There are several core technologies available today that are helping to create an efficient, productive and sustainable future for humankind. Solar power and big data are just two of these technologies. Together, they’re changing how energy is bought, sold, delivered and used responsibly. Below is a look at five ways big data is set to take solar power to new places in 2020 and beyond.
1. Predicting Productive Weather Conditions
About 80% of rooftops analyzed in Google’s rooftop solar survey are viable for solar installations. Knowing this number helps dispel the misconception that residential and commercial solar projects are practical investments only in a narrow swath of climates.
Nevertheless, predicting weather conditions is important for solar power and other renewables to work at peak efficiency. Predictive analytics also helps energy companies seamlessly balance renewables with traditional power generation facilities to keep supplies in line with peaks and troughs in demand. With historical satellite data and real-time weather and environmental data, IBM says it can use predictive models to inform smart infrastructure design. The result is a 10% increase in the renewable power generated at a site, even without adding new panels or turbines.
2. Supporting Proactive Maintenance
One of the best things about renewable power is that it supports a less centralized energy grid. An energy supplier on one coast can contribute clean power to the grid that a company on the opposite coast can purchase ” even if the energy they use is physically delivered by a local utility.
Solar panels and wind turbines are geographically dispersed and often installed by the dozens or hundreds at the most productive sites. Maintaining this amount of physical infrastructure effectively ” compared to a relatively compact coal-fired power plant ” is a challenge. Big data provides the means to engage in widespread condition monitoring for individual parts, panels and turbines.
A fairly small crew can oversee maintenance operations even for large energy generation sites thanks to sensors and data loggers deployed in the field. These tools indicate when solar panels are performing sub-optimally (when they’re dirty or obscured by a shadow, for instance) or when an important part, like a sun-tracking motor, is showing signs of wear or impending failure.
3. Choosing Sites to Build On (Or Decommission)
After a couple of decades, the owner of a solar array or wind turbine must decide whether to decommission the site and return the land to its previous condition or continue maintaining the equipment and using it to generate and sell power. Making the right decision requires as much data as possible about ongoing maintenance costs, projected costs and historical productivity trends for the site. Big data makes it easier to decide when an investment has run its course and when it has life left in it.
Big data makes it easier to choose suitable sites for renewable energy projects too, as well as understand the environmental impact of placing energy infrastructure. For example, the rain-sheltering effect of solar panels and their impact on drainage and soil retention isn’t perfectly understood, but surveyors and mapping specialists with the right tools can use data to better balance the needs of the landscape with the desired result of the build.
4. Bringing Costs Down
Cost is one of the most frequently cited barriers when it comes to solar power adoption. Solar panels inherently become more cost-effective as the material sciences mature, thereby making the investment more attractive over time and making it easier to leave traditional sources of energy behind, whether in one’s investment portfolio or in one’s energy consumption.
Big data helps brings costs down too. In fact, it’s a natural consequence of the factors we’ve been discussing, including optimizing the placement and maintenance of infrastructure instead of building new. Better-connected smart energy grids contribute to cost savings in their own way by providing real-time analysis for energy companies during outages and making restorative service calls more accurate and quicker to carry out.
5. Creating New Energy Business Models
Another way big data helps provide lower ” and more stable ” prices for renewables is by facilitating solar power purchase agreements (PPAs). With the right data at their disposal, including productivity projections, solar companies can offer low- or zero-cost solar equipment for their customers with convenient, low, locked-in prices.
The combination of big data and solar power has supported the creation of other brand-new energy distribution business models too. In addition to PPAs, there are community-based solar co-ops and solar leases. Solar panels are affordable enough for some companies and customers to buy outright. In other cases, having access to the right data can help identify cases where other types of agreement are more appropriate for the parties involved.
In these ways and more, big data and solar power make an ideal match that will continue paying major dividends. Solar panels let us tap into almost inexhaustible power ” and data helps us do it democratically, efficiently and cost-effectively.
