Modelling Future Pathways for Industrial Process Heat Decarbonisation in New Zealand: The Role of Green Hydrogen

Abstract

Green hydrogen is a potential enabler of deep decarbonisation for industrial process heat. We assess its role in Aotearoa New Zealand using a bottom-up, least-cost energy-system model based on the integrated MARKAL-EFOM system (TIMES), which includes hydrogen production electrolysis, storage, and delivery of end-use technologies for process heat, as well as alternative low-carbon options. Drawing on detailed data on industrial energy use by sector and temperature band, we simulate pathways to 2050 under varying assumptions for electrolyser and fuel prices, technology efficiencies, electricity decarbonisation and carbon prices. In most scenarios, the least-cost pathway involves widespread electrification of low- and medium-temperature heat, with green hydrogen playing a targeted role where high-temperature requirements and process constraints limit direct electrification. Sensitivity analysis reveals that hydrogen uptake increases under higher carbon prices, lower electrolyser capital expenditure, and when grid connection or peak capacity constraints are binding. These results suggest that policy should prioritise rapid industrial electrification while focusing hydrogen support on hard-to-electrify, high-temperature processes, such as primary metals and mineral products, alongside enabling infrastructure and standards for hydrogen production, transport, and storage.

1. Introduction

The New Zealand government has committed to achieving net-zero greenhouse gas emissions by 2050 (other than for biogenic methane) under its Climate Change Response Act. To enable this path, a concerted cross-ministerial effort is focusing on decarbonising industrial process heat, supported by funding mechanisms such as the Government’s Investment in Decarbonising Industry Fund (Energy Efficiency and Conservation Authority. GIDI Process Heat Contestable Fund). Regarded as a promising solution, green hydrogen produced by electrolysis using renewable electricity is considered one of the most feasible technologies that could help reduce New Zealand’s greenhouse gas emissions [1].

Globally, hydrogen production remains dominated by fossil fuels, with low-carbon hydrogen—green (produced through electrolysis), blue (utilising carbon capture and storage), or biomass-based—accounting for less than 1% of total output [2]. Most hydrogen is consumed in industrial applications, such as oil refining, ammonia production, and methanol production [3,4]. To reduce emissions, green hydrogen offers a viable alternative to replace fossil-based hydrogen, particularly in energy-intensive industries such as steelmaking and fertiliser production [2,4,5]. Recent reports from the International Energy Agency’s Global Hydrogen Review 2024 and the U.S. Department of Energy’s Industrial Decarbonization Roadmap highlight the accelerating growth of low-emission hydrogen projects and the increasing role of green hydrogen in hard-to-abate sectors [4,5].

In parallel, several countries have positioned hydrogen as a key enabler of their clean energy transitions. The United Kingdom and Australia are exploring the integration of hydrogen into gas networks and heating systems [6,7], while Germany and the United States have scaled up their national strategies to support production, infrastructure, and deployment [8,9,10,11,12]. These initiatives highlight the global momentum behind hydrogen development but also reveal the challenges of scaling up technologies, attracting investment, and ensuring policy coherence to achieve long-term decarbonisation goals [10,11,12].

From a sustainability perspective, the transition to green hydrogen represents not only a technological shift but also a systemic change toward cleaner production, resource efficiency, and long-term resilience. Its adoption aligns with national and global sustainability objectives by addressing emissions reduction, energy security, and innovation in industrial energy use [13,14,15,16].

Across New Zealand, interest in green hydrogen technologies has grown in recent years. Projects such as Hiringa Energy’s hydrogen refuelling network for heavy transport, the Ballance Agri-Nutrients partnership for fertiliser production, and the Southern Green Hydrogen Project in Southland demonstrate both domestic and export potential. However, despite this momentum, the role of hydrogen as a zero-carbon fuel in the industrial sector remains relatively underexplored.

In New Zealand, the industrial sector is the second-largest energy user, surpassed only by the transport sector. It also ranks as the second-largest contributor to energy-related emissions (see Figure 1). Figure 1 summarises sectoral final-energy use and energy-related emissions in 2019, showing that industry is second only to transport on both metrics, which motivates our focus on industrial heat decarbonization in the scenarios that follow.

Notably, process heat, in its various types, accounts for over three-quarters of industrial energy use. The remaining energy use is split between motive power and a combination of electronics and lighting (as depicted in Figure 2). Figure 2 decomposes industrial energy use by end-use category, underscoring why our modelling disaggregates heat by temperature band (low, intermediate, high) and delivery mode (indirect/direct). Process heat dominates the industrial energy balance and, therefore, the decarbonization challenge modelled in Section 4.

This study, therefore, aims to examine, using a clearly defined modelling mechanism, how hydrogen could contribute to the least-cost decarbonisation of industrial process heat within a broader energy-system context. Specifically, the objectives are to (i) identify current industrial heat use patterns, (ii) evaluate hydrogen’s cost-competitiveness relative to other low-carbon options, and (iii) assess future scenarios under varying cost and efficiency assumptions.

To achieve this, we develop a bottom-up, least-cost energy-system model based on the integrated MARKAL-EFOM system (TIMES) to assess opportunities for decarbonising industrial process heat through the use of green hydrogen. The Energy End-Use Database (EEUD) provided by the Energy Efficiency and Conservation Authority (EECA) is used to identify the existing composition of industrial process heat based on fuel type, sector, and other relevant factors. Hydrogen technologies that can provide the same energy services are investigated and assessed against other ‘green’ alternatives in the framework of the TIMES model. Hydrogen uptake is further tested under various price and efficiency scenarios. From an energy system perspective, the decarbonisation of industrial process heat must balance environmental objectives with cost efficiency and energy security. Cost optimisation, therefore, plays a pivotal role in identifying feasible pathways that achieve emissions reductions without compromising industrial competitiveness. In this context, hydrogen is analysed not as an isolated technology but as one component within a broader optimisation framework that compares its economic performance with other low-carbon alternatives such as electrification and biomass. This approach enables us to assess hydrogen’s potential contribution to the least-cost industrial heat supply under various future cost and efficiency conditions. It is important to note that the purpose of this study is not to claim that hydrogen is currently the least-cost option for industrial process heat. Rather, the analysis adopts a scenario-based approach using the TIMES optimisation framework to identify under what future cost and efficiency conditions hydrogen could become part of a least-cost decarbonisation pathway. By incorporating a range of techno-economic assumptions to 2050, the model captures possible trajectories of technology learning, cost decline, and policy support that may influence the competitiveness of hydrogen relative to other low-carbon alternatives.

This study contributes to the literature by evaluating the competitiveness of green hydrogen under a range of techno-economic conditions specific to New Zealand’s industrial landscape. Using a TIMES-based framework, we identify the least-cost pathways for decarbonising process heat to 2050 and explore scenarios under which hydrogen could emerge as a preferred option. The findings offer empirical insights to inform policymakers in supporting industrial decarbonization strategies and advancing sustainability goals.

The paper is organised as follows: the subsequent section breaks down current energy use patterns in New Zealand’s industrial sector. Section 3 examines the options for decarbonising process heat, highlighting specific use cases. Section 4 describes the modelling framework, while the results are presented and discussed in Section 5. Finally, Section 6 wraps up the discussion, drawing conclusions and shedding light on potential policy implications.

2. Current Industry Energy Use

2.1. Energy End-Use Database

The EEUD, developed by the EECA, provides a comprehensive breakdown of New Zealand’s energy use by sector, fuel, and technology (

Table 1. EEUD and Energy Balance (EB) reconciliation.

Comparison by Sector (PJ)			Comparison by Fuel (PJ)
Sector	EB	EEUD	Fuel	EB	EEUD
Mining	6.3	6.0	Biogas	0.1	0.1
Food Processing	50.5	49.8	Coal	23.8	22.1
Textiles	1.2	1.2	Diesel	17.2	17.4
Wood, Pulp, and Paper	14.5	62.6	Electricity	54.5	53.4
Chemicals (including petrol)	37.7	38.1	Fuel oil	1.1	1.1
Non-metallic Minerals	7.4	7.3	Geothermal	4.8	4.8
Basic Metals	26.4	26.5	LPG	3.7	4.1
Equipment Manufacturing	0.7	1.0	Natural gas	67.9	67.9
Building and Construction	9.2	9.2	Petrol	0.1	0.1
Unallocated	62.7	12.9	Wood	43.8	43.8
Total	216.8	214.7	Total	216.8	214.7

). We rely on the 2019 dataset for this analysis, as it precedes the distortions introduced by the 2020 COVID-19 lockdowns, thereby offering a more representative picture of typical industrial energy use. To ensure dataset reliability, we cross-checked EEUD values against the official energy balance tables published by the Ministry of Business, Innovation & Employment (MBIE) in its Energy Balance Tables. The two sources show a high degree of alignment. The primary inconsistency arises in biomass allocation—MBIE’s balance assigns a portion of biomass use to an “unallocated” category, whereas EEUD attributes it explicitly to the wood, pulp, and paper sector. After adjusting the balance data accordingly, the discrepancy disappears, affirming the validity of the EEUD for sectoral energy analysis.

2.2. Industrial Energy Use by Fuel

Figure 3 shows the composition of fuel use for energy in New Zealand’s industrial sector in 2019. Fossil fuels provided slightly over half of the primary energy, while electricity and direct use of renewables provided approximately a quarter each (panel A) (Note that fossil fuels used to produce electricity are not counted here). Panel B provides more detail; natural gas is the largest single fuel source, accounting for around 60% of fossil fuel energy, with coal and diesel supplying the majority of the remaining fossil fuels. Direct use of renewable energy primarily involves the combustion of wood residues (biomass), while geothermal steam accounts for the remainder. The use of solar and biogas is minimal.

2.3. Industrial Energy Use by Type

As depicted in Figure 4, the distribution of industrial energy is segmented by end-use type. The intermediate-temperature process heat, ranging between 100 °C and 300 °C, emerges as the predominant category, followed by high-temperature process heat. In total, over three-quarters of the energy used in the industrial sector, around 165 PJ annually, is used to provide heat

A clear pattern of energy use across sectors is evident in Figure 5. The wood, pulp, and paper manufacturing sector is the largest energy user, primarily relying on intermediate-temperature process heat. High-temperature heat is used in the petrochemical sector, basic metals processing, and non-metallic minerals manufacturing (which includes the manufacture of cement and glass). The remainder of this section provides a detailed breakdown of the composition of these end uses.

2.3.1. Sectoral Breakdown of High Temperature Industrial Process Heat

Industrial processes are classified as high-temperature in the EEUD if they operate above 300 °C.

Table 2. Detailed breakdown of high-temperature process heat.

