How Big Data is Changing Renewable Energy
Renewable Energy Struggles
With the effects of anthropogenic climate change starting to rear their ugly faces, a number of countries have signed agreements, enacted policies, and made pledges to curb global greenhouse gas emissions. Despite the current US administration’s stance and policies on the matter, the renewable energy sector has steadily been growing over the years. While renewable energy consumption has risen and petroleum imports have decreased, the US still consumes roughly 21 million barrels of petroleum per day.
Oil and natural gas dominate the energy sector, but renewables are starting to make an impact. In 2018, wind and solar accounted for 10% of all US electricity generation for the first time ever, and, by the end of this year, non-hydro renewables are projected to hold a 20% share of the energy market.
As you can see from the charts above, while there has been a steady increase in market share for renewables, its adoption has paled in comparison to other fuel sources. As coal’s role in energy consumption continues to decline, it is expected that renewables and (mostly) natural gas will fill the gap. So why has it taken so long for renewable energies to penetrate the market? As with many new technologies looking to disrupt established industries, there are considerable barriers to entry. According to the Union of Concerned Scientists, the five biggest barriers for renewables to overcome are capital costs, siting and transmission, market entry, unequal playing field, and reliability misconceptions.
- Capital Costs
Unlike other forms of energy, operation and maintenance costs are fairly cheap for renewables, and their fuel is essentially free. As a result, most of the expenses come from building the technology. And, unlike oil and gas which pass much of the costs of fuel onto the consumers, renewables cannot do so. This leads to financial institutions lending at higher rates due to the increased risk of investment.
2. Siting and Transmission
Renewables like solar and wind rely on a decentralized model to source their power. Nuclear, coal, and natural gas rely on few, centralized, high output plants, whereas solar and wind rely on many small generating stations that span across a large area. The concept is very similar to a decentralized blockchain. While decentralization offers many advantages over centralized models, most notably grid resilience, the issues lie in siting and transmission. It can be prohibitively expensive to build a solar or wind farm on a piece of land, since doing so requires myriad hoops to jump through, from permits to contracts to approval by the landowners. All of this takes time and money. Then you need to set up the infrastructure to move the electricity from where it’s generated to where the consumer is.
3. Market Entry
Trying to penetrate an already established and very wealthy industry is no easy task. Tack on the investment risks associated with these projects and it becomes clear why it is taking so long to gain a larger share of the market. In order to gain investor confidence, these projects need to demonstrate scale, specifically an ability to provide energy to consumers when it isn’t windy, or it’s raining or nighttime. Energy storage continues to remain one of the biggest hurdles for renewables to overcome, though significant progress has been made in recent years.
4. Unequal Playing Field
As with all multi-billion dollar industries, established companies have plenty of money to throw around for political influence and favorable policies. According to the IMF, direct and indirect subsidies for coal, oil, and gas rose to nearly $650 billion in 2015, outspending the pentagon by $50 billion in the same year. US taxpayers help fund the industry’s research and development, mining, drilling, and electricity generation. Additionally, the fossil fuel industry spreads misinformation and cherry-picked data to influence consumers and governments. Exxon, for example, has known since the 1980’s about the potential affects and consequences of their emissions.
5. Reliability Misconceptions
As I touched upon earlier, some of the biggest misconceptions about renewable energy are grounded in their cost and their ability to store the energy they generate, specifically for times when there isn’t a constant source providing that energy. While these concerns are legitimate, lots of progress has been made towards ameliorating these issues.
Enter Big Data
As I’m sure we’ve all heard at this point, over 90% of all the world’s data has been created in the past two years. Along with government agencies and corporate America, the renewable energy sector has embraced data analytics to take advantage of big data and machine learning. Here are some ways data analytics are changing the game in renewable energies:
- Predicting Weather from Historical Data
Weather can often be intermittent, making it difficult to accurately predict weather patterns, specifically wind and sunlight. As solar and wind farms operate, they collect and store data. With the rise in big data, predictive analytics and machine learning can be combined with satellite data and historical weather patterns to better predict weather conditions in advance, increasing production and efficiency considerably. Rather than increasing the number of solar and wind farms, the goal is to increase the efficiency or existing infrastructure. IBM’s Hybrid Renewable Energy Forecasting (HyREF) does just this. It boasts a 10% increase in renewable power generation integrated into the grid, enough to power an additional 14,000 homes using the same infrastructure.
2. Streamlining Operations and Management
As solar and wind farms grow and their technologies advance, maintaining these vast farms becomes an increasingly difficult task. To solve these issues, big data analytics can help companies streamline their O&M processes. Extra Storage Space (ESS), one of the largest self-storage management companies in the US, is using big data to more efficiently manage operations of various solar plants. Using Virtual Irradiance (IV), a program that uses big data to collect ground-level irradiance (sunlight intensity) accurately, the program eliminates a need for expensive and potentially faulty on-site sensors. The software collects data on how well solar panels perform in varying weather conditions, and can alert ground crews to locate problems and take swift action.
3. Incentivizing Investors
As previously discussed, financial institutions are apprehensive about investing in renewable energy projects due to the higher risks associated with the technology and an inability to pass much of the costs onto the consumer. Additionally, due to the lack of reliable data on the long-term viability of these projects compared to their established counterparts, investors have been hesitant to back such ventures. Finally, there is an inherent risk relying on relatively unpredictable and uncontrollable weather patterns, making energy output volatile. However, thanks to big data tools, companies are becoming increasingly more efficient at forecasting energy generation based on data collected from past performance and historical weather trends. This information can be used to determine a more precise number of solar panels or wind turbines for a given site, as well as predict the proper energy output. The more accurately these programs can predict energy generation and output, the less risky these ventures become.
Take kWh Analytics, the market leader in solar risk management. They claim that “By leveraging the most comprehensive performance database of solar assets in the United States (20% of the U.S. asset class) and the strength of the global insurance markets, kWh Analytics’ customers are able to minimize risk and increase equity returns of their solar portfolios.” Their Solar Revenue Put helps solar investors reduce their capital costs by improving lender terms and de-risking the asset with an insurance-backed production guarantee for up to 95% of expected energy output. Additionally, their software solution, HelioStats, “enables solar investors to deploy more capital more intelligently by providing data integration, analytics, and performance benchmarking for their solar investments.”
Wrapping Up
Anthropogenic climate change is going to affect billions of lives and all ecosystems we rely on. Our dependence on fossil fuels and the resulting pollution has worsened the Holocene Extinction, the sixth mass extinction event in Earth’s history, that we are currently experiencing. It has been an uphill battle for renewable energies to penetrate the energy industry currently dominated by oil and gas. But as technologies advance and big data plays a big role in predictive analytics and increasing efficiency, our reliance on these harmful fossil fuels can decrease as we turn to more sustainable and clean forms of energy.