26 Module 5: The New Zealand Context
Conditions, Constraints, and Empirical Grounding
26.1 §5.1 A Renewable Grid Against a Fossil Heat Sector
New Zealand occupies an unusual position in the global energy transition. Its electricity system is among the most renewable in the developed world, drawing the great majority of its generation from hydro, geothermal, and wind resources. The approximate shares by generation technology over recent years, hydro contributing around 57 to 60 percent of annual generation, geothermal contributing 18 to 20 percent, and wind contributing a further 7 to 9 percent, combine to give New Zealand one of the lowest grid carbon intensities of any industrialised country. The electricity system is not decarbonised; it remains exposed to dry hydro years and to gas-fired peaking generation that operates under high hydro scarcity conditions. But its structural carbon intensity is low and declining, and the marginal emissions from incremental grid electricity consumption are substantially below those of fossil fuel combustion at the point of use.
Against this low-carbon electricity system stands a process heat sector that remains overwhelmingly dependent on fossil fuels. Industrial and commercial process heat accounts for approximately 27 to 30 percent of New Zealand’s total energy-related greenhouse gas emissions, and fossil fuels serve the large majority of that heat demand. The structural explanation for this persistence is not primarily technological. It is geographic and infrastructural. New Zealand’s industrial heat users are distributed across a largely rural landscape, connected to a transmission and distribution network that was designed around historical industrial load profiles and that was not engineered to absorb large additional loads without reinforcement. The economics of electrification depend on access to a transmission grid that can deliver the required increment of electricity reliably and at acceptable cost. In many locations, that access requires infrastructure investment that is neither trivial nor guaranteed.
A further structural feature of the New Zealand process heat sector is its geographic division between fuel types. The North Island’s industrial heat demand is served predominantly by natural gas, supplied through the Maui and Pohokura fields via the national high-pressure gas transmission network. The South Island has no natural gas transmission network. Its industrial heat demand has historically been served by coal, the majority of it South Island coal mined at the Escarpment and Stockton mines on the West Coast and transported by rail and road to industrial users in the Southland, Canterbury, and Otago regions. The South Island’s industrial process heat sector is therefore a coal-decarbonisation problem in a way that the North Island’s is not, and the range of low-carbon alternatives differs accordingly. Biomass is more competitive in a coal-replacement context than in a gas-replacement context because the delivered cost premium of biomass over coal is smaller than the delivered cost premium of biomass over gas.
Fonterra’s commitment, made publicly and incorporated into its sustainability reporting framework, to eliminate coal from its New Zealand manufacturing operations by 2037 creates a specific and time-bounded decision context for the largest single industrial heat user in the country. Fonterra operates eight large dairy processing facilities in the South Island alone, together consuming a substantial fraction of the South Island’s total industrial coal demand. The scale and concentration of this demand commitment makes the transition pathway choices analytically important beyond the individual facility level: the aggregate grid impact of multiple large-scale electrification decisions occurring simultaneously within the same regional transmission zone creates infrastructure consequences that individual site assessments cannot anticipate and that make the system-level regret architecture of Module 4 analytically necessary rather than merely theoretically attractive.
The structural disconnect identified here, a low-carbon grid that is not straightforwardly accessible to the large fossil-fuelled heat users most likely to benefit from electrification, is the empirical grounding for the framework’s multi-layer architecture. It is what makes the GXP hosting capacity assessment a first-order analytical concern rather than a background condition, and it is what gives the 23-of-64 finding its practical significance.
26.2 §5.2 The GXP Structure and Electrification Constraints
The New Zealand electricity transmission system is operated by Transpower, which manages the national grid at grid exit points from which electricity flows into regional distribution networks. A Grid Exit Point (GXP) is the metered boundary between the national transmission grid and a regional distribution network. For a large industrial user seeking to electrify its heat supply, the relevant question is whether the GXP that supplies its regional distribution network has sufficient hosting capacity to accommodate the additional electrical load without triggering network reinforcement requirements. If it does, the incremental electricity can be supplied without infrastructure investment. If it does not, reinforcement is required, and the commercial terms governing who funds that reinforcement determine whether the electrification pathway’s economics are as favourable from the site perspective as they appear.