Sector and Technology	Energy Use (PJ)	Percent of Total
Petroleum and Chemicals	33.75	51.9%
Natural Gas Boiler Systems	7.06	10.8%
Natural Gas Reformer	22.20	34.1%
Natural Gas Furnace/Kiln	3.73	5.7%
Natural Gas Burner (Direct Heat)	0.36	0.5%
Boiler Systems—Other Fossil Fuel	0.26	0.4%
Furnace/Kiln—Other Fossil Fuel	0.15	0.2%
Primary Metal Manufacturing	23.71	36.4%
Electric Furnace	20.93	32.2%
Natural Gas Furnace/Kiln	2.10	3.2%
Natural Gas Industrial Ovens	0.24	0.4%
Furnace/Kiln—Other Fossil Fuel	0.43	0.7%
Non-Metallic Minerals	5.99	9.2%
Coal Furnace/Kiln	4.19	6.4%
Natural Gas Furnace/Kiln	1.62	2.5%
Electric Furnace/Kiln	0.18	0.3%
Other	1.64	2.5%
Natural Gas Furnace/Kiln	1.52	2.3%
Electric Furnace/Kiln	0.12	0.2%
Total	65.08

characterises high-temperature heat by sector, fuel, and technology. Its primary application is concentrated within three sub-sectors, and within those sectors, it is limited to a handful of energy-intensive industries. Given the specialised nature of these industrial processes, which are often set up around a particular fuel source, it becomes challenging to draw overarching conclusions regarding potential fuel-switching opportunities.

Petroleum and Chemicals Sector

The largest single use of high-temperature heat in the petroleum and chemical manufacturing sector is to power natural gas reforming, a process where natural gas is heated to produce syngas (a mixture of hydrogen and carbon monoxide) [16]. Depending on the application, the hydrogen is either separated and used for chemical processes (as in the production of ammonia) or the syngas mixture is used directly (as in methanol production). Given that hydrogen emerges as a valuable byproduct of the reforming process, it is commercially impractical to consider using hydrogen as an initial input fuel. According to the MBIE, in New Zealand, the primary applications of natural gas reforming are in methanol production and ammonia-urea manufacturing.

Methanol production is a significant consumer of New Zealand’s gas supply, accounting for around 45%. Methanex New Zealand has solidified its position through long-term supply contracts. Of this allocation, around 30%, which translates to 13.5% of the total supply, is used for processing heat. The reminder serves as a feedstock during the reforming process (Methanex New Zealand. Submission on Process Heat in New Zealand: Opportunities and Barriers to lowering emissions). Natural gas is integrated into the manufacturing process, and it is unlikely that Methanex would operate in New Zealand without natural gas. Modelling by the Climate Change Commission has assumed the closure of the two existing Motunui methanol trains in 2029 and 2039 (He Pou a Rangi Climate Change Commission. Modelling and data).

Ammonia and urea production is another large user of natural gas reforming. Ballance Agri-Nutrients, the owner of New Zealand’s only ammonia-urea production plant, is planning a green hydrogen plant to supply hydrogen as a feedstock for this process, eventually removing the need for natural gas reforming. More details are provided in Section 3.4.2.

Crude oil refining is the third major energy user in the petrochemicals sector. High temperatures are used to separate crude oil into various end products and to remove impurities. However, Refining New Zealand has confirmed the closure of the Marsden Point refinery beginning in April 2022, switching to an import-only facility, which will dramatically reduce its energy use (Reuters. Refining NZ says on track to convert refinery to import terminal).

Primary Metal Manufacturing Sector

Electricity provides most of the energy for primary metal manufacturing, which is dominated by two operations: the New Zealand Aluminium Smelter facility at Tiwai Point in Southland and the New Zealand Steel Plant at Glenbrook (Ministry of Business, Innovation & Employment. Primary Metal and Metal Product Manufacturing Factsheet). In both cases, electric furnaces heat metal ore to high temperatures as part of the smelting process. Natural gas furnaces are utilised in steel production to heat ladles carrying molten iron and steel, as well as to reheat steel slabs before hot rolling. The steel mill also uses large quantities of coal as a chemical reductant to process iron sand into iron; however, this coal use is classified as industrial process and product use related (i.e., non-energy). The use of hydrogen as a chemical reductant in place of coal is currently being investigated in a New Zealand context (Wellington UniVentures, Advanced Materials: Green Steel).

Non-Metallic Minerals

Within the non-metallic minerals sector, the largest energy use is to produce clinker, a precursor to cement, using coal-fired kilns (Ministry of Business, Innovation & Employment. Non-metallic Mineral Products Factsheet). Golden Bay Cement, standing as New Zealand’s sole integrated cement manufacturer, is introducing alternative fuels such as wood waste and rubber tyres into its production process (ConcreteNZ. NZ Concrete Industry Emission Reduction Briefing). Other notable energy uses in this sector include the production of lime products in high-temperature kilns and glass manufacturing using natural gas and electric furnaces (Ministry of Business, Innovation & Employment. Non-metallic Mineral Products Factsheet).

2.3.2. Intermediate Temperature Process Heat Demand by Industrial Sector and Technology

Intermediate-temperature process heat, defined as temperatures between 100 °C and 300 °C, is the largest end-use category in the industrial sector. The wood, pulp, and paper processing industries are the primary consumers, accounting for over two-thirds of intermediate temperature energy use, with timber drying kilns (which use pressurised hot water to heat air in the kiln) and particle board and fibreboard manufacturing (Ministry of Business, Innovation & Employment. Wood Processing Factsheet). A significant portion of the primary energy for these processes is sourced from renewable fuels, predominantly wood residues, complemented by geothermal heat.

Food manufacturing accounts for nearly 30% of intermediate temperature heat use, with coal and gas being the primary fuels. Boilers are the primary heat providers in this sector, accounting for around 85% of the heat demand, while industrial ovens also play a significant role.

Table 3. Detailed breakdown of intermediate temperature process heat.

Sector and Technology	Energy Use (PJ)	Percent of Total
Wood, Pulp and Paper	51.7	64.5%
Wood Boiler Systems	43.7	54.5%
Geothermal Boiler Systems	4.56	5.7%
Natural Gas Boiler Systems	2.75	3.4%
Coal Boiler Systems	0.46	0.6%
Boiler Systems—Other	0.24	0.3%
LPG Burner	0.001	0.0%
Food Manufacturing	23.0	28.7%
Natural Gas Boiler Systems	11.6	14.4%
Coal Boiler Systems	7.35	9.2%
Natural Gas Industrial Ovens	3.00	3.7%
Boiler Systems—Other	0.67	0.8%
Electric Oven/Heater	0.28	0.4%
Coal Industrial Oven	0.14	0.2%
Other	5.4	6.7%
Boiler Systems—Other	3.75	4.7%
Natural Gas Boiler Systems	0.83	1.0%
Electric Resistance Heater	0.37	0.5%
Natural Gas Furnace/Kiln	0.27	0.3%
Coal Boiler Systems	0.19	0.2%
Total	80.2

provides a detailed breakdown of the fuels and technologies used to provide intermediate-temperature process heat.

2.3.3. Low-Temperature Process Heat

Low-temperature heat combines process heat and water heating. Approximately 90% of low-temperature heat is utilised in food manufacturing, with nearly 95% of this heat being supplied by boilers (see

Table 4. Breakdown of low-temperature industrial heat.

Sector and Technology	Energy Use (PJ)	Percent of Total
Food Manufacturing	17.2	89.7%
Coal Boiler Systems	9.56	49.9%
Natural Gas Boiler Systems	7.16	37.4%
Other	0.47	2.4%
Other Sectors	1.97	10.3%
Gas Boilers	0.62	3.3%
Gas Burners	0.49	2.6%
Other	0.85	4.4%
Total	19.2

). Natural gas is the primary fuel source in the North Island, while coal is more prevalent in the South Island. Examples of typical end uses are the pasteurisation of dairy products and hot water for sterilising and cleaning equipment.

2.3.4. Mobile Motive Power

Mobile motive power refers to the use of energy in powering mobile industrial equipment and is primarily allocated to the mining and construction sectors. Typical use cases include earth-moving equipment and mining trucks. Diesel provides almost all the fuel (>97%) with a small amount of petrol included.

2.3.5. Stationary Motive Power

End-use demand for stationary motive power is spread across sectors and is supplied mainly by electric motors (87% of energy use). Note that pumping is included with this grouping and accounts for one-third of the energy demand. Non-electric uses include the use of diesel-powered stationary engines in the mining and construction sectors, as well as natural gas pump stations in the petrochemical sector.

This end-use category captures all electric industrial processes that have not been assigned to any previous category. This is primarily because the electrified processes currently in place are not being considered for a transition to hydrogen. Beyond lighting, this category also includes other applications such as refrigeration, fan systems, and air compression.

2.4. Electronics and Lighting

To assess the potential for hydrogen to provide clean fuel for process heat, we combine the three end-use categories of process heat and calculate the current use of fossil fuels in these applications. Currently, electrified processes are omitted from our analysis, as are those powered by renewable energy sources. Natural gas reforming is excluded for the reasons discussed in Section 2.3.1. Additionally, we adjust the energy use for the closure of the Marsden Point oil refinery, which is scheduled to close from April 2022 (Radio New Zealand. Refining NZ confirms Marsden Point switch to import-only terminal from April 2022). This effectively sets an upper bound for industrial heat uses, which could be fuelled by green hydrogen, using 2019 as the benchmark year. The results of this analysis are presented in

Table 5. Process heat to be decarbonised.

Temperature and Heat Type	Energy Use (PJ)
High-temperature industrial heat
Boilers	3.8
Direct heat	14.3
Intermediate temperature industrial heat
Boilers	27.6
Direct heat	3.4
Low-temperature industrial heat
Boilers	17.7
Other	0.5
Total	67.4
Other heat uses in industry
Natural gas reformers	22.2
Renewable or electrified heat	71.3
Natural gas allocated to the refinery 1	3.5

¹ Value from Refining New Zealand Annual Report 2019, p. 33 [17]. We assumed natural gas was used to produce high-temperature steam and adjusted the value for high-temperature boiler systems accordingly.

.

This overview of energy use across New Zealand’s industrial sectors provides the empirical foundation for the subsequent modelling analysis. Understanding the current composition of process heat by fuel type and industrial activity is essential for parameterising the TIMES model and identifying where hydrogen substitution is technically feasible and economically meaningful. By establishing the baseline structure of industrial energy demand, this section directly supports the scenario development presented in Section 3, ensuring that the subsequent modelling reflects realistic sectoral conditions and energy pathways.

3. Clean Technologies for Industrial Heat

Building on the sectoral energy patterns outlined in the previous section, this section examines the main options available for decarbonising industrial process heat in New Zealand. Each pathway, ranging from fuel switching and electrification to the use of biomass and green hydrogen, is discussed in terms of its technological maturity, cost, and suitability for different temperature ranges and industrial processes. This discussion summarises the available options and frames the comparative assessment that follows in the modelling analysis. By linking these alternatives to the study’s overarching goal of identifying the least-cost and most sustainable pathways to decarbonisation, this section provides essential context for evaluating hydrogen’s potential role within New Zealand’s broader energy transition.

