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Optimal Operation of Integrated Heat Pump-instant Water Heaters with Renewable Energy
Available online at www.sciencedirect.com
ScienceDirect Energy Procedia 105 (2017) 2151 – 2156
The 8th International Conference on Applied Energy – ICAE2016
Optimal operation of integrated heat pump-instant water heaters with renewable energy Evan M. Wanjiru*1, Sam M. Sichilalu2, Xiaohua Xia1 1
Centre of New Energy Systems, Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria 0002, South Africa 2 Faculty of engineering, Mosi-O-Tunya Unversity of Science and Technology, Lusaka, Zambia
Abstract Developing nations such as South Africa are energy insecure despite their high potential for renewable energy sources such as solar. This has forced various governments to initiate energy efficiency and conservation programs. Water heating contributes to a significant percentage of the electricity consumption in domestic and office buildings. Therefore, integration of efficient water heating systems and renewable energy would ensure energy efficiency in these buildings hence lowering the electricity cost and greenhouse gas emissions. This paper introduces an optimal control strategy for heat pump and instant water heaters powered using integrated energy systems. The control strategy can lead to 35% of power-not-delivered, 7.5 kWh energy sold back to the grid while lowering the energy cost by about 19% in a day. © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license © 2016 The Authors. Published by Elsevier Ltd. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Selection and/or peer-review under responsibility of ICAE Peer-review under responsibility of the scientific committee of the 8th International Conference on Applied Energy.
Keywords: optimal control; energy efficiency; solar; heat pump water heater; instant water heater.
1. Introduction The world, particularly the developing nations are facing increased energy demand as a consequence of increasing population, urbanization and improved living standards. For instance, Eskom, South Africa’s power utility, has in the recent past been unable to meet the energy demand. This has led to widespread black outs (load shedding) [1], causing economic losses to the tune of US$ 7.2 billion per month [2]. Lebanon meets most of her energy needs from oil imports while the deficit is compensated through many small backup generators [3]. Africa’s largest economy, Nigeria, has low connectivity and poor grid quality forcing many homes and businesses to use small generators to meet their energy needs [4]. In addition, Pakistan’s electricity supply is 25-50% short of demand leading to load shedding of up to 12 and 20 hours and urban and rural areas respectively [5]. Various governments are therefore implementing measures to reduce the pressure on the national grid. For instance, the government of South Africa,
* Corresponding author. Tel.: +27 12 420 6767; fax: +27 12 362 5000. E-mail address: [email protected].
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the 8th International Conference on Applied Energy. doi:10.1016/j.egypro.2017.03.607
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through various agencies, has implemented energy efficiency and conservation strategies to curb wastage, reduce the pressure on the national grid and greenhouse gas emissions [2]. Efficient domestic water heating technologies such as heat pump water heaters (HPWHs) should be adopted. HPWHs operate on the principle of the refrigerant cycle converting one unit of electrical energy to produce three units of thermal energy [6]. This means that they can reduce the energy consumption by two-thirds when they simply replace resistance heaters translating to a reduced cost of energy to the endusers as well as monthly peak demand charges [7]. However, there still exists technological challenges of optimal operation, system designing, sizing and integration of HPWHs. Integration of HPWHs with distributed renewable energy systems would further increase the savings to the owners [8]. Various studies have looked at ways of optimally controlling HPWHs at domestic level incorporating renewable energy systems [8–10]. The studies show that optimal control of HPWHs while incorporating renewable energy systems is an economically feasible solution to providing hot water. One major drawback with HPWHs, despite their high coefficient of performance, is their slow rate of heating; such that, in situations with sudden demand for hot water, they are unable to meet it. Further, since HPWHs are normally centrally located, there are energy and water losses associated with the hot water conveyance to the consumption point [11]. This paper introduces an optimal control strategy to provide hot water using HPWHs and instant heaters. The HPWH seeks to meet the hot water demand in the kitchen faucet and bathroom sink that require less hot water while the instant heater takes up hot water from the HPWH and only heats it further if it is not at the required temperature. These two water heating devices are powered using both solar energy as well as grid. The optimal controller will minimize the grid energy consumption as well as the operation of the instant heater, essentially saving energy. Further, the grid can accept excess power from the renewable sources through an appropriate feed-in-tariff. 2. Controller design
Fig 1: Schematic diagram of the integrated water heating system.
