings and 
examines the levelized cost of hydrogen (LCOH) for green 
hydrogen co-firing in gas turbines (GT) across different stages 
of electrolyzer technological advancement, as reflected by 
anticipated cost reductions and market readiness in 
Scenarios I to III. Utilizing Monte Carlo Simulation, the model 
produces probability distributions for various LCOH results. 
Additionally, the outcomes of the sensitivity analysis are 
presented, emphasizing the major risk factors associated with 
green hydrogen co-firing initiatives in Peninsular Malaysia. 

4.1 LCOH distributions 
The LCOH formula in Eq (1) includes several input 

parameters that are subject to change and uncertainty. To 
address this uncertainty, the current study uses a Monte Carlo 
simulation approach that incorporates the variability of these 
inputs into the LCOH calculations. As described in the 
Materials and Methods section, this procedure entails 
determining the uncertain variables in the LCOH formula, also 
known as the "transfer equation." The probability 
distributions from Table 1 and Table 2 are then used to 
generate independent random values.  The random value 
generation functions were integrated into Microsoft Excel to 
facilitate simulation. Unlike many studies that adhere to 
traditional replication rules, this study determined the 
number of replications using the methodology proposed by 
Benalcazar et al. [22]. This approach revealed that 300,000 
replications provide an accurate representation of the LCOH 
while preserving computational efficiency. This thorough 



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34 

 

approach ensures that all potential outcomes and 
uncertainties regarding green hydrogen production and co-
firing costs in Peninsular Malaysia are thoroughly 
investigated.  The LCOH distributions for each scenario are 
shown in Figure 7. The y-axes of these distributions have been 
rescaled to a range of 0 to 1 to facilitate comparison, 
highlighting the impact of various parameters on the LCOH 
distributions.  As shown in Figure 7, Scenario I has the widest 
distribution with longer tails than the other two scenarios, 
indicating the greatest level of uncertainty. The LCOH 
distributions narrow gradually from Scenario I to Scenario III, 
indicating a reduction in uncertainty as electrolyzer-specific 
costs fall from 2023 to 2050.  

 
Figure 7. Uncertainty LCOH distributions 

 

In Scenario I, LCOH values cluster around a mode value 
of $7.69 per kg, indicating that this is the most likely value 
based on 2023’s electrolyzer-specific costs. Scenarios II and 
III exhibit LCOH mode values of $5.03 per kg and $4.64 per kg, 
respectively. This represents a reduction in LCOH mode 
values by 35% and 40% from the baseline of Scenario I for 
Scenario II and Scenario III, respectively. The greater shift in 
LCOH mode from Scenario I to Scenario II is primarily due to 
a greater reduction in electrolyzer-specific investment costs, 
emphasizing the rapid development expected by 2030. 
According to the most recent IEA report, the implementation 
of electrolyzer projects in the pipeline could result in an 
installed capacity of 170-365 GW by 2030 [101], driving 
further cost reductions. Table 4 provides additional 
information, such as the distributions' 5th, 50th, and 95th 
percentiles. 

Table 4. 5th, 50th, and 95th percentiles of the LCOH distributions 

LCOH ($/kg) Percentiles 

P5 P50 P95 

Scenario I (2023) 4.98 8.07 12.53 

Scenario II (2030) 3.60 5.39 7.75 
Scenario III (2050) 3.15 4.73 6.89 

 

4.2 Primary factors influencing the LCOH 
The sensitivity analysis results for each scenario in the 

study are illustrated in Figures 8 (a) to 8 (c). Parameters with 
absolute values close to 1 have the greatest impact on the 
calculated LCOH. The horizontal bars are arranged in 
descending order of their influence on LCOH, from most to 
least significant. The relative importance of these parameters 
varies over the years studied. However, one consistent trend 
is that electrolyzer power consumption remains the most 
influential factor across all scenarios. Its influence is 

predicted to persist through the market maturity of 
electrolyzers. Specifically, in Scenarios II and III, representing 
the years 2030 and 2050, the influence of electrolyzer power 
consumption increases to 0.88, compared to 0.72 in Scenario 
I.Electrolyzer power consumption has been the main area of 
research related to green hydrogen production [47-100], and 
this study highlights the reasons why. Given its significant 
impact on the calculated LCOH, it is crucial to enhance 
research and development efforts to reduce electrolyzer 
power consumption. This will be essential for the future of 
widely commercially available green hydrogen in Peninsular 
Malaysia, aiming to lower the LCOH. 

