Renewable energy solutions are evolving at a rapid pace. Companies around the globe are recognizing the importance of investing in sustainable technologies to navigate future environmental and economic realities. According to a report by the International Energy Agency, global investment in digital electricity infrastructure and software has increased by over 20% annually since 2014. New wind, solar, and energy storage technologies have all played a large part in this growth.
To discuss the future of these technologies, Neurio’s Senior Computer Scientist, Elena Popovici, participated on a panel at a Vancouver meetup on February 28, on data science and visualization in the renewable energy sector. Alongside her were Kristin Vidi and Rebecka Klinstrom from Clir Renewables, as well as Brian Roth from Solarmass Energy.
Thanks to Vancouver-based groups Data Viz and Data Science for Social Good for co-hosting the event, and creating an opportunity to explore how data helps spot anomalies, minimize downtime, and advance the industry.
Data analytics and renewable energy management
Foundational to today’s advances in clean tech is a network of hardware, software, and data. Over 90% of all of the world’s data was created in the past two years. Coupling this fact with a rising global commitment towards 100% renewable energy, data analytics play an increasingly important role in shaping the future of renewable energy management.
However, relying entirely on renewable sources like wind and solar comes with a challenge: they are intermittent and often out of synch with when energy is most needed. Total reliance on these sources without proper management often results in inefficient energy storage and usage. With the right hardware and software in place, households and businesses have the ability to monitor, control and maximize their energy consumption and generation. Data analysis and visualization techniques make this possible.
For example, Neurio’s smart sensor and energy monitoring software work to help homeowners intelligently manage their home battery usage. An algorithm first analyzes data points such as real-time electricity usage, power generated from solar, the weather, the billing tariff of the utility company, and the battery capacity. Then, it makes a decision about when and how much to charge or discharge the battery.
By forecasting upcoming energy consumption, homes and businesses can better manage the unpredictable nature of solar and wind power. Not only does this save the user money, it’s good for the grid. Reducing the demand for electricity during peak periods in turn reduces the need for expensive infrastructure required to manage those peak consumption times.
As we see the rise of renewable energy sources, an increased focus on predictive analytics is necessary to manage grids based entirely on renewable energy. While this reality may seem far away, South Australia is already well into building the world’s largest virtual power plant in collaboration with Tesla. Connecting over 50,000 homes to Tesla batteries and a network of solar panels, the goal is to provide enough energy to power the entire state.
Want to learn more about how one of Neurio’s energy management solutions could help you? Reach out today, and someone on our team would be happy to chat. Connect with us on Twitter to get updates on current events and industry news.