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Fig 1 shows the schematic diagram of the water heating model comprising of the HPWH and the instant heater that are powered using the grid energy, Pg, and solar, Ppv. HPWH meets the total hot water demand for the kitchen and bathroom with the instant heater acting as back up whenever the water from the HPWH is not at the required temperature. Switches uhp and uih control the power flow to the HPWH and instant heater respectively. Further, the grid supplements power from the solar to keep the devices operating optimally. The model seeks to minimize the consumption of power from the grid, Pg, and the use of the instant heater as shown in equation (1). N
N
J=ɘ t s pe Pg (j) +(1-ɘሻ t s Pih uih (j) j=1
(1)
j=1
where ts is the sampling interval, pe is the time-of-use (TOU) tariff, Pih LVWKHLQVWDQWKHDWHUUDWHGSRZHUȦ is the weighting factor and N is the total number of samples. This objective function is subject to the following constraints; Pg (j)+Ppv (j)=Php u1 (j)+Pih uih (j), (2) hp
Tmin Thp o M Tmax ,
(3)
ih Tih min To M Tmax ,
(4) (5) (6) (7)
uhp M , uih M , -Pg M , hp
where Php is the HPWH rated power,Tmin and Tih min are the HPWH’s and instant heater’s minimum allowable temperature while Tmax is the maximum allowable temperature, which is the same for both ih HPWH and instant heater. Thp o (j) and To (j) are the state variables representing the HPWH and instant heater water temperature respectively, while uhp(j), uih(j) and Pg(j) are the control variables. In order to develop the model, it is assumed that the temperature of water in the HPWH is even throughout the storage. The temperature of water getting into the instant heater is assumed to be 90% of the temperature leaving the HPWH. Both the HPWH and the instant heater experience same temperature losses, namely the stand by losses and the losses caused by the inlet of cold water. The temperature variation in either of the two is therefore modeled as, cmt Tሶ (j)=Q o (j)-Q s (j)-Q d (j)
(8)
where, c is the specific heat capacity of water, mt is the mass of water inside the HPWH or the instant heater, Qo (j) is the total power output from either of the two devices, Qs (j) is the standby losses and Qd (j) is the loss associated with the inlet of cold water into the device. A case study was conducted in a kitchen and bathroom of the University of Pretoria, Engineering 1 building. This arose as the university is looking for a viable and efficient means of providing hot water in in the building. Currently, the kitchens in the building are fitted with instant heaters for providing boiling water to make hot beverages. There, however, lacks hot water in the kitchen and bathroom faucets meaning that during winter, occupants are highly inconvenienced while using cold water. Since the bathroom taps have no hot water, the demand was chosen from the usage of the water in the kitchen and hand sinks. The hourly hot water demand profile for the two devices is shown in Fig 2.
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Fig 1: Hot water demand profile
3. Results and discussion This is a linear optimization problem solved in MATLAB using OPTI toolbox preferred for its high speed. Sampling interval, ts =30 min is chosen over a 24-hour operating cycle leading total samples, N=48 The optimal control of the HPWH and the instant heater is shown in Fig 3. Both devices are operating
Fig 2: HPWH and Instant heater optimal schedules
during the cheaper off-peak period. This, indeed, is in line with the desire to shift the load to off-peak periods. The HPWH switches on at 01:30 to start heating the water in anticipation of the hot water demand. It only switches off during the morning peak so as to shift the load from peak time and then switches on till 17:00 when the controller detects that the temperature of water in the HPWH is sufficient to meet the demand for the rest of the day. However, since the temperature of water from the HPWH isn’t sufficiently hot to make beverages, the optimal controller switches on the instant heater at 06:00 in order to keep the temperature within the required temperature range (95-100oC). The controller thereafter switches it off during the morning peak period and thereafter resumes heating the water to meet the boiling water demand. The controller eventually switches off the instant heater at 18:00. This is because the boiling water in the instant heater is sufficient to meet the remaining demand.