3.1. Hydrogen-Fuelled Technologies

Hydrogen can be used as a combustion fuel to provide industrial heat similar to natural gas. However, due to its different combustion characteristics, pure hydrogen cannot be directly substituted for natural gas in most existing equipment. Compared to natural gas, hydrogen has a higher combustion temperature, faster flame speed, and lower thermal emissions (i.e., how effectively it transfers heat) [17].

Table 6. Hydrogen heating technologies readiness.

Equipment Type	Technology Readiness	Pilot Completed	Specific Challenges
Boiler/Indirect dryer	Prototype demonstrated in operational environment	Yes	-
Direct dryer/Oven	Validated in lab	Unknown	Flue gas composition
Kiln	Validated in lab	Unknown	Flue gas composition, heat transfer mechanism
Conventional furnace	Validated in relevant environment	Yes	Heat transfer mechanism
Glass furnace	Validated in lab	Unknown	Flue gas composition, heat transfer mechanism, refractory materials

Note: Adapted from [18] Figure 5.

summarises the readiness of the most common heating equipment types. Most technologies are in the early stages of development.

3.1.1. Boilers

Many industrial heat applications utilise boilers to heat water, creating pressurised steam that subsequently delivers heat for the end use. For these applications, hydrogen-fuelled boilers can be used to supply indirect heat in the same manner as existing boilers. In practice, converting or upgrading natural-gas-fired boilers to accommodate hydrogen may be easier than replacing coal or wood-fired boilers with a hydrogen equivalent [17]. Suppliers in the United Kingdom have offered to sell hydrogen-compatible boilers at the same price as natural gas boilers, albeit in a residential rather than industrial setting (The Engineer. Big Four make price promise on domestic hydrogen boilers).

3.1.2. Direct Heat Applications

Direct heat applications typically involve heating a solid material where the heat is applied directly, usually at a high temperature, via a burner, furnace, kiln, or oven. Various hydrogen-fuelled technologies can provide direct heating for various applications in a manner similar to natural gas. A key consideration in direct heat applications is the change in flue gas composition and moisture content between hydrogen and natural gas, as this can come into direct contact with the heated product. Due to the potential impacts on product quality, direct-fired equipment will likely require a greater level of demonstration readiness to achieve user acceptability [19].

3.2. Challenges of Using Hydrogen for Heat

According to [20], several challenges associated with combusting hydrogen for heat have been identified. These include the following:

• The high combustion velocity of hydrogen, when compared to carbon-containing fuels, coupled with its non-luminous flame, complicates optical monitoring.
• The relatively low radiant heat transfer compared to other fuels requires other media (such as clinker dust) to be introduced into the fuel stream. This may require redesigning the current burners.
• Hydrogen causes corrosion and brittleness when it interacts with some metals, requiring new coatings and other protective measures.
• Handling and storing hydrogen on-site present complexities compared with traditional fuels.

While all these challenges are surmountable, addressing them may incur additional costs, potentially diminishing the commercial appeal of hydrogen.

3.3. Other Hydrogen Uses in Industry

Beyond its role as an energy carrier, hydrogen also provides crucial non-energy services in industrial production. It functions as a chemical reducing agent in direct-reduction steelmaking and as a feedstock in the synthesis of ammonia and methanol. These applications differ from combustion-based heat supply because they depend on specific reaction chemistry and material balances. In the current modelling framework, such uses are discussed qualitatively but not endogenously represented, as the NZIES industrial module aggregates energy-service demands rather than individual chemical-process flows. Incorporating these non-energy uses in future work would require defining dedicated process chains with hydrogen as an intermediate commodity and exogenous material-demand drivers. Doing so would allow an integrated assessment of hydrogen’s dual role in energy and materials decarbonisation while maintaining internal system consistency.

3.3.1. Steel Manufacturing

In New Zealand, steel production relies on coal as a chemical-reducing agent to process iron sand, resulting in significant CO₂ emissions [18]. Research into the use of hydrogen gas as a reducing agent has been performed at a pilot scale. However, due to uncertainties surrounding costs and the requisite significant alterations to operational processes in a commercial setting, this technology is too nascent to be modelled [21].

New Zealand’s only ammonia-urea production plant is located in Kapuni, Taranaki [22]. Natural gas is reformed to produce hydrogen, which is then combined with nitrogen to make ammonia using the Haber process [23]. The plant owner, Ballance Agri-Nutrients, has initiated a project to produce green hydrogen via electrolysis, powered by a dedicated wind farm, aiming to replace natural gas in the production process [24]. Surplus hydrogen would be provided to the transport sector to support heavy vehicles.

3.3.2. Flexible Green Hydrogen for Export

The Southern Green Hydrogen Project is investigating the business case for developing an export market for green hydrogen, either as liquified hydrogen or ammonia. This would involve a large-scale hydrogen plant in Southland that could reduce production (and consequently, electricity demand) during dry years, providing flexibility to the electricity market. The primary export markets targeted are Japan and South Korea [24].

3.4. Alternative Fuels and Technologies

3.4.1. Electrification

Depending on the specific application, there are many alternative electric process heat technologies. The electrification of low- and intermediate-heat applications is possible with existing, mature technologies, such as compression heat pumps, electric boilers, infrared heaters, and microwave heaters [25]. A range of direct electrification options can substitute for fossil fuel heat across common industrial end uses. For steam driven processes, electricity immersion steam boilers and electrode steam boilers are suitable. Electric process heaters serve indirect heating applications. Electric kilns are appropriate for ceramics firing. Low temperature direct heating can be provided by electric infra-red heaters, while high temperature direct heating can be provided by electric plasma gas heaters. Microwave heaters are suited to drying solid materials. Open loop and closed loop heat pumps can supply low pressure steam and other low temperature indirect heat. Electric furnaces are applicable to glass melting and metal melting [26]. Direct electrification of industrial processes often allows for greater efficiency. However, there are cost concerns around peak pricing as well as distribution and network charges [27].

3.4.2. Biomass

Biomass represents another alternative renewable fuel source. It is already widely used in the wood, pulp and paper sector, given the large volume of woody waste generated during normal operations [28]. A 2017 report by Scion estimated the potential residual biomass fuel to be between 17 and 32 PJ annually, depending on the assumptions made regarding recoverability [29]. Recent research from EECA and DETA Consulting found that for industrial process heat users in the South Island aiming to decarbonise their operations, biomass stands out as the preferred choice [30].

3.4.3. Biofuels

Biogas and biomethane, derived from organic matter, offer an additional alternative that is compatible with existing gas equipment. However, factors such as cost, availability and competition for organic feedstocks may limit uptake. An industry report has estimated 7.2 PJ of biogas available by 2040, equivalent to around 3% of New Zealand’s total gas usage in 2019 [22].

3.4.4. Geothermal Heat

For around 60 years, New Zealand has utilised its high-temperature geothermal resources, located mainly in the central North Island, for direct industrial use and electricity generation [31]. Industry uses are largely in the wood processing and dairy sectors, for example, to provide heat for drying. The New Zealand Geothermal Association has set an ambitious goal to increase annual direct primary geothermal energy use by 7.5 PJ from its 2017 levels, aiming to reach this by 2030 [32].

4. TIMES Modelling

4.1. TIMES Modelling Framework

To assess the potential for hydrogen technologies to supply process heat in New Zealand, we developed an integrated energy systems assessment model for New Zealand based on the TIMES. TIMES modelling framework is a type of technology-rich energy system model developed by the International Energy Agency (IEA) as part of the Energy Technology Systems Analysis Program (ETSAP). TIMES provides a detailed characterisation of the energy resources and transformation technologies in an economy and is widely used for analysing climate and energy scenarios and policies [33]. The energy system encompasses primary energy sources, secondary energy forms, and energy service demands, while transformation technologies encompass power generation technologies and fuel refining. In brief, given a set of energy sources, technologies, demands and constraints, the model minimises the total discounted cost of the energy system over the entire modelling period using linear optimisation. Comprehensive details pertaining to the TIMES model are available in the accompanying documentation [34,35,36].

4.1.1. Process Overview, Data, and Replication Notes

This study applies the TIMES framework (NZIES instance) to explore least-cost configurations for decarbonising industrial process heat in Aotearoa New Zealand. The model minimises total discounted system cost subject to technology, resource, demand, and policy constraints, and is used here as a scenario tool to examine “if–then” relationships rather than to predict present-day optima (see Figure 6 and Section 4.2). The time horizon spans 2019–2050, calibrated to 2019, and is solved in five-year steps with 96 intra-year time slices (24 h × 4 seasons) to capture diurnal and seasonal patterns, as well as peak-capacity requirements.

The input data combines the EECA Energy End-Use Database (2019) for industrial heat by sector, fuel, end-use, and temperature band, reconciled with the MBIE Energy Balance tables, with public information on existing generation capacity and future build options. The industrial representation distinguishes between low-, intermediate-, and high-temperature heat, further separating indirect (boilers) and direct heat (burners, furnaces, kilns). For each end-use, existing and new technology options are parameterised with capital expenditure (CAPEX), operating expenditure (OPEX), efficiency, availability, and lifetime; numerical values are documented in Appendix A

Table A1. Existing heat technologies in NZIES.

End-Use Technology	Energy Use 2019 (PJ)
Direct high-temperature process heat
Natural gas furnace	9.6
Coal furnace/kiln	4.2
Electric furnace	0.2
Fuel oil furnace	0.6
Indirect high-temperature process heat
Natural gas boiler	3.6
Fuel oil boiler	0.3
Direct intermediate process heat
Natural gas oven	3.3
Other (coal and electric)	0.8
Indirect intermediate process heat
Biomass boiler	43.7
Geothermal boiler	4.7
Natural gas boiler	15.2
LPG boiler	4.1
Coal boiler	8.0
Other fuels—boiler	0.5
Direct low-temperature process heat
Natural gas burner	0.4
Electric heater	0.05
Indirect low-temperature process heat
Coal boiler	6.2
Natural gas boiler	2.6
Fuel oil boiler	0.01
Low-temperature water heating
Coal boiler	3.4
Natural gas boiler	5.5
Other fuels—boiler	0.2

Note: excludes natural gas reforming, refinery energy use, and electricity use for aluminium smelting.

and

Table A2. New heat technologies in NZIES.

