Renewable Energy Economics, Policies and Planning
Zeinab Ghasemi Sangi; Abbas Tarkashvand; Hanieh Sanaeian
Abstract
The height of buildings is one of the main features of urban configuration that affects energy consumption. However, to our knowledge, the complexity of relationships between the height parameters and energy use in urban blocks is poorly understood. In this context, the present study investigates the ...
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The height of buildings is one of the main features of urban configuration that affects energy consumption. However, to our knowledge, the complexity of relationships between the height parameters and energy use in urban blocks is poorly understood. In this context, the present study investigates the effect of the height distribution of buildings located in a residential complex on the energy consumption required for cooling and heating. This research simulates different possible layouts through computational software. For this purpose, first, the density of a residential complex was determined based on the rules and regulations of Tehran city and according to the site dimensions and certain site coverage. Then, the required building density was distributed in different layouts based on their diversity at different heights. The product of this stage involved 7 different layouts in which the height varied from 1 floor to the maximum number calculated in each part of the simulation. In the next step, the annual energy consumption for cooling and heating the complex was calculated for each of these layouts and compared with each other. The parametric generative model was created in the Grasshopper plugin from Rhino software, and the energy consumption was evaluated with the Honeybee plugin over one year. Also, the research findings were validated through DesignBuilder software using the EnergyPlus engine. The results of the energy simulation indicate that the height distribution of the blocks can have a significant effect on energy consumption. In the optimal case, proper layout reduces the annual cooling and heating energy consumption by 28 % and 13 %, respectively. Therefore, achieving an optimal value for each of the cooling and heating loads depends on the specific priorities and conditions of the design project. If the design project's priority is to reduce heating energy consumption, increasing the height and distributing the floors evenly between the blocks is a better answer. However, if the priority is to mitigate cooling energy consumption, the optimal layout can include low-rise blocks and a single very high-rise block.
Renewable Energy Resources and Technologies
Abir Hmida; Abdelghafour Lamrani; Mamdouh El Haj Assad; Yashar Aryanfar; Jorge Luis Garcia Alcaraz
Abstract
Around the globe, a 60 % increase in energy demand is predicted to occur by the end of the year 2030 due to the ever-increasing population and development. With a registered temperature up to 50 °C in August 2020, which is classified as one of the hottest regions in the world, the demand for cool ...
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Around the globe, a 60 % increase in energy demand is predicted to occur by the end of the year 2030 due to the ever-increasing population and development. With a registered temperature up to 50 °C in August 2020, which is classified as one of the hottest regions in the world, the demand for cool temperatures in Gabes-Tunisia to achieve the thermal comfort of people ensuring the product storage has become more and more intense. Removing heat from buildings represents the most extensive energy consumption process. In this paper, an absorption-refrigeration system driven by solar energy is proposed. A parametric simulation model is developed based on the TRNSYS platform. A comparison between different models for global radiation calculation and experimental meteorological data was carried out. It has been proven that the Brinchambaut model seems to be the most convenient in describing the real global radiation, with an error of up to 3.16 %. An area of 22 m² of evacuated tube solar collector ensures the proper functioning of the generator and achieves a temperature up to 2 °C in the cold room.
Renewable Energy Resources and Technologies
Selfa Johnson Zwalnan; Nanchen Nimyel Caleb; Mahan Morgan Mangai; Nantim Yohana Sanda
Abstract
The effect of solar collector configurations on the thermal efficiency of an active solar water heater was investigated using TRNSYS in this study. Two versions of a solar heater were formulated on the basis of serpentine and riser-header flat plate configurations. Both models were simulated based on ...
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The effect of solar collector configurations on the thermal efficiency of an active solar water heater was investigated using TRNSYS in this study. Two versions of a solar heater were formulated on the basis of serpentine and riser-header flat plate configurations. Both models were simulated based on the same parameters and weather conditions. Besides, in accordance with clear sky and cloudy sky conditions, a parametric analysis was performed to determine the impact of varying parameters on the thermal efficiency of the two models. The results showed that the serpentine-based device model provided about 2.62 % more usable thermal energy than the riser-header configuration. In addition, both models demonstrated the same response and sensitivity to changes in the collector area and the volume of the tank. However, on a cloudy day, the efficiency of serpentine showed a significant improvement and sensitivity to flow variance with an efficiency gap of about 30 % to the riser header configuration.
Environmental Impacts and Sustainability
Mohammad Hossein Jahangir; Mahnaz Abolghasemi; Seyedeh Mahsa Mousavi Reineh
Abstract
Drought is considered as a destructive disaster that can have irreversible effects on different aspects of life. In this study, artificial neural network was used as a powerful means of modeling nonlinear and indefinite processes in order to simulate drought intensities at 7 synoptic stations of Khorasan ...
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Drought is considered as a destructive disaster that can have irreversible effects on different aspects of life. In this study, artificial neural network was used as a powerful means of modeling nonlinear and indefinite processes in order to simulate drought intensities at 7 synoptic stations of Khorasan Razavi from more than 35 years ago up to the year 2014. Input data were the calculations of the two indicators of PNPI and SPI by DIC software, and the output layer (drought intensity) was taken to the Matlab software and employed as the teaching data (from 25 years), experiment (from 5 years), and validation (from another 5 years). The 3-9-1 structure of the network of layers had the maximum accuracy with the error rate of less than 2 % and high correlation (more than 90 %). After trial and error for each station through sigmoid stimulation function in the Perceptron network, it was observed that the stations of Mashhad and Quchan had the minimum error and the maximum error was related to the station of Neyshabur. The results of comparisons and observations showed that the artificial neural network had high efficiency in simulation of the data. The obtained correlation amount of 0.999 for the base station represented the small error of the model in prediction. Drought forecasting was performed in this study by the trained algorithm in the artificial neural network without using the observation data. The results showed that rainfall, temperature, and speed models had a positive role in forecasting the provinces that would experience drought. Due to its lower amount of error, SPI indicator was selected for mapping, the findings of which showed that the highest drought intensity belonged to the near normal to normal wet lands.
