Multi linear regression-based modeling and performance monitoring of flat plate solar collector outlet temperature in Alice, South Africa

In a period of rapidly increasing energy demand, the exploitation of abundantly available solar energy is imperative. Temperate climates like South Africa show good potential for utilizing solar-driven technologies such as solar water heaters. These systems offer an attractive alternative over conventional water geysers as a means to supply hot water for residential use. In South Africa, the solar water heater industry is growing rapidly as the government offers incentives manufactures and consumers. This necessitates the determination of performance of these systems through experimental analysis as well as performance prediction. This study evaluated the summer and winter performance of a flat plate, thermosyphon solar water heater under climatic conditions encountered in Alice, South Africa by considering the collector outlet temperature. The performance and weather data obtained were used to develop a multi linear regression (MLR) model for each season. MLR is a simple and easily applicable modelling approach which uses a set of input and output data to determine the model coefficients of a linear relation of two or more variables. The collector outlet temperature was correlated with solar radiation, ambient temperature, relative humidity, and collector inlet temperature since these variables have a direct impact on the collector temperature rise. Results from the performance showed that the collector performs well, attaining temperatures up to 87.2oC during the summer season and 70oC during winter season. The summer and winter percentage mean absolute error for the whole monitoring period were 4.07 percent and 6.2 percent respectively which indicate that MLR can be successfully applied to predict collector outlet temperatures in both seasons

Evaluation of the thermal performance and cost effectiveness of radiant barrier thermal insulation materials in residential construction

Reducing heating and cooling systems loads in buildings is a cost effective way to decrease energy consumption in residential houses. This reduction can be achieved in many ways including proper insulation of the building envelope. In recent years, considerable attention was given to the use of radiant reflective insulating barriers. Over the past years, reflective barrier insulation companies nationwide have experienced significant growth resulting in an industry average growth rate of 26.8%. This significant growth is expected to continue as a result of increased cooling demands and pressure from the energy sector and the economy. Growth is also predicted to be prevalent amongst the southern regions of the United States in efforts to reduce high cooling energy costs, which are expected to prevail. This significant growth has not been felt by the radiant barrier industry in Louisiana. This is mainly due to the lack of knowledge and amount of research available in quantifying radiant barriers thermal effectiveness for hot and humid climatic conditions widely encountered in the State. In order to improve the competitiveness of the reflective insulation industry, the primary goal of this research is to develop a simple estimating tool that may be used by homeowners, state agencies, and contractors to assess the effectiveness and economic benefits of radiant barrier insulation systems under the climatic conditions encountered in United States. Current research achieved this objective by adopting a multi‐dimensional research approach that developed this estimating tool over three main phases and then combined results of these phases to provide an overall assessment tool for this technology. In the first phase, the energy saving benefits of radiant barrier was quantified experimentally for the climatic conditions and construction practices prevalent in United States. A transient heat transfer finite element (FE) model was developed to predict the ceiling heat gain or loss through the attic space in residential buildings and to accurately estimate savings in cooling and heating loads produced by the radiant barrier application. Validity of the models was established by comparing their prediction with experimental data. In the second phase, economic effectiveness of radiant barrier technology was evaluated. In the third phase, development of the estimating tool and dissemination of the results was achieved. Results showed that radiant barrier can reduce heat flux transferred from roof to the condition space significantly

A Review of Photovoltaic Thermal (PVT) technology for residential applications: performance indicators, progress, and opportunities

