Gaining efficiency insights
While the previous actions target discrete types of industrial assets, a final class of energy efficiency measures has to do with using data for facility or enterprise-wide gains.
To achieve this, you first need to deploy sensor networks for real-time monitoring and control.
A final action concerns how data itself is stored and handled.
Having accurate, timely data on energy use is critical for understanding how well efficiency measures are working. Hence, any efficiency initiative should be preceded or accompanied by a process of data acquisition and control.
Bringing industrial assets into an IoT network makes it possible to deploy smarter, more efficient operations across buildings and plants. And the opportunities for more efficient operations extend to the technology itself, where efficiencies can be gained through cloud hosting and management.
Action 9: Deploying smart building management systems
The carbon impact
Modeling by the Energy Efficiency Movement suggests widespread use of building management systems (BMS) could yield annual electricity savings of between 994 terawatt-hours and 1.5 petawatt-hours a year by 2030, while cutting annual gas use by 126 to 252 terawatt-hours.
This could deliver between 593 and 901 MtCO2 emissions savings a year. Taking a mid-point estimate, this could create almost 3.5 gigatons of savings between 2024 and 2030.
Why do it?
Heating, ventilation and air conditioning (HVAC) systems alone are associated with more than 40% of a typical commercial building’s energy load, with around 35% of this usually wasted. A BMS can control up to around 70% of a building’s energy load if lighting is included as well.
Combining artificial intelligence with a digital BMS can cut HVAC emissions by as much as 40% and reduce energy costs by 25%. A smart BMS can save substantial proportions of a building’s energy use costs through detection, diagnostic, historical analysis and predictive capabilities.
For example, the deployment of smart BMS in a facility in Bengaluru, India, resulted in building operational and management cost savings of up to 10% and a 19% saving in energy management costs. The deployment of smart BMS also resulted in emissions savings of up to 34%.
How much could industry save through BMS adoption?
Why do it?
Heating, ventilation and air conditioning (HVAC) systems alone are associated with more than 40% of a typical commercial building’s energy load, with around 35% of this usually wasted. A BMS can control up to around 70% of a building’s energy load if lighting is included as well.
Combining artificial intelligence with a digital BMS can cut HVAC emissions by as much as 40% and reduce energy costs by 25%. A smart BMS can save substantial proportions of a building’s energy use costs through detection, diagnostic, historical analysis and predictive capabilities.
For example, the deployment of smart BMS in a facility in Bengaluru, India, resulted in building operational and management cost savings of up to 10% and a 19% saving in energy management costs. The deployment of smart BMS also resulted in emissions savings of up to 34%.
How much could industry save through BMS adoption?
Building the business plan
- The majority of commercial buildings that have been constructed over the past two decades are likely to have a BMS installed from the outset, although in some cases there may be benefits to updating older systems.
- A digital BMS will usually offer the greatest benefit in older commercial buildings that do not have a system installed.
- Research indicates around 75% of buildings built before the year 2000 fall into this category.
Next steps
- Carry out an audit of global facilities to determine which ones already have BMS installations, and from when.
- Focus on the oldest, highest-energy-use buildings when prioritizing BMS deployment.
- Consider combining BMS installations as part of wider IoT deployment programs, to maximize the value of in-building sensor networks.
Action 10: Moving data to the cloud
The carbon impact
Data center owners have a significant incentive to improve energy efficiency. Electricity use, for server power and climatization, is usually by far the biggest cost associated with data centers, so using energy as efficiently as possible carries a major financial benefit.
However, upgrading in-house data centers is no easy task, particularly if they are hosting critical enterprise applications.
This is one reason why enterprise workloads are increasingly being hosted in the cloud, where third-party providers purchase, maintain and upgrade the IT hardware, and can negotiate favorable (and to a growing extent clean) energy sourcing terms from power providers.
Cloud hosting can give companies access to more scalable and flexible computing and data storage infrastructures, including server virtualization, managed by specialists that are highly focused on efficiency and may even be reducing emissions through the use of renewable energy.
Why do it?
There are at least three reasons cloud data center operators will tend to have greater efficiency savings than individual on-premises data storage and compute arrangements:
- Cloud computing and co-location facilities usually operate at a much higher level of efficiency compared to smaller, on-premises servers. In cloud data centers, prediction and monitoring of demand can help ensure that over-provisioning of supply can be more easily avoided compared to on-premises provision.
- Energy use accounts for a significant percentage of a cloud operator’s overall operating expenses, so there is a strong financial incentive to optimize the operational efficiency of IT equipment.
- Advanced infrastructure technologies in hyperscale data centers reduce the energy for lighting and cooling the facility.
Building the business plan
- For many companies, the cloud can be a less expensive alternative to continued on-premises data management. But the extent to which financial savings are achievable from a switch to the cloud is influenced by a range of variables.
- These include the size of the business making the transition, costs and inefficiencies embedded in the existing architecture, decisions around whether investment in a single cloud versus multi-cloud is appropriate and legacy costs associated with on-premises data processing facilities.
- Research suggests that while the cloud can be initially more expensive than on-premises data management, because of migration investment costs, cloud-based services will usually become cost-effective over time.
Next steps
- Efficiency is only one factor to consider when contemplating cloud migration— organizational capabilities such as improved speed and business agility may be some of the biggest benefits—so review the technological and regulatory pros and cons of embarking on the move.
- Consider the extent to which your business may already be using cloud-based applications and services and see if and how these can be extended cost effectively.
- Choose cloud hosting for the data you collect and manage as part of your other energy efficiency initiatives.