PowerNet Limited manages the electricity distribution networks in the Southland, Otago, and parts of the West Coast regions on behalf of the network owners Electricity Invercargill Limited, Electricity Southland Limited, and The Power Company Limited. Under the commercial terms governing new and altered connections on these networks, a new connection or a significant increase in contracted supply capacity triggers an economic calculation comparing the estimated cost of any required network extension or upgrade with the Network Contribution, the amount the network determines as the maximum giving an economic return from future line charges at the requested supply capacity. If the estimated extension and upgrade cost exceeds the Network Contribution, the customer is required to pay the difference as a Customer Contribution, an up-front lump-sum payment covering the network investment that will not be recovered through future line charges alone.
For large industrial connections with a contracted supply capacity exceeding 100 kVA, additional obligations apply. When the projected coincident demand of the new connection exceeds 10 percent of the available subtransmission capacity at the relevant zone substation, and the existing demand at that substation already exceeds 80 percent of its firm capacity, a Customer Contribution towards subtransmission network expansion may be required. The customer is also required to enter into a Capacity Guarantee Agreement, a formal contractual commitment to maintain the contracted supply capacity for a period of ten years, or to compensate the network for the balance of its unrecovered investment if the capacity is reduced before that period expires. These commercial terms are directly relevant to the framework’s system-level regret calculation: the Customer Contribution and associated network upgrade costs represent a genuine system cost that may not appear in the site-perspective assessment but is borne by someone, either the connecting customer or the broader network, depending on the specific commercial outcome of the connection assessment.
The Edendale dairy processing facility connects to the national transmission system at the Edendale GXP (identifier EDN0331) within the Mararoa-Waimea transmission cluster. The Mararoa-Waimea cluster serves the eastern Southland region and supplies Fonterra’s Edendale facility, which is among the largest individual electricity consumers connected to this part of the Southland distribution network. The GXP’s hosting capacity, meaning the additional electrical demand that can be accommodated without triggering subtransmission reinforcement, is subject to genuine uncertainty because it depends on the simultaneously evolving demand from other users in the zone, the timing of planned Transpower investments in the national grid infrastructure serving the cluster, and the coincident demand pattern of any new large loads connecting in the same region.
The uncertainty in headroom estimation is the empirical basis for the headroom multiplier dimension of the FutureArtefact ensemble. The multiplier spans the range from a constrained scenario, in which other industrial users in the region are also electrifying and residual headroom is limited, to an unconstrained scenario, in which the reference headroom is available in full. Sub-Module SM-5.2-A documents the published capacity data for the Mararoa-Waimea cluster and the reserve margin methodology that governs how headroom is estimated.
Mararoa-Waimea GXP Capacity Data — published capacity figures, reserve margin methodology, and uncertainty sources — is in SM-5.2-A. Process when verifying the headroom multiplier range used in the FutureArtefact ensemble design.
26.3 §5.3 Biomass as the Competing Pathway
Biomass combustion for industrial process heat is not a new technology, and in a coal-replacement context it represents a well-understood transition option with several structural advantages over electrification. It does not require grid infrastructure development. It uses existing combustion and steam generation equipment, which can be modified rather than replaced to accept biomass fuel, reducing capital expenditure relative to a full boiler replacement. It is not exposed to electricity price volatility or electricity market scarcity events. And in New Zealand’s carbon pricing environment, biomass combustion from sustainably managed forestry is treated as carbon-neutral for ETS purposes, eliminating the ETS cost exposure that coal combustion carries.
The principal competing pathway in the Edendale proof of concept is the 2035_BB biomass boiler pathway: a configuration in which the facility’s coal-fired boilers are replaced with or converted to burn wood residues and forest biomass sourced from the Southland regional supply chain. New Zealand’s South Island has a substantial plantation forestry estate, dominated by Pinus radiata, concentrated in the Southland, Otago, and West Coast regions. The harvesting cycle for commercial plantation forestry produces significant volumes of residue material, logging slash, bark, sawmill offcuts, and harvest debris, that are available as biomass fuel feedstock. Much of this material currently has limited alternative economic use, making it potentially available at a cost that is competitive with coal on an energy-equivalent basis.