Solar energy has been one of the accessible and affordable renewable energy technologies for the last few decades. Photovoltaics and solar thermal collectors are mature technologies to harness solar energy. However, the efficiency of photovoltaics decays at increased operating temperatures, and solar thermal collectors suffer from low exergy. Furthermore, along with several financial, structural, technical and socio-cultural barriers, the limited shadow-free space on building rooftops has significantly affected the adoption of solar energy. Thus, Photovoltaic Thermal (PVT) collectors that combine the advantages of photovoltaic cells and solar thermal collector into a single system have been developed. This study gives an extensive review of different PVT systems for residential applications, their performance indicators, progress, limitations and research opportunities. The literature review indicated that PVT systems used air, water, bi-fluids, nanofluids, refrigerants and phase-change material as the cooling medium and are sometimes integrated with heat pumps and seasonal energy storage. The overall efficiency of a PVT system reached up to 81% depending upon the system design and environmental conditions, and there is generally a trade-off between thermal and electrical efficiency. The review also highlights future research prospects in areas such as materials for PVT collector design, long-term reliability experiments, multi-objective design optimisation, techno-exergo-economics and photovoltaic recycling

Emerging Technologies for the Energy Systems of the Future

Energy systems are transiting from conventional energy systems to modernized and smart energy systems. This Special Issue covers new advances in the emerging technologies for modern energy systems from both technical and management perspectives. In modern energy systems, an integrated and systematic view of different energy systems, from local energy systems and islands to national and multi-national energy hubs, is important. From the customer perspective, a modern energy system is required to have more intelligent appliances and smart customer services. In addition, customers require the provision of more useful information and control options. Another challenge for the energy systems of the future is the increased penetration of renewable energy sources. Hence, new operation and planning tools are required for hosting renewable energy sources as much as possible

Modelling of small capacity absorption chillers driven by solar thermal energy or waste heat

Aquesta recerca es centra en el desenvolupament de models en règim estacionari de màquines d’absorció de petita potència, els quals estan basats en dades altament fiables obtingudes en un banc d’assajos d’última tecnologia. Aquests models podran ser utilitzats en aplicacions de simulació, o bé per a desenvolupar estratègies de control de supervisió dels sistemes d’aire condicionat amb màquines d’absorció. Per tant, l’objectiu principal d’aquesta investigació és desenvolupar i descriure una metodologia comprensible i que englobi el procés sencer: tant els assajos, com la modelització, com també el desenvolupament d’una estratègia de control per a les màquines d’absorció de petita potència. Basant-se en la informació obtinguda de forma experimental en el banc d’assajos, s’han desenvolupat cinc models, cadascun amb una base teòrica diferent. Els resultats mostren que és possible obtenir models empírics summament precisos utilitzant únicament com a paràmetres d’entrada les variables dels circuits externs d’aigua. Aquest treball finalitza amb la proposta de dues estratègies òptimes de control i el seu ús per al control on-line de sistemes basats en refredadores tèrmiques d’absorció.This research deals with the development of the simple, yet accurate steady-state models of small capacity absorption machines which are based on highly reliable data obtained in the state-of-the-art test bench. These models can further be used in simulation tools or to develop supervisory control strategies for air-conditioning systems with absorption machines. Therefore, the main aim of this research is to develop and to describe a comprehensive methodology which encloses entire process which consists of testing, modelling and control strategy development of small capacity absorption machines. Five different models are developed based on the experimental data obtained in the test bench. The results show that it is possible to develop highly accurate empirical models by using only the variables of external water circuits as input parameters. Finally, two optimal control strategies are developed to demonstrate how these models can be used for on-line control of absorption systems

Modelling and optimisation of decentralised hybrid solar biogas system to power an organic Rankine cycle (ORC-Toluene) and air gap membrane distillation (AGMD) for desalination and electric power generation

