Concerns over energy consumption and the impact of fossil fuels on global warming are leading to radical innovations in the field of energy conservation. From advanced AI systems for utilities to simple design elements and smart architectural solutions, widespread adoption lags behind the pace of innovation.
Optimising Consumption: Innovations in Policy and the Market
The concept of net zero energy buildings (designed to consume only as much energy as they produce) has been around for some years, but the industry is still in a nascent stage globally. The US are at the forefront, with California leading the charge, and followed by a string of European countries.
Governments have played a pivotal role in levelling the policy field and spurring adoption of energy conservation strategies. California mandated all new residential developments to be net zero by 2020; commercial by 2030; and has also applied stringent rules on the retrofit market. Similarly, EU regulators have issued directives aimed at making all new buildings nearly zero energy by 2020.
The trend has slowly taken root elsewhere. The largest net zero commercial building in the US opened in Silver Springs near Washington D.C. last year, the Unisphere by the architectural firm EwingCole. The building uses a combination of solar panels, daylight harvesting, natural ventilation, radiant heating, hybrid cooling and pours excess electricity into the utility grid.
In Asia, the National University of Singapore’s School of Design and Environment launched in February 2019, the island city’s ‘first new build net zero energy building’, using similar sustainable and energy conservation strategies.
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Verified Zero Energy Buildings Use Less Than Half the Energy of Typical Buildings in US3
Clever technological solutions, both big and small, support these green achievements.
Smart windows can control the light and heat entering a building or vehicle by turning from clear to dark, thus lowering air conditioning costs. The University of Nevada developed one prototype that does this quicker than any other, achieving 94% opacity in 60 seconds and also removes the unaesthetic bluish tint typical of similar products.
Smart thermostats adapt to user behaviour by learning the habits of a house’s occupants and adjust temperatures accordingly.
Timers can be applied to energy saving outlets to cut off power when chargers are not in use.
Higher up the spectrum, Google is using its AI system, DeepMind, to control its data centre cooling systems. Every 5 minutes, their cloud-based AI pulls data to predict how different combinations of actions will affect energy consumption in the future and identify what steps to take.
Efficient Production and Transmission of Energy
Artificial intelligence is a glittering allure for the energy sector. Researchers at Stanford University, for example, apply AI to enhance grid stability. By assessing data on past power fluctuations and identifying weak spots, the grid harmonises inputs generated by multiple sources (hydropower, wind, solar) with seamless efficiency. Less power outages occur as a result.
Similarly, Google and DeepMind have been applying machine learning algorithms to the wind power industry. Algorithms correlate weather forecasts with historical turbine data predicting output up to 36 hours in advance. Doing so has strengthened the business case for wind power by obviating to one of the industry’s main issues namely the inconsistency of power generation resulting from unpredictable weather.
On the other side of the Atlantic, the UK’s National Grid have been using drones to inspect overhead lines and machine learning technology to analyse the drone footage. AI assesses the condition of the lines identifying the parts in need of repair or replacement.
All this is just a start. The potential to increase efficiency in the generation, transmission and storage of power is endless. According to Frost & Sullivan, a consulting firm, AI will give a boost to the renewable energy sector and allow utility companies to analyse consumer behaviour leading to an optimised distribution of energy supply and demand.
A Case for Widespread Adoption
To reap the benefits of technological prowess, innovation should go hand in hand with large-scale consumer adoption. A survey conducted of top European executives of utility companies by Roland Berger, another consulting firm, on the adoption of ‘smart’ utilities powered by AI, found that even though a majority of CEOs consulted believed that AI will have a big impact on their business, only 5% had a clearly defined implementation roadmap.
Finding a Global Pathway to Adoption
The world can learn from the example set by California and the EU. Policy makers at all levels of government can create incentives for the adoption of energy-efficient technology from a municipal level up until the highest perch of government.
Tax breaks incentivise utility companies to adopt green technology. Deploying AI for example, can streamline the maintenance of power lines especially for providers in poor counties with little cash to spare for expensive physical monitoring by ground experts.
Progress is expensive. International bodies like the World Bank and IMF could step in to help their commitment to green financing. Other big institutional investors can follow the lead of Norway’s enormous sovereign wealth fund, which announced a multi-billion US dollar divestment from fossil fuels and is redirecting that money into green energy initiatives.
Finally, consumers can take it upon themselves to make informed choices and enlarge the market for energy conservation solutions by purchasing products designed to lighten humanity’s footprint on Earth.