The utilization rate, based on the variability of the 
capacity factor of solar power plants in Malaysia (assumed to 
be the primary power source for electrolyzers), also 
significantly influences the LCOH. In Scenario I, it has an 
absolute value of 0.42, but this sensitivity drops to 0.26 and 
0.14 in Scenarios II and III, respectively. This shift from 
second place behind electrolyzer power consumption in 
Scenario I to third place in Scenarios II and III indicates that 
the utilization rate’s influence will diminish as electrolyzers 
mature in the market up to 2050. 

It is important to note that the range of capacity factor 
for solar power plants in Peninsular Malaysia is assumed to 
remain constant in this study. Future developments in solar 
power plants, which may increase the capacity factor, and the 
integration with battery energy storage systems (BESS) are 
not considered here. These factors could further increase the 
capacity factor and, consequently, the utilization rate. Plus, 
the narrow range of capacity utilization employed in this 
study reflects that solar irradiance in Peninsular Malaysia is 
not highly impacted by future climate changes. The specific 
investment cost of electrolyzers, which varies from Scenario I 
to III, shows a significant drop of LCOH sensitivity from 0.39 
in Scenario I to 0.09 and 0.01 in Scenarios II and III, 
respectively. This reduction moves it from third place in 
Scenario I to last place in Scenario III in terms of influencing 
factors. The decrease in specific investment costs from 2023 
to 2050 is a key reason for this reduction in influence, as 
higher specific investment costs have a greater sensitivity to 
LCOH than lower specific investment costs. Therefore, it is 
important to reduce the specific investment cost of 
electrolyzers until the LCOH becomes less sensitive to this 
factor. The LCOH shows increasing sensitivity to changes in 
electricity prices in 2030 and 2050 (Scenarios II and III). In 
recent years, the correlation between electricity prices and 
LCOH has increased significantly, climbing to second 
place after the electrolyzer power consumption parameter. 
This indicates that LCOH has become increasingly sensitive to 
electricity prices over time. Hydrogen demand from GTs 
shows fluctuating sensitivity towards LCOH, with a very low 
correlation in Scenario I, a slight increase in Scenario II, and a 
drop again in Scenario III. On the other hand, the battery 
replacement interval year and water price have negligible 
sensitivity in all scenarios. This implies that changes in these 
variables have little effect on the economic performance of 
green hydrogen production and co-firing systems in 
Peninsular Malaysia’s GT. Figure 9 illustrates the sensitivity 
dynamics of key parameters affecting the LCOH over the 
scenario years. The three primary factors significantly 
influencing LCOH are electrolyzer power consumption, 
electricity price, and utilization rate. These factors are crucial 
for green hydrogen production, highlighting the need for 
industry and policymakers to focus on these aspects for the 
green hydrogen co-firing concept in Peninsular Malaysia’s 
GTs. 



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35 

 

4.3 Implications for policies 
While electrolyzer power consumption can be managed 

through advances in electrolyzer technology, electricity 
prices in Peninsular Malaysia are mainly determined by the 
government and Tenaga Nasional Berhad (TNB), Malaysia's 
largest power utility company. In future years, LCOH will be 
more sensitive to electricity prices, necessitating a specific 
tariff design to ensure a competitive LCOH as green hydrogen 
usage grows, particularly for potential co-firing in Peninsular 
Malaysia's GTs.  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Despite the possibility of using green hydrogen for GT co-
firing in this study, Malaysia's generation by source is 
expected to continue to consume a significant amount of 
natural gas in the future. In fact, the government's 
rationalized natural gas subsidy plan may result in significant 
increases in future electricity costs for consumers, 
particularly during economic downturns or geopolitical 
tensions, which have historically caused volatility in global 
gas prices. The Kumpulan Wang Industri Elektrik (KWIE) 
fund can help to reduce electricity tariff increases, but its 
limitations and potential depletion must be recognized [102].  

