The recent G7 Summit took bold stands on a variety of issues such as the pandemic response and preparing the global economy for the future. Yet many believe more could have been done on the issue of climate change, especially expediting commitments on net zero carbon emissions and coal phase out.
There are three takeaways here. First, climate change is high on the global agenda, especially in a post-Covid world; second, this is the decade for action on climate change; and third, world leaders must find clear pathways to net zero. There are many paths that companies and organisations can take to reach net zero, which is why you see many trying different approaches to reach their goal. This is a classic situation summarised by American psychologist Barry Schwartz—the Paradox of Choice—that more choices lead to hesitation and dissatisfaction.
Interestingly, a key solution might be more apparent than some realise. Not only does this solution have an entire technology stack already developed and deployed at scale, it can also help achieve 40 percent reduction in energy-related greenhouse gas emissions over two decades. In fact, the International Energy Agency (IEA) calls it the 'first fuel' of a sustainable global energy system. To top it all, this solution has arguably one of the highest returns on investments (RoI) of all solutions out there. This solution is called 'energy efficiency'. Ever since Amory Lovins first talked about this area in his seminal paper 45 years ago, the world has had an ambivalent relationship with energy efficiency.
The idea has always looked attractive on paper, with its own unit of 'negawatt'—a term that represents a watt of energy that you have not used through energy conservation. There have been challenges with execution which may be classified under three broad buckets comprising of CapEx, Measurement, and Savings.
The principal-agent problem arises when the cost is borne by someone else, and the benefits are enjoyed by a different party. This, when coupled with the concept that the upfront CapEx pays itself over a long-time horizon, creates a less-than-desired platform for change. Measurement and verification of savings have been a contentious issue. In fact, the baselining of Business as Usual (BAU) consumption is fraught with debate as there are many ways of deciphering consumption data. Historically, the sustainability of savings has been a challenge. Post-energy efficiency interventions, savings start eroding as reflex behaviour begins to take root again for a variety of reasons. Therefore, the stickiness of savings is a pain point.
These are all valid concerns. However, we are at an inflection point where these concerns can be addressed comprehensively through a mix of financial and technological levers. Let me address them one by one:
Financial engineering: Energy efficiency projects get top-notch billing from lending institutions as they promise savings. In addition, a record amount of patient capital is moving into this space, which has a longer time horizon for returns. In combination, it provides the upfront CapEx paid by a financial entity in exchange for a return horizon over the lifecycle of the project. This removes the challenge around the principal-agent problem described above. A classic example of this is the newly launched Decarbonisation Partners by BlackRock and Temasek, which invests in decarbonisation solutions.
Global measurement and verification protocols: Over the years, many internationally reputed global protocols have been developed that address the issue of measurement and verification of savings, including the knotty problem of benchmarking. In addition, there are many technologies available that not only allow us to create a believable baseline but also bankable savings.
Stickiness of savings: For me, this is the most exciting development in recent times. The sustainable realisation of energy efficiency savings used to be largely predicated on a better-trained workforce that would work to keep a facility at the renewed level of efficiency. That stickiness is difficult to maintain. Technology is addressing this problem with machine learning algorithms that provide independent inputs on the right level of efficiency of various components of a building, so one can measure against this automated feedback loop to create savings. What’s more, since these systems are self-learning, they can deliver additional savings each year by analysing more operational data. The self-learning capabilities of the software can far exceed what humans can achieve on their own.
While energy efficiency might have had its share of issues in the past, with focused attention, there are great strides that can be made to reach these goals.
The writer is a vice president and general manager at Honeywell Building Technologies – India, ASEAN, Korea.
The thoughts and opinions shared here are of the author.
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