Technology	Capital Cost ($/kW)	Fixed Opex ($/kW/y)	Variable Opex ($/GJ)	Lifetime
Direct high-temperature process heat
Biogas furnace	371	26.72	0.58	20
Hydrogen furnace/kiln	429	16	0.58	20
Electric furnace	193	23	0.38	10
Indirect high-temperature process heat
Natural gas boiler	250	9.00	0.58	20
Electrode boiler	308	11.08	0.48	15
Biomass boiler	990	35.00	1.15	20
Hydrogen boiler	366	13.18	0.58	20
Direct intermediate process heat
Hydrogen heater/burner	429	16	0.58	20
Hydrogen oven	429	32.04	0.58	20
Electric heater	231	8.31	0.38	15
Indirect intermediate process heat
Natural gas boiler	250	9.00	0.58	20
Electrode boiler	308	11.08	0.48	15
Biomass boiler	990	35.00	1.15	20
Hydrogen boiler	366	13.18	0.58	20
Direct low-temperature process heat
Electric heater	231	8.31	0.38	15
Electric heat pump	577	20.77	0.77	15
Hydrogen heater	429	16	0.58	20
Indirect low-temperature process heat
Natural gas boiler	250	9.00	0.58	20
Electrode boiler	308	11.08	0.48	15
Biomass boiler	990	35.00	1.15	20
Hydrogen boiler	366	13.18	0.58	20
Low-temperature water heating
Natural gas boiler	250	9.00	0.58	20
Electrode boiler	308	11.08	0.48	15
Biomass boiler	990	35.00	1.15	20
Hydrogen boiler	366	13.18	0.58	20

Note: Source data by technology family: hydrogen end-use base values from Element Energy (2019), Hy4Heat WP6: Conversion of Industrial Heating Equipment to Hydrogen; electrolyser CAPEX and efficiency trajectories from BEIS (2021), Hydrogen Council (2024), and IRENA (2024); other mature non-hydrogen technologies (e.g., electrode, biomass, and electric boilers) assume constant-real-term costs based on EECA and MBIE datasets for New Zealand industry. All values are expressed in 2020 NZD and linked to the scenario trajectories in Table A3 and Table A4.

. Hydrogen is produced by electrolysis with explicit cost and efficiency trajectories; storage and transport are not modelled as separate assets but are captured in a delivered-cost representation at the end-use site.

Common parameters and assumptions align with recent national analyses: a 5% discount rate, a carbon-price path rising from NZ$30/t in 2019 to NZ$180/t in 2035 and NZ$250/t in 2050, closure of the Marsden Point refinery from 2022, and retirement of the Tiwai aluminium smelter by the end-of 2024. Inter-island electricity transfers are constrained by the High Voltage Direct Current (HVDC) link, while intra-island transmission is approximated via average expansion costs rather than modelled as explicit bottlenecks. Other sectoral fuel-demand paths follow externally published projections to ensure consistency of the system context.

Scenario design varies three hydrogen-related parameter blocks—electrolyser capital expenditure (Capex), electrolyser efficiency, and hydrogen end-use technology costs—each along two trajectories (“steady progress” and “rapid development”). The 2 × 2 × 2 combinations yield eight internally consistent scenarios (

Table A5. Scenario numbers and combinations.

	Electrolyser Cost	Electrolyser Efficiency	Demand Technology Cost
1	Steady progress	Steady progress	Steady progress
2	Steady progress	Steady progress	Rapid development
3	Steady progress	Rapid development	Steady progress
4	Steady progress	Rapid development	Rapid development
5	Rapid development	Steady progress	Steady progress
6	Rapid development	Steady progress	Rapid development
7	Rapid development	Rapid development	Steady progress
8	Rapid development	Rapid development	Rapid development

), with time profiles reported in

Table A3. Steady progress scenario assumptions.

	2025	2035	2050
PEM electrolyser
Capital cost ($/kW)	1404	998	882
Fixed opex ($/kW/y)	66.8	63.2	61.6
Efficiency	72%	80%	82%
Demand technologies
Hydrogen boiler
Capital cost ($/kW)	366	340	304
Fixed opex ($/kW/y)	13.2	12.2	10.9
Hydrogen burner/kiln
Capital cost ($/kW)	429	398	356
Fixed opex ($/kW/y)	16.0	14.3	12.8
Hydrogen oven
Capital cost ($/kW)	429	398	356
Fixed opex ($/kW/y)	32.0	28.6	25.6

and

Table A4. Rapid development scenario assumptions.

	2025	2035	2050
PEM electrolyser
Capital cost ($/kW)	716.4	343	298.5
Fixed OPEX ($/kW/y)	33.4	31.6	30.8
Efficiency	80%	85%	88%
Demand technologies
Hydrogen boiler	348	293	286
Capital cost ($/kW)	12.5	10.5	10.3
Fixed OPEX ($/kW/y)
Hydrogen burner/kiln	408	343	335
Capital cost ($/kW)	14.7	12.3	12.0
Fixed OPEX ($/kW/y)
Hydrogen oven	408	343	335
Capital cost ($/kW)	29.4	24.7	24.1
Fixed OPEX ($/kW/y)	716.4	343	298.5

. For each scenario, the model endogenously selects technology portfolios and capacity additions that meet energy-service demands at the lowest cost, subject to all constraints.

Model outputs include the evolution of industrial heat by fuel and temperature band, adoption of hydrogen and electrification technologies, capacity additions/activity for key supply and end-use technologies, and system-level costs and emissions (Section 5; Figure 7 and Figure 8;

Table A6. NZIES modelling results—direct high temperature process heat energy use (PJ).

	2020	2025	2030	2035	2040	2045	2050
Scenarios 1–5, 7 (no hydrogen)
Coal furnace/kiln	4.06	3.21	2.37	1.52	0.68	0.00	0.00
Electric furnace	0.84	3.55	6.45	9.34	12.24	14.55	14.55
Natural gas furnace/kiln	9.27	7.34	5.41	3.48	1.55	0.00	0.00
Fuel oil furnace	0.38	0.44	0.33	0.21	0.09	0.00	0.00
Scenario 6
Coal furnace/kiln	4.06	3.21	2.37	1.52	0.68	0.00	0.00
Electric furnace	0.84	3.55	6.45	9.34	5.76	7.96	7.86
Hydrogen furnace	0.00	0.00	0.00	0.00	6.48	6.59	6.69
Natural gas furnace/kiln	9.27	7.34	5.41	3.48	1.55	0.00	0.00
Fuel oil furnace	0.38	0.44	0.33	0.21	0.09	0.00	0.00
Scenario 8
Coal furnace/kiln	4.06	3.21	2.37	1.52	0.68	0.00	0.00
Electric furnace	0.84	3.55	6.45	9.34	5.66	0.00	0.00
Hydrogen furnace	0.00	0.00	0.00	0.00	6.58	14.55	14.55
Natural gas furnace/kiln	9.27	7.34	5.41	3.48	1.55	0.00	0.00
Fuel oil furnace	0.38	0.44	0.33	0.21	0.09	0.00	0.00

Note: This excludes heat use for aluminium smelting, oil refining, and natural gas reforming. Scenario numbers are presented in Table A5 on the previous page.

and

Table A7. NZIES modelling results—other process heat energy use, all scenarios (PJ).

	2020	2025	2030	2035	2040	2045	2050
High-temperature process heat—indirect
Electrode boiler	0.00	0.00	0.00	0.96	2.07	3.04	3.82
Natural gas boiler	3.71	3.82	3.70	2.80	1.75	0.78	0.00
Fuel oil boiler	0.11	0.00	0.12	0.05	0.00	0.00	0.00
Intermediate process heat—direct
Electric heater/oven	0.15	0.99	1.85	2.71	3.53	4.06	4.06
Natural gas oven	3.15	2.51	1.85	1.19	0.53	0.00	0.00
Other heating	0.76	0.56	0.36	0.16	0.00	0.00	0.00
Intermediate process heat—indirect
Coal boiler	7.68	5.66	3.64	1.62	0.00	0.00	0.00
Electrode boiler	0.00	0.00	1.34	10.25	19.66	30.24	39.85
Geothermal boiler	4.66	4.46	4.27	4.07	3.88	3.68	3.48
LPG boiler	3.77	2.88	1.85	0.82	0.00	0.00	0.00
Natural gas boiler	16.18	21.13	24.88	21.05	16.12	7.58	0.00
Biomass boiler	43.80	41.96	40.12	38.28	36.44	34.60	32.76
Low-temperature process heat—direct
Electric heater	0.06	0.15	0.23	0.32	0.40	0.47	0.47
Natural gas burner	0.41	0.33	0.24	0.15	0.07	0.00	0.00
Low-temperature process heat—indirect
Coal boiler	4.83	4.36	2.80	1.25	0.00	0.00	0.00
Electrode boiler	0.00	0.00	0.43	2.65	5.61	7.02	8.82
Natural gas boiler	3.99	4.46	5.59	4.92	3.21	1.80	0.00
Fuel oil boiler	0.00	0.00	0.00	0.00	0.00	0.00	0.00
Low-temperature water heating
Coal boiler	3.06	2.42	1.55	0.69	0.00	0.00	0.00
Electrode boiler	0.00	0.00	0.31	2.68	4.91	7.03	9.12
Natural gas boiler	5.63	6.42	7.13	5.75	4.21	2.09	0.00
Boiler—other fuels	0.44	0.28	0.13	0.00	0.00	0.00	0.00

). Replication is facilitated by the complete tabulation of inputs and scenario values in Appendix A, together with the process summary provided here. Key limitations to bear in mind are the delivered-cost abstraction for hydrogen storage/transport, the simplified treatment of intra-island grid constraints, and the exclusion of major non-energy hydrogen uses (e.g., reductant/feedstock), which are noted for future extensions of NZIES.

4.1.2. Basic Principles and Mathematical Formulation of TIMES (NZIES)

TIME is a linear, bottom-up, partial-equilibrium optimisation framework that finds the least-cost configuration of an energy system over a long horizon, subject to technical, resource, demand, and policy constraints. In our NZIES instance, the horizon spans 2019–2050 in 5-year steps with 96 intra-year time slices (24 h × 4 seasons). Two geographical nodes (North and South Islands) are linked by an HVDC transfer capacity; within-island transmission is approximated via average expansion costs. Demands for industrial heat services (by temperature band and mode of delivery) and other sectoral fuel demands are exogenous; technologies transform commodities to meet these demands. Costs include investments, fixed and variable O&M, fuels and imports, and emissions costs under an explicit carbon-price path; a salvage term credits the residual value of capacity at the horizon.

Sets and indices

$p\in \mathcal{P}$ technologies/processes;

$c\in \mathcal{C}$ commodities (energy carriers and emissions);

$r\in \mathcal{R}=\left\{\mathrm{NI},\mathrm{SI}\right\}$ regions;

$t\in \mathcal{T}$ periods (5-year);

$s\in \mathcal{S}$ intra-year time slices (${\sum }_s{w}_s=1$, with weights $w_s$);

$\mathcal{G}\subset \mathcal{P}$ electricity-generating processes; $\mathcal{E}\subset \mathcal{C}$ emission commodities.

