Near-Future Trends in the Energy Sector

Whilst many industries have deployed AI and ML applications to solve existing traditional problems. It is the forward-looking possibilities that are more interesting and imperative for the energy domain. This has already given rise to new solutions, which are in turn steering the development of the sector. Such as insight generation, infrastructure planning, and automated decision making

December 20, 2018. By News Bureau

Tags:

There are grand changes stirring in the energy sector. Predominantly rooted in the accelerating rise of renewables. Companies and players across the sector are facing numerous challenges, old and new. These include an urgency to modernise aging infrastructure, a shifting regulatory landscape, increased energy efficiency (EE) programs, and more diverse consumer behaviours. As such, there is a wide array of trends occurring to meet them, some in concert, and others in conflict. 

The IEA has just released its World Energy Outlook for 2018 (WEO 2018). Hearteningly, for the first time in history there are less than 1 billion people who do not have access to energy. But this year will also see energy-related CO2 emissions reaching an historic high. Renewables are still projected to overtake all other sources except gas by 2040. But key to this will be ensuring that their inherent volatility is sufficiently bounded for mass adoption. Renewable electricity generation is carrying ever more expectations, but the extent of its ability to meet demand, and how the future power system will function is still an open path.

The one consistent factor positively driving the rise of renewables, and the trends to be outlined here, is the development of a dazzling span of new technologies. It is quite a task to distil them all down, so instead let’s look at some macro trends which will have a significant influence over the sector, and global energy system.

The most notable common thread across all of these is the application of artificial intelligence (AI) software, or more specifically, its machine learning (ML) aspect. As the volumes of available data to crunch from across the energy system increase, so will the strength and variety of ML applications. With each passing day software ‘machines’ are better learning how to interact with the ever-increasing complexity of the energy system.

So, one macro trend is how AI and ML are increasingly being combined with other technologies, such as the Internet of Things (IoT). Digitisation and digitally interconnected systems are being embraced, to bridge intelligence into operations through big data, analytics, and intelligent algorithms.

Whilst many industries have deployed AI and ML applications to solve existing traditional problems. It is the forward-looking possibilities that are more interesting and imperative for the energy domain. This has already given rise to new solutions, which are in turn steering the development of the sector. Such as insight generation, infrastructure planning, and automated decision making.

Most problem-solving techniques within energy to date, have been developed for the legacy ecosystem, and are typically top-down. This is suited to the former centralised, more regulated, and less dynamic legacy landscape, which is typically focused on generating volumetric trend insights. However, the next trend of more smart-meter integration and so meter-level data, will offer the opportunity for better understanding at a disaggregated level.

Combining granular consumption data across many meters, with other forms of data, will provide tremendous potential for predictive layers of intelligence. These include the impact of changing patterns by specific customers, and better understanding of hidden behaviours. Smart-meters will also mean more visibility of data for consumers. This will be a significant step towards building their awareness, and motivating changes in their behaviour, as part of more effective EE and demand-side management programs?

The future will see more dynamic and varied consumption patterns, which will combine with an increase in variability from the next trend, distributed energy resource (DER) assets. Greater decentralisation of energy will be significantly driven by the increased use of electric vehicles (EVs) and the need for more remote charging. For example, in India there has already been a policy change whereby individuals are now permitted set up EV charging stations, equipped with solar rooftop for self-generation. Through this they can start selling electricity, which further alludes to a more consumer driven energy sector. Blockchain has been promoted as one way to assist with adoption, and as acceptance rapidly grows, feels like a significant near-future follow-on trend.

Within the context of EVs, the most cutting-edge application will of course be self-driving cars, and the complexity will be immense. It will not be possible to follow traditional practices of creating heuristics or setting rules for every possible situation. This will instead need to be done through ML algorithms absorbing many data streams from the environment, to improve real-time reactions through iterative learning. It is worth noting that according to the WEO 2018, oil will remain the dominant transportation fuel for quite some time. Most of the world still only knows about oil and combustion engine vehicles, not EV’s. So, there is still a question mark over when EV’s will hit tipping point, before we can begin to consider when self-driving vehicles will take off.

DERs coupled with distributed resource management systems (DERMs), will be harnessed by the next trend, increasing prevalence of virtual power plants (VPPs). These are cloud-based systems that aggregate and integrate distributed resources, and their capacities and capabilities. Giving a more reliable power supply by enhancing the overall power generation efficiency, and the trading or selling of power on exchanges or the open market. In principle this will benefit the grid and customers alike.

VPPs could partially lead into another likely trend, the advent of new multinational power markets. These have long been established in Europe, for example the Scandinavian common market. But the time may be right for similar attempts in Asia, as national markets become more liberalised. India is already supplying electricity to Bangladesh and Nepal, and now both are permitted to also bid at the Indian Energy Exchange (IEX). So, it is a logical extension that a group of Asian, or African, countries could develop common regional-hub infrastructure for power plants and transmission.

The barriers to such common power infrastructure and markets have been as much political as they are technical. This speaks of the overall golden key required for all of these trends to succeed - The role of government, and strong policy support for new and growing technologies? As the WEO 2018 concludes, the links between energy and geopolitics are only strengthening. Governments will determine where our energy destiny lies. So, the final trend we are optimistic of seeing, is far greater government-to-government, and government-to-business dialogue. To advance and boost the wonderful array of new technologies that will have a critical role to play in a successful renewables transition.

Please share! Email Buffer Digg Facebook Google LinkedIn Pinterest Reddit Twitter
If you want to cooperate with us and would like to reuse some of our content,
please contact: contact@energetica-india.net.
 
 
Next events
 
 
Last interviews
 
Follow us