The economics of the biomass pathway depend on three interacting factors that are each genuinely uncertain at the planning horizon relevant to a 2035 investment decision. The first is biomass availability, which is a function of plantation harvest schedules, the competing demand from other potential biomass users including the wood-processing industries, electricity generators with co-generation capacity, and any new industrial biomass demand from other coal-phase-out commitments in the same region. The Southland region’s dairy, meat processing, and wood products sectors share potential access to the same biomass resource base, and the simultaneous pursuit of biomass pathways by multiple users could constrain availability and drive up delivered costs above levels that are currently indicative.
The second factor is delivered cost, which reflects logistics as much as feedstock price. Biomass has a lower energy density than coal on both a mass and volume basis, meaning that the transport cost per unit of delivered energy is higher. The delivered cost from a specific supply zone to the Edendale facility depends on the distance from the supply cluster, the transport mode, and the processing required to bring the moisture content and particle size within combustion specifications. These logistics characteristics mean that the biomass supply chain is spatially sensitive in a way that the coal supply chain, which uses established rail logistics from the West Coast, was not.
The third factor is the sustainability certification requirement. While biomass is treated as carbon-neutral under New Zealand’s ETS, the policy treatment is subject to ongoing review, and the conditions under which biomass remains exempt from ETS liability may change. Internationally, sustainability certification requirements for biomass are becoming more stringent, and facilities seeking to use biomass as a coal replacement under corporate sustainability commitments face reputational as well as regulatory risks if supply chain sustainability is inadequately documented. Sub-Module SM-5.3-A provides the resource and cost estimates and the FutureArtefact calibration for biomass availability and cost multipliers.
Southland Biomass Resource and Cost Estimates — resource volumes, delivered cost structure, seasonal availability, and FutureArtefact multiplier calibration — is in SM-5.3-A. Process when verifying the biomass availability and cost multiplier ranges.
26.4 §5.4 Policy Uncertainty as a Structural Driver
Carbon pricing is the most consequential policy variable for the Edendale pathway comparison. It directly affects the operating cost of the coal-fired baseline, the ETS exposure of any pathway that retains combustion emissions, and the relative attractiveness of electrification and biomass as coal alternatives. The New Zealand Emissions Trading Scheme, the primary carbon pricing instrument in New Zealand’s climate policy, has been in operation since 2008 but has undergone such substantial design changes over that period that its future price trajectory cannot be inferred with confidence from either its historical pattern or its current settings. This is not merely a matter of parameter uncertainty; it is a matter of policy uncertainty in the structural sense of §1.3. The design of the scheme, the stringency of its industrial allocation provisions, the treatment of biomass emissions, and the level of the price cap are all subject to ongoing political and institutional contestation.
The scheme’s price history illustrates the point. From its inception until approximately 2017, the New Zealand ETS price was suppressed to near-zero levels by the availability of cheap international units, in particular Assigned Amount Units from countries with surplus Kyoto commitments, which domestic participants could use to meet their obligations at negligible cost. The removal of international unit access in 2015 and the subsequent redesign of the scheme through the 2019 amendments produced a substantial and sustained increase in the NZU price from under NZD 10 per tonne in 2017 to above NZD 60 per tonne by 2021, with further increases to above NZD 80 per tonne by 2022 before price softening through 2023. The fixed price option, which sets a cap on the NZU price, has been progressively raised from NZD 25 per tonne to NZD 50 per tonne to the current NZD 173 per tonne, signalling an intent to allow prices to rise substantially but with the political mechanism for reversing that intent still in place.
