Set Of Solar Panels Research Articles

Remodelling of the heating systems of a sports centre based on life cycle assessment. Part I: Boiler replacement.

The remodelling study of heating and cooling installations of the municipal sports centre of Ordizia (Spain) has been widened including a renewable energy proposal, integrating also the concept of life cycle analysis (LCA) of the installation which allows therefore, to analyze the environmental impact prior its approval and implementation. The analysis of the inclusion of two set of solar panels (thermal and photovoltaic) in addition to the substitution of the old diesel boiler by a more efficient natural gas equipment, in order to satisfy the power demand of the installations, has been studied by means of life cycle analysis. The supply directly from the grid is the alternative with the greatest impact, while the photovoltaic is the most efficient one from an environmental standpoint. However, when solar irradiation is insufficient for the needs of the sports centre, a hybrid system is the best choice. In a similar way, in order to satisfy the heat demand, the combination of thermal panels with the natural gas boiler has been proven to be a good solution.

Stochastic Analysis of a Three-Unit Non-Identical Repairable System with Simultaneous Working of Cold Standby Units

Here, stochastic analysis of a repairable system of three units has been carried out by taking one unit in operation (called main unit) and two identical units (called duplicate units) in cold standby. The switch device is used to convert the standby units into operative mode. A single server is hired to handle repair activities of the units who visits the system instantly whenever needed. The repair done by the server is perfect and thus the repaired unit follows the same lifetime distribution as the original. The constant failure rates are considered for both main and the duplicate units while their repair time distributions are taken as arbitrary. Some important reliability measures including mean sojourn times (MST), transition probabilities (TP), mean time to system failure (MTSF), availability, expected number of repairs for both kinds of units separately, expected number of visits by the server and busy period analysis of the server due to repair are determined using semi-Markov process (SMP) and regenerative point technique (RPT). The arbitrary values of the parameters are considered to examine the behaviour of some significant reliability measures through graphs. The possible application of the system model can be visualized in a power supply system of a house where a set of solar panels are kept in spare for their simultaneously working when main power supply is discontinued.

Water harvesting cube

Water scarcity is at the center of the world’s greatest challenges, including famine, disease, and sustainable development. In many countries, there are active researches aimed at improving the supply of fresh water through actions such as seawater desalination and water recycling. Researchers are also working, on a smaller scale, to harvest water from the atmosphere to serve individual households or small communities. Cool surface condensation, fog catchers, and humidity harvesting are three examples of sustainable approaches that relied on affordable and simple equipment. This paper aims to introduce the possibility of using water condensation to generate potable water by using a self-sustainable-energy device. The device is scalable; being able to meet the needs of a single household and up to a residential district. The focus of this research is on the function of a water-harvesting cube. It consists of a set of solar panels, an energy converter, a dehumidifier(s), a water treatment component, and a water storage tank. The sum of all parts forms a 1 × 1 × 1 m cube. The premise of the proposal is that one dehumidifier can produce a sufficient amount of pure water for an individual’s various daily uses. The researcher conducted two experiments during the summer of 2018, one in London, Ontario, Canada, and the other in Doha, Qatar. The result showed that in an environment of 50–70% relative humidity, a single dehumidifier could produce up to 15 L of pure water per day. The research here proves that the proposed water harvesting cube is efficient, affordable, and requires low maintenance.

The Queen’s Residence Energy Challenge

The Queen’s Residence Energy Challenge (QREC) is an energy conservation initiative taking place in the residence halls at Queen’s University coordinated by the AMS Sustainability Office and the Sustainability Coordinator for Student Affairs . It is a two-part competition. Part one of the competition is an interresidence competition in which each residence hall will be competing to reduce their energy expenditures. Energy use will be compared to the corresponding time in the previous year, and the residence that reduces their energy use by the highest percentage will win the competition. This part of the project is being organized by members of the AMS Sustainability Office and the Sustainability Coordinator (Office of Student Affairs), and Residence Life staff and floor dons are helping execute it. The second part of the competition is an inter-university pledge drive, in which residents will be encouraged to sign a pledge stating that they will be participating in the QREC. Queen’s will be competing against the Universities of Waterloo and Guelph, and the school that has the highest percentage of residents participating will win a set of solar panels as a symbol of energy conservation and renewable energy. This part of the project is being coordinated by the Sierra Youth Coalition who has obtained funding from the Ontario Power Authority. The goals of the QREC are to reduce overall energy use in the residences, help students living in residence learn about their own energy consumption and ways to reduce it, and create a culture of sustainability at Queen’s. In this presentation I will go through the overall timeline of executing and planning the project, provide examples of ways to reduce energy consumption in residence, and provide results of both parts of the competition.