Main variables

$K_{p,r,t}$ available capacity; $A_{p,r,t,s}$ activity level; $I_{p,r,t}$ new capacity;

$M_{c,r,t,s}^{\mathrm{imp}}$, $M_{c,r,t,s}^{\exp }$ imports/exports;

$F_{c,r\to r^{\prime },t,s}$ inter-regional flow (used for electricity across the HVDC).

Key parameters

$I{C}_{p,t}$ investment cost; $FO{M}_{p,t}$ fixed O&M; $VO{M}_{p,t}$ variable O&M;

${\alpha }_{p,c}^{\mathrm{in}}$, ${\alpha }_{p,c}^{\mathrm{out}}$ input/output coefficients per unit activity;

${\varphi }_{p,t,s}$ availability (capacity-to-activity) factor; $L_p$ economic lifetime;

$P_{c,t}^{\mathrm{fuel}}$ commodity price; $E{F}_c$ emission factor; $C{P}_t$ carbon price;

$D_{c,r,t,s}$ exogenous final demand (incl. energy-service demands);

$Y_t$ years represented by period $t$; $d_t$ discount factor to base year;

$\overline{HVDC}$ rating of the inter-island link; ${\rho }_p(t,\tau )$ survival of vintage $\tau$ in period $t$.

Objective function

Minimise the present value of the total system cost:

$$\begin{array}{cccc}& \mathrm{m}\mathrm{i}\mathrm{n}{\displaystyle \sum _{t\in \mathcal{T}}}{d}_t\{{\displaystyle \sum _{p,r}}[I{C}_{p,t}{I}_{p,r,t}+Y_{t}FO{M}_{p,t}{K}_{p,r,t}]+{\displaystyle \sum _{p,r,s}}{Y}_t{w}_{s}VO{M}_{p,t}{A}_{p,r,t,s}+{\displaystyle \sum _{c,r,s}}{Y}_t{w}_s{P}_{c,t}^{\mathrm{fuel}}{M}_{c,r,t,s}^{\mathrm{imp}}+{\displaystyle \sum _{c\in \mathcal{E},p,r,s}}{Y}_t{w}_{s}C{P}_{t}E{F}_c{\alpha }_{p,c}^{\mathrm{in}}{A}_{p,r,t,s}\}-\mathrm{S}\mathrm{a}\mathrm{l}\mathrm{v}\mathrm{a}\mathrm{g}\mathrm{e}& & \end{array}$$

(1)

The salvage credit for capacity built in $\tau$ that still has residual life in the terminal period $T$ is

$$\mathrm{Salvage}=\sum _{p,r}\sum _{\tau \le T}{d}_{T}I{C}_{p,T}{I}_{p,r,\tau }{\displaystyle \frac{\mathrm{m}\mathrm{a}\mathrm{x}(0,L_p-(T-\tau \left)\right)}{L_p}}$$

(2)

Core constraints

(i) Energy/commodity balance (each $c,r,t,s$)

$$\sum _p{\alpha }_{p,c}^{\mathrm{out}}{A}_{p,r,t,s}+M_{c,r,t,s}^{\mathrm{imp}}+\sum _{r^{\prime }\ne r}{F}_{c,r^{\prime }\to r,t,s}=D_{c,r,t,s}+\sum _p{\alpha }_{p,c}^{\mathrm{in}}{A}_{p,r,t,s}+M_{c,r,t,s}^{\exp }+\sum _{r^{\prime }\ne r}{F}_{c,r\to r^{\prime },t,s}$$

(3)

(ii) Activity–capacity linkage (each $p,r,t,s$)

$$A_{p,r,t,s}\le {\varphi }_{p,t,s}{K}_{p,r,t}$$

(4)

(iii) Capacity accumulation with vintaging (each $p,r,t$)

$$K_{p,r,t}=K_{p,r}^{\left(0\right)}{\rho }_p(t,t_0)+\sum _{\tau \le t}{I}_{p,r,\tau }{\rho }_p(t,\tau )$$

(5)

(iv) Electricity adequacy and reserve (optional, each $r,t$)

$$\sum _{p\in \mathcal{G}}{DERAAE}_p{K}_{p,r,t}\ge (1+{\mathrm{RM}}_t){PeakLoad}_{r,t}$$

(6)

(v) HVDC inter-island transfer limits (each $t,s$)

$$-\overline{HVDC}\le F_{\mathrm{elec},\mathrm{NI}\to \mathrm{SI},t,s}\le \overline{HVDC}$$

(7)

(vi) Resource/technology bounds and policy constraints

Availability of domestic resources, maximum build rates, minimum/maximum activity shares, and exogenous closures (e.g., Marsden Point refinery from 2022; Tiwai aluminium smelter by the end of 2024) are implemented as linear bounds on $I_{p,r,t}$ and $A_{p,r,t,s}$. Emissions costs enter through $C{P}_t$ in (1); caps can alternatively be imposed by linear constraints on total emissions if required. Cross-sector fuel demand paths are derived from external projections to maintain system consistency. This formulation is the standard TIMES structure adapted to our NZIES data and scenarios. All numerical inputs for industrial end-uses and technology parameters are presented in Appendix A Table A1 and Table A2, while scenario-dependent cost and efficiency trajectories are reported in Table A3, Table A4 and Table A5, along with disaggregated model outputs in Table A6 and Table A7.

4.1.3. Time-Slicing and Demand Distribution

We represent each model year by 96 time slices constructed as 24 hourly segments for a typical day in each of four seasons. Let τ index seasons (summer, autumn, winter, spring) with n_τ days, and h index hours 1…24. Define the combined slice σ ≡ (τ,h) and the slice set S. The duration weight of slice σ is

$$w_{\sigma }={\displaystyle \frac{n_{\tau }}{365}}\cdot {\displaystyle \frac{1}{24}},\sum _{\sigma \in S}{w}_{\sigma }=1$$

(8)

For electricity, we derive shape factors from the public half-hourly system load. Let $d_{\tau ,h}$ be the typical-day hourly demand (MW) for season τ. Define a season-normalised hourly shape and re-normalise across the year so that energy is preserved:

$${\varphi }_{\tau ,h}={\displaystyle \frac{d_{\tau ,h}}{\frac{1}{24}\sum _{h^{\prime }}{d}_{\tau ,h^{\prime }}}},{\tilde{\varphi }}_{\sigma }={\displaystyle \frac{{\varphi }_{\tau ,h}}{\sum _{{\sigma }^{\prime }\in S}{w}_{{\sigma }^{\prime }}{\varphi }_{{\sigma }^{\prime }}}},\sum _{\sigma \in S}{w}_{\sigma }{\tilde{\varphi }}_{\sigma }=1$$

(9)

The slice demand used in the energy-balance constraints is then

$$D_{r,t,\sigma }^{\mathrm{el}}=D_{r,t}^{\mathrm{el}}{\tilde{\varphi }}_{\sigma }$$

(10)

For industrial process-heat, we model demands as quasi-baseload with a flat profile, i.e., ${\tilde{\varphi }}_{\sigma }^{\mathrm{ph}}=1$. Where sectoral data indicate seasonality, we may apply seasonal multipliers $m_{\tau }$ satisfying ${\sum }_{\sigma }{w}_{\sigma }{m}_{\tau \left(\sigma \right)}=1$.

The resulting 96-element vectors (${\tilde{\varphi }}_{\sigma }$ for electricity and any $m_{\tau }$ for process-heat) are available from the corresponding author on reasonable request to enable exact replication without printing long tables.

4.2. The New Zealand Integrated Energy System

Building on an existing work programme, we have expanded the New Zealand Integrated Energy System model (NZIES), an instance of the TIMES model developed at the University of Auckland’s Energy Centre over recent years (NZIES development was started by Dr Kiti Suomalainen during her tenure as a Research Fellow in the Energy Centre). The TIMES model applied in this study is designed to explore least-cost system configurations under a set of assumed future conditions rather than to predict the present-day optimal solution. Each scenario represents an internally consistent techno-economic future that allows examination of ‘if–then’ relationships, specifically, if hydrogen technologies achieve significant cost reductions or efficiency gains, then how might this alter industrial fuel choices? This approach ensures that the model’s outcomes reflect long-term strategic insights rather than near-term cost competitiveness. Existing energy resources and conversion technologies are based on public data released annually by MBIE (Ministry of Business, Innovation & Employment. Energy Statistics and Modelling). This includes existing reserves of fossil fuels and installed capacities for electricity generation plants. Primary energy sources include oil, natural gas, coal, and renewable resources (such as hydroelectric power, solar irradiation, wind energy, geothermal resources, and biomass). A refinery technology model simulates the production of refined petroleum products, such as gasoline, diesel, and aviation fuel, which can also be directly imported.

The electricity sector transforms primary energy sources into electricity. The major existing generation technologies include hydro (5.4 GW), thermal (2.4 GW), geothermal (0.96 GW), wind (0.69 GW), and solar (0.12 GW). The capacity of new electricity generation is constrained by technical, economic, and regulatory feasibility, as presented in MBIE’s future generation stack report (Ministry of Business, Innovation & Employment. New Zealand generation stack updates). This anticipates a modest increase in hydro and geothermal capacity, leaving the model to select from thermal, wind, and solar expansion. Figure 6 provides a schematic overview of NZIES.

The model operates with a time horizon spanning from 2019 to 2050, using 2019 as the calibration reference year. From 2020, results are calculated for an average year within five-year intervals up to 2050. Each year is modelled in 96 time-slices representing 24 h of an average day in each of four seasons: summer, autumn, winter, and spring. These time slices enable the model to capture daily and seasonal patterns of energy use, thereby allowing for more accurate prediction of peak capacity requirements.

Installed capacities in 2019 for hydro, geothermal, wind, solar and thermal plants are calibrated to the MBIE statistics used to initialise NZIES. From 2020 onward, capacity additions are chosen endogenously to minimise total discounted system cost while meeting energy balances in every time slice. Expansion is bounded by MBIE’s future-generation stack (technology-specific build limits and resource potentials), together with availability factors and lifetimes, as outlined in Table A2. We do not impose exogenous capacity trajectories by technology; the annual installed capacity mix is therefore a model outcome under these published constraints.

Electricity Network Constraints: Representation and Comparison With/Without Bottlenecks

Electricity network characteristics influence least-cost industrial heat pathways by shaping both adequacy at peaks and spatial power transfers. In NZIES, these effects are captured through three simplified, but transparent elements designed for system-level scenario analysis.

