The adaptive predictive control of an energy efficient central water heating system applied in the South African commercial sector
Abstract
Since the introduction of load shedding in the latter part of 2007, Eskom, the electrical
utility of South Africa, have been forced to implement energy efficient and energy management
measures to ensure the stability of the national grid. Solutions within the residential,
commercial and industrial sectors have been implemented which specifically targeted the
reduction of electrical demand during peak hours as well as methods to reduce the total
electrical demand in the country. One of the target areas within the residential and commercial
sectors are sanitary water heating systems due to the ease with which energy efficient
technologies and energy management solutions can be implemented. Unlike some parts of
the world where water heating is supplied by district water heating networks for sanitary
as well as space heating purposes, South Africa predominantly utilizes decentralized water
heating systems for sanitary purposes due to the annual moderate climate in South Africa.
Conventional electrical resistance heaters have been dominating the sanitary water heating
market in South Africa for decades but energy efficient technologies such as solar and heat
pump water heaters have recently been key attributes in the pursuit to reduce the energy
demand within the residential and commercial sectors. Although water heating only accounts
for 8% of the total energy demand in the commercial sector, the demand for water heating
services continues to increase due to the higher demand for accommodation throughout the
city centres in South Africa. In Johannesburg, the largest city in South Africa, a demographic
shift developed where most of the city's population started to relocate to the city centre in
an effort to move closer to the central business district. This created an opportunity where
building owners started to reconstruct high rise office buildings into apartment units to fill
the accommodation void.
The central water heating systems, which included heat pump water heaters, of two
renovated high rise apartment buildings were evaluated between 2011 and 2014. What
became evident within the measured data throughout the four years was the high hot water
consumption of the respective buildings. With hot water consumption data being a crucial component in the design of any water heating system, the measured consumption data was
compared to high density population consumption profiles of research done in the commercial
sector of South Africa. The substantial variance in the consumption profiles highlighted the
concern in using outdated consumption data when designing a water heating system.
Various models have been developed internationally to predict hot water load profiles of
district water heating systems in an effort to reduce energy costs by means of optimum control
strategies. However limited research have been done on consumption profile prediction in the
South African residential and commercial sectors where decentralized water heating systems
reign supreme.
The purpose of this study was to develop a control algorithm to predict in-time hot water
consumption profiles for commercial high rise buildings based on historic population density
group classification data. The measurements of the renovated commercial high rise buildings
were used as input for the developed hot water scheduler software to predict the required
hot water consumption per hour of a building. This is done by optimally controlling the
water heating equipment utilizing the predicted consumption profiles to optimize the energy
savings potential of a building. Several simulation scenarios were compared to the actual
consumption data of the two buildings which showcased the techo-economic benefit of the
hot water scheduler as an energy management tool. The tool illustrated the added benefit
of utilizing the simulation results to size a central water heating system based on the results
provided by the hot water scheduler.
Energy savings of up to 55% are possible when controlling the operating schedule of
energy efficient heating equipment such as heat pump water heaters using the developed
hot water scheduler. The conclusive outcome of this study demonstrates the advantage of
controlling the schedule of water heating equipment, using population density classified hot
water consumption profiles, to reduce energy costs of a water heating system for high rise
apartment buildings
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- Engineering [1379]
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