Nigeria’s electricity reliability gap has made petrol and diesel generator sets (FFGs or ‘gensets’) the default ‘backup grid’ for households and businesses. More than 86 million people in Nigeria have no or intermittent electricity access, and around 41 million small businesses and 17 million households are estimated to use fossil-fuel generators, with roughly USD $8 billion spent each year on fuel for expensive, highly polluting power. In practice, grid unreliability – not just lack of access – is the primary driver of FFG use across households and micro, small and medium sized businesses (MSMEs). This creates an urgent need for decarbonisation through zero-emission generator (ze-gens) alternatives.
FFGs persist not because they are efficient, but because they deliver a simple service proposition. They provide power on demand, paid for when needed, and with familiar support networks (fuel sellers and local mechanics). This combination of reliability, flexible payment, and service familiarity has allowed generators to dominate despite high running costs and severe pollution impacts. Any ze-gens that want to scale must match or exceed this proposition. Therefore, ze-gen adoption is as much a technology innovation question, as it is a business model question, and specifically how new business models are adapted to specific local needs.
As part of the Zero-Emission Generators (ZE-Gen) programme, we recently launched new programmes to support business model innovation and testing in Nigeria and Uganda. This short paper summarises our learnings from this process and considers three dominant business model archetypes: (1) PAYGo ownership, (2) solar leasing for SMEs and institutions, and (3) Energy as a Service (EaaS), to show where each works, where each breaks, and what would need to change for sustainable scale.
Business model fundamentals
PAYGo ownership: the default model. PAYGo lets customers acquire a ze-gen via instalments (often over 12–24 months). During repayment, providers run collections and basic monitoring; after ownership transfers, long term service is often informal or ad hoc. It scales – or fails – as a credit portfolio, based on repayment discipline and portfolio quality, not sustained service revenues. For the distributor, PAYGo works an asset backed loan: cash inflows follow a repayment schedule, while the main risks are arrears, default, and the real cost of enforcement or repossession. Service uptime matters largely because poor performance triggers non payment and raises collection costs; once ownership transfers, the model has limited contractual leverage and no predictable recurring revenue stream.
Leasing: fewer customers, bigger systems, concentrated risk. Solar leasing targets SMEs and institutions (clinics, schools, religious and community facilities) with larger, more critical loads. The provider (often with a finance partner) installs a solar plus battery system, retains ownership during the contract term, and charges a fixed recurring fee that typically bundles installation, maintenance, and servicing. Contracts are usually lease to own (ownership transfers at term end) or long term leases with renewal. Compared to PAYGo, leasing concentrates more capital into fewer sites: revenues come from higher value contracts, and service performance is part of the commercial offer – not an add on.
Energy as a Service: closest to the generator experience, hardest to execute. Energy as a Service (EaaS) sells reliable electricity as a service. The provider retains ownership of the assets and customers pay via subscription, rental, or usage based fees (enabled by metering and mobile payments). Customers are buying reliability, not an asset they plan to amortise. Unlike PAYGo or leasing, EaaS revenues depend on ongoing service delivery and asset utilisation. The provider carries installation, maintenance, repair, and replacement obligations, so profitability hinges on whether recurring payments can cover depreciation, cost of capital, operations, logistics, and losses.
What makes each model attractive and where it struggles
PAYGo is common because it lowers the upfront barrier to ze-gen adoption in a cash constrained market and builds on familiar off grid solar payment practices. For customers, it removes the need for a large upfront payment, ensures regular but manageable instalments, and reduces the need for bank-style paperwork. For providers, PAYGo relies on familiar products and sales playbooks.
However, the PAYGo structure doesn’t always align value and payments. Especially in weak grid settings where ZE Gens are used as backup, value for the consumer is based on instances of grid outages, while repayments are regular. This mismatch can force credit flexibility (grace periods, rescheduling) that is hard to price and can erode repayment norms. In addition, after ownership transfer, consumers can face increased service and warranty costs, putting extra pressure on fragile unit economics and intermittent utilisation. The result is a familiar pattern: PAYGo portfolios can look healthy at pilot stage, then degrade with scale when collections discipline and service execution cannot keep up.
Finally, PAYGo models can also skew sales incentives in ways that harm long-term portfolio stability. With rewards based on sales volume over portfolio quality, credit losses can accumulate. A clear maturity shift (‘PAYGo 2.0’) is being driven by the need for stronger credit discipline. Experts note that the push for more rigour includes sales incentives tied to repayment performance (loan quality) rather than volume of loans. When incentives reward pure sales volume, portfolios can skew toward customers who cannot afford the product, creating defaults, repossessions, reputational damage, and higher servicing costs.
Solar leasing turns capex into an operating expense while shifting performance risk to the provider. For customers, leasing can remove large upfront capex, provide predictable payments, and support reliability through provider servicing commitment. For the provider, leasing can increase revenue per customer based on asset and service package and ensure predictable cashflow with larger individual contracts in place.