First, inter-island transfers between the North and South Islands are represented by an explicit HVDC link whose flow is limited to its historical rating in each intra-year time slice. Second, intra-island transmission is not modelled as a full alternating-current network; instead, its economic effect is approximated by an average transmission-expansion-cost term embedded in new-generation investment decisions. This ensures that the model internalises part of the cost of delivering additional electricity to end-uses. Third, temporal adequacy is enforced through a 96-slice chronology (24 h × 4 seasons), which requires generation and transfer capacity to meet demand in both seasonal and daily peak slices. Together, these three mechanisms approximate how network limitations influence system operation while keeping NZIES computationally tractable for long-run scenario analysis.

To test the sensitivity of results to these approximations, we compare two internally consistent cases:

(1)

Constrained-Grid (default)—the HVDC transfer limit remains binding, the intra-island expansion-cost term is active, and the 96-slice adequacy structure is applied.

(2)

No-Bottleneck (variant)—the HVDC transfer constraint is relaxed (non-binding across the horizon), the intra-island expansion-cost adder is set to zero, while the 96-slice adequacy requirement is retained so that temporal balancing remains identical.

This comparison isolates the influence of transmission bottlenecks without altering any other model assumptions, such as fuel prices, technology costs, or carbon price trajectories. Removing grid bottlenecks accelerates the adoption of electric technologies for low- and intermediate-temperature process heat, particularly electrode boilers and other electric heaters, as peak-slice adequacy can be achieved with greater flexibility and lower implicit delivery costs. However, the qualitative pattern of hydrogen adoption remains unchanged: hydrogen is not selected for low- or intermediate-temperature heat and appears only in high-temperature direct-heat applications under rapid-learning scenarios. Hence, the presence or absence of simplified network bottlenecks affects the timing and mix of electrification options but not the direction of technology choice.

While NZIES does not include a spatially explicit alternating-current network or distribution-level feeder constraints, this comparative analysis demonstrates that the paper’s central conclusions are robust to the treatment of network capacity. Future model extensions could add more granular spatial nodes or stochastic representations of connection limits to explore site-specific impacts in greater detail

4.3. Industrial Sector End-Uses and Technologies

4.3.1. Ammonia and Urea Production

Building on the analysis presented in Section 2, we develop a set of end-use scenarios and technologies that describe New Zealand’s industrial sector. Three specific use cases are defined separately to allow the demand path to be independently specified: aluminium smelting, natural gas reforming, and energy use at the oil refinery. The aluminium smelter uses electricity only and is assumed to close at the end of 2024, in line with current announcements (E. Harding. Tiwai aluminium smelter to stay open until end of 2024). Natural gas reforming is also specified separately as a significant energy use case that is unsuitable for hydrogen fuel switching. Lastly, New Zealand’s oil refinery, which is modelled to use natural gas and electricity as fuel sources, is assumed to close in 2022.

To characterise industrial heat, we specify high-, intermediate-, and low-temperature end uses for indirect heat (supplied by boilers) and direct heat (supplied by furnaces, burners, and kilns). The remaining industrial end uses—mobile motive power, stationary motive power, and lighting and electrical—are specified using generic technologies. These technologies utilise inputs based on the current fuel ratio calculated from the EEUD.

Within each industrial heat end use, we designate the technologies available to provide the energy service (including the different fuels). Using the largest sector as an example, indirect intermediate temperature process heat is provided by boilers, which may be fuelled by biomass, geothermal, natural gas, LPG, coal, or other fuels. ‘Other fuels’ has a tiny share and captures the residual fuels in the ratio calculated from the EEUD (for example, fuel oil and diesel). Full details of technologies available to provide each type of industrial heat is provided in Table A1 in the Appendix A.

4.3.2. Industrial Heat End-Uses and Fuel Switching

As technologies approach the end of their economic lifespan, the model will invest in new technologies to continue meeting the demands of end-use. To explore the potential for hydrogen use, we incorporate new technologies into the model, including those that utilise hydrogen, which can be selected to supply energy services up to 2050. Again, taking intermediate temperature heat as an example, possible new technologies include hydrogen boilers, electrode boilers, biomass boilers, and natural gas boilers (available on the North Island only). Technologies are characterised by their capital cost, fixed and variable operating costs, efficiency (at converting energy into heat), availability factor, and economic lifetime. It is possible to specify these parameters at different time periods to allow for technological improvements. The model will select the most cost-effective technology to meet energy demand, considering not only the immediate cost but also the total system cost over all time periods and end uses. Details of new technologies by end use are included in Table A2 in the Appendix A.

4.4. Hydrogen Supply and System Integration

4.4.1. Green Hydrogen Production Modelling

We specify a technology for hydrogen production via electrolysis, including the same parameters as for end-use technologies, such as capital and operational costs, efficiency, and so forth. For the sake of simplicity, we only specify production technology rather than modelling hydrogen storage and transport separately. This would be a useful addition to future work. The hydrogen technology thus represents all costs associated with delivery to the end-use location.

In this version of NZIES, hydrogen storage, compression, and off-site transport are not modelled as independent assets. Instead, their costs are captured in a delivered-cost representation at the end-use site, reflecting the total expense of producing and supplying hydrogen to industrial consumers. This simplification allows the model to focus on least-cost energy-system outcomes while maintaining computational tractability. To make this abstraction more transparent, the following subsection introduces two typical supply pathways and a levelized-cost-of-hydrogen (LCOH) sensitivity analysis, illustrating how storage, transport, and utilisation choices affect hydrogen’s delivered cost without altering the overall NZIES structure.

Beyond the representation of hydrogen supply and delivery costs, a parallel simplification concerns the scope of its end-use. In this study, hydrogen is represented solely as a combustion fuel for supplying process heat, allowing for a consistent comparison with electrification and biomass across various temperature bands. Major non-energy uses of hydrogen—such as its role as a chemical feedstock or reducing agent in steelmaking and the synthesis of ammonia or methanol—are excluded from the quantitative analysis because these applications follow dedicated industrial process chains rather than generic heat-demand pathways. Their exclusion avoids double-counting energy and material flows but does not affect the main comparative outcomes. Including such uses in a future NZIES release would likely increase hydrogen demand and improve cost competitiveness through economies of scale and shared logistics infrastructure.

4.4.2. Hydrogen Supply Pathways, Storage Options, and LCOH Sensitivity

Two practical hydrogen-supply archetypes are considered to capture the range of industrial configurations likely to be found in New Zealand. The first grid-connected, behind-the-metre (BTM) electrolysis system draws electricity from the grid and supplies hydrogen directly to adjacent industrial processes. Compressed-gas buffer storage provides short-term balancing over hours or days. This configuration enables relatively high electrolyser utilisation; in our sensitivity analysis, a capacity factor (CF) of 0.9 is adopted. The second archetype, co-located renewables + buffer, couples electrolysers directly to on-site wind or solar generation with compressed-gas buffer storage (and, where appropriate, limited battery smoothing). Its utilisation rate is lower because of renewable intermittency; we adopt CF = 0.5.

For both archetypes, hydrogen delivery and buffer storage costs are expressed as an additive logistics term (ΔLCOH = 0–1 NZD kg⁻¹), covering options such as on-site compressed-gas storage or short-distance delivery by tube-trailer or small pipeline. These values are consistent with the cost ranges reported in recent techno-economic assessments, ensuring comparability with international studies.

The Levelized Cost of Hydrogen (LCOH, in NZD kg⁻¹) is calculated using the following formulation:

$$LCOH={\displaystyle \frac{I.CRF+O_{fix}}{H_{annual}}}+{\displaystyle \frac{P_{e\times }0.03333}{\eta }}$$

(11)

where $I$ is electrolyser capital cost (NZD kW⁻¹), $CRF$ is the capital-recovery factor (discount rate = 5%, lifetime = 20 years), $O_{fix}$ is fixed O&M (NZD kW⁻¹ y⁻¹), $P_e$ is the electricity price (NZD MWh⁻¹), $\eta$ is efficiency, and $H_{annual}$ represents annual hydrogen output (kg kW⁻¹ y⁻¹) derived from the capacity factor and energy content of hydrogen (33.33 kWh kg⁻¹ LHV). Parameter values follow the “steady progress” and “rapid development” paths in Table A3 and Table A4.

Under the rapid-development trajectory (CAPEX = 716 → 343 → 299 NZD kW⁻¹; η = 0.80 → 0.85 → 0.88 from 2025 to 2050), the resulting LCOH falls from approximately 3.37–6.53 NZD kg⁻¹ in 2025 to 2.71–5.29 NZD kg⁻¹ by 2050, depending on electricity price (50–100 NZD MWh⁻¹) and capacity factor (0.9–0.5). Under the steady-progress path (CAPEX = 1404 → 998 → 882 NZD kW⁻¹; η = 0.72 → 0.80 → 0.82), LCOH declines more modestly, reaching 2.71–4.75 NZD kg⁻¹ in 2050 at CF = 0.9 and 3.26–5.29 NZD kg⁻¹ at CF = 0.5. Adding the ΔLCOH logistics component yields a delivered-at-use cost range of ≈2–6 NZD kg⁻¹ by 2050.

These values are consistent with international projections and align with the scenario outcomes in Section 5, where hydrogen becomes cost-competitive only in the rapid-development cases (Scenarios 6 and 8) and primarily for high-temperature direct-heat applications. Electrification remains the least-cost solution for low- and intermediate-temperature heat.

At the plant level, hydrogen implementation requires attention to safety and spatial constraints, including hazardous-area zoning, ventilation design, and separation distances for electrolysers and compressed-gas storage. Hydrogen embrittlement may necessitate material upgrades in pipelines and fittings, while retrofit costs for burners and furnaces include adjustments to nozzles and controls to accommodate different flame characteristics. These elements can be reflected in the model through CAPEX adders to hydrogen end-use technologies or within the ΔLCOH logistics term, offering a transparent way to represent such factors in future NZIES developments.

4.5. Non-Industrial Demand Sectors and Modelling

4.5.1. Sectoral Modelling Overview

End-use demands in the other sectors of the economy—residential, commercial, transport, and agriculture, forestry, and fishing—are modelled by fuel demand rather than specific end-use. Energy demand forecasts by fuel up to 2050 for these sectors are taken from the Climate Change Commission’s ‘Demonstration path’ scenario (He Pou a Rangi Climate Change Commission. Modelling and data). Current energy use by fuel for each sector is taken from MBIE’s 2019 Energy Balance Tables.

Using the NZIES model, we have designed a series of scenarios to investigate the impact of different costs and efficiencies of hydrogen production and its end-use technologies on the uptake of hydrogen as a fuel. Throughout these scenarios, we employ a set of common modelling assumptions to present a realistic picture of New Zealand’s energy sector’s evolution over the forthcoming decades.

4.5.2. Scenario and Modelling Assumptions

The core assumptions across all scenarios are listed below. Many of these assumptions align with the modelling work undertaken by the Climate Change Commission (CCC). Additional assumptions are based on current public statements, such as the announced closure of the Marsden Point oil refinery, scheduled for April 2022.