For an investment decision with a fifteen-year horizon, the ETS price trajectory from 2025 to 2040 is one of the most important uncertain drivers of pathway economics. The electrification pathway eliminates direct combustion emissions and therefore eliminates ETS liability on that component of the facility’s carbon account. The biomass pathway also eliminates direct combustion emissions if biomass is accepted as carbon-neutral, which is the current policy treatment but is subject to review. The coal baseline, if it were to continue, would face escalating ETS costs. The question of whether the ETS price rises sufficiently to make either transition pathway clearly more attractive than the other on carbon-cost grounds alone cannot be answered from current settings or historical trends. It requires the structured exploration across plausible ETS price trajectories that the FutureArtefact ensemble provides.
The National Environmental Standards for Industrial Greenhouse Gas Emissions, commonly called the NES, establish a coal phase-out pathway that prohibits new coal-fired boilers above a defined scale threshold and sets sunset dates for existing coal-fired equipment in specified industrial categories. The NES timeline directly constrains the Edendale decision: the deadline for coal phase-out creates a forcing condition that makes the decision non-optional regardless of whether the pathway economics are favourable at any given ETS price. The interaction between the NES timeline and the uncertainty about which pathway performs best across plausible futures is what makes the proof-of-concept analysis analytically interesting and practically important. Sub-Module SM-5.4-A provides the ETS design history, price trajectory data, and NES timeline that ground the ETS and policy dimensions of the FutureArtefact ensemble.
NZ ETS Design History and Price Trajectory — scheme design changes, price history, and coal phase-out NES timeline — is in SM-5.4-A. Process when verifying the ETS price range in the FutureArtefact design.
26.5 §5.5 The Analytical Landscape: RETA, GIDI, and TIMES-NZ
Three institutional tools shape the analytical and policy landscape within which the Edendale decision is made and within which the framework positions itself. Each serves a purpose the framework does not, and the framework addresses a gap that none of the three currently fills.
RETA (Regional Energy Transition Accelerator) is an EECA-led programme that provides rapid, standardised assessments of decarbonisation opportunities and infrastructure requirements across New Zealand’s industrial and commercial heat sectors at a regional scale. The RETA methodology uses publicly available GXP capacity data, survey-based energy demand estimates, and indicative technology cost parameters to screen large numbers of sites quickly, identifying clusters where electrification and biomass transitions are potentially feasible and mapping the grid infrastructure that would be required to enable them. The Southland RETA assessment identifies the Mararoa-Waimea cluster as a constraint zone and provides the reference capacity estimate that grounds the headroom multiplier in the FutureArtefact ensemble. The RETA methodology is designed for coverage and speed: it produces regional maps of opportunity and constraint, not site-specific investment decisions. The framework takes RETA outputs as calibration inputs, not as decision-informing conclusions.
GIDI (Government Investment in Decarbonising Industry) is a government co-investment fund administered by EECA that provides capital grants to industrial facilities committing to fossil fuel phase-out. GIDI funding changes the effective capital cost of transition investments for eligible applicants, shifting the private cost of the transition partially from the facility operator to the government. For the framework’s site-perspective evaluation, GIDI co-investment reduces the capital cost component of the pathway NPV calculation. For the system-perspective evaluation, GIDI funding represents a transfer that reduces the private cost without reducing the system cost; it does not affect the regional infrastructure consequences of the pathway choice. The framework’s multi-perspective evaluation makes this distinction analytically visible: a GIDI-supported electrification pathway may appear cost-competitive from the private perspective even in futures where the infrastructure-conditional system cost assessment would prefer the biomass pathway. The policy-adjusted evaluation frame of Module 4’s §4.4 is specifically designed to capture this effect.