Evan M. Wanjiru et al. / Energy Procedia 105 (2017) 2151 – 2156
Fig 3: Optimal grid power consumption
From optimal control of the two hot water devices, grid power is optimally consumed as shown in Fig 4. The grid power is first consumed at 01:30 when the HPWH switches on. This power consumption then increases at 06:00 when both HPWH and instant heater are on. This power consumption from the grid arises as solar energy is not present. When the controller switches off the devices at the beginning of the morning peak, the solar power is present, which is fed back to the grid. After the morning peak, the grid supplements the solar energy in meeting the power requirement of the devices while they are in operational. By selling renewable power back to the grid, the cost of power to the consumer is significantly lowered. The power to the grid appears spasmodic since the model assumes that there is no energy storage through a battery. Consequently, whenever the renewable solar energy is in excess, it is immediately sold to the grid to be used by others or other loads. Variation of hot water temperature while using the HPHW and the instant heater is shown in Fig 5.
Fig 4: Hot water temperature variation
The HPWH is allowed to operate to a lowest of 80 oC. However, in meeting the overall hot water demand, it doesn’t reach the minimum required temperature for boiling water, at 95 oC. The instant heater comes in and keeps the boiling water within the prescribed temperature range. The temperature of water in HPWH rises from 01:30 when the controller switches on the HPWH. At this time, water demand from HPWH is very low, leading to a temperature of up to 89.13 oC. Temperature starts to decline as water demand increases through the peak period. The demand is high throughout the working hours of the day
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such that even though the HPWH is switched ON, the temperature keeps declining as a result of the incoming cold water. Despite this, the HPWH is able to meet the overall water demand without violating its constraints. Similarly, just before 06:00 when the controller switches on the instant heater, the temperature of water inside the instant heater starts to decline due to the boiling water demand. Once it is switched on for just 30 minutes, the temperature rises sufficiently to meet the demand across the morning peak. Thereafter, the temperature keeps fluctuating within the temperature constraints in response to boiling water demand and the heating that is taking place inside the instant heater. When the controller finally switches off the instant heater at 18:00, the boiling water demand is low leading to a low rate of temperature loss. This temperature falls to 95.23 oC at the end of the operating cycle. The optimal controller can save to up to 35% of power-not-delivered from the grid in a 24-h operating cycle with about 7.7 kWh of energy sold back to the grid through an appropriate feed-in-tariff. The control strategy also leads to about 19% savings on energy cost while compared to the existing thermostatic control of the devices. These savings are significant in lowering the operating cost of the hot water devices over a long period of time. The adoption of these devices with optimal control strategy and renewable energy in many office and domestic buildings is therefore recommended as an efficient way of providing hot water. Through feeding heated water from HPWH to the instant heater, less energy is required to heat the water to the boiling level as desired. 4. Conclusion This paper introduces an optimal control strategy for controlling the operation of HPWH connected to an instant heater. The devices are powered using the renewable solar energy and the grid power, which can also receive back power through an appropriate feed-in-tariff. This control strategy leads to significant savings on energy and energy cost to the consumer. It offers a novel solution that would encourage the uptake and hence market penetration of HPWHs in developing nations like South Africa hence improving the efficiency of providing hot water in domestic houses. References [1] K. C. van Blommestein and T. U. Daim, “Residential energy efficient device adoption in South Africa,” Sustainable Energy Technologies and Assessments, vol. 1, pp. 13–27, 2013. [2] P. Nel, M. Booysen, and B. van der Merwe, “Energy perceptions in South Africa: An analysis of behaviour and understanding of electric water heaters,” Energy