Waste Energy for Life Cycle Assessment

Demırbas, Ayhan

doi:10.1007/978-3-319-40551-3

Cited by 9 publications

(4 citation statements)

References 194 publications

(240 reference statements)

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“…Factually, the energy sector is presently characterized by high uncertainty on the feasible direction in both the short and long term run sequence to the fast depletion rate with the associated ecological hazards of the utilization of the limited fossil sources, the technological and economic barriers of the RE sources, couple with the hypothesis of shale gas being a promising bridge to RE sources to prolong the lifespan of the finite energy sources [94]. However, the level of development of RE sources constitutes only 14 % of the total world energy demand [91] and grows at an average of 2.6%/yr [95