The intensive use of fossil fuels to meet the world energy and water demand has caused several environmental issues, such as global warming, air pollution and ozone depletion. Therefore, the integration of stand-alone decentralised hybrid renewable energy systems is a promising solution to satisfy the global energy-water demands and minimize the effects of fossil fuels utilisation. Among these hybrid technologies, concentrated solar power (CSP) combined with waste-based biogas to power organic Rankine cycle for cogeneration provide the means to generate dispatchable, reliable, renewable electricity and water in high direct normal incidence (DNI) regions around the world. Due to the strong inverse correlation between DNI resources and freshwater availability, most of the best potential CSP regions also lack sufficient freshwater resources. The current study proposes and applies a novel multi-dimensional modelling technique based on artificial neural networks (ANN) for hourly solar radiation and wind speed data forecasting over six locations in Oman. The developed model is the first attempt to integrate two ANN models simultaneously by using enormous meteorological data points for both solar radiation and wind speed prediction. The developed model requires only three parameters as inputs, and it can predict solar radiation and wind speed data simultaneously with high accuracy. As a result, the model provides a user-friendly interface that can be utilised in the energy systems design process. Consequently, this model facilitates the implementation of renewable energy technologies in remote areas in which gathering of weather data is challenging. Meanwhile, the accuracy of the model has been tested by calculating the mean absolute percentage error (MAPE) and the correlation coefficient (R). Therefore, the model developed in this study can provide accurate weather data and inform decision makers for future instalments of energy systems. Furthermore, a novel proposed hybrid solar and biogas system for desalination and electric power generation using advanced modelling techniques to integrate the stand-alone off-grid system has been designed. The novelty emerges from some facts, which are centralised around the use of a hybrid electric generation via Concentrated Solar Power (CSP) and anaerobic digestion biogas to achieve higher stability and profitability. Meanwhile, the cogeneration through the waste heat of the ORC drives the AGMD, which benefits as well from the higher stability due to hybridisation. In addition, an innovative and user-friendly modelling approach has been applied, and this efficiently integrates the individual energy components, i.e. PTC, anaerobic biogas boiler, ORC and AGMD, which fosters the optimisation of the proposed system. The models have been developed in the MATLAB/Simulink® software and have been used to investigate the system area, dimensions, and cost and to ensure that the electrical and water demand of the end-user are met. In addition, a new detailed thermo-economic assessment of the proposed hybrid solar biogas for cogeneration in off-grid applications has been investigated. An energy, exergy, and cost analysis has been performed and to fully utilise this, a sensitivity assessment on the developed model has been analysed to examine the effects of various design parameters on the thermo-economic performance. Finally, implementing an in-depth simulation testing of the system in a rural region in Oman is presented. The novel integrated solar and biogas system that has been designed through advanced modelling in the MATLAB/ Simulink® is integrated with a robust multi-objective optimisation technique to determine the best operating configuration. Three objective functions namely, maximising power and water production, and minimising the unit exergy product costs have been formulated. The turbine efficiency, top ORC vapor temperature and ORC condenser temperature has been selected as the decision variables. The non-dominated sorting genetic algorithm (NSGA-II) has been employed to solve the optimisation problem and produce a Pareto frontier of the optimal solutions. Further, the TOPSIS approach has been used to select the optimal solution from the Pareto set. The study constitutes the first attempt to holistically optimise such a hybrid off-grid cogeneration system in a robust manner

A quick review of the applications of artificial neural networks (ANN) in the modelling of thermal systems

Thermal systems play a main role in many industrial sectors. This study is an elucidation of the utilization of artificial neural networks (ANNs) in the modelling of thermal systems. The focus is on various heat transfer applications like steady and dynamic thermal problems, heat exchangers, gas-solid fluidized beds, and others. Solving problems related to thermal systems using a traditional or classical approach often results to near feasible solutions. As a result of the stochastic nature of datasets, using the classical models to advance exclusive designs from the experimental dataset is often a function of trial and error. Conventional correlations or fundamental equations will not proffer satisfactory solutions as they are in most cases suitable and applicable to the problems from where they are generated. A preferable option is the application of computational intelligence techniques focused on the artificial neural network model with different structures and configurations for effective analysis of the experimental dataset. The main aim of current study is to review research work related to artificial neural network techniques and the contemporary improvements in the use of these modelling techniques, its up-and-coming application in addressing variability of heat transfer problems. Published research works presented in this paper, show that problems solved using the ANN model with regression analysis produced good solutions. Limitations of the classical and computational intelligence models have been exposed and recommendations have been made which focused on creative algorithms and hybrid models for future modelling of thermal systems.http://www.etasr.com/index.php/ETASR/indexdm2022Mechanical and Aeronautical Engineerin