 

 

 
(a) 

 

 
(b) 

 

 
(c) 

 
Figure 8. Key LCOH cost drivers for (a) Scenario I (2023), (b) Scenario II (2030), and (c) Scenario III (2050) 



MN. Rahman /Future Technology                                                                                        November 2024| Volume 03 | Issue 04 | Pages 25-41 

36 

 

 

 
Subsidies could be provided, but they may have an 

impact on the government's fiscal performance. As a result, 
these factors may contribute to future LCOH price 
uncertainty, which is highly dependent on electricity prices. 
The study concludes that new policy instruments will be 
required to support green hydrogen production, particularly 
in Peninsular Malaysia, which faces high levels of uncertainty 
and risk in the coming decade. The effective implementation 
of such policies has the potential to lay a solid foundation for 
the decarbonization of the energy sector while also increasing 
the economic competitiveness of Peninsular Malaysia's GTs, 
which currently rely heavily on fossil fuels. Furthermore, 
these findings fuel the ongoing debate about the importance 
of policy interventions to promote hydrogen technologies and 
infrastructure in Peninsular Malaysia. As the LCOH in 
Peninsular Malaysia becomes more competitive, green 
hydrogen could emerge as a viable alternative to natural gas. 
As a result, policymakers must concentrate their efforts on 
creating strategic blueprints for establishing a hydrogen 
supply chain, considering the strategic location of production 
facilities and the availability of renewable resources. 
Furthermore, policies and strategies for expanding the 
hydrogen supply chain should be inextricably linked to public 
policies that increase RE capacity.  

5. Conclusions 

This study evaluates the economic performance of large-
scale green hydrogen co-firing GT using PEM electrolyzers 
powered by solar energy in Peninsular Malaysia through a 
Monte Carlo approach. It focuses on three key years: 2023, 
2030, and 2050, each representing different stages of market 
maturity for green hydrogen production, as indicated by the 
specific investment cost of electrolyzers. The findings 
highlight the evolving economics of green hydrogen in 
Peninsular Malaysia. In 2023, the LCOH ranged from $3.54 to 
$16.82 per kg, reflecting early-stage challenges and 
uncertainties. Scenario I in 2023 showed the widest 
distribution with longer tails, supporting the high level of  

 

 
uncertainty. By 2030, the outlook will improve significantly, 
with the conceptual co-firing system potentially achieving the 
LCOH of $2.68 to $9.43 per kg. Looking ahead to 2050, the 
study suggests a bright future for green hydrogen, with the 
LCOH potentially dropping to $2.30 to $8.54 per kg, and a 
mode of $4.64 per kg. This research fills a significant 
knowledge gap by illuminating the long-term prospects for 
green hydrogen production and co-firing in Peninsular 
Malaysia’s GTs. While the uncertainty distributions of LCOH 
vary across the years, the study indicates that green hydrogen 
could become a competitive and economically viable fuel for 
Peninsular Malaysia’s GTs by 2050. The sensitivity analysis 
highlights the changing key cost drivers: early-stage 
investments in electrolyzers are crucial in 2023, while 
electricity prices become increasingly important in 
influencing LCOH in 2030 and 2050. This underscores the 
need for additional policy support mechanisms to mitigate 
risks associated with green hydrogen energy investments. 

Acknowledgment 
The author wishes to extend their appreciation to TNB 
Research for their specific GT-related information and their 
insights on the hydrogen demand from GT. 

Ethical issue 
The author is aware of and complies with best practices in 
publication ethics, specifically with regard to authorship 
(avoidance of guest authorship), dual submission, 
manipulation of figures, competing interests, and compliance 
with policies on research ethics. The author adheres to 
publication requirements and states that the submitted work 
is original and has not been published elsewhere. 

Data availability statement 
The datasets analyzed during the current study are available 
and can be given upon reasonable request from the 
corresponding author. 

Conflict of interest 

The author declares no potential conflict of interest. 

Figure 9. Dynamics of the studied key parameter sensitivity to LCOH 



MN. Rahman /Future Technology                                                                                        November 2024| Volume 03 | Issue 04 | Pages 25-41 

37 

 

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