Top Cleantech Trends to Watch in 2016

By Posted on January 13, 2016

Swad Komanduri
Manager, Market Analysis (VFA), NextEnergy

As the new year gets underway, it is natural for “lists” of trends to be made. NextEnergy’s market analysis team synthesized these lists to find the trends most likely to impact our technology partners and policymakers. Five key trends were identified by NextEnergy staff: increased integration of demand response capable devices, increased automation in power flow decisions, increased development of new materials enabling energy efficiency, hastened pace of demand for energy storage, and increased use of real-time big data analytics.

With the announcement of the Clean Power Plan in 2015, its effects will start to take shape in 2016. While the plan provides states the flexibility to develop their own portfolio of technologies and policies to meet requirements, there are solutions that naturally lend themselves to adoption based on the provisions. The primary such solution is increased adoption of demand-side energy efficiency technologies. By allowing emissions targets to be met by energy efficiency programs, the Clean Power Plan encourages states to adopt low cost, high impact solutions to reduce the demand for fossil fuels. According to Joshua Brugeman, Director of Energy Efficiency at NextEnergy, “energy efficiency and demand reduction measures are cost-effective solutions for states to meet the Clean Power Plan requirements.” As a result, the EPA estimates that the overall electricity demand will reduce by 7% by 2030. Numerous demand response programs have already been deployed in pilot programs across the nation, and technologies such as smart thermostats have played a role in their success. Look for demand-response capable devices and systems to have increased adoption in the coming year.

Along the same lines, in order to accomplish the energy efficiency needs, power flow decision will be increasingly automated. The algorithms needed to make these decisions are a key area of technological focus according the Department of Energy’s Quadrennial Technology Review. These systems combined with smart, demand-response capable equipment will be the primary beneficiaries of the federal government’s push towards increased efficiency.

A complementary method to achieving efficiency gains is through the use of new materials. Specifically for building and automotive technologies, new materials to reduce the energy demands of particular interest to the major players. On the building side, the development of materials to better insulate windows and building skeletons have been an area of focus in the DOE emerging technology roadmaps. On the vehicle side, the focus on light-weighting and transition to electric vehicles has created a demand for new and innovative materials.

Another key effect of the shift away from fossil fuels is the increased adoption of intermittent energy sources, such as solar and wind power. Since these systems require energy storage to increase their consistency and reliability, stationary energy storage systems should see increased adoption as well. These systems will vary in scale, from grid scale to residential scale, depending on the particular approaches adopted by states, but overall the Clean Power Plan should increase the demand for stationary energy storage.

An underlying current to the vast majority of technology and policy development is the presence and importance of big data. The first manifestation of this is the coming of the “connected world.” The utility of obtaining and communicating data is clearer than ever before, and the demand is now for new products and devices that are capable of doing so. Therefore, many hitherto isolated systems will be equipped with communication capabilities. This creates opportunities for new business models, particularly when systems involving data from multiple sources begin to communicate with one another. In order to ensure that this is feasible and reliable, the development of communication standards and protocols focused on interoperability will be key. With many devices capable of communicating vast amounts of information, the processing of data becomes vital. There are two main needs with the emergence of big data. Firstly, the ability to process and visualize the meaning of the data to humans is key. Therefore, methods to analyze and present relevant data in real time to key stakeholders will be in demand more than ever. Secondly, the ability to use data to make predictions is also in demand. By drawing conclusions from the available data and using predictive analytics to shape, guide, and automate decision making will be important in the years to come.

2016 should be an exciting year!

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