TIMES-NZ is New Zealand’s national energy system model, maintained by the University of Auckland’s Energy Centre. It provides economy-wide scenario analysis spanning the full energy system from primary supply to end-use demand, with the long-run investment and operational logic of a least-cost energy system optimisation under declared policy constraints including the emissions budgets. TIMES-NZ scenario outputs, including electricity price trajectories, sectoral demand projections, and national emissions pathways under different policy environments, provide exactly the kind of exogenous future condition boundary data that belong in a FutureArtefact ensemble as contextual calibration for the ETS price and electricity tariff dimensions. The framework treats TIMES-NZ scenario outputs as ensemble calibration inputs: they inform the ranges of the ETS price and electricity tariff multipliers, ensuring that the futures tested in the Edendale ensemble are consistent with plausible national energy trajectories. A more advanced integration, in which TIMES-NZ and the framework exchange scenario outputs in a Gauss-Seidel coupling, is the national-scale vision item described in Module 7.
TIMES-NZ and the NZ Energy Modelling Ecosystem — detailed technical assessment of TIMES-NZ capabilities, the wider NZ modelling ecosystem, integration pathways, and the ReferenceArtefact specification for governed external document linkage — is in SM-5.5-A. Skip if TIMES-NZ technical detail is not required.
26.6 §5.6 Grounding the FutureArtefact Uncertain Drivers
Module 5 has established the specific New Zealand conditions that generate the analytical uncertainties the FutureArtefact ensemble is designed to explore. This closing section provides the explicit mapping between every uncertain driver declared in the FutureArtefact schema and the observable New Zealand condition from which its range is derived. The mapping is the evidence that the ensemble design is grounded in the specific decision context, not in abstract uncertainty exploration.
Table 5.6 presents the complete mapping. For each driver, the table identifies the source document or institutional data that provides the reference value, the New Zealand condition that generates the uncertainty around that reference, and the section of Module 5 where the condition is discussed.
Table 5.6: FutureArtefact uncertain driver grounding
| Driver field | Reference value | Range | NZ condition generating uncertainty | Grounded in |
|---|---|---|---|---|
| headroom_mult | 1.00 | 0.60 to 1.30 | Competing electrification demand in Mararoa-Waimea cluster; Transpower investment timing | §5.2, SM-5.2-A |
| demand_growth_mult | 1.00 | 0.90 to 1.20 | Regional dairy sector growth; Fonterra production investment cycle; rural population trends | §5.1 |
| hydro_class | normal | dry, normal, wet | Interannual variability in South Island hydro inflows; NIWA seasonal hydrology data | §5.1 |
| biomass_availability_mult | 1.00 | 0.70 to 1.30 | Plantation harvest schedule; competing biomass demand from other Southland industrial users | §5.3, SM-5.3-A |
| biomass_cost_mult | 1.00 | 0.70 to 1.30 | Logistics maturity; competing demand price pressure; transport infrastructure development | §5.3, SM-5.3-A |
| ets_price_nzd_per_tco2 | 65 | 30 to 140 | NZ ETS design history; Climate Change Commission budget modelling; political price risk | §5.4, SM-5.4-A |
| upgrade_capex_mult | 1.00 | 0.80 to 1.30 | Uncertainty in PowerNet connection assessment; Transpower subtransmission upgrade cost estimates | §5.2, SM-5.2-A |
| voll_nzd_per_mwh | 10000 | 5000, 10000, 15000, 20000 | Electricity Authority VOLL settings; scarcity event frequency under dry hydro | §5.2 |
| p_elec_mult | 1.00 | 0.85 to 1.30 | Electricity tariff uncertainty; wholesale price trajectory from TIMES-NZ scenarios | §5.5 |
| p_biomass_mult | 1.00 | 0.70 to 1.30 | Biomass market price uncertainty; supply chain maturity | §5.3, SM-5.3-A |
| ets_mult | 1.00 | 0.50 to 2.00 | ETS price trajectory uncertainty applied as site-cost overlay multiplier | §5.4, SM-5.4-A |
Together these eleven driver dimensions and their ranges constitute the analytical specification of the uncertainty space that the Edendale proof of concept explores. Each range is defensible by reference to a documented New Zealand condition. Each driver is traceable to the section of Module 5 that provides the empirical grounding. The FutureArtefact schema, as specified in Module 3 §3.5, carries all eleven fields and their specific values for each future in the ensemble. Module 6 describes how these values are used to construct and evaluate the 64-future paired ensemble.