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Renewables heat up

Renewables, smart homes, AI and IoT will have a massive impact on how energy companies need to address the market in 2018, predicts COLIN BEANEY, IFS’s Global Industry Director for Energy & Utilities.

Every year we’re seeing a virtuous circle speeding up around renewables; 2018 will be no exception. The more renewables are taken up, the smarter and more scalable the technology becomes, with lower construction, operating and maintenance costs. Crucially, the cheaper the energy produced becomes too.

In 2009, it cost just under US$ 300 to generate 1 MW of electricity using solar photovoltaic panels. In 2016, the cost was down to US$ 100. All around the world, renewables companies are now able to offer cheaper energy alternatives. In September 2016 in Nevada, state energy provider NV Energy lost almost 6 percent of its customer base overnight as 15 of the top casinos and hotels in Las Vegas switched over to smaller renewable energy providers. Why? “The sharp decline in the cost of renewable energy” and “being able to control what your supply looks like”, said MGM Resorts, one of the main companies moving account.

BMI’s 2017 Global Renewables Outlook predicts ‘the capacity of renewables will double between 2016 and 2026’. A 2017 Financial Times report, The Big Green Bang, how renewable energy became unstoppable, shows that renewables capacity globally rose by 9 percent in 2016, a 400 percent increase from 2000. Solar power increased by 30 percent worldwide in 2016, and for the second year in a row renewable energy made up more than half the world’s new power generation capacity.

Asian countries are spearheading the development. China accounted for more than 40 percent of capacity growth in global renewable energy in 2016, but other high-power Asian markets, like India, Malaysia, and the Philippines are also expanding in renewables. This boom will in turn affect players in other geographies that will not want to fall behind.

How will this impact energy providers? Most important will be the new opportunities to adapt your business model, join new joint ventures or create new charging models—all these will be essential. Take energy provider Octopus, which delivers renewable pay-as-you-go energy through its easy-to-use online portal to customers in the UK and France. Octopus is now the UK’s largest investor in solar farms, but focuses heavily on customer service, flexible payment models and transparent billing as key customer benefits—as well as renewable energy.

With smart homes, consumers will call the shots

Amazon Alexa, Google Home, the Sony LF-S50G, the Harman Kardon Allure – what has this new generation of smart home assistants got to do with Energy & Utilities? Potentially, a lot. According to analysts like RBC’s Mark Mahaney, Alexa could earn US$10 billion for Amazon by 2020. In addition, MarketsandMarkets predicts that the smart home market will be worth US$ 138 billion by 2023.

Smart meters constitute a big part of this, enabling customers to check and calculate their real-time energy consumption levels in the home to take appropriate steps to cut down energy costs. Thus, smart meters are expected to hold a major share of the smart home market by 2023.

With one single solution for switching between devices in the home, consuming and storing energy and controlling its costs, consumers will have an increasingly powerful role. Following this, they will be in a position to drive even more flexible service and billing systems.

One example of companies leveraging this demand for increased flexibility is HomeServe, a one-stop digital service company providing emergency and energy services to the home. Through its monthly digital subscription model, it supplies services to over 7.8 million homes in the UK and over 3 million homes in the US—including energy services, boilers and meters through third-party suppliers. HomeServe itself owns no energy assets, but with its strong customer service and simple payment models generating powerful loyalty and revenue, service providers like HomeServe could become energy providers—soon, as customer-centric energy provision booms.

The success of agile, customer-centric firms like HomeServe and Octopus is a wake-up call for energy providers. Customers increasingly hold the balance of power in a digital market. For Energy & Utilities companies, it is a reminder of how new vital, flexible, and agile billing and service, as well as operations, can pose either a competitive advantage or a threat— depending on how you are addressing the market.

The industry gets smarter as AI and IoT move ahead

As consumer demand dictates energy supply and billing, IoT, machine learning and AI capabilities will add another dimension to this, not just in the field at the edge of operations, but at the heart of products and in homes, too.

Gartner predicts that “by 2022, more than 80 percent of enterprise IoT projects will have an AI component, up from less than 10 percent today.” But what would a machine-to-machine, cloud-based energy system, discretely sited in consumers’ homes, look like? In 2016 in Hawaii, Microsoft collaborated on a renewable energy initiative using 499 IoT-connected home water heaters, all IoT-enabled and connected to Microsoft Azure Cloud, to create an autonomous discrete energy grid that stores overspill energy for future use. The 499 water heaters are called Grid-Interactive Electric Thermal Storage (GETS) devices. The machines monitor energy consumption and performance, and store hot water when there is a surfeit of renewable solar and wind energy. Each heater is able to store 52 – 120 gallons of piping hot water. Combined, the water heaters can hold 15 to 25 kilowatt-hours energy. Hawaii spends about US$ 6 billion every year importing oil, so being able to store excess renewably generated energy could have a major impact, helping Hawaii reach its goal of its state utilities generating 100 percent of its electricity from renewable resources by 2045. One of the most impressive aspects of the Hawaii story is its precision business case. For an island with a lot of renewable wind and solar energy, storage was a key priority and would deliver obvious customer benefits.

