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In this article, we describe the structure, the functioning, and the tests of parabolic trough solar thermal cooker (PSTC). This oven is designed to meet the needs of rural residents, including Urban, which requires stable cooking temperatures above 200 °C. The cooking by this cooker is based on the concentration of the sun's rays on a glass vacuum tube and heating of the oil circulate in a big tube, located inside the glass tube. Through two small tubes, associated with large tube, the heated oil, rise and heats the pot of cooking pot containing the food to be cooked (capacity of 5 kg). This cooker is designed in Germany and extensively tested in Morocco for use by the inhabitants who use wood from forests.
During a sunny day, having a maximum solar radiation around 720 W/m2 and temperature ambient around 26 °C, maximum temperatures recorded of the small tube, the large tube and the center of the pot are respectively: 370 °C, 270 °C and 260 °C. The cooking process with food at high (fries, ..), we show that the cooking oil temperature rises to 200 °C, after 1 h of heating, the cooking is done at a temperature of 120 °C for 20 min. These temperatures are practically stable following variations and decreases in the intensity of irradiance during the day. The comparison of these results with those of the literature shows an improvement of 30–50 % on the maximum value of the temperature with a heat storage that could reach 60 min of autonomy. All the results obtained show the good functioning of the PSTC and the feasibility of cooking food at high temperature (>200 °C).
Residential and commercial buildings account for more than one-third of global energy-related greenhouse gas emissions. Integrated multi-energy systems at the district level are a promising way to reduce greenhouse gas emissions by exploiting economies of scale and synergies between energy sources. Planning district energy systems comes with many challenges in an ever-changing environment. Computational modelling established itself as the state-of-the-art method for district energy system planning. Unfortunately, it is still cumbersome to combine standalone models to generate insights that surpass their original purpose. Ideally, planning processes could be solved by using modular tools that easily incorporate the variety of competing and complementing computational models. Our contribution is a vision for a collaborative development and application platform for multi-energy system planning tools at the district level. We present challenges of district energy system planning identified in the literature and evaluate whether this platform can help to overcome these challenges. Further, we propose a toolkit that represents the core technical elements of the platform. Lastly, we discuss community management and its relevance for the success of projects with collaboration and knowledge sharing at their core.
Eldorado summer schools
(1994)
This work presents a basic forecast tool for predicting direct normal irradiance (DNI) in hourly resolution, which the Solar-Institut Jülich (SIJ) is developing within a research project. The DNI forecast data shall be used for a parabolic trough collector (PTC) system with a concrete thermal energy storage (C-TES) located at the company KEAN Soft Drinks Ltd in Limassol, Cyprus. On a daily basis, 24-hour DNI prediction data in hourly resolution shall be automatically produced using free or very low-cost weather forecast data as input. The purpose of the DNI forecast tool is to automatically transfer the DNI forecast data on a daily basis to a main control unit (MCU). The MCU automatically makes a smart decision on the operation mode of the PTC system such as steam production mode and/or C-TES charging mode. The DNI forecast tool was evaluated using historical data of measured DNI from an on-site weather station, which was compared to the DNI forecast data. The DNI forecast tool was tested using data from 56 days between January and March 2022, which included days with a strong variation in DNI due to cloud passages. For the evaluation of the DNI forecast reliability, three categories were created and the forecast data was sorted accordingly. The result was that the DNI forecast tool has a reliability of 71.4 % based on the tested days. The result fulfils SIJ’s aim to achieve a reliability of around 70 %, but SIJ aims to still improve the DNI forecast quality.