Assumptions:

• The oil refinery operated by Refining New Zealand ceases from 2022.
• The New Zealand Aluminium Smelter at Tiwai Point closes by the end of 2024 (We are aware of the ongoing back-and-forth debates about the Tiwai point closure (see: https://www.stuff.co.nz/business/130537641/tiwai-point-aluminium-smelter-set-to-stay-open-long-term-says-broker (accessed on 25 May 2025).
• The discount rate of 5% is applied, aligning with the current recommendation of the Treasury (New Zealand Treasury. Discount Rates).
• Imported fuel prices are set in line with the assumptions of the CCC.
• The CO₂ emissions price is projected to increase from $30/tonne in 2019 to $180/tonne in 2035, reaching $250/tonne in 2050, consistent with CCC’s assumptions (We do not assume a complete fall to net zero emissions as the model does not contain zero-carbon alternatives for all end uses (for example to replace diesel in mining and construction equipment)).
• Hydrogen demand technologies are to be available from 2025.

Green hydrogen production technologies are developing rapidly. As more capacity is installed, a significant ‘learning by doing’ phase occurs. There is considerable uncertainty about how quickly technology will develop and the expected cost paths, resulting in a wide range of projected costs [36]. For example, in February 2021, the Hydrogen Council revised its forecast for the capital cost of electrolysers. The updated projection expects to fall to around USD 200–250/kW (NZD 295–365/kW) at the system level by 2030 (Hydrogen Council. Hydrogen Insights: A perspective on hydrogen investment, market development and cost competitiveness), making a 30–50% larger fall than the Council’s 2020 forecast.

To explore this uncertainty, we have developed two scenarios for hydrogen production costs, production efficiency, and demand technology costs: the ‘steady progress’ and the ‘rapid development’ scenarios (We had initially planned to include high-cost or ‘slow development’ scenarios. However, as initial results showed no hydrogen uptake under the ‘steady progress’ scenario there was little to be gained by including scenarios even less favourable to hydrogen use). The steady progress scenarios envision cost reductions and efficiency improvements as capacity is scaled up, and hydrogen technology becomes more widely adopted. They are largely based on projections from August 2021 by the United Kingdom’s Department for Business, Energy and Industrial Strategy (Hydrogen Council. Hydrogen Insights: A perspective on hydrogen investment, market development and cost competitiveness). The rapid development scenario is grounded in a more optimistic projection for cost reductions in electrolyser and demand technologies, as well as improvements in electrolyser efficiency. Combining the two scenarios for the three parameter sets, we have derived eight different scenario combinations. These combinations facilitate an exploration of the determinants influencing hydrogen adoption, as estimated through the NZIES model. Full details of each scenario are provided in Table A3, Table A4, Table A5, Table A6 and Table A7 in the Appendix A.

Embedded sensitivity. Although we do not present separate one-factor tornado charts, the eight internally consistent scenarios (2 electrolyser CAPEX paths × 2 electrolyser efficiency paths × 2 hydrogen end-use cost paths) already operate as a structured sensitivity design over the learning-driven uncertainties that matter most for hydrogen competitiveness. The carbon-price path (NZ$30→180→250 t⁻¹ CO₂ by 2050) follows the national trajectory used by the Climate Change Commission, providing a policy-anchored baseline against which the technology-learning envelope is assessed. Temporal adequacy and transfer limits are represented through 96 intra-year time slices and the HVDC inter-island constraint, allowing grid flexibility and supply–demand co-variation to influence least-cost portfolios endogenously. References to Table A3, Table A4, Table A5, Table A6 and Table A7 and

Table 7. Hydrogen use in different NZIES estimations.

Electrolyser Cost	Electrolyser Efficiency	Demand Technology Cost	Result
Steady progress	Steady progress	Steady progress	No hydrogen use
Steady progress	Steady progress	Rapid development	No hydrogen use
Steady progress	Rapid development	Steady progress	No hydrogen use
Steady progress	Rapid development	Rapid development	No hydrogen use
Rapid development	Steady progress	Steady progress	No hydrogen use
Rapid development	Steady progress	Rapid development	Hydrogen for direct high-temperature heat
Rapid development	Rapid development	Steady progress	No hydrogen use
Rapid development	Rapid development	Rapid development	Hydrogen for direct high-temperature heat

enable readers to trace the full parameter ranges and outcomes.

4.5.3. Robustness and Embedded Sensitivity

To make the sensitivity logic explicit, we summarise comparative-statics implied by the cost-minimisation structure and the scenario envelope:

Electrolyser learning curves (CAPEX/efficiency; hydrogen end-use costs). Hydrogen adoption exhibits a switching-threshold: uptake appears only when electrolyser CAPEX follows the rapid-learning path and hydrogen end-use equipment approaches cost parity—Scenarios 6 and 8—supplying high-temperature direct heat by 2050; otherwise uptake is zero and electrification dominates (Scenarios 1–5, 7) (See Table A3, Table A4 and Table A5, Table 7, Figure 7 and Figure 8).

Carbon price (policy-anchored path). Higher carbon prices increase the shadow cost of fossil fuels system-wide, bringing forward the phase-out of coal and gas. Given electricity decarbonisation in the build stack and the relative efficiency advantage of direct electrification at low/intermediate temperatures, the directional effect is to reinforce electrification; hydrogen’s comparative case remains concentrated in high-temperature uses when learning lowers its delivered cost (Assumptions in Section 4.5.1; outcomes in Table 7).

Grid constraints (temporal and transfer). The 96-slice chronology captures peak/seasonal adequacy; the HVDC limit constrains inter-island balancing. In this representation, tighter effective constraints primarily reshape the timing and mix of electrification options (e.g., electrode boilers vs. other electric heat sources) rather than facilitating hydrogen uptake at low/intermediate temperatures. Hydrogen remains a potential option for high-temperature processes, particularly under rapid learning (See Section 4.1.1, Section 4.1.2, Section 4.1.3 and Section 4.2; Table A6 and Table A7).

Parameter evolution follows four rules. (1) Bookended hydrogen trajectories. Electrolyser CAPEX/efficiency and hydrogen end-use costs follow the “steady progress” and “rapid development” paths in Table A3 and Table A4 (eight combinations listed in Table A5). (2) Mature non-hydrogen end-uses. Costs are held constant in real terms unless published learning evidence is available; efficiencies and lifetimes are constant. (3) Exogenous policy/closure inputs. Announced changes (e.g., refinery and smelter closures; carbon-price path) are imposed consistently across scenarios as in Section 4.5.1. (4) Calibration and consistency checks. We calibrate 2019 activity to the MBIE energy balance and verify internal consistency with Table 7 and Figure 7 and Figure 8. These rules document trends transparently and avoid subjective tuning.

5. Results and Discussion

Table 7 presents the main results of the model estimations. Of the eight scenarios estimated, six showed no hydrogen uptake for providing industrial process heat. Given that all other assumptions, parameters and alternative technologies remained constant in the estimation, these six scenarios gave identical results. The LCOH sensitivity presented above confirms that hydrogen becomes cost-competitive only under rapid technological progress and favourable electricity prices, explaining why uptake appears exclusively in the high-temperature direct-heat scenarios, whereas direct electrification remains the least-cost pathway for low- and intermediate-temperature applications. Figure 7 shows the fuel sources for industrial process heat in the six scenarios where hydrogen is not adopted. In these cases, the main driver of decarbonisation is electrification, leading to the complete phase-out of coal by 2040, followed by natural gas by 2050. This outcome reflects a highly plausible near-term pathway for New Zealand, as electrification technologies for low- and medium-temperature heat are commercially available and align with existing decarbonization programmes led by the Energy Efficiency and Conservation Authority (EECA).

The two scenarios that result in the use of hydrogen technologies for providing industrial heat are (1) the rapid development for all the electrolyser costs, efficiencies, and the cost of end-use technologies (scenario 8); and (2) the ‘rapid development’ in capital costs for electrolysers and hydrogen demand technologies, with steady progress on electrolyser efficiency improvements (scenario 6). In scenario 8, with the most favourable assumptions for hydrogen technologies, hydrogen is projected to supply 12.4% of energy for industrial heat by 2050, and 5.7% in scenario 6 (see Table A6). In both cases, hydrogen is used to provide high-temperature process heat via a hydrogen burner or furnace, beginning from 2040 as the relative cost of hydrogen technology falls. However, for lower-temperature applications, hydrogen is not a cost-effective solution. Figure 8 presents the fuel breakdown of industrial heat in these scenarios. Across the eight combinations, this pattern behaves like a threshold sensitivity: hydrogen appears only when rapid electrolyser CAPEX reductions (≤NZD 343 kW⁻¹ by 2035 and ≤NZD 299 kW⁻¹ by 2050) coincide with faster cost declines in hydrogen end-use equipment (Scenarios 6 and 8); otherwise, electrification fully dominates process-heat decarbonisation by 2050. While the profiles are similar, a higher electrolyser efficiency in the latter part of the period (2045–2050) results in higher hydrogen take-up. Nevertheless, these hydrogen-adoption scenarios should be viewed as exploratory rather than predictive. The feasibility of achieving rapid cost reductions and efficiency gains depends on the global supply chain’s maturity, domestic renewable electricity expansion, and supportive policy frameworks. Without strong incentives or infrastructure investment, such rapid technological progress may be difficult to realise within the given timeframe.

The results highlight two distinct decarbonisation pathways. In the first, electrification dominates as the least-cost and most immediately deployable option, relying on technologies already demonstrated in New Zealand’s food-processing and manufacturing sectors. In the second, hydrogen plays a complementary but delayed role, entering primarily in hard-to-electrify, high-temperature industries such as non-metallic minerals, steel, and chemicals. The feasibility of this pathway hinges on parallel progress in renewable generation, hydrogen distribution networks, and storage solutions.

It is worth noting that even in the scenarios with hydrogen use, there is a significant increase in the electrification of industrial heat. This result aligns with findings from other international studies. For instance, [37] observed that in Europe, up to 78% of industrial heat could be electrified using existing technologies, rising to 99% when considering technologies under development. In contrast, hydrogen technologies are generally much less developed. Similarly, a 2018 report by the think tank Beyond Zero Emissions advocated for electrifying industrial heat in Australia, highlighting that agreements for the long-term supply of renewable electricity are already in place (M. Lord. Electrifying Industry. Beyond Zero Emissions, Melbourne, 2018). This international evidence reinforces that industrial electrification is a realistic and cost-efficient first step, whereas hydrogen is more likely to occupy niche applications until capital costs decline and supply chain maturity improves.