for Sustainable Development, vol. 32, pp. 62–70, 2016. [3] O. Ibrahim, F. Fardoun, R. Younes, and H. Louahlia-Gualous, “Optimal management proposal for hybrid water heating system,” Energy and Buildings, vol. 75, pp. 342–357, 2014. [4] J. O. Dada, “Towards understanding the benefits and challenges of Smart/Micro-Grid for electricity supply system in Nigeria,” Renewable and Sustainable Energy Reviews, vol. 38, pp. 1003–1014, 2014. [5] F. Shaikh, Q. Ji, and Y. Fan, “The diagnosis of an electricity crisis and alternative energy development in Pakistan,” Renewable and Sustainable Energy Reviews, vol. 52, pp. 1172–1185, 2015. [6] S. M. Sichilalu and X. Xia, “Optimal energy control of grid tied PV–diesel–battery hybrid system powering heat pump water heater,” Solar Energy, vol. 115, pp. 243–254, 2015. [7] P. Rousseau and G. Greyvenstein, “Enhancing the impact of heat pump water heaters in the South African commercial sector,” Energy, vol. 25, no. 1, pp. 51–70, 2000. [8] S. Sichilalu, T. Mathaba, and X. Xia, “Optimal control of a wind-PV-hybrid powered heat pump water heater,” Applied Energy, 2015. [9] S. M. Sichilalu and X. Xia, “Optimal power dispatch of a grid tied-battery-photovoltaic system supplying heat pump water heaters,” Energy Conversion and Management, vol. 102, pp. 81–91, 2015. [10] S. Sichilalu, H. Tazvinga, and X. Xia, “Optimal control of a fuel cell/wind/PV/grid hybrid system with thermal heat pump load,” Solar Energy, vol. 135, pp. 59–69, 2016. [11] D. S. Sowmy and R. T. Prado, “Assessment of energy efficiency in electric storage water heaters,” Energy and Buildings, vol. 40, no. 12, pp. 2128–2132, 2008.
ScienceDirect Energy Procedia 105 (2017) 2151 – 2156
The 8th International Conference on Applied Energy – ICAE2016
Optimal operation of integrated heat pump-instant water heaters with renewable energy Evan M. Wanjiru*1, Sam M. Sichilalu2, Xiaohua Xia1 1
Centre of New Energy Systems, Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria 0002, South Africa 2 Faculty of engineering, Mosi-O-Tunya Unversity of Science and Technology, Lusaka, Zambia
Abstract Developing nations such as South Africa are energy insecure despite their high potential for renewable energy sources such as solar. This has forced various governments to initiate energy efficiency and conservation programs. Water heating contributes to a significant percentage of the electricity consumption in domestic and office buildings. Therefore, integration of efficient water heating systems and renewable energy would ensure energy efficiency in these buildings hence lowering the electricity cost and greenhouse gas emissions. This paper introduces an optimal control strategy for heat pump and instant water heaters powered using integrated energy systems. The control strategy can lead to 35% of power-not-delivered, 7.5 kWh energy sold back to the grid while lowering the energy cost by about 19% in a day. © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license © 2016 The Authors. Published by Elsevier Ltd. (http://creativecommons.org/licenses/by-nc-nd/4.0/). Selection and/or peer-review under responsibility of ICAE Peer-review under responsibility of the scientific committee of the 8th International Conference on Applied Energy.
Keywords: optimal control; energy efficiency; solar; heat pump water heater; instant water heater.
1. Introduction The world, particularly the developing nations are facing increased energy demand as a consequence of increasing population, urbanization and improved living standards. For instance, Eskom, South Africa’s power utility, has in the recent past been unable to meet the energy demand. This has led to widespread black outs (load shedding) [1], causing economic losses to the tune of US$ 7.2 billion per month [2]. Lebanon meets most of her energy needs from oil imports while the deficit is compensated through many small backup generators [3]. Africa’s largest economy, Nigeria, has low connectivity and poor grid quality forcing many homes and businesses to use small generators to meet their energy needs [4]. In addition, Pakistan’s electricity supply is 25-50% short of demand leading to load shedding of up to 12 and 20 hours and urban and rural areas respectively [5]. Various governments are therefore implementing measures to reduce the pressure on the national grid. For instance, the government of South Africa,
* Corresponding author. Tel.: +27 12 420 6767; fax: +27 12 362 5000. E-mail address: [email protected].
