How CSPs Are Prioritizing Sustainability with On-Site Renewable Energy Solutions
As the telecommunications sector expands, so will its energy usage. According to Ericsson, mobile networks consume 0.6% of the world’s electricity, with estimates indicating that operators spend more than $25 billion on energy expenditures each year. As a result, for Communication Service Providers, energy efficiency and sustainability are becoming more essential problems (CSPs).
Many CSPs are investigating on-site renewable energy options to solve these problems. By 2025, 60% of CSPs are expected to prioritise on-site renewable energy, up from less than 10% in 2022. Cell sites, data centres, and other energy-intensive places can be powered by on-site renewables, decreasing CSPs’ dependency on non-renewable energy sources.
Several CSPs have already begun to investigate on-site renewables, with Deutsche Telekom working with Ericsson to explore solar and wind-powered cell sites, Telenor Group investigating solar and wind-based energy solutions for cell sites, and Telefónica implementing a Smart Site model for mobile site design that incorporates renewable energy sources.
In addition to lowering the carbon footprint of CSPs, on-site renewables can assist to lower energy prices. As energy prices rise, CSPs are focusing more on energy efficiency to save money. CSPs can minimise their dependency on nonrenewable energy sources and cut their energy expenses by installing on-site renewables and energy efficiency efforts.
CSPs and tower companies should bear in mind that various sites may require different solutions based on weather conditions and power demands as they investigate on-site renewable energy alternatives. Because of the number of bands, urban cell sites may require more power than rural or suburban sites, and solar power may not be possible in these places with today’s methods.
CSPs should create a roadmap including network planning and operations, sustainability teams, procurement, and finance to successfully integrate on-site renewables into their networks. They should also work with vendor partners to harmonise roadmaps and objectives/targets for renewable energy usage.
AI has the potential to significantly assist CSPs in optimising their energy use and reducing their dependency on nonrenewable energy sources. AI can help by offering predictive analytics and real-time monitoring of energy consumption. This can assist CSPs in identifying areas where energy consumption can be lowered and optimising operations to be more energy-efficient.
Moreover, AI-powered algorithms can assist CSPs in optimising renewable energy systems such as solar panels or wind turbines to maximise energy output. AI, for example, may evaluate meteorological data to forecast the quantity of solar radiation or wind speed, which can assist CSPs in determining the best position for renewable energy systems and adjusting their output accordingly.
Furthermore, AI may assist CSPs in identifying prospective places for on-site renewables installation by identifying sites with high energy demand and high potential for renewable energy solutions using data-driven insights. CSPs may simulate numerous scenarios and decide the most efficient solution for a specific location using AI-powered simulations, taking into consideration aspects such as weather patterns, power consumption, and cost-effectiveness.
Another method AI may assist CSPs in reducing their carbon footprint is through optimization of Radio Access Network (RAN) operations. The RAN is the component of the mobile network in charge of connecting user devices to the network and handling data transfer. RAN is a substantial contribution to mobile network energy usage, and improving RAN operations may result in considerable savings in power consumption and carbon emissions.
Real-time RAN data may be analysed by AI-powered algorithms to discover locations where power consumption can be lowered without affecting network performance. For example, AI may monitor traffic patterns and alter the power settings of RAN equipment in real-time to decrease power consumption while satisfying performance requirements.
AI may also be used to improve RAN equipment placement, ensuring that the equipment is placed in the most energy-efficient areas and eliminating the need for more equipment. CSPs may dramatically cut their power usage, lower their carbon footprint, and increase network performance by improving RAN operations.
Overall, artificial intelligence may assist CSPs in making educated decisions about energy use and the installation of renewable energy solutions. CSPs may lower their carbon footprint and contribute to a more sustainable future by employing AI to optimise their energy use and maximise the use of renewable energy.
Finally, on-site renewable energy solutions provide various advantages for CSPs, including a lower carbon footprint, cheaper energy costs, and enhanced dependability during extreme weather events. CSPs may progress towards a more sustainable and lucrative future by emphasising on-site renewables and adopting energy efficiency programmes.
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