Investigation into the effects of flow distribution on the photovoltaic performance of a building integrated photovoltaic/thermal solar collector

The conversion of solar energy into usable forms of energy such as electricity and heat is attractive given the abundance of solar energy and the numerous issues recently raised in the consumption of fossil fuels. Solar conversion technologies may generally be categorised as either photovoltaic or solar thermal types capable of converting incidental sunlight into electricity and heat respectively. The photovoltaic cell is able to transform incidental sunlight into electricity via the Becquerel effect, however, the single junction crystalline silicon solar cell, the predominant cell type in today’s photovoltaic market is only able to utilise a small portion (less than 20%) of incidental sunlight for this purpose. A majority of the remaining portion is absorbed much like a traditional solar thermal collector and sunk as heat by the cell, elevating its operating temperature. Given the negative effect of temperature on photovoltaic cell operation, where a linearly proportional drop in conversion efficiency with elevated temperature can be expected, photovoltaic conversion can be reduced significantly particularly in areas of high irradiance and ambient temperatures. Based on the intrinsic absorption characteristics of the photovoltaic cell, a third type of solar panel referred to as the hybrid photovoltaic thermal collector (PVT) collector has been developed where fluid channels running along the underside of the photovoltaic panel transfer heat away from the cells to minimise this detrimental effect. Furthermore, heat captured from the cells may then be used for space heating or domestic hot water improving the overall collector efficiency. In this study a unique building integrated PVT (BIPVT) collector is investigated consisting of an aluminium extrusion with structural ribs, fluid channels, and solar conversion materials. In order to evaluate this design, a mathematical model of the collector was developed in order to determine both thermal and electrical yield of the proposed design. The thermal analyses of the building integrated PVT collector in previous studies have generally adopted the approach applied to traditional solar thermal collectors where the distribution of coolant fluid flowing through the piping array is assumed uniform. For a conventional solar thermal collector this simplification may be reasonable under certain circumstances, however, given the temperature sensitivity of photovoltaic cells and their electrical connection scheme, this assumption may lead to significant modelling error. In order to further investigate this issue, a mathematical model has been developed to determine the photovoltaic yield of a BIPVT collector operating under non-homogeneous operating temperature as a result of flow maldistribution. The model is composed of three steps individually addressing the issues of 1) fluid flow, 2) heat transfer, and 3) the photovoltaic output of a BIPVT array. Fluid analysis was conducted using the finite element method in order to obtain the individual fluid channel flow rates. Using these values, a heat transfer analysis was then conducted for each module forming the BIPVT array to calculate the photovoltaic operating temperature for the constituent cells forming the array. During this step the finite difference method was utilised to approximate the fin efficiency of the building integrated collector, taking into account its irregular geometry. Finally the photovoltaic yield was calculated using a numerical approach which considered the individual operating temperature of the PV cells. During this step a new method was identified to determine the values of series and shunt resistances and also the diode constant required for the modelling of photovoltaic devices based on the multi-dimensional Newton-Raphson method and current-voltage equations expressed using the Lambert W-function. Experimentation was carried out to validate the new modelling methods. These models were combined to quantify the detrimental impact of flow mal-distribution on photovoltaic yield for a number of scenarios. In the case where flow uniformity was poorest, only a 2% improvement in photovoltaic yield was obtained in comparison to a traditional photovoltaic panel operating under the same environmental conditions. For the case where flow uniformity was optimal however, photovoltaic output was improved by almost 10%. This work has shown that the effects of poor flow distribution has the potential to have a substantial negative impact on the photovoltaic output of a building integrated solar collector especially given the variability in its physical geometry. The appropriate design of this technology should therefore consider the effects of this phenomenon. The methodology presented in this study can be used to approximate PV output for a BIPVT array with different array geometries and operating characteristics. Furthermore, the method to calculate solar cell modelling parameters developed in this study is not only useful for the analysis of hybrid PVT systems, but for the general analysis of photovoltaic systems based on crystalline silicon solar cells