Smart Life-cycle Optimisation and Diagnostic Technologies for Buildings Energy Saving
视频来源：https://www.youtube.com/watch?v=uR2--sZkEQc
Smart technologies save up to 42% of energy consumption in buildings with life-cycle optimisation, diagnosis and commissioning of central air conditioning systems
“Smart” is one of the buzzwords that always catch public attention. Our phones are smart. Our cities are smart. And of course, our buildings are only smart when they are energy efficient. In Hong Kong, over 90% of electricity is used by buildings, and central air conditioning accounts for more than 50% of total energy consumption in commercial and industrial buildings. However, poor efficiency of air conditioning systems due to improper or obsolete design, operation, control and maintenance means that much of the energy is wasted. To boost the overall energy efficiency of commercial and industrial buildings, Professor WANG Shengwei of the Department of Building Environment and Energy Engineering led a research team to formulate all-round optimisation strategies that enhance energy performance of buildings in general, and of air conditioning systems in particular.
Optimised design – probabilistic approach
Central air conditioning systems are complex and gigantic in scale. In the perfect scenario, air conditioning systems function best if energy efficiency is optimised throughout its life cycle, meaning from its design and conception stage, to operation stage. Professor Wang’s team uses a probabilistic approach in the design stage to simulate and predict the cooling load, operation condition and reliability of the air conditioning equipment. “The common practice is to design chiller plants based on the peak cooling loads, but they only need to run in full load a few days each year. That means for the rest of the year, the chiller plants are oversized and much energy is wasted as a result. Our approach considers each factor affecting the energy efficiency and performance of air conditioning system as a probability distribution. How these factors interact with each other under different circumstances can be predicted and addressed in the design stage. That would help us design chiller plants in optimal configuration and sizes,” explained Professor Wang.
Optimised commissioning – adaptive balancing
Traditionally, the design of a central air conditioning system is tuned to certain specific conditions or balance points, but the actual system characteristics may differ significantly when it is in operation. Professor Wang thus includes different operation options in his design solutions to allow flexibility. “For example, instead of building one bigger pump of 100% required capacity, we build three smaller pumps that add up to the same capacity instead. That gives the leeway of running one to three pumps according to the actual need. When the cooling demand is low, the system may choose to turn off one or two small pumps to save energy.” This is called an adaptive balancing between the performance and the energy cost. In an application case, the probabilistic chiller design with coordinating pump design resulted in 41% of energy saving[1].
Optimised diagnostics – automated troubleshooting
In the operation stage, one important measure is fault diagnosis because components may fail over time leading to performance degradation. They also need to be cleaned or tuned up from time to time for high efficiency. Thus, Professor Wang’s team devised a system to check where the fault is when the air conditioning system is not performing optimally, and to fix the problem as soon as possible. In newer information-super-rich buildings with built-in IoT sensors and building automation systems that collect bulk volume of data every day, the team would deploy big data analytics to effectively locate the problem. But even in older information-poor buildings where very little data is available, the team may still be able to deeply analyse energy use on building-level to find out the pain points that lead to wastage.
Optimised control and demand responses – for smart grids and more
Renewable energy is desirable, but green sources like solar energy and wind energy are intermittent in nature. Experts have been finding ways to build smart grids where consumers and producers can communicate to flexibly alter their energy consumption and supply patterns for less wastage and higher efficiency. Besides various optimal control strategies to control air-conditioning systems to operate at high energy efficiency, Professor Wang has also been developing grid-responsive building technologies to optimise interoperation with future smart grids.
“A grid-responsive building lets the power users and suppliers work in synergy to maintain a balance between demand and supply. The key is to make users consume less power when the grid is short of generation and consume more when the grid power generation is sufficient,” said Professor Wang. For instance, when the suppliers foresee a drop in, say, solar energy in the coming 48 hours, they notify the users so that they can store energy before it happens. Or, when a heat wave is expected to arrive in a few days, users may save up more energy ahead of time to run their air-conditioners. And yes, in future, there may be some kind of energy storage device in every home.
Saving millions kWh of electricity each year
In the past 10-plus years, Professor Wang and his team have been conducting consultancy projects for public and private clients to optimise the air-conditioning systems for various kinds of premises, such as commercial complexes, shopping malls, hotels and production buildings of bio-medicines. Among these buildings are household names such as International Commerce Centre (ICC), Holiday Inn Express, etc. The energy efficiency of these buildings has been greatly enhanced, saving millions of kWh of electricity each year, equivalent to millions of dollars in electricity bill. The latest version of these technologies, namely smart, energy-efficient and energy-flexible building technologies, are being implemented and demonstrated in the new super-large development of SHK group, i.e., West Kowloon Station Topside Commercial Development
[1] Hangxin Li & Shengwei Wang (2020) A systematic and probabilistic approach for optimal design and on-site adaptive balancing of building central cooling systems concerning uncertainties, Science and Technology for the Built Environment, 26:7, 888-900, DOI: 10.1080/23744731.2020.1776068
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