As Winston Churchill said
Never waste a good crisis.
Well the telecom industry might not be in crisis yet, but the global energy crisis has pushed their operational expenses (OPEX) to unsustainable levels. It is time to make the most of this crisis, and move our industry forward.
In 2021, energy accounted for 15-40% of OPEX, and this percentage is expected to have grown even further. With gas prices up by 65% and electricity up by 30%, the need to take action is becoming ever more pressing, with the additional requirements of 5G compounding the issue. According to the latest TowerXChange Energy report a basic site carrying two tenants requires 5-6kW to run satisfactorily, while a few years ago this was as low as 3-4kW. Most of these sites have energy systems designed to cater for a 3kW demand, meaning dimensioning plans are out dated, and the need to employ technology to make towers work harder is vital.
The obvious solution to reducing OPEX, and more specifically energy costs is through the use of Artificial Intelligence (AI). By optimising energy usage through AI, tower companies can reduce energy consumption. AI analyses billions of real-time data points from sites across the network, identifying inefficiencies, allowing it to take action, or recommending human intervention. This deeper analysis leads to a 20-30% reduction in diesel consumption, and up to 30% reduction in CO2 emissions.
Tower companies should be leveraging existing data to enact, enable, and unlock hidden efficiencies through automation. Decisions need to be data-driven, rather than based on assumptions or imperfect contexts. In other industries, such as banking, medicine and even the consumer side of the telecom industry, the use of automation has enabled significant improvements in efficiency, directly improving profits and employee satisfaction. Network infrastructure is large and complex, there is simply too much data to be handled by a team of humans, leading to inevitable energy waste. The use of data trends, patterns, and other insights can enable the identification of hidden efficiencies that are not visible through unstructured and fragmented data
Mobile Network Operators (MNOs) rely on diesel generators to power their network sites in areas where there is no reliable power grid. These generators are often left running even when they are not needed, leading to wasted diesel and run time. In this example the PowerX AI system identified a diesel generator that was regularly continuing to run when the grid was available. This kind of issue would have been lost in the mountains of data had it been left to be detected by humans, but the AI noticed immediately, saving the company.
By implementing remote management systems that allow them to monitor generator, solar, battery and grid usage in real time MNOs can reduce this kind of waste. These efficiencies will significantly reduce fuel consumption and lower their energy costs, without compromising, and potentially improving, the reliability of their network.
MNOs can reduce their energy costs by using low-cost renewable energy sources, such as solar and wind power. These sources are increasingly affordable and reliable, and can help MNOs reduce their dependence on non-renewable energy sources, which are increasingly inconsistent and expensive. By investing in renewable energy infrastructure, MNOs can reduce their energy costs and improve their environmental sustainability. Furthermore, they can also benefit from government incentives and tax breaks that encourage the use of renewable energy sources.
For companies that have implemented CO2 and GHG targets, AI can help them track their performance, and gather reports on the effects, both in improving sustainability and in reducing (or otherwise) the costs, of individual programs.
MNOs can get the most out of their existing assets by optimizing them for efficiency and cost-effectiveness. For example, by regularly cleaning and repairing solar panels, MNOs can ensure that they are operating at their full potential, and by using efficient software and batteries, they can reduce energy waste and support more equipment with the same capacity. By optimizing their existing assets, MNOs can improve their efficiency and reduce their energy costs, without the need for significant investments in new infrastructure.
Solar panels are an important source of renewable energy for MNOs, but are a prime example of an unoptimised asset. They become less efficient over time due to dirt, dust, and other contaminants, meaning regular cleaning and maintenance are needed for them to operate at their full potential.
We have found a large number of solar panels are operating at less than half their expected rate, due to dust, broken strings or stolen panels. Left to a team of humans these issues will not be picked up until a worker goes to the site and reports it back. But thanks to pattern recognition technology tied into radiance data, AI can identify broken or dirty solar panels immediately. PowerX can even run a cost/benefit analysis, and only recommend a fix, only when there is a positive ROI.
In the example above 2 breakers had tripped within a couple of days of each other, causing a significant downturn in the sites solar energy. Previously this issue would have gone unnoticed for months, until a regular check had taken place, but thanks to PowerX it was identified immediately, resolved and the site was back to full operating efficiency within a couple of days.
MNOs can reduce energy waste and support more equipment with the same capacity by using efficient software and batteries. Efficient software can help reduce the energy consumption of network equipment, while batteries can store excess energy for use during periods of low production. By investing in efficient software and batteries, MNOs can improve their energy efficiency and reduce their energy costs, while also improving the reliability of their network. Additionally, the use of batteries can help reduce the need for diesel generators, leading to further cost savings and environmental benefits.
There are five steps that tower companies and MNOs can take to keep energy costs under control:
Rising energy costs are a major concern for tower companies and MNOs, but by leveraging existing data and implementing AI you can get control back. By taking the steps outlined above, and following the best practices of other industries, tower companies and MNOs can reduce energy consumption, cut costs, and improve their profitability. With the right approach, it is possible to turn energy challenges into opportunities and drive growth and innovation in the telecom industry.
One conversation dominated the exhibition hall this year, and that was the emergence of truly independent TowerCos in a market typically dominated by MNOs or MNO-backed TowerCos. TowerCos are not new to MENA, but the cultural shift towards the independent TowerCo model as the de facto route to network growth and management certainly is.
How AI allows you to staff every tower with a team of local, maximising each towers potential without additional hiring.