Stephen Tangwe

Modelling of an on-farm direct expansion bulk milk cooler to establish baseline energy consumption without milk pre-cooling: A case of Fort Hare Dairy Trust, South Africa

Storage of milk at a low temperature of 4°C inhibits bacterial growth. As such bulk milk coolers (BMC) are used for cooling and storage of milk on dairy farms. This paper presents performance monitoring of a direct expansion bulk milk cooler to establish its baseline energy consumption without milk pre-cooling through mathematical modelling. A data acquisition system comprising a power meter, a data logger, temperature sensors and relative humidity and ambient temperature sensors was constructed to capture the energy consumption of the BMC, room temperature and ambient conditions. On-farm milk records were used to determine milk production per milking session. Two milking times were considered, that is for the morning and the late afternoon periods. The average daily electrical energy consumption of the BMC for the two milking times was 48.31 kWh and 43.23 kWh, respectively. Mathematical models represented as multiple linear regression models were built and developed using the experimental data. The developed mathematical models gave good agreement with the experimental results as evidenced by correlation coefficients of 0.922 and 0.8995. ReliefF algorithm revealed that volume of milk is the principal contributor to the energy consumption of the BMC for both the AM and PM milking.

Prediction of coefficient of performance and simulation design of an air-source heat pump water heater

Purpose The purpose of this study was to build and develop mathematical models correlating ambient conditions and electrical energy to the coefficient of performance (COP) of an air-source heat pump (ASHP) water heater. This study also aimed to design a simulation application to compute the COP under different heating up scenarios, and to calculate the mean significant difference under the specified scenarios by using a statistical method. Design/methodology/approach A data acquisition system was designed with respect to the required sensors and data loggers on the basis of the experimental setup. The two critical scenarios (with hot water draws and without hot water draws) during the heating up cycles were analyzed. Both mathematical models and the simulation application were developed using the analyzed data. Findings The predictors showed a direct linear relationship to the COP under the no successive hot water draws scenario, while they exhibited a linear relationship with a negative gradient to the COP under the simultaneous draws scenario. Both scenarios showed the ambient conditions to be the primary factor, and the weight of importance of the contribution to the COP was five times more in the scenario of simultaneous hot water draws than in the other scenario. The average COP of the ASHP water heater was better during a heating cycle with simultaneous hot water draws but demonstrated no mean significant difference from the other scenario. Research limitations/implications There was a need to include other prediction parameters such as air speed, difference in condenser temperature and difference in compressor temperature, which could help improve model accuracy. However, these were excluded because of insufficient funding for the purchase of additional temperature sensors and an air speed transducer. Practical implications The research was conducted in a normal middle-income family home, and all the results were obtained from the collected data from the data acquisition system. Moreover, the experiment was very feasible because the conduction of the study did not interfere with the activities of the house, as occupants were able to carry out their activities as usual. Social implications This paper attempts to justify the system efficiency under different heating up scenarios. Based on the mathematical model, the performance of the system could be determined all year round and the payback period could be easily evaluated. Finally, from the study, homeowners could see the value of the efficiency of the technology, as they could easily compute its performance on the basis of the ambient conditions at their location. Originality/value This is the first research on the mathematical modeling of the COP of an ASHP water heater using ambient conditions and electrical energy as the predictors and by using surface fitting multi-linear regression. Further, the novelty is the design of the simulation application for a Simulink environment to compute the performance from real-time data.

Comparative analysis of the coefficient of performance of an on-farm direct expansion bulk milk cooler

Milk cooling is one of the energy intensive processes in the dairy farm and dairy processing. In a dairy farm, the bulk milk cooler (BMC) should cool milk from a temperature of 35°C to a storage temperature of 4°C. Since the BMC is the major equipment used to extract heat from the milk, it is important to understand the efficiency of the system in a bid to reduce demand in dairy farms. This study presents a comparative analysis on the COP of a direct expansion BMC to establish its performance under the morning (AM) and late afternoon (PM) milking times. A data acquisition system was designed to capture the power consumption of the BMC, refrigerant temperature at the compressor and condenser inlet and outlet points, milk temperature as well as the relative humidity and ambient temperature. Findings from the study showed that on average the COP of the AM milking time was higher (2.20) than that of the PM milking time of the BMC (1.93). It was noted that, increase in milk volume led to increase in the COP such that the peak period with high milk volumes recorded high COP increase by 12.61% and 19.81% for the AM and PM milking times respectively. Notwithstanding, the performance of the BMC was also directly influenced by the change in ambient temperature.

