It is well known that photovoltaic solar energy is one of the cleanest and cheapest technologies to generate energy in many parts of the world even more in Spain. And a system that is rapidly becoming popular. But there is also a very unknown aspect that will play a leading role to further reduce costs and boost its development and that is the data, that can be accumulated or handled from the installation.
Solar plants can generate a huge amount of digital information. A coal-fired power plant or any other fossil fuel of 1GW on average will generate approximately 10,000 QTY (data flow), a wind farm of similar size could produce 51,000 or even five times more, but a solar park of those dimensions? It shoots up to 439,000 QTY.
Data, the big deal.
Data is important for a small home planta but when it comes to large solar plants the numbers shoots up.
The discrepancy derives largely from the nature of the solar installation as it can be used as a distributed generation. Large thermal power plants and wind farms are generally built around a relatively small number of large assets, while solar parks are built around a large number of very small assets.
To take a random example, a wind farm of 88 turbines with a capacity of 141 MW, and conversely, a solar park that generates 62 MW, or less than half, but has 144,000 solar panels. Each panel will generate information on the production of energy, temperature and other parameters, inverters, trackers, junction boxes will also produce continuous flows about their current state or possible problem areas.
At first glance, it may sound like a bad thing. More data means having to install more computing capacity or incur additional fees in the cloud. However, data can play and will play the main role in reducing one of the costs that have apparently been insensitive to technological advances: labour costs associated with maintenance operations.
Reduction in labour costs.
Labour still represents between 1% and 7% of the total revenues of a solar project, and remains one of the largest expenses not linked to construction and original financing.
Efficient asset performance management can reduce the cost of energy development of a large power plant by 1% to 3.5%, a deceptively small number that becomes an imminent force at scale. For a 50 megawatt plant that operates with a capacity factor generation capacity of 30% for € 15 ct / kWh, this can mean an additional income of 500,000 euros per year, and most of that incremental cash is converted into profits. (50,000 kilowatts hours’ x capacity factor 0.03 x 8,760 hours per year x 0.15 kWh x 0.03 LCOE reduction = 591,300 euros.) Over a period of 30 years, the total reaches more than 17 million. For a financial entity or a capital partner, debt leverage grows by the same factor.
Take the USA as an example.
Some US states are already benefiting from the generation of so much data. For example, the operator of the Arizona electrical system that manages more than 1,700 megawatts of solar energy for its 1.2 million customers in a territory that covers more than 93,000 square kilometres. Solar assets range from solar plants to energy scale, urban systems and self-consumption facilities. However, maintenance is managed by a small group of technicians who can prioritize repairs. And are about ten or less.
The decrease in solar costs is one of the most notable technological stories of our time. The price of solar energy has fallen 85% between 2010 and 2019, according to Bloomberg New Energy Finance, and another 63% is expected to fall by 2050. But it hasn't happened because of gravity. The first solar pioneers like SunPower focused on efficiency. Then new techniques arrived that allowed producers to obtain more wafers from an ingot. Micro-inverters, modular systems, photovoltaics with monitoring and better project management have also helped reduce costs. The data has been comparatively underutilized. But everything indicates that this will change from now on.
Data is information, information is money, big money.
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