1876-6102 © 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the 8th International Conference on Applied Energy. doi:10.1016/j.egypro.2017.03.607
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through various agencies, has implemented energy efficiency and conservation strategies to curb wastage, reduce the pressure on the national grid and greenhouse gas emissions [2]. Efficient domestic water heating technologies such as heat pump water heaters (HPWHs) should be adopted. HPWHs operate on the principle of the refrigerant cycle converting one unit of electrical energy to produce three units of thermal energy [6]. This means that they can reduce the energy consumption by two-thirds when they simply replace resistance heaters translating to a reduced cost of energy to the endusers as well as monthly peak demand charges [7]. However, there still exists technological challenges of optimal operation, system designing, sizing and integration of HPWHs. Integration of HPWHs with distributed renewable energy systems would further increase the savings to the owners [8]. Various studies have looked at ways of optimally controlling HPWHs at domestic level incorporating renewable energy systems [8–10]. The studies show that optimal control of HPWHs while incorporating renewable energy systems is an economically feasible solution to providing hot water. One major drawback with HPWHs, despite their high coefficient of performance, is their slow rate of heating; such that, in situations with sudden demand for hot water, they are unable to meet it. Further, since HPWHs are normally centrally located, there are energy and water losses associated with the hot water conveyance to the consumption point [11]. This paper introduces an optimal control strategy to provide hot water using HPWHs and instant heaters. The HPWH seeks to meet the hot water demand in the kitchen faucet and bathroom sink that require less hot water while the instant heater takes up hot water from the HPWH and only heats it further if it is not at the required temperature. These two water heating devices are powered using both solar energy as well as grid. The optimal controller will minimize the grid energy consumption as well as the operation of the instant heater, essentially saving energy. Further, the grid can accept excess power from the renewable sources through an appropriate feed-in-tariff. 2. Controller design
Fig 1: Schematic diagram of the integrated water heating system.
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Fig 1 shows the schematic diagram of the water heating model comprising of the HPWH and the instant heater that are powered using the grid energy, Pg, and solar, Ppv. HPWH meets the total hot water demand for the kitchen and bathroom with the instant heater acting as back up whenever the water from the HPWH is not at the required temperature. Switches uhp and uih control the power flow to the HPWH and instant heater respectively. Further, the grid supplements power from the solar to keep the devices operating optimally. The model seeks to minimize the consumption of power from the grid, Pg, and the use of the instant heater as shown in equation (1). N
N
J=ɘ t s pe Pg (j) +(1-ɘሻ t s Pih uih (j) j=1
(1)
j=1
where ts is the sampling interval, pe is the time-of-use (TOU) tariff, Pih LVWKHLQVWDQWKHDWHUUDWHGSRZHUȦ is the weighting factor and N is the total number of samples. This objective function is subject to the following constraints; Pg (j)+Ppv (j)=Php u1 (j)+Pih uih (j), (2) hp
Tmin Thp o M Tmax ,
(3)
ih Tih min To M Tmax ,
(4) (5) (6) (7)
uhp M , uih M , -Pg M , hp
where Php is the HPWH rated power,Tmin and Tih min are the HPWH’s and instant heater’s minimum allowable temperature while Tmax is the maximum allowable temperature, which is the same for both ih HPWH and instant heater. Thp o (j) and To (j) are the state variables representing the HPWH and instant heater water temperature respectively, while uhp(j), uih(j) and Pg(j) are the control variables. In order to develop the model, it is assumed that the temperature of water in the HPWH is even throughout the storage. The temperature of water getting into the instant heater is assumed to be 90% of the temperature leaving the HPWH. Both the HPWH and the instant heater experience same temperature losses, namely the stand by losses and the losses caused by the inlet of cold water. The temperature variation in either of the two is therefore modeled as, cmt Tሶ (j)=Q o (j)-Q s (j)-Q d (j)
(8)
where, c is the specific heat capacity of water, mt is the mass of water inside the HPWH or the instant heater, Qo (j) is the total power output from either of the two devices, Qs (j) is the standby losses and Qd (j) is the loss associated with the inlet of cold water into the device. A case study was conducted in a kitchen and bathroom of the University of Pretoria, Engineering 1 building. This arose as the university is looking for a viable and efficient means of providing hot water in in the building. Currently, the kitchens in the building are fitted with instant heaters for providing boiling water to make hot beverages. There, however, lacks hot water in the kitchen and bathroom faucets meaning that during winter, occupants are highly inconvenienced while using cold water. Since the bathroom taps have no hot water, the demand was chosen from the usage of the water in the kitchen and hand sinks. The hourly hot water demand profile for the two devices is shown in Fig 2.
