Biomass Boiler Installation in Giza, Egypt

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Gas Fuel Thermal Fluid Oil Heater Installation in Egypt Company Profile Romiter Group Limited are committed to manufacturing and exporting complete enery saving heating equipment, including thermal oil boiler (Thermal fluid heat transfer product), thermal oil steam generator, cryogenic storage Dewar. After many years reach & development, Romiter Group can offer coal fired thermal

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Giza North Power Project is a 2,250MW dual-fuel fired power project. It is located in Giza, Egypt.

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Downloadable (with restrictions)! Hybrid air-water heat pump systems combine the efficiency of the former with the boiler backup system when external conditions are unsuitable. For the rural house sector, the use of biomass boilers as backup also allows the sustainable use of local natural resources. The appropriate choice of size for both units is a complex decision that depends not only on demand and climate but also on other parameters, such as the storage tank and the control strategy. Specifically with biomass boilers, this choice has not been sufficiently addressed in the scientific literature. For this reason, a dynamic model of this hybrid scheme has been created, the analysis of which has been carried out with energy, environmental and economic indicators. This model has been applied to a single-family house in three areas in Spain with a higher demand for heating than cooling and with different efficiency standards, comparing different sizes of inverter heat pump with commercial features to cover the required demand together with the boiler. With all the reservations given by the variability of the case studies analyzed, it can be stated that the approximate value of a heat pump with a nominal capacity of 6070 % of the peak demand of the home is the most cost-effective option as it obtains the finest combined seasonal performance, reduced environmental impact, lower operating costs and in its life cycle. With this design, relevant participation of the boiler is assured, contributing to low unitary emissions and allowing the heat pump to operate at its finest efficiency, also reducing its number of starts and stops. Parameters such as greater storage or a lower pump stop temperature also improve its performance, within limits near the reference situation for Spain, also considering its charges for biomass and electricity consumed.

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abuot them About Them They are Egyptian Commercial office for Food Industries, known as ECOBIL, located in Cairo, Egypt. WE are a specialized agency office, with long History Ecobil office, started the year 2000 by Eng. Hani Fouad as a regional office of a famous Italian Engineering company carrying out projects in the Consulting and

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Biomass is a carbon-neutral renewable energy resource. Biochar produced from biomass pyrolysis exhibits preferable characteristics and potential for fossil fuel substitution. For time- and cost-saving, it is vital to establish predictive models to predict biochar properties. However, limited studies focused on the accurate prediction of HHV of biochar by using proximate and ultimate analysis results of various biochar. Therefore, the multi-linear regression (MLR) and the machine learning (ML) models were developed to predict the measured HHV of biochar from the experiment data of this study. In detail, 52 types of biochars were produced by pyrolysis from rice straw, pig manure, soybean straw, wood sawdust, sewage sludge, Chlorella Vulgaris, and their mixtures at the temperature 100 13796 0 13796 0 0 11439 0 --:--:-- 0:00:01 --:--:-- 11429 ranging from 300 to 800C. The results showed that the co-pyrolysis of the mixed biomass provided an alternative method to increase the yield of biochar production. The contents of ash, fixed carbon (FC), and C increased as the incremental pyrolysis temperature for most biochars. The Pearson correlation (r) and relative importance analysis between HHV values and the indicators derived from the proximate and ultimate analysis were carried out, and the measured HHV was used to train and test the MLR and the ML models. Besides, ML algorithms, including gradient boosted regression, random forest, and support vector machine, were also employed to develop more widely applicable models for predicting HHV of biochar from an expanded dataset (total 149 data points, including 97 data collected from the published literature). Results showed HHV had strong correlations (|r| > 0.9, p0.90. The ML models showed better performance with test R2 around 0.95 (random forest) and 0.970.98 before and after adding extra data for model construction, respectively. Feature importance analysis of the ML models showed that ash and C were the most important inputs to predict biochar HHV.