EnergyTech – The New World for Energy through Technology


Technological innovation in the energy industry is not a choice anymore, it is essential. We must stop thinking of ourselves as energy companies. To thrive today, harnessing the abilities and tools of today’s world, we need to be Tech companies that focus on Energy. Utilising Big Data Analytics, Machine Learning, AI and blockchain to name but a few, our opportunity to transform the industry is both massive and critical.

The energy mix has changed. 5 years ago, 35% of our energy was produced by coal. Today that has reduced to just 3% of our combined energy source. In contrast, renewables have increased from 12% to 30% of the energy mix. We have not seen this sort of rapid change since the dash for gas in the 1990’s (30 years ago). This surge towards renewable power started via the race for renewable certificates. However, residential solar is already at a position of grid parity and according to UBS and the Rocky Mountain Institute, residential solar plus storage will achieve parity by 2020.

We have also seen the demand for electricity drop. In the past 5 years alone, demand has dropped by approximately 10GW while the number of devices we own has increased exponentially. This reduction has developed through a combination of energy efficiency and increasingly smart demand-side management via peaking units, residential solar and the like. This downward shift in national demand is likely to continue with solar & storage, Electric Vehicles and infrastructure initiatives such as microgrids like the Brooklyn – Queens energy project USA example which allows communities to trade electricity with each other. These initiatives will reduce the reliance on the National Grid, creating sustainable local Energy Markets.

Many commentators have bought into the opinion that this could accelerate the Death Spiral it does indicate that the old ways of energy infrastructure, the silos that dominant companies implemented to deal with the old residential and generation ways of distribution, are no longer fit for purpose.


A connected home department that is not developing efficient control over a large number of assets through their connected homes is missing the point of smart connectivity.


Electric Vehicles

The sale of new fossil fuel cars is set to be phased out in Scotland by 2032 and the rest of the UK by 2040, Europe 2025-2040 as well as India and other Asian nations by 2040. With China also considering the ban, car manufacturers are not going to invest in developing new fossil fuel cars. The electrification of our cars could well revolutionalise the industry before the 2040 deadline and will be the world’s largest distributed energy storage solution. It will also reduce the cost of residential storage as car batteries reemployed after their car life, are ideal for residential use.


This trend will dramatically change the structure and fuel mix of the energy market.


Big Data


The increased use of sensors and real-time data collection has seen exponential growth in the volume and variety of the data gathered from customers. This data only becomes useful when utilized properly and effectively. With the correctly applied analytics, faster and more efficient business decisions can be made to power our energy industry.


By 2020 it is predicted that 1.7MB of new information will be created per person per second. Considering the population of the planet by 2020 is forecasted to reach 7.8bn, it means in a second there will be 13,260,000,000 MB of data produced and available to use. Half a quintillion MB every year. This increase in data is in part due to the explosion of IoT. How we harness this multitude of data points, how we determine insights and understand both predictive and insight into the date created will determine the smart ability of a business. Total Connectivity is the stage we are moving towards. Being able to turn your lights on from the other side of the world is a nice gadget but has limited benefit. However, a smart connected energy company, a DNO or a collection of consumers being able to automatically dim the lighting of multiple homes in peak periods does provide intrinsic economic value. This is the energy connectivity tipping point where usability meets business revenue.


As an industry, we need to get smarter on; how we are going to use the data produced from the connectivity of IOT and deliver real-world scenarios that customers will appreciate while creating the revenue stream an energy business requires. This is why we built a customer experience team at Limejump, we want to work with customers to create products and solutions that work for them. There are 50billion smart devices out there which generate an overwhelming amount of data yet less than 0.5% of that data is ever used. A report from the US said that for a fortune 1000company a 10% increase in data use would result in $65million of additional income. Think about that, by moving from using 0.5% of our data to using 0.55% we can receive $65 million more in income, a clear financial win.



The possibilities of AI are endless from customer service, answering technical questions from engineers to better-predicting weather forecasts, demand and generation forecasts. The information flow from all this data is huge.

Demand management is also seeing an explosion of AI activity: For example:

With DeepMind, Google was able to reduce its total data center power consumption by 15% which will be hundreds of millions of dollars over the next few years.

    • They have also used AI to save 40% on power consumed for cooling.


  • In a test by Siemens in 2017, AI took over control of a gas turbine in Asia resulting in nitrogen oxide levels dropping by 20% percent.

The effect of this automated data collection, the efficiency of automated, data-supported decision making, mixed with the right people with the correct skill set leads to educated data usage and reporting. The old paradigm that knowledge is king proves true as the correct application of machine learning that drives sustainable decision making, advanced business thinking, combined with human ability will lead to improved customer solutions and service. Not to forget, increasing efficiency and thus revenue while retaining the human element of customer service provides that sweet spot for product, price and promise.

Customers are looking at ways to solve their own problems, give them more time, improve their lives. Generally, people want an easier life and with AI and IOT its easier than ever to give them a solution that works for everyone individually and works for the Energy company collectively. Providing any incremental improvement such as forecasting analytics through expert human and machine learning provides that extra ability that customers prize.

Utilising big data, AI and retaining that human connection is the driver to produce the EnergyTech of the future. At Limejump, that future is now.

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