Compared to direct electrification, hydrogen technologies face energy inefficiencies at each stage of production and consumption. Depending on the production, storage, transport, and end-use technologies, the ‘round-trip’ efficiency has been estimated to range from 18 to 62 percent of the initial electricity input. This efficiency gap challenges the competitiveness of green hydrogen against electrification, especially in scenarios where direct electrification is feasible [38,39]. These conversion losses imply that large-scale hydrogen adoption would require substantial additional renewable capacity and grid upgrades, raising questions about system-level feasibility under New Zealand’s resource and spatial constraints. Across the eight combinations in Table A5, hydrogen appears only when electrolyser CAPEX follows the rapid trajectory (≤NZD 343/kW by 2035; ≤NZD 299/kW by 2050) and hydrogen end-use technologies reach cost parity by ~2030 (the “rapid development” end-use trajectory in A4). Under these conditions, hydrogen supplies 5.7% (Scenario 6) to 12.4% (Scenario 8) of industrial heat in 2050, exclusively in high-temperature direct-heat uses (Table 7; Figure 8). With all other assumptions held constant, any intermediate parameter values that lie between the “steady progress” and “rapid development” bookends in A3–A4 would yield outcomes bounded by this envelope—i.e., either no uptake (as in Scenarios 1–5, 7) or ≤12.4% uptake limited to high-temperature applications. This threshold (or “switching-value”) behaviour is expected in least-cost linear optimisation and explains why adding several intermediate scenarios would not change the qualitative policy message that widespread electrification dominates, with targeted hydrogen only when costs cross parity for high-temperature heat. See Table A3, Table A4, Table A6 and Table A7 for the associated parameter values and fuel breakdowns.

Although NZIES co-optimises all energy carriers, it adds little new biomass for process heat by 2050—biomass-boiler output falls from 43.8 PJ in 2020 to 32.8 PJ in 2050 across all scenarios (Table A7). This contrasts with current practice and survey evidence that many heat users plan coal-to-biomass switching [30].

To facilitate interpretation of the integrated energy-system outcomes, Section 5.1 highlights biomass separately, as it represents both the largest existing renewable fuel for process heat and a key policy focus for coal-to-biomass switching in New Zealand.

5.1. Biomass Within the Integrated Energy System

Biomass occupies a distinctive position in New Zealand’s integrated energy system. Empirically, it already supplies a major share of process heat, especially in the wood, pulp, and paper industries, and many firms plan near-term coal-to-biomass conversions according to recent EECA/DETA Consulting surveys. However, in the NZIES simulations, biomass use declines from 43.8 PJ in 2020 to 32.8 PJ in 2050 across scenarios (Table A7). Understanding this apparent contradiction is essential for interpreting the optimisation outcomes and for designing effective decarbonisation policies. Interestingly, the NZIES estimations show minimal adoption of biomass as a low-carbon heat technology. This result contrasts with a recent survey conducted by EECA and DETA Consulting, which revealed that many heat users intend to decarbonise their operations by switching from coal to biomass (Energy Efficiency and Conservation Authority. Decarbonising Industrial Process Heat Webinar—Presentation slides). There are several possible explanations for this difference. An important assumption in TIMES models is that of perfect knowledge and foresight, which entails taking a system-wide view over all time horizons. Biomass technologies, while offering lower fuel costs, tend to have higher capital and fixed costs. This means that even if an individual firm is inclined to switch to biomass, it might overlook the demand from other enterprises and sectors within the economy. In NZIES, the capital cost is spread over the technology’s economic lifetime, typically 15 years. It is worth noting that firms in New Zealand tend to continue using old equipment beyond its expected lifespan, which can mitigate the impact of the initial capital outlay. Another possibility is that biomass boilers are now available and operate similarly to coal boilers, so firms may be more familiar with the technology. Moreover, limited domestic biomass supply and competing land-use priorities further constrain large-scale deployment, reducing the realism of high-biomass scenarios in the New Zealand context.

In the same survey, firms expressed a current reluctance towards electrification. They cited concerns over higher distribution costs and greater uncertainty about electricity prices, especially at peak times. Another significant concern is the potential for electricity outages, which can pose challenges for starting or stopping processes. The forward-looking TIMES model accounts for this by building additional generation capacity. However, real-world firms may have a different view on future capacity or be more risk averse. This divergence underscores the importance of complementing model-based results with behavioural and institutional insights when assessing the feasibility of industrial transitions.

5.2. Other Sectors in the Economy

In this analysis, the energy composition and demand of the other economic sectors are assumed to remain constant. A significant increase in the electrification of transportation is assumed (which is considered in future generation capacity projections), as well as increased electrification and biofuel adoption in the agricultural, commercial, and residential sectors. One area not modelled in detail is large-scale energy storage, such as addressing inter-seasonal or dry-year risks to hydro generation. As hydrogen’s role expands, these cross-sectoral interactions will become increasingly relevant, particularly for balancing seasonal demand and integrating variable renewable generation. The government-funded NZ Battery Project is exploring options to resolve New Zealand’s dry-year challenges and promote the decarbonisation of the broader energy system, including the Lake Onslow pumped hydro scheme (Ministry of Business, Innovation & Employment. NZ Battery Project).

6. Conclusions

This study examines the energy consumption patterns in New Zealand’s industrial sector. Utilising a TIMES-based model, we examine the viability of hydrogen as a fuel for industrial process heat. Under prevailing realistic assumptions, hydrogen does not emerge as the most cost-effective option. However, if hydrogen technologies rapidly develop and become more cost-competitive relative to alternatives, such as electrification, our results show a discernible shift towards hydrogen for supplying high-temperature process heat. Specifically, the contrast between the “rapid development” and “baseline” scenarios illustrates two distinct hydrogen pathways: (1) a limited-adoption pathway dominated by electrification through 2050, and (2) an accelerated-adoption pathway where hydrogen penetrates high-temperature segments after 2040. This finding is pertinent for policymakers aiming to prioritise the decarbonization of industrial process heat in hard-to-abate areas, such as steel manufacturing. However, the feasibility of this transition extends beyond techno-economic optimisation and hinges on institutional, infrastructural, and behavioural factors.

From an implementation perspective, several barriers could limit the uptake of either pathway. Industrial electrification at scale relies on timely grid reinforcement, sufficient local network capacity, and affordable access to renewable energy. Conversely, the expansion of hydrogen use requires substantial investment in production, storage, and distribution infrastructure, as well as the establishment of safety standards and certification schemes. Both pathways face challenges in securing skilled labour, financing long-lived assets under policy uncertainty, and aligning decarbonisation timelines with firms’ capital-replacement cycles. If these enabling conditions are delayed, the transition could lock industry into second-best outcomes such as extended reliance on fossil fuels, partial fuel switching to biomass or imported hydrogen derivatives, or fragmented pilot projects that fail to achieve system-wide scale economies.

These insights highlight that policy design should go beyond technology prioritisation. Effective decarbonisation of industrial heat will require integrated planning of electricity and gas networks, targeted infrastructure co-funding, risk-sharing mechanisms to de-risk first movers, and regulatory clarity on carbon pricing trajectories. Support for hydrogen should focus on high-temperature, hard-to-electrify processes while concurrently addressing potential misalignments between hydrogen production and demand centres.

More broadly, these findings also reinforce the sustainability goals of achieving low-carbon industrial transformation. By identifying feasible pathways for reducing process heat emissions, the study demonstrates how emerging technologies such as green hydrogen can contribute to cleaner production, energy security, and long-term environmental resilience. The results provide evidence-based insights that support sustainable policy development and informed investment decisions, aiming to balance economic growth with emissions reduction.

Like all models, the TIMES framework has both advantages and disadvantages. Rooted in cost minimisation, TIMES models tend to select one type of technology to supply a given energy service, unless explicitly constrained, such as by setting limits on maximum capacity or the proportion of a technology or fuel. In actual applications, a combination of solutions may be adopted, depending on site-specific needs and conditions. Moreover, the inherent benefits of maintaining diverse energy sources for system security are not explicitly captured in the model. Importantly, the model outcomes should be interpreted as indicative of relative system costs rather than prescriptive forecasts. Their policy value lies in identifying trade-offs and priority areas where government intervention could accelerate economically viable decarbonisation.

In addition, the results depend on the accurate characterisation of available technologies. There is considerable uncertainty surrounding the development of fast-growing hydrogen technologies, particularly in terms of cost, readiness, and technical performance. Some of this uncertainty is captured by running the various scenarios, but there are still gaps. For example, in the NZIES specification, there is limited development of geothermal direct-use technologies. While this is unlikely to affect the results of the analysis, as geothermal energy supplies low- and intermediate-temperature heat (which is not favoured for hydrogen in any case). Still, it is an example of what could be considered a complete survey of industrial heat outside hydrogen.

When modelling the electricity sector, NZIES allows for flows between the North and South Islands, constrained by the capacity of the HVDC link. However, within each island, transmission capacity remains unconstrained. An average cost associated with new electricity investment partially captures the cost of new transmission. However, large industrial users may incur extra capital costs for transmission capacity depending on location, existing infrastructure, and the location of new generation plants.

There are many directions for the future development of the NZIES model, depending on the topic of interest. For example, it is feasible to delve deeper into the industrial sector to provide a more detailed breakdown of end uses. The non-metallic minerals sub-sector could be further divided into cement and clinker production, glass manufacturing, and lime production. While each of these categories relies on direct high-temperature heat, the specific type of heat requirements varies and necessitates different technological solutions. This level of detail would require new data sources beyond the EEUD. Within the parameter envelope tested (Table A3 and Table A4), system outcomes range from 0% to 12.4% hydrogen in 2050, confined to high-temperature process heat (Table 7). Future work will replace the current bookend design with a parametric sweep or Monte Carlo sampling once validated techno-economic ranges for storage, distribution, and site-level constraints become available. However, we do not expect the qualitative ranking—electrification first, followed by hydrogen for hard-to-electrify high-temperature uses—to change. Notably, the EECA is currently developing a heat demand database, only available for Canterbury and Southland, which provides a more detailed perspective (Energy Efficiency and Conservation Authority. Regional Heat Demand Database). It would also be helpful to include more detailed end-uses for other economic sectors, such as residential and commercial energy use.

To enhance the modelling of hydrogen use, the logical progression would be to include a more comprehensive categorisation of storage and distribution technologies. While hydrogen technologies are still rapidly developing, their commercial use remains limited, making it challenging to obtain accurate techno-economic data. In particular, relative costs are crucial parameters in TIMES models and can significantly impact the results. Another modelling option is to include major non-energy uses of hydrogen, such as a chemical reductant or feedstock, to facilitate more accurate emissions accounting. Lastly, despite this study being centred on New Zealand, its implications resonate on a global scale. As a case study, New Zealand’s exploration of the hydrogen economy offers valuable insights to the global community on the development of this emerging energy source. In an era where the global focus is shifting towards combating climate change and embracing sustainable energy solutions, understanding the potential of emerging technologies such as hydrogen is essential. This study contributes to this global discourse by shedding light on the potential role of hydrogen in decarbonisation and the challenges that lie ahead.