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