Performance monitoring and prediction of a domestic split-type air conditioner

It has been very challenging to accurately monitor and predict the performance of air conditioners due to system operation complexity and huge number of already installed systems. This has made it cumbersome and somewhat difficult to accurately ascertain the effect of this technology on the grid, the amount of achievable energy savings, emission reduction and water usage savings upon replacing traditional space conditioning devices with this system, especially for countries like South Africa whose primary source of energy is coal. The accuracy of the existing system monitoring and prediction methods is low. This paper intends to develop four models of higher accuracy that monitor and predict the heating and cooling performance in terms of COP and energy of a domestic split-type air conditioner. These multiple linear regression models were built via data experimentally obtained for environmental, system thermal variation and human behavioural variation predictors. With a high correlation existing between the predictors and the various responses (correlation coefficient of models between 0.95 and 0.97), the models possessed a determination coefficient of between 0.90 and 0.94. Hence, the developed models have a higher accuracy in predicting system performance irrespective of the season of operation. It was also realised that just about 57.63% of total daily heating energy is used for daily cooling by the system.

Impact of standby losses and potential reduction by installation of isotherm blanket on the hot water cylinders

Air source heat pump (ASHP) water heater is an energy-efficient device for sanitary hot water production. The study focused on monitoring the electrical energy consumed to compensate for the standby losses of three hot water cylinders without and with isotherm blankets. Accordingly, the analysis of thermal energy losses was performed using 150 L high-pressure geyser and 150 L split and integrated types ASHP water heaters without hot water being drawn off throughout the entire monitoring period. Likewise, to experimentally determine the thermal losses, a data acquisition system (DAS) was constructed to measure the average ambient temperature and relative humidity as well as the cumulative electrical energy to compensate for the standby losses. The results on average electrical energy consumed to compensate for the standby losses of the geyser, split and integrated types ASHP water heaters without the isotherm blankets were 2.71 kWh, 1.33 kWh and 0.94 kWh, respectively. The introduction of a 40 mm thick isotherm blankets on the hot water cylinders resulted in the electrical energy reduction by 18.5%, 15.8% and 3.2 % for the geyser, split and integrated types ASHP water heaters, respectively. The multiple comparison tests revealed a significant difference on the geyser standby losses under the two configurations.

Design of a heat pump water heater performance monitoring system: To determine performance of a split type system

Purpose This paper aims to show that by using air source heat pump (ASHP) water heater in the residential sector, the energy consumption from sanitary hot water production can be reduced by more than 50 per cent. Hence, this study quantitatively and qualitatively confirms that domestic ASHP water heater is a renewable and energy efficient device for sanitary hot water production. Design/methodology/approach Design and building of a data acquisition system comprises a data logger, power meters, flow meters, temperature sensors, ambient and relative humidity sensor and an electronic input pulse adapter to monitor the ASHP water heater performance. All the sensors are accommodated by the U30-NRC data logger. The temperature sensors are installed on the inlet pipe containing a flow meter and the outlet pipe of the ASHP unit, the vicinity of both evaporator and expel cold air. An additional temperature sensor and a flow meter that cater for hot water drawn off measurements are incorporated into the data acquisition system (DAS). Findings The result from a specific monitoring split type ASHP water heater gives an average daily coefficient of performance (COP) of 2.36 and the total electrical energy of 4.15 kWh, and volume of hot water drawn off was 273 L. These results were influenced by ambient temperature and relative humidity. Research limitations/implications The cost involved in purchasing the entire sensors and data logger limits the number and categories of ASHP water heaters whose performance were going to be monitored. Pressure sensors were excluded in the data acquisition system. Practical implications The data acquisition system can easily be designed and the logger can also be easily programed. Hence, no high technical or computer skills are needed to install the DAS and to be able to read out the results. Social implications Hence, the data acquisition system can be installed on the entire domestic Eskom roll out air source heat pump water heaters to effectively determine the coefficient of performance and demand reductions. Originality/value This DAS is the first of its kind to be built in South Africa to be used to determine the performance of an ASHP water heater with high accuracy and precision. DAS is also robust.

