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The Internet of Things (IoT) has the potential to significantly transform the industrial sector. The McKinsey Global Institute predicts that the total potential economic impact of IoT will be in the rangeof $3.9 trillion to $11.1 trillion per year in 2025.1
On the top end, this would amount to 11% of the world economy. General Electric (GE)predicts that $1.3 trillion of value can be captured in the electricity value chain from 2016 to 2025 globally by IoT.2
In its simplest form, IoT has three components: digitization of assets, collection of data about the assets,and computational algorithms to control the system formed by the interconnected assets. Although
there is a lot of hype around IoT, the power sector has been the beneficiary of two recognizable early consumer-oriented applications of IoT: smart meters and smart thermostats.
In its initial incarnation, smart meters were internet-connected devices to send electricity consumption data to the utility. In newer incarnations, a variety of add-on services have been created, for instance
customer services like energy management portal, net metering, prepaid purchase of electricity, and data analytics based services for utilities like outage location, pilferage identification, management
of distribution voltage to reduce losses, and others. After the installation of advanced metering infrastructure (AMI), the city of Burbank, California reported 1%–2% reduction in usage per customer,
87% reduction in field visits to customers, 15 minutes or less response time as opposed to hours or days to metering-related customer requests, and improvement to reliability of grid with drop in System
Average Interruption Frequency Index (SAIFI) from 0.34 to 0.24, and System Average Interruption Duration Index (SAIDI) from 27.8 minutes to 9.5 minutes.3
Smart thermostats are internet-connected devices that measure temperature and/or humidity inside a home or office and send the data to the cloud. An automated algorithm or an authorized user on
a smart phone can change the temperature setting of the thermostat. A variety of machine-learning applications have been developed to balance energy-saving and user-customized comfort. Nest, a
leading manufacturer of smart thermostats has reported a drop in electricity bill of 10%–12% for heating and about 15% for cooling.4 Extending this concept to large commercial buildings, according to a study
conducted by Gartner, an integrated building management system that manages cooling, heating, and lighting can help reduce energy consumption by 50%.5
In Asia, several pilots of smart meters, smart buildings, and smart cities are ongoing. Smart meters have the potential to significantly improve customer service and reduce cost through easier payments and
better outage management; improve energy access by enabling new business models for providing electricity in off-grid applications. Smart thermostats and smart meters in conjunction with other IoT solutions have the potential to spur a variety of smart buildings and smart city applications.
                                                                                                       The Internet of Things in the Power Sector
More recently, IoT solutions are entering the domain of industrial operations. In the power sector, the most popular application in this category is condition monitoring and predictive maintenance of a wide
variety of assets. The IoT-based approach transitions from traditional reactive and periodic maintenance strategies to proactive strategies. The applications are focused on the highest value assets in generation
plants, and in the transmission and distribution grid. In this application of IoT, assets are continuously monitored with sensors, the collected data is sent to the cloud where a variety of machine learning and
artificial intelligence algorithms are used to predict the health and impending failure of the assets, and determine the optimal time to perform maintenance.
In Asia, many grids are plagued with unreliable service. This is primarily because of aging equipment; poor maintenance; and in many cases, the struggle to upgrade power systems to keep up with very high
annual demand growth rates. Investment in IoT for both existing and new equipment has the potential to significantly reduce unscheduled downtime by identifying problems before they occur, thereby
improving reliability and reducing costs. According to the Asian Development Bank (ADB) publication Energy Outlook 2013, Asia and the Pacific will require a cumulative investment of about $11.7 trillion
in the energy sector to meet business as usual (BAU) energy demand from 2010 to 2035. Demand side investments (additional to BAU case) of $ 7.3 trillion will be required to deploy advanced energyefficient
technologies for transport, residential, commercial, and industrial sectors. Other applications of IoT are optimal use of generation assets to increase the efficiency of production.
In conventional power plants, IoT would be used to tune the operation of a power plant in real time and to balance production with life cycle cost of maintenance and life of equipment. As an example,
GE has launched digital power plant systems for gas and coal plants. GE claims its digital technologies when applied to new coal and gas fired power plants can increase fuel efficiency by 3%, power output
by 2%, and reduce unplanned downtime by 5%, operation and maintenance costs by 25%, and fuel consumption during starts by 20%.6
 In Asia, these strategies may be used to reduce cost of electricity production and emissions.
Another good example of IoT use for optimization of operations is in the wind power industry where
(i) wake losses are reduced in a wind farm by adjusting pitch and yaw angles of individual turbines,
(ii) turbines production is increased above rated value in a controlled manner as long as the stress and
fatigue loading are within acceptable limit, and (iii) settings of individual turbines are optimized to local
conditions to increase output. GE claims a 5% to 10% increase in annual energy production with these
A futuristic application of IoT is a holistic optimization of the entire power network with the goal of decentralization and defossilization of the power sector. IoT has the potential to achieve such a
transformation in which (i) renewable energy is generated close to load centers; (ii) energy storage devices are used to store excess energy and deliver energy during periods of high demand; (iii) demand
response is used to balance supply and demand; (iv) flexible centralized fossil fuel-based power plants plan production based on real-time predictions of variable renewable generators; and (v) dispatch logic,
and controllers are used to manage the flow of power. Several of these transformations are being tested in a number of pilots in island grids in Asia with the goal of achieving close to 100% renewable energy in
the power sector and IoT will be a key enabler.
viii   Sustainable Development Working Paper Series No. 48
There are several challenges to the adoption of IoT in Asia and the Pacific. The following list summarizes
the challenges and the way forward:
(i) Financial constraints. A large amount of investment would be required to modernize the energy infrastructure in Asia and the Pacific to achieve the benefits of IoT. It should be noted that this
investment is much less than the larger infrastructure investment. IoT investment should be done alongside new infrastructure investments. For existing equipment, the balance sheet of
many utilities may not be healthy for market-based financing of IoT projects, therefore it may be impossible to structure results-based or outcome-based vendor or commercial financing for the
IoT projects. ADB has worked with and invested in state-owned utilities since its founding. It is therefore in a unique position, using results-based lending, sovereign lending and other financial
vehicles, to enable the IoT transformation, thereby assisting the utilities toward achieving higher reliability, efficiency, and customer satisfaction.
(ii) Policy impediments. The power subsidy policy in many countries in Asia and the Pacific disincentivizes market-based investment in energy infrastructure. In addition, there is political
pressure to keep electricity rates low and employ large numbers of people. These are not conducive to increasing efficiency through IoT driven automation. ADB-funded development
interventions such as technical assistance programs and loans may be a vehicle for these countries to develop an IoT transformation road map that is based on best practices and lessons
learned from similar initiatives (e.g., telecommunications, online banking, online retailing, and others).
(iii)Capacity limitations. Strong information and communication technology and analytics
skills would be required to fully realize the benefits of IoT, and these skills may not be readily
available in these countries. Furthermore, strong capability would be required to implement
business transformation of the magnitude required by IoT projects to gain higher efficiencies
and reliability, and overall lower cost. Given these requirements, an IoT road map should have
capacity building and knowledge transfer as one of the focus areas so that skills development is an essential part of the transformation. 



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