Energy and Greenhouse Gas Emission Assessment of Conventional and Solar Assisted Air Conditioning Systems

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Energy consumption in the buildings is responsible for 26% of Australia’s greenhouse gas emissions where cooling typically accounts for over 50% of the total building energy use. The aim of this study was to investigate the potential for reducing the cooling systems’ environmental footprint with applications of alternative renewable energy source. Three types of cooling systems, water cooled, air cooled and a hybrid solar-based air-conditioning system, with a total of six scenarios were designed in this work. The scenarios accounted for the types of power supply to the air-conditioning systems with electricity from the grid and with a solar power from highly integrated building photovoltaics (BIPV). Within and between these scenarios, systems’ energy performances were compared based on energy modelling while the harvesting potential of the renewable energy source was further predicted based on building’s detailed geometrical model. The results showed that renewable energy obtained via BIPV scenario could cover building’s annual electricity consumption for cooling and reduce 140 tonnes of greenhouse gas emissions each year. The hybrid solar air-conditioning system has higher energy efficiency than the air cooled chiller system but lower than the water cooled system.

Highlights

  • The increasing concern over rapid growth of energy consumption and the need for reduction of greenhouse gas emissions in building services has become one of the priority objectives when planning the design of new buildings [1,2]

  • For the cooling demand, power consumption requirements and greenhouse gas emissions based on the local weather conditions

  • To test the potential of the solar power used by the building, an annual cumulative insolation analysis was performed using a building model and accounting for the nearby shading elements

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The increasing concern over rapid growth of energy consumption and the need for reduction of greenhouse gas emissions in building services has become one of the priority objectives when planning the design of new buildings [1,2]. The increased living standards, occupant comfort demands and building architectural characteristic trends, such as increasing application of transparent rather than opaque surfaces in the building envelope or even glass buildings, drive the growing energy demand for air-conditioning [3,4]. This occurs in residential and commercial buildings and in the educational building sector. The local availability of renewable energy sources should be considered a priority [6] for integration in sustainable green building designs. The cooling demand occurs in the daytime when the activities are occurring in the building, and the demand reduces to the background level after the sunset

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The Evaluation of Single-Family Detached Housing Units in terms of Integrated Photovoltaic Shading Devices: The Case of Northern Cyprus
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  • John Ogbeba + 1 more

In this paper, we evaluate passive and active strategies that can be used in solving the heating problems in the residential sector of Northern Cyprus. In doing so, we propose the use of photovoltaics as a shading device (PVSD). PVSD is known to produce clean energy from solar radiation and it also reduces the energy consumed for cooling. We use an empirical method to evaluate the performance of a typical family detached dwelling in Famagusta, Cyprus. The simulation result derived from the study indicates that the strategic use of PVSDs for openings oriented towards the east, west, and south can reduce its energy consumption by almost 50% in three months of the year and cut down up to 400 kWh of energy consumption through the year, thus raising the comfort level of the building by about 20%. It will also generate nearly 2800 W that can provide up to 50% of the electricity demand.

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Cu(In,Ga)Se2 (CIGSe) has been proven to be a better candidate as a light absorber layer in thin-film solar cells. However, most processes require high vacuum and high temperature during deposition, which results in significant loss of materials and is not applicable to a flexible substrate. Solution processes often involve low processing temperature and cheap precursor, can be used with flexible substrates, and offer the possibility of roll-to-roll manufacturing, potentially reducing manufacturing costs for the module. Here, we have experimentally investigated the optimum synthesis conditions for CIGSe nanoparticles fabricated by using a facile and a non-vacuum reflux method for low-temperature solution processes. By employing various reflux conditions by changing the temperature of heating mantle, single-phase CIGSe nanoparticles were synthesized at 200 °C. On the other hand, synthesized products with an impure multi-phase were formed at heating mantle temperatures lower than 200°C. XRD measurements confirmed that the Ga content of the CIGSe nanoparticles increased with increasing heating mantle temperature. In addition, the average diameter of the CIGSe nanoparticles increased with increasing reaction time from 5 min to 30 min at a fixed heating mantle temperature of a 200 °C. The optical band gap is calculated by using ultraviolet-visible (UV-Vis) absorption spectra, decreased from 1.69 eV to 1.29 eV with increasing reaction time due to the increased CIGSe nanoparticles size. From our results, we can conclude that the characteristics of the CIGSe nanoparticles can be effectively controlled by using simple growth conditions, thereby providing many advantages for the fabrication of absorber layers for use in CIGSe solar cells.

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An Innovative Adaptive Control System to Regulate Microclimatic Conditions in a Greenhouse
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In the recent past home automation has been expanding its objectives towards new solutions both inside the smart home and in its outdoor spaces, where several new technologies are available. This work has developed an approach to integrate intelligent microclimatic greenhouse control into integrated home automation. Microclimatic control of greenhouses is a critical issue in agricultural practices, due to often common sudden daily variation of climatic conditions, and to its potentially detrimental effect on plant growth. A greenhouse is a complex thermodynamic system where indoor temperature and relative humidity have to be closely monitored to facilitate plant growth and production. This work shows an adaptive control system tailored to regulate microclimatic conditions in a greenhouse, by using an innovative combination of soft computing applications. In particular, a neural network solution has been proposed in order to forecast the climatic behavior of greenhouse, while a parallel fuzzy scheme approach is carried out in order to adjust the air speed of fan-coil and its temperature. The proposed combined approach provides a better control of greenhouse climatic conditions due to the system’s capability to base instantaneous solutions both on real measured variables and on forecasted climatic change. Several simulation campaigns were carried out to perform accurate neural network and fuzzy schemes, aimed at obtaining respectively a minimum forecasted error value and a more appropriate fuzzification and de-fuzzification process. A Matlab/Simulink solution implemented with a combined approach and its relevant obtained performance is also shown in present study, demonstrating that through controlled parameters it will be possible to maintain a better level of indoor climatic conditions. In the present work we prove how with a forecast of outside temperature at the next time-instant and rule-based controller monitoring of cooling or heating air temperatures and air velocities of devices that regulate the indoor micro-climate inside, a better adjustment of the conditions of comfort for crops is achievable.

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Climate control is vitally important to the operation of greenhouses. However, many conventional methods for controlling greenhouse climate are not efficient enough since they are either based on an on-off control method or a proportional control method. To maintain a steady climate, an intelligent switching control strategy for greenhouse climate control system was designed using time series to analyze historical data from greenhouse climate control system and predict target attribute's value to regulate climatic conditions such as suppress or raise the environmental factor based on prediction results. The simulated results showed that the greenhouse climate can be stabilized and maintained within the ideal range by the proposed control strategy.

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