An experimental study to determine the performance and potential saving of swimming pool air source heat pump water heater

Swimming pool desirable water set temperature can range from 27-30 °C depending on the season of the year. The energy consumption in a bid to heat up the water to the set point temperature can be daunting especially when utilizing convectional electric heaters. The implementation of a swimming pool, air source heat pump as an efficient and renewable energy device could lead to a significant reduction in the energy consumption. The paper focused on the determination of the dynamic power consumption of the swimming pool heat pump which is correlated to the coefficient of performance (COP) of an installed pool heat pump required to heat up a 75000 liters of stored water to set point temperature of 30 °C. A data acquisition system was designed to accommodate power meters, heat pump inlet and outlet water temperature sensors, flow meter and the ambient temperature sensor. All the sensors and power transducers were housed by a data logger configured to log every one minute. Base on the experimentally determine energy consumption of the swimming pool heat pump and the COP during various heating up cycles, the potential electrical energy saved could be achieved. The achievable demand and energy saving of the swimming pool heat pump water heater could facilitate the economic cost analysis with the goal of determining simple payback period.

A review on the thermodynamic and electrical properties of South African acceptable refrigerants as R22 substitutes in domestic air conditioners in South Africa

Air conditioners are responsible for human comfort, food preservation and equipment maintenance in residential, commercial and industrial sectors and the working fluid of this system is the refrigerant which forms the heart of most modern air conditioning systems. It is therefore imperative that care be taken in the choice of refrigerants for this system. In this light, South Africa has decided on the acceptable refrigerants R407A, R410A, R717, R744, R134a and R600. This paper seeks to literally survey the acceptable alternative refrigerants in South Africa, their characteristics, their thermodynamic and electrical impact on an air conditioning system. These characteristics include volumetric cooling capacity (VCC), pressure ratio, compressor power and COP. It reveals pressure ratio for the various alternatives is higher than for R22 with R410A emerging highest, the cooling capacity of all the refrigerants are lower than that of R22 except R717 and R744. COP of some of these refrigerants were noticed to be higher than that of R22 with that of R600 being the highest and compressor power of some of the alternatives were discovered to be lower than that of R22 with that of R600 being the lowest. R407A was recommended as a potential R22 substitute due to its zero ODP and insignificant difference in crucial parameters between the latter and the former.

An innovative optimization technique on performance efficiency verification in a coal thermal power plant unit

Coal thermal power plant, like most power plants is constructed solely for electricity generation. More explicitly, routine energy efficiency interventions are carried out in a unit of the power plant to ensure that it continues to operate at optimal performance as per the manufacturer rating. The study focused on the development and building of a multiple linear regression model for the power generated in a unit of the coal thermal power plant; with air heater temperature, main super heater steam temperature, high pressure heater temperature, condenser well temperature, and mass of coal burnt as the predictors. The model was developed using three months after outage as well as three months data after a year of the intervention from open literature. An optimization technique known as the constraint linear least square regression was applied in computing the optimal input data set corresponding to a desired response, whereby the mathematical model equation was used as the constraint equation. The benefits of the optimization technique were to enable the plant engineers to schedule a service plan on the unit. This was done with respect to the specific components of the unit observed to be under performing by judging from the final results after running the optimization. Based on the number of predictors showing a significant difference between the actual and the optimized data set, the maintenance can be termed minor or major intervention.

A quantitative and qualitative methodology to evaluate performance improvement of a coal power plant in South Africa by the virtue of energy efficiency intervention

The Industrial and Commercial sectors in South Africa consume more than 80% of the electricity generated by Eskom. The generation of electricity to meet the demand in these sectors is primarily derived from the coal thermal power plant. The goal of Eskom is to sustain the demand and equally reduce environmental pollution. Eskom has embarked on energy efficiency initiatives on their coal boiler plant in a bid to decrease the amount of coal burnt and in turn increase the electricity generated. The study focused on the analysis of the before and after outage data obtained from the unit cards in one of the Eskoms “once through” 600 MW coal boiler with a mechanical conversion efficiency of 35 % (from manufacturer specification). Multiple linear regression models were developed and built to predict the power generated and sent out in correlation with the predictors (average air heater temperature, average main stream super heater temperature, average high pressure heater temperature, the total mass of coal burnt, auxiliary power consumption, average of the cold well and hot well condenser temperature and pressure). The data obtained 3 months before and after an outage showed an average power generated of 434.95 MW and 502.08 MW respectively. The results also revealed that the cumulative energy gained was 44000 MWh. Finally, the reliefF algorithm ranked all predictors as primary factors with the high pressure heater and main stream super heater temperatures contributing the most by virtue of the weight of importance to the power generated.