How to Reduce Diesel Costs at Telecom Towers in Nigeria: 6 Causes of Fuel Waste to Look For

Nigeria’s telecom networks depend on reliable power at every site. But reliable power does not automatically mean efficient power.

At one tower, an extra period of generator runtime may look like a small operating issue. Across hundreds or thousands of sites, repeated every day, it can become a material OPEX problem.

That is why the most useful starting point is not a new generator, a new battery or another fuel-control process. It is a better operating question: Where is diesel being used unnecessarily across the tower portfolio

and what is causing it?

For Nigerian TowerCos and mobile network operators, that question matters more as networks expand. In May 2026, the Nigerian Communications Commission (NCC) said operators had planned more than 12,000 additional coverage and capacity sites, with more than 5,000 already completed. More sites mean more energy assets, more field activity and more opportunities for small inefficiencies to multiply.

Nigeria cost context

The National Bureau of Statistics reported an average diesel retail price of ₦3,277.47 per litre in May 2026 - 86.4% higher than May 2025. Prices have since moved, but the lesson remains: diesel exposure is expensive and volatile, so wasted runtime matters.

Why diesel waste is difficult to see across a tower network

A telecom tower rarely relies on one energy source. Depending on the location, the site may use grid power, a diesel generator, batteries, solar or a hybrid combination. The operating problem isn't just whether each asset works. It is whether the sources are working together in the most efficient order.

Nigeria’s Service-Based Tariff structure also reflects how different grid conditions can be. NERC defines service bands by minimum daily supply - from at least 20 hours for Band A to lower service commitments for Bands B to E. In practice, actual tower-level availability still varies by feeder, location and outage pattern.

That makes a portfolio average a weak place to manage diesel from. One tower may genuinely need long generator runtime. Another may be burning diesel because the grid returned and the site did not switch back. A third may have an oversized generator operating inefficiently at low load.

The job is to separate necessary diesel use from avoidable diesel use.

What a small amount of avoidable diesel can cost

Using the NBS May 2026 national average of ₦3,277.47 per litre, even a small daily amount of unnecessary consumption becomes significant over a month. The example below is illustrative only; actual generator fuel consumption depends on generator size, condition and load

Avoidable diesel per day	Illustrative cost per day	Illustrative cost over 30 days
5 litres	₦16,387	₦491,621
10 litres	₦32,775	₦983,241
20 litres	₦65,549	₦1,966,482

Multiply that across 100, 500 or 1,000 sites and the operating question changes quickly. The aim is not to assume every tower is wasting fuel. It is to identify the sites where the data says something is not behaving as expected.

1. The generator is running while grid power is available

This is one of the clearest forms of avoidable diesel use.

A tower can remain on generator after grid supply returns because of a changeover problem, operating practice, control logic or an unresolved electrical fault. If teams only see generator runtime, they may know that the generator ran for eight hours but not whether it needed to run for eight hours.

The useful comparison is generator runtime against verified grid availability.

·  When did grid power become available?

·  When did the generator start and stop?

·  Was there an overlap between grid availability and generator operation?

·  How often does the pattern repeat at the same site?

Once those signals are viewed together, unnecessary runtime becomes easier to identify, investigate and verify after corrective action.

2. The generator is too large for the actual tower load

Bigger is not automatically better when it comes to generator efficiency.

Generators are generally less efficient when they spend long periods operating at low load. A tower may have been designed conservatively, inherited equipment from an older configuration or had its load reduced over time while the generator stayed the same.

enee.io’s Nigeria operating model illustrates the effect using a typical example: an oversized genset at around 25% load may consume roughly 0.5 litres per kWh, compared with about 0.3 litres per kWh for a better-matched unit operating around 60% load. Actual fuel curves vary by generator make, model, age and condition, so the decision should be based on the site’s measured load profile.

Before replacing a generator, answer three questions:

·  What is the site’s normal load?

·  What is the true peak load?

·  How much of the generator’s rated capacity is actually being used?

Right-sizing should be a data decision, not a rule of thumb.

3. Diesel use does not match generator behaviour

Fuel records tell you what was delivered. Generator data tells you how the equipment actually operated. The gap between the two is where useful questions begin. An unexplained variance does not automatically mean theft. It could be a recording error, leakage, generator inefficiency, refuelling timing, fuel movement between sites or an operating issue. The important point is that the discrepancy becomes visible enough to investigate.

A stronger fuel-control process compares:

·  Generator runtime

·  Electrical load and output

·  Expected fuel consumption

·  Recorded fuel deliveries or refuelling events

·  Historical behaviour at the same site

That turns diesel management from a reconciliation exercise at the end of the month into an operational exception that can be investigated earlier.