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Fig 1: Hot water demand profile
3. Results and discussion This is a linear optimization problem solved in MATLAB using OPTI toolbox preferred for its high speed. Sampling interval, ts =30 min is chosen over a 24-hour operating cycle leading total samples, N=48 The optimal control of the HPWH and the instant heater is shown in Fig 3. Both devices are operating
Fig 2: HPWH and Instant heater optimal schedules
during the cheaper off-peak period. This, indeed, is in line with the desire to shift the load to off-peak periods. The HPWH switches on at 01:30 to start heating the water in anticipation of the hot water demand. It only switches off during the morning peak so as to shift the load from peak time and then switches on till 17:00 when the controller detects that the temperature of water in the HPWH is sufficient to meet the demand for the rest of the day. However, since the temperature of water from the HPWH isn’t sufficiently hot to make beverages, the optimal controller switches on the instant heater at 06:00 in order to keep the temperature within the required temperature range (95-100oC). The controller thereafter switches it off during the morning peak period and thereafter resumes heating the water to meet the boiling water demand. The controller eventually switches off the instant heater at 18:00. This is because the boiling water in the instant heater is sufficient to meet the remaining demand.
Evan M. Wanjiru et al. / Energy Procedia 105 (2017) 2151 – 2156
Fig 3: Optimal grid power consumption
From optimal control of the two hot water devices, grid power is optimally consumed as shown in Fig 4. The grid power is first consumed at 01:30 when the HPWH switches on. This power consumption then increases at 06:00 when both HPWH and instant heater are on. This power consumption from the grid arises as solar energy is not present. When the controller switches off the devices at the beginning of the morning peak, the solar power is present, which is fed back to the grid. After the morning peak, the grid supplements the solar energy in meeting the power requirement of the devices while they are in operational. By selling renewable power back to the grid, the cost of power to the consumer is significantly lowered. The power to the grid appears spasmodic since the model assumes that there is no energy storage through a battery. Consequently, whenever the renewable solar energy is in excess, it is immediately sold to the grid to be used by others or other loads. Variation of hot water temperature while using the HPHW and the instant heater is shown in Fig 5.
