How Big Data Makes Renewable Energy More Competitive

Two weeks ago we attended the Renewables UK Marketplace and I presented the Planet OS story by participating in a session about big data. I was joined by several other leaders from the renewable energy big data market. Paul Usher started off the session and made it clear that renewable energy companies could gain significant competitive advantage through advanced analytics and big data.

However, this business advantage doesn’t come easy because big data analytics are hard to implement, and the most time consuming part is simply preparing the data for analysis. Most big data teams spend 40–60% of their time preparing data or ‘data wrangling’ as it’s called by many. The problem is even worse with geospatial data which has many diverse formats including time series, raster, and vector data. Luckily, there are new emerging technologies like Kinetica and Datahub that help companies reduce the time they spend wrangling geospatial data. The time saved can be spent instead on developing advanced analytical models that deliver competitive advantage to the business.

I observed many parallel themes between this event and the Wind Europe Summit. The wind energy industry is clearly maturing, although in different ways between onshore and offshore. Innovation is a major goal across the entire supply chain as companies rush to increase revenues and drive costs down. New technologies like floating turbines and energy storage could have an enormous impact on the future of renewable energy. Meanwhile the industry is tirelessly optimizing the performance of both operations and assets to reduce costs and be more competitive with traditional energy sources like coal and gas. Advanced analytics is a critical tool for renewable energy companies to achieve this competitive advantage.

Originally published at planetos.com on October 23, 2016.