4. Battery performance is forcing the generator to start earlier

At hybrid or battery-backed sites, diesel cost can rise even when the generator itself is working normally. If batteries are not delivering the expected autonomy, the generator may start sooner and run longer. The cause could be degraded battery health, charging issues, configuration, temperature, increased site load or an operating strategy that no longer matches actual demand.

The decision is not simply whether the battery bank is 'good' or 'bad'. It is whether battery performance is supporting the intended operating window and reducing generator dependency as designed. Monitoring battery state, charge and discharge behaviour alongside generator activity gives operators the context to distinguish a fuel problem from a storage problem.

5. Switching between power sources is slow or poorly controlled

Every transition between grid, generator, battery and solar is an operating decision.

If those decisions are delayed or inconsistent, the site can burn diesel longer than necessary, cycle generators more often, underuse available grid or renewable energy, or expose batteries to an operating pattern they were not designed for.

Time-stamped energy data helps answer what happened in sequence: grid failed, generator started, grid returned, generator continued, site switched back. Once the sequence is visible, operations teams can separate an equipment fault from a control or process issue.

6. One tower is behaving differently from comparable sites - and nobody sees it early

Portfolio averages are useful for reporting. They are less useful for finding waste. The better approach is to compare similar sites and look for exceptions. A tower with much higher generator runtime than comparable locations may be responding to genuine grid conditions, but it may also be signalling a switching problem, abnormal load, battery issue or equipment inefficiency.

The key word is comparable. Towers should be grouped sensibly by factors such as region, grid conditions, load, tenancy and power-system configuration before performance is compared.

The objective is not to label the highest-cost site as 'bad'. It is to know which site deserves a closer look first.

Common mistakes when trying to reduce tower diesel costs

Reducing diesel OPEX is not simply a matter of telling field teams to use less fuel. Several common approaches can create activity without improving the underlying decision.

Starting with equipment replacement before establishing a baseline. Without a measured load and source profile, it is easy to solve the wrong problem or oversize the replacement.

Using fuel purchases as the only measure of fuel consumption. Deliveries are an accounting record. They do not explain generator behaviour.

Managing the network from one portfolio average. Average performance can hide expensive outliers.

Treating every alarm with the same priority. Operations teams need to distinguish events that threaten uptime or cost from those that can wait.

Comparing towers that are not operationally similar. A low-grid rural site should not automatically be benchmarked against a high-grid urban site.

Start with visibility before deciding what to fix This is where the Decision Intelligence approach matters.

The sequence should be simple:

1.     Problem - identify the operating behaviour that looks wrong.

2.     Cost - quantify what that behaviour is costing in diesel, site visits, downtime risk or asset life.

3.     Solution - correct the specific cause, whether it is switching, right-sizing, maintenance, storage or operating practice.

4.     Value - verify that the change reduced cost or improved reliability and keep watching for recurrence.

That order matters. It prevents the monitoring system, generator, battery or solar asset from becoming the starting point of the conversation. The starting point is the expensive operating question.

How enee.io helps TowerCos work by exception

enee.io brings grid, generator, solar, battery and site-load data into one monitoring environment so operations teams can see what is happening at individual towers and across the wider portfolio.

The system is designed to work across different makes, models and ages of energy equipment. Its plug-and-play monitors feed data through the eDGe gateway, which can communicate over built-in 4G or Wi-Fi, while Proteus provides online reporting for multi-site operations.

That means different teams can work from the same evidence:

·  Executives can see portfolio-level energy cost, performance and exceptions.

·  Regional managers can compare sites and prioritise the locations that need attention.

·  Field teams can see site-level information before travelling and arrive with a clearer diagnostic picture.

The goal is not to create another dashboard that someone has to watch all day. It is to make abnormal behaviour easier to spot, so people spend more time acting on the right sites and less time searching for the problem.

A practical monthly review for tower energy teams

A useful diesel-cost review does not need to start with dozens of metrics. Begin with a small number of questions that lead to action:

·  Which towers had the highest generator runtime relative to grid availability?

·  Which generators spent the most time at low load?

·  Where did expected diesel consumption differ from fuel records?

·  Which battery-backed sites started generators earlier than expected?

·  Which sites had repeated switching or power-source events?

·  Which towers moved furthest away from the performance of comparable sites?

Then rank the sites by financial impact, reliability risk and ease of corrective action. That creates a practical worklist instead of a long report.

Key takeaway: measure the cause, not just the fuel bill

Diesel is necessary at many Nigerian telecom sites. Waste is not.

The opportunity is not to assume every generator should run less. It is to understand why each generator is running, which sites are behaving differently and what the difference is costing.

At one tower, the saving may be modest. Repeated across a large portfolio, the same operating improvement can become meaningful.

See the problem. Quantify the cost. Fix the cause. Verify the value. If you manage energy or operations across a telecom tower network, enee.io can help you identify the sites and operating behaviours worth investigating first.

Request an Executive Energy Cost Review https://zcmp.eu/sxz1