With the dramatic increase and distribution of energy production and storage, as well as the growth of electricity consumers, we face more complex and severe challenges. However, it is also an important opportunity to promote energy efficiency and prioritise green energy.
We can restructure the market to incentivise the most effective strategies to reduce overall resource waste and increase productivity by reducing electricity demand and balancing peaks.
I believe we have a major opportunity to reshape the energy ecosystem with software, data, cloud computing and artificial intelligence. We could even call it the "Energy Internet" (IoE), a concept that could become a reality in the near future.
For years, people have been talking about the innovative potential of the "software layer" for energy markets. The software layer covers both market rules, such as pricing and taxes, and software that runs the entire energy system, analyzing and forecasting, and even performing tasks such as operating water pumps or air conditioning systems intelligently.
Software, AI and other energy Internet innovations make this possible.
Software brings all the power together
Let's take a break from the chaos of the real world, because solving real problems is complicated and exhausting.
Consider this: Energy prices are fully dynamic, real-time and open to incremental participants who can sell their energy to the grid. Such energy can be priced to accurately reflect its "greenness" (that is, its share of carbon dioxide), the efficiency and abundance of energy production. On a given day, when wind turbines in an area are running at full capacity, wind prices reach a low and thermal power prices peak.
If we can establish this kind of transparent market pricing system, we can create an ecosystem for AI-driven third-party energy optimization programs in different scenarios and industries.
Optimizing energy ecosystems with software solutions
Every customer, from desalination plants to electric car owners, would benefit equally from an optimized tariff mechanism, which in turn would reflect other factors such as the greenness, abundance and marginal cost of energy.
Let's take this one step further and consider this exciting scenario: a future of internet-connected energy-consuming devices that can drive demand in line with energy targets and prices. Imagine building cooling systems in sync with green power generation systems. Pumps and even electric vehicles, water heaters or air conditioners in fields can work in conjunction with the grid to meet heating, cooling and charging needs. This approach not only optimises electricity prices, but also reduces waste and emissions, helping to maximise the value of existing infrastructure.
Let us also not forget that, in certain circumstances, energy consumers may also become energy suppliers. Future electric cars could also supply power to the grid at a reasonable price when energy needs to be stored.
Energy Internet for Speed
As the energy transition accelerates, we need to consider how to make more use of the energy Internet. The key challenge is to find and launch the right projects and to collaborate with all participants to accelerate progress.
Over the past few decades, we've learned that software can travel at the speed of light. It runs efficiently, drives productivity quickly, and helps us explore and improve every day.
In terms of urgency, this "software layer" in our energy ecosystem could work with existing hardware, such as factories and equipment, and sensor-equipped data flow and execution components could potentially reduce costs. So I believe these AI solutions can be faster than building new infrastructure or upgrading hardware. With this in mind, we can leverage a growing number of software-driven approaches to accelerate the energy transition.
Energy exists in a wide range of ecosystems to meet basic human needs. The power industry is water intensive. Agriculture is also completely dependent on water. In large developed countries such as the United States, agriculture accounts for about 40 percent of water consumption and another 40 percent goes to power systems.
Look beyond "FEW"
The energy transition will be more promising if we address our energy transition needs in three aspects: food, energy and water (FEW).
Often, upgrading to photovoltaic or wind power reduces dependence on water. For water-stressed areas, this can inspire people to think of new ways to improve water use.
AI contributes to efficient water use strategies. For outdoor agriculture, some AI strategies can reduce water use by up to 40 percent while promoting crop health and productivity in precise, smart ways. At the same time, it takes a lot of energy to pump water, so we can save a lot of energy and water simply by improving crop health.
On the other hand, even if renewable energy is used in agriculture, it does not mean that we can pump a lot of water into farmland. AI can help us iterate on optimization directions, such as crop health, and help us find strategies to save precious FEW resources.
The combination of the aforementioned IOE-driven strategies has the greatest effectiveness. In the future, through software and data, many optimization systems can communicate with each other and work together to maximize efficiency and achieve optimization. AI, software and cloud technologies will help us save energy, maximize green energy, save water, and increase agricultural and industrial productivity.
But most of all, it's about improving the quality of human life in challenging circumstances.