Fig 4: Hot water temperature variation
The HPWH is allowed to operate to a lowest of 80 oC. However, in meeting the overall hot water demand, it doesn’t reach the minimum required temperature for boiling water, at 95 oC. The instant heater comes in and keeps the boiling water within the prescribed temperature range. The temperature of water in HPWH rises from 01:30 when the controller switches on the HPWH. At this time, water demand from HPWH is very low, leading to a temperature of up to 89.13 oC. Temperature starts to decline as water demand increases through the peak period. The demand is high throughout the working hours of the day
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such that even though the HPWH is switched ON, the temperature keeps declining as a result of the incoming cold water. Despite this, the HPWH is able to meet the overall water demand without violating its constraints. Similarly, just before 06:00 when the controller switches on the instant heater, the temperature of water inside the instant heater starts to decline due to the boiling water demand. Once it is switched on for just 30 minutes, the temperature rises sufficiently to meet the demand across the morning peak. Thereafter, the temperature keeps fluctuating within the temperature constraints in response to boiling water demand and the heating that is taking place inside the instant heater. When the controller finally switches off the instant heater at 18:00, the boiling water demand is low leading to a low rate of temperature loss. This temperature falls to 95.23 oC at the end of the operating cycle. The optimal controller can save to up to 35% of power-not-delivered from the grid in a 24-h operating cycle with about 7.7 kWh of energy sold back to the grid through an appropriate feed-in-tariff. The control strategy also leads to about 19% savings on energy cost while compared to the existing thermostatic control of the devices. These savings are significant in lowering the operating cost of the hot water devices over a long period of time. The adoption of these devices with optimal control strategy and renewable energy in many office and domestic buildings is therefore recommended as an efficient way of providing hot water. Through feeding heated water from HPWH to the instant heater, less energy is required to heat the water to the boiling level as desired. 4. Conclusion This paper introduces an optimal control strategy for controlling the operation of HPWH connected to an instant heater. The devices are powered using the renewable solar energy and the grid power, which can also receive back power through an appropriate feed-in-tariff. This control strategy leads to significant savings on energy and energy cost to the consumer. It offers a novel solution that would encourage the uptake and hence market penetration of HPWHs in developing nations like South Africa hence improving the efficiency of providing hot water in domestic houses. References [1] K. C. van Blommestein and T. U. Daim, “Residential energy efficient device adoption in South Africa,” Sustainable Energy Technologies and Assessments, vol. 1, pp. 13–27, 2013. [2] P. Nel, M. Booysen, and B. van der Merwe, “Energy perceptions in South Africa: An analysis of behaviour and understanding of electric water heaters,” Energy for Sustainable Development, vol. 32, pp. 62–70, 2016. [3] O. Ibrahim, F. Fardoun, R. Younes, and H. Louahlia-Gualous, “Optimal management proposal for hybrid water heating system,” Energy and Buildings, vol. 75, pp. 342–357, 2014. [4] J. O. Dada, “Towards understanding the benefits and challenges of Smart/Micro-Grid for electricity supply system in Nigeria,” Renewable and Sustainable Energy Reviews, vol. 38, pp. 1003–1014, 2014. [5] F. Shaikh, Q. Ji, and Y. Fan, “The diagnosis of an electricity crisis and alternative energy development in Pakistan,” Renewable and Sustainable Energy Reviews, vol. 52, pp. 1172–1185, 2015. [6] S. M. Sichilalu and X. Xia, “Optimal energy control of grid tied PV–diesel–battery hybrid system powering heat pump water heater,” Solar Energy, vol. 115, pp. 243–254, 2015. [7] P. Rousseau and G. Greyvenstein, “Enhancing the impact of heat pump water heaters in the South African commercial sector,” Energy, vol. 25, no. 1, pp. 51–70, 2000. [8] S. Sichilalu, T. Mathaba, and X. Xia, “Optimal control of a wind-PV-hybrid powered heat pump water heater,” Applied Energy, 2015. [9] S. M. Sichilalu and X. Xia, “Optimal power dispatch of a grid tied-battery-photovoltaic system supplying heat pump water heaters,” Energy Conversion and Management, vol. 102, pp. 81–91, 2015. [10] S. Sichilalu, H. Tazvinga, and X. Xia, “Optimal control of a fuel cell/wind/PV/grid hybrid system with thermal heat pump load,” Solar Energy, vol. 135, pp. 59–69, 2016. [11] D. S. Sowmy and R. T. Prado, “Assessment of energy efficiency in electric storage water heaters,” Energy and Buildings, vol. 40, no. 12, pp. 2128–2132, 2008.