However, leasing is highly sensitive to capital structure, performance liability, and slow sales cycles. On the capital side, the larger system scale requires a high front up cost usually covered by high-cost local debt. Mismatch between the timeframe and requirements of servicing this debt and asset repayments can make provider balance sheets vulnerable. On the performance side, any delays in response and repair can cause customers to revert to generators or challenge payments, especially in low-tolerance contexts (e.g. healthcare or education). Finally, unlike PAYGo, where defaults are distributed across many small customers, leasing concentrates risk in fewer sites with longer procurement decisions, slow deployment, and higher overall impact on the portfolio performance. Leasing can work well in pilots and concentrated geographies, but scaling without tenor matched capital and credible service infrastructure is difficult.
EaaS aligns most closely with how many customers experience generators: a service used when the grid fails, not an asset purchased for long term payback. It reduces friction by removing large upfront payments and long credit commitments, enabling customers to pay for reliability when they need it and have cash. The model is particularly attractive where reliability matters more than ownership (e.g. healthcare, education, hospitality), or power demand is intermittent but high value (e.g. production clusters). For providers, EaaS offers the potential to deploy standardised assets across multiple customers, manage systems actively by upgrading or redeploying them, building long-term customer relationships.
However, EaaS is operationally and financially demanding for the provider. As the provider retains ownership, technical, operational, and financial risks sit on the balance sheet – and unit economics can erode rapidly if utilisation, losses, or service costs are mis estimated. These risks mean EaaS often performs best in dense, clustered environments where assets can be monitored, serviced, and redeployed efficiently – and struggles in dispersed, low utilisation contexts.
Summary of key strengths and struggles for each business model archetype
| Business model | Strengths | Struggles |
| PAYGo | No upfront cost Small instalment payments Standardised playbooks for providers | High default risk High service and warranty costs Misaligned incentives for sales teams |
| Solar leasing | No upfront cost Reliability through servicing commitment Larger predictable contracts in place | Capital intensity for provider Performance liability Longer sales cycles |
| Energy as a Service | Value for consumer is shifted from asset to reliable access to energy Capacity can scale with user needs Building long-term customer relationships | Provider bears all risks High operational requirements Economics depend on utilisation |
Scaling business models for ze-gen adoption
Based on this analysis, technology and finance providers can consider the following recommendations for implementing the different business models and deliver ze-gens at scale:
- PAYGo works when credit discipline and service capability are engineered for portfolio quality, or in other words when sales incentives, deposits and pricing are tied to repayment performance, and not just volume. It also requires appropriate consumer education and awareness of service and post-ownership support.
- Leasing ze-gens can outcompete FFGs for SMEs and institutions, but scale depends on tenor matched capital and measurable service performance. Design constraints need to be understood from the start, including costed technician coverage, parts logistics, and response times built into pricing and operations. Use-case or geographic focus can support providers to deploy more efficiently, reduce service cost, and build local relationships.
- EaaS requires utilisation, operations and loss management, such as misuse or theft, to be designed as core to the model features. Site selection for MSME clusters, markets or anchor loads can support sustained and predictable demand and create opportunities to reduce response times and logistics costs. Service-level commitments should be clear and transparent for all parties to avoid misinterpretation, and robust asset tracking and metering can help limit system misuse, damage or theft.
However, successful business models not only address the underlying model risks, but also take into account local consumer needs and market conditions. It is not enough to understand what could work on theory; success often depends on meeting consumers where they are, working with the right local partners, and understanding specific local usage to design appropriate solutions. Therefore, ZE-Gen has launched the Local Innovation Facility in Nigeria and Uganda to support the development and testing of localised business models and capture important insights on success factors for ze-gen adoption. The pilots will focus on:
- Testing a wide variety of repayment options, including payment size, downpayment size, hybrid models linked to usage, overall repayment tenor or deal collateral
- Testing a variety of digital solutions, including payment channels, customer relationship management systems, asset and usage tracking
- Testing different distribution and customer acquisition channels
- Testing additional revenue streams and servicing options
Rather than seeking a single ‘best’ ZE-Gen business model, the evidence suggests that scale in Nigeria and Uganda will come from a portfolio of well designed models, each tightly matched to specific customer segments and underpinned by appropriate finance and service infrastructure. We can’t wait to see how these projects progress.
Call to action
Through ZE-Gen, a coalition of international and local partners, including support from the UK Government’s Ayrton Fund and IKEA Foundation, is working to accelerate the adoption of zero-emission generators through innovation, market intelligence, awareness raising and business model testing. ZE-Gen’s Local Innovation Facility is one part of this effort, helping companies in Nigeria and Uganda develop solutions grounded in local realities and customer needs. For ZE Gen’s Local Innovation Facility and similar interventions, the next phase is moving beyond pilots toward evidence backed pathways to scale.
As this work progresses, we are keen to collaborate with financiers, innovators, distributors and energy providers to identify the approaches that can unlock investment, strengthen service networks and deliver clean, reliable power at scale. If ze-gens are to move from promising alternatives to the default backup power solution, both the technologies and the business models need to fit local needs.