For energy providers, 2018 will be about finding the sweet spot, connecting consumers’ demands for increased flexibility and cost control to new services and charging models based on renewable energy sources and emerging technologies—those who succeed with this will be the winners.

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Now IBM’s Watson joins IoT revolution in agriculture

Global expansion of the Watson Decision Platform taps into AI, weather and IoT data to boost production

IBM has announced the global expansion of Watson Decision Platform for Agriculture, with AI technology tailored for new crops and specific regions to help feed a growing population. For the first time, IBM is providing a global agriculture solution that combines predictive technology with data from The Weather Company, an IBM Business, and IoT data to help give farmers around the world greater insights about planning, ploughing, planting, spraying and harvesting.

By 2050, the world will need to feed two billion more people without an increase in arable land [1]. IBM is combining power weather data – including historical, current and forecast data and weather prediction models from The Weather Company – with crop models to help improve yield forecast accuracy, generate value, and increase both farm production and profitability.

Roric Paulman, owner/operator of Paulman Farms in Southwest Nebraska, said: “As a farmer, the wild card is always weather. IBM overlays weather details with my own data and historical information to help me apply, verify, and make decisions. For example, our farm is in a highly restricted water basin, so the ability to better anticipate rain not only saves me money but also helps me save precious natural resources.”

New crop models include corn, wheat, soy, cotton, sorghum, barley, sugar cane and potato, with more coming soon. These models will now be available in the Africa, U.S. Canada, Mexico, and Brazil, as well as new markets across Europe and Australia.

Kristen Lauria, general manager of Watson Media and Weather Solutions at IBM, said: “These days farmers don’t just farm food, they also cultivate data – from drones flying over fields to smart irrigation systems, and IoT sensors affixed to combines, seeders, sprayers and other equipment. Most of the time, this data is left on the vine — never analysed or used to derive insights. Watson Decision Platform for Agriculture aims to change that by offering tools and solutions to help growers make more informed decisions about their crops.” 

The average farm generates an estimated 500,000 data points per day, which will grow to 4 million data points by 2036 [2]. Applying AI and analysis to aggregated field, machine and environmental data can help improve shared insights between growers and enterprises across the agriculture ecosystem. With a better view of the fields, growers can see what’s working on certain farms and share best practices with other farmers. The platform assesses data in an electronic field record to identify and communicate crop management patterns and insights. Enterprise businesses such as food companies, grain processors, or produce distributors can then work with farmers to leverage those insights. It helps track crop yield as well as the environmental, weather and plant biologic conditions that go into a good or bad yield, such as irrigation management, pest and disease risk analysis and cohort analysis for comparing similar subsets of fields.

The result isn’t just more productive farmers. Watson Decision Platform for Agriculture could help a livestock company eliminate a certain mold or fungus from feed supply grains or help identify the best crop irrigation practices for farmers to use in drought-stricken areas like California. It could help deliver the perfect French fry for a fast food chain that needs longer – not fatter – potatoes from its network of growers. Or it could help a beer distributor produce a more affordable premium beer by growing higher quality barley that meets the standard required to become malting barley.

Watson Decision Platform for Agriculture is built on IBM PAIRS Geoscope from IBM Research, which quickly processes massive, complex geospatial and time-based datasets collected by satellites, drones, aerial flights, millions of IoT sensors and weather models. It crunches large, complex data and creates insights quickly and easily so farmers and food companies can focus on growing crops for global communities.

IBM and The Weather Company help the agriculture industry find value in weather insights. IBM Research collaborates with start up Hello Tractor to integrate The Weather Company data, remote sensing data (e.g., satellite), and IoT data from tractors. IBM also works with crop nutrition leader Yara to include hyperlocal weather forecasts in its digital platform for real-time recommendations, tailored to specific fields or crops. IBM acquired The Weather Company in 2016 and has since been helping clients better understand and mitigate the cost of weather on their businesses. The global expansion of Watson Decision Platform for Agriculture is the latest innovation in IBM’s efforts to make weather a more predictable business consideration. Also just announced, Weather Signals is a new AI-based tool that merges The Weather Company data with a company’s own operations data to reveal how minor fluctuations in weather affects business.

The combination of rich weather forecast data from The Weather Company and IBM’s AI and Cloud technologies is designed to provide a unique capability, which is being leveraged by agriculture, energy and utility companies, airlines, retailers and many others to make informed business decisions.