Modeling and Simulation of a Solar Thermal System for Domestic Space Heating Using Radiators Low Temperature

This article presents the study of the thermal behavior of a solar heating system at low temperature for an old individual home built in the 1990s. In which, on one hand, a traditional fluid heating boiler is replaced by a storage tank heated by a set of solar panels and on the other hand, the existing conventional radiators (75° C/65 °C) are replaced by radiators at low temperature (50° C/45 °C). The numerical model is used to evaluate temperature changes of each part of the system (collection, storage, distribution and indoor air of the room).Comparing these results with those obtained by a home heated by radiators at high temperature associated with a traditional boiler. The simulation entry parameters include the climatic conditions concerning the area of Adrar (27.10 N, 0.17 W, altitude279 m) in southAlgeriafor four successive days in January where the average minimum and maximum temperatures are respectively about 4 ° C and19 °C. The results show that the integration of solar heating using low temperature radiators in an old individual home provides adequate comfort conditions while minimizing the energy consumption of 20%. Furthermore, this heating technique helps to decrease each year 20% of carbon emissions and reduce energy costs.

Parasol and GreenSwitch

Several companies have recently announced plans to build "green" datacenters, i.e. datacenters partially or completely powered by renewable energy. These datacenters will either generate their own renewable energy or draw it directly from an existing nearby plant. Besides reducing carbon footprints, renewable energy can potentially reduce energy costs, reduce peak power costs, or both. However, certain renewable fuels are intermittent, which requires approaches for tackling the energy supply variability. One approach is to use batteries and/or the electrical grid as a backup for the renewable energy. It may also be possible to adapt the workload to match the renewable energy supply. For highest benefits, green datacenter operators must intelligently manage their workloads and the sources of energy at their disposal. In this paper, we first discuss the tradeoffs involved in building green datacenters today and in the future. Second, we present Parasol, a prototype green datacenter that we have built as a research platform. Parasol comprises a small container, a set of solar panels, a battery bank, and a grid-tie. Third, we describe GreenSwitch, our model-based approach for dynamically scheduling the workload and selecting the source of energy to use. Our real experiments with Parasol, GreenSwitch, and MapReduce workloads demonstrate that intelligent workload and energy source management can produce significant cost reductions. Our results also isolate the cost implications of peak power management, storing energy on the grid, and the ability to delay the MapReduce jobs. Finally, our results demonstrate that careful workload and energy source management can minimize the negative impact of electrical grid outages.

Parasol and GreenSwitch

Several companies have recently announced plans to build "green" datacenters, i.e. datacenters partially or completely powered by renewable energy. These datacenters will either generate their own renewable energy or draw it directly from an existing nearby plant. Besides reducing carbon footprints, renewable energy can potentially reduce energy costs, reduce peak power costs, or both. However, certain renewable fuels are intermittent, which requires approaches for tackling the energy supply variability. One approach is to use batteries and/or the electrical grid as a backup for the renewable energy. It may also be possible to adapt the workload to match the renewable energy supply. For highest benefits, green datacenter operators must intelligently manage their workloads and the sources of energy at their disposal. In this paper, we first discuss the tradeoffs involved in building green datacenters today and in the future. Second, we present Parasol, a prototype green datacenter that we have built as a research platform. Parasol comprises a small container, a set of solar panels, a battery bank, and a grid-tie. Third, we describe GreenSwitch, our model-based approach for dynamically scheduling the workload and selecting the source of energy to use. Our real experiments with Parasol, GreenSwitch, and MapReduce workloads demonstrate that intelligent workload and energy source management can produce significant cost reductions. Our results also isolate the cost implications of peak power management, storing energy on the grid, and the ability to delay the MapReduce jobs. Finally, our results demonstrate that careful workload and energy source management can minimize the negative impact of electrical grid outages.