Leveraging Artificial Intelligence in Electrical Engineering
As an electrical contractor and engineering firm, Blanco Electric is naturally interested in studying how the introduction of Artificial Intelligence in electrical engineering could bring about positive changes in the design and planning of electrical installations in office buildings.
One of the critical challenges shared by all cities and building companies around the world is the high energy consumption of this type of building, with significant environmental and economic implications.
It behooves general contractors, electricians, HVAC companies, insulation specialists, roofers, door and window manufacturers, all the trades working together in the construction industry to explore how AI can be harnessed to design buildings more efficiently.
In the world of electrical engineering, we are looking at electrical circuits, panels and cabling systems that reduce power consumption without compromising the lifestyle, efficiency, and productivity of the occupants of future buildings.
The Need for Energy Efficiency in Office Buildings
Energy efficiency in office buildings is not just a matter of reducing micro-economic costs; it's an essential part of mitigating resource usage and waste, controlling environmental pollution, and harnessing macro-economic issues related to the state of the supply chain. Buildings account for approximately 40% of global energy usage and a third of greenhouse gas emissions.
Reducing energy consumption therefore impacts the carbon footprint of cities and businesses, and contributes to slowing down the anthropogenic effect on climate change.
The study titled "The impact of the wall insulation material and variable refrigerant flow system on building energy consumption and cost" by Hamza Shaikh et al. highlights the potential of energy-saving technologies in reducing power consumption in office buildings. This study found that replacing conventional air conditioners with Variable Refrigerant Flow (VRF) AC systems can reduce electrical power consumption by 42-45%.
Artificial Intelligence in Electrical Engineering
Considering the ability of AI to learn from data and make predictions, it finds relevant applications in electrical engineering. One such application is in predicting energy consumption in buildings.
A research study by Hai-Xiang Zhao and Frédéric Magoulès reviews models developed for this purpose, which include artificial intelligence methods. With AI, it becomes possible to analyze factors such as weather conditions, building structure, and the operation of components like lighting and HVAC systems to predict energy consumption with a good degree of accuracy.
For the electrical engineer, this prediction capability can be used to design efficient electrical circuits, panels, and cabling systems.
The study "Energy Management in an Agile Workspace using AI-driven Forecasting and Anomaly Detection" by H. Manzoor et al. developed a Persuasive Energy Conscious Network (PECN) that uses AI to forecast future energy demands and detect anomalous power consumption patterns. This is an excellent illustration of how AI can be used in energy management.
Case Studies and Real-life Examples
We are seeing new real-life applications of artificial intelligence in electrical engineering with a view to increasing energy efficiency in office buildings. For instance, Google used DeepMind's machine learning algorithms to reduce the energy used for cooling its data centers by 40%.
Such AI-based systems can be implemented in office buildings to optimize the use of HVAC systems, lighting, and other energy-consuming components. These applications are all in the purview of VEDI, one of the services we specialize in.
In their study "Intelligent Electrical Device Load Scheduling for Building Energy Management", C. Setianingsih et al. developed a system that uses AI to calculate the optimal duration of use for each electrical device to ensure that a predetermined monthly budgetary limit is not exceeded. This is yet another real-life application of AI to budget management, with a direct impact on the economic efficiency of office buildings and the management of their energy footprint.
Balancing Energy Efficiency with Lifestyle, Efficiency, and Productivity
Reducing energy consumption can’t come at the cost of the comfort and productivity of the occupants of an office building. With its computational power, Artificial Intelligence can help strike a balance.
For instance, AI can optimize the operation of HVAC systems to maintain a comfortable temperature while minimizing energy use. AI can also manage lighting systems to ensure adequate lighting levels that support workers’ productivity while reducing energy consumption.
A research study published by Chauncey Starr discusses the balance between social benefits and technological risks, a concept that is highly relevant in this context.
Another study titled "Lockdown Impact due to Corona Pandemic on Electric Power Quality and Its Alternative Solutions for a University Office Building" published by Ida Ayu Vadanti Locana Diwy et al. found that overvoltage and harmonics were issues to be addressed in order to maintain the quality of electric power. This research paper opens up a discussion on the impact of changes in the usage pattern of electrical appliances on power quality and the potential solutions to these problems.
Blanco Electric’s analysis
We are firmly convinced that AI will completely change the way electrical engineers approach the issue of sustainability and efficiency in the management of power in office buildings.
By accurately predicting energy consumption and optimizing the design and operation of electrical systems, AI will reduce the environmental and economic footprint of energy consumption in office buildings.
As noted above, these changes will require factors that are typically difficult to measure, such as productivity of employees and comfort in the workspace, to be integrated in the data set fed to the AI.
Any new technology has unforeseen costs. When DOS and then Windows enabled the PC revolution, the incidental cost of software bugs skyrocketed. But the cost and availability of hardware also diminished. In the end, the balance of two opposite factors was positive and gave Corporate America decades of productivity gains, a phenomenon that had never been seen before at this scale.
The introduction of artificial intelligence in electrical engineering as part of its best practices promises to help the construction industry tackle issues that it could never address in a way that made economical sense before. We have to remain on top of the progress in this field, and Blanco Electric intends to provide its clients with solutions that integrate AI recommendations.
● Starr, C. (1969). Social Benefit versus Technological Risk. Science, 165(3899), 1232.
● Zhao, H.-X., & Magoulès, F. (2012). A review on the prediction of building energy consumption. Renewable and Sustainable Energy Reviews, 16(6), 3586–3592.