[1] The UN Department of Economic and Social Affairs, “World Population Prospects: The 2017 Revision”

[2] Business Insider Intelligence, 2016 report: https://www.businessinsider.com/internet-of-things-smart-agriculture-2016-10


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What if Amazon used AI to take on factories?

By ANTONY BOURNE, IFS Global Industry Director for Manufacturing

Amazon recently announced record profits of $3.03bn, breaking its own record for the third consecutive time. However, Amazon appears to be at a crossroads as to where it heads next. Beyond pouring additional energy into Amazon Prime, many have wondered whether the company may decide to enter an entirely new sector such as manufacturing to drive future growth, after all, it seems a logical step for the company with its finger in so many pies.

At this point, it is unclear whether Amazon would truly ‘get its hands dirty’ by manufacturing its own products on a grand scale. But what if it did? It’s worth exploring this reality. What if Amazon did decide to move into manufacturing, a sector dominated by traditional firms and one that is yet to see an explosive tech rival enter? After all, many similarly positioned tech giants have stuck to providing data analytics services or consulting to these firms rather than genuinely engaging with and analysing manufacturing techniques directly.

If Amazon did factories

If Amazon decided to take a step into manufacturing, it is likely that they could use the Echo range as a template of what AI can achieve. In recent years,Amazon gained expertise on the way to designing its Echo home speaker range that features Alexa, an artificial intelligence and IoT-based digital assistant.Amazon could replicate a similar form with the deployment of AI and Industrial IoT (IIoT) to create an autonomously-run smart manufacturing plant. Such a plant could feature IIoT sensors to enable the machinery to be run remotely and self-aware; managing external inputs and outputs such as supply deliveries and the shipping of finished goods. Just-in-time logistics would remove the need for warehousing while other machines could be placed in charge of maintenance using AI and remote access. Through this, Amazon could radically reduce the need for human labour and interaction in manufacturing as the use of AI, IIoT and data analytics will leave only the human role for monitoring and strategic evaluation. Amazon has been using autonomous robots in their logistics and distribution centres since 2017. As demonstrated with the Echo range, this technology is available now, with the full capabilities of Blockchain and 5G soon to be realised and allowing an exponentially-increased amount of data to be received, processed and communicated.

Manufacturing with knowledge

Theorising what Amazon’s manufacturing debut would look like provides a stark learning opportunity for traditional manufacturers. After all, wheneverAmazon has entered the fray in other traditional industries such as retail and logistics, the sector has never remained the same again. The key takeaway for manufacturers is that now is the time to start leveraging the sort of technologies and approaches to data management that Amazon is already doing in its current operations. When thinking about how to implement AI and new technologies in existing environments, specific end-business goals and targets must be considered, or else the end result will fail to live up to the most optimistic of expectations. As with any target and goal, the more targeted your objectives, the more competitive and transformative your results. Once specific targets and deliverables have been considered, the resources and methods of implementation must also be considered. As Amazon did with early automation of their distribution and logistics centres, manufacturers need to implement change gradually and be focused on achieving small and incremental results that will generate wider momentum and the appetite to lead more expansive changes.

In implementing newer technologies, manufacturers need to bear in mind two fundamental aspects of implementation: software and hardware solutions. Enterprise Resource Planning (ERP) software, which is increasingly bolstered by AI, will enable manufacturers to leverage the data from connected IoT devices, sensors, and automated systems from the factory floor and the wider business. ERP software will be the key to making strategic decisions and executing routine operational tasks more efficiently. This will allow manufacturers to keep on top of trends and deliver real-time forecasting and spot any potential problems before they impact the wider business.

As for the hardware, stock management drones and sensor-embedded hardware will be the eyes through which manufacturers view the impact emerging technologies bring to their operations. Unlike manual stock audits and counting, drones with AI capabilities can monitor stock intelligently around production so that operations are not disrupted or halted. Manufacturers will be able to see what is working, what is going wrong, and where there is potential for further improvement and change.

Knowledge for manufacturing

For many traditional manufacturers, they may see Amazon as a looming threat, and smart-factory technologies such as AI and Robotic Process Automation (RPA) as a far off utopia. However, 2019 presents a perfect opportunity for manufacturers themselves to really determine how the tech giants and emerging technologies will affect the industry. Technologies such as AI and IoT are available today; and the full benefits of these technologies will only deepen as they are implemented alongside the maturing of other emerging technologies such as 5G and Blockchain in the next 3-5 years. Manufacturers need to analyse the needs which these technologies can address and produce a proper plan on how to gradually implement these technologies to address specific targets and deliverables. AI-based software and hardware solutions will fundamentally revolutionise manufacturing, yet for 2019, manufacturers just have to be willing to make the first steps in modernisation.

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