Linear Model of DHW System Using Response Surface Method Approach

Abstract

Using alternative and clean energy resources is considered the most effective method to deal with the environment and energy crises nowadays. In this study a comparative analysis of FPC data for DHW are theoretically and experimentally evaluated to optimise the design parameters. A forced circulation solar heating system using flat-plate collector, is modelled using T*SOL as a new approach, for hot water requirements of a laboratory unit at Szent Istvan University, in Gödöllő, Hungary. The modelling shows 69% solar fraction and 510 kWh annual solar gain. Furthermore, the comparison study was based on these two factors, and the two results matched with 93.12% accuracy. After the modelling, practically, the exergy analysis was conducted to determine and highlight the losses of the system. Since Hungary is considered a cold climate country, it was found that the thermal and optical losses from the collector and the piping system were tremendous. Then all the necessary design parameters were studied to achieve the optimal working points using non-linear correlation response surface method (RSM, which has never been used as an analysis tool in the solar field) at two perspectives (solar fraction and annual yield) for seven factors using R script. The factors were collector surface area, inclination angle, glycol-water ratio, tank capacity, boiler capacity, desired hot water temperature, and volume flow-rate. We identified the most influential single factors using ParetoPlot and each two-factorsꞌ interaction using contour plots. The most influential factors on the solar yield are solar collector surface area, tank capacity, desired hot water temperature and volume flow rate by magnitude effects of +129.7, +125.3, +50.9 and +17.2 kWh per annum, respectively.

Feasibility Study of Using Solar Thermal Energy for Heating Swimming Pools in Central European Climate (Hungary as a Case Study)

“…The number of experiments is determined by the formula 2 k , where k is a variable number. As each variable has two values [-1, +1], the total experiment number was 2 5 = 32. In addition to these 32 experiments, we conducted two more experiments considering that pool depth (B) is 1.5 m to identify second-degree non-linear coefficients.…”

“…Meanwhile, European countries such as Germany, Poland, Spain, Denmark, Italy, Austria, and Switzerland aggregate 27.1 GW [4]. According to the European Solar Thermal Industry Federation (ESTIF), Europe can save up to 5,600 tonnes of crude oil in 2020 by solar thermal energy [5]. By the end of 2050, the European Union will provide a solar thermal capacity of 1200 GW overall.…”

Analysis of Energy Consumption of a Thermo-Technical System with an Absorption Heat Pump

“…With continuous population growth and rising standards, energy consumption is also increasing. Therefore, renewable energy sources such as geothermal energy [1], biomass [2], solar energy [3] and wind power [4] need to be used more. By generating clean energy from renewable sources, green energy buildings [5] can reduce their dependence on fossil fuels, which is crucial for mitigating climate change.…”

Effects of Dynamic Shading on Thermal Exergy and Exergy Efficiency of a Photovoltaic Array

“…Although the first law of thermodynamics discusses the energy analysis of the PV systems, it does not discuss the contribution of energy types of the operating sources and it does not distinguish irreversibility [4]. The second law of thermodynamics, namely exergy, can be defined as the maximum work that can be theoretically obtained from a thermodynamic system [5].…”