What does ChatGPT think about energy optimisation in buildings?

What does ChatGPT think about energy optimisation in buildings?

Authors: Jayantika Soni and OpenAI’s ChatGPT

I asked OpenAI's #ChatGPT What are the challenges in energy optimisation in buildings in the tropics?

It churned out: 

“Energy optimization in buildings in tropical regions can present a number of challenges, including:

1. High temperatures and humidity: Buildings in tropical regions need to be designed to withstand high temperatures and humidity, which can lead to increased energy consumption for cooling.

2. Insufficient insulation: Many buildings in tropical regions may not have sufficient insulation, which can lead to increased energy consumption for heating and cooling.

3. Lack of energy-efficient building materials: The availability of energy-efficient building materials in tropical regions may be limited, which can make it difficult to construct buildings that are energy-efficient.

4. Limited access to renewable energy sources: Many tropical regions may have limited access to renewable energy sources, such as solar or wind power, which can make it more difficult to reduce energy consumption in buildings.

5. High cost of energy: The price of energy in tropical regions may be high, which can make it more difficult to invest in energy-efficient technologies and practices.

6. Non-availability of energy data: There may be a lack of energy data available for tropical regions, which can make it difficult to identify opportunities for energy savings and to track progress in energy efficiency.”

All of these are extremely valid points. But it still begs the question of what prohibits building owners to overcome these challenges. In our work at Resync, we have seen financial investment in bigger ticket items like insulation and renewable energy sources to adopt these technologies which can help them save costs. However, given the dynamic nature of Singapore’s real estate market, it also makes sense to building owners to often focus on solutions that can provide immediate benefits than doing CAPEX-heavy solutions such as renewables. Also, Singapore is densely packed with vertical buildings catering to more people/energy usage per sqm, thus the space for renewables like solar is quite limited. It is altogether a different topic of discussion that the variation in weather in the tropics may cause fluctuations in the energy generated and thus used in building/supplied to the grid.

Given this context, I asked ChatGPT further questions on what impedes building owners to do something about this problem. [Side note: I like how ChatGPT remembers context and answers accordingly]. It highlighted the same problem of the need for more financial resources/funding and not just focusing on the short-term thinking. However, it raised some interesting points I had neglected (the peril of being a tech person), such as

1. “Lack of awareness: Building owners may not be aware of the benefits of energy efficiency or of the available technologies and practices that can help to improve energy efficiency.

2.  Lack of technical expertise: Building owners may not have the technical expertise to identify and implement energy-efficient solutions.

3.  Limited government support: Some governments may not provide sufficient support or incentives to encourage building owners to invest in energy-efficient technologies and practices.

4.  Limited availability of energy-efficient products and services: Building owners may not have access to energy-efficient products and services in their area, which can make it difficult to improve energy efficiency.”

These responses brought me back to some of our customer conversations, where often the BD team at Resync spent enough time educating them about the solutions, technology, and how they (SMEs) can tap into the IMDA support for using Resync’s energy-efficient technologies. 

The issues around lack of awareness, technical expertise, and availability of energy-efficient solutions also raise the point that the data being collected can be simplified into easy-to-absorb information. This has been one of the pivotal points for us to build the product at Resync. 

When you are a data company, one of the most important points for you is to understand that data and use machine learning to make better-informed decisions. And most importantly, make sure the whole value chain of stakeholders understands the data and their implications well. Resync’s product has been designed to showcase simplified and detailed data for every step of the stakeholder. In a real estate organisation, it can range from CXOs, building managers, and facility managers to technicians and Resync’s smart building product serve as a single stop which caters from their high-level needs of understanding carbon emissions, energy cost per building to deeper understanding for technicians and facility managers about individual asset level performance. 

The data-driven energy optimisation for buildings focuses on understanding each building’s individual assets, goals, and controllable parameters. As a result, a custom and real-time machine learning-driven energy optimisation is executed for each building. 

In a nutshell, building owners can benefit from a data-driven energy optimization solution in several ways: 

1. Increased energy efficiency and reduced costs: By using real-time and machine learning-driven optimisation, building owners can make sure their assets such as from the ACMV systems are running optimally. Thus, reducing energy cost and increasing their bottom line.

2. Better monitoring: By digitalising their energy consumption from a high level to sub-distribution box levels, they can understand energy consumption in real-time and identify and address issues promptly. 

3. Understanding emissions and charting out a path to sustainability: Using Resync’s accurate carbon emissions (based on the source of energy in that country), the building owners can track their carbon emissions and energy use intensity. These data points serve as pillars in sustainability reporting and also in understanding building owners’ their GreenMark journey. 

However, ChatGPT tells me that’s not it, there are more benefits. Building owners who do data-driven energy optimisation also benefit from increased property value, increased tenant satisfaction, better compliance, and better decision-making. These are also valid points but often not so prominently visible to a company like ours but building owners can keep track of them. Various studies suggest these as other benefits of smart buildings enabled by data-driven optimisation.

There’s tremendous potential and case for optimising buildings in the tropics. The low-hanging fruits are definitely using low-cost solutions with both immediate and long-term benefits and ideally, if there is government support to try out such technologies, it helps building owners experiment with technology to drive energy efficiency in their buildings. Resync’s smart building solution ticks these boxes and can help drive buildings to meet their energy reduction and sustainability goals. 

PS: I had a lot of fun writing this piece with ChatGPT; its insights are spot-on, succinct, and easy to understand for anyone. I am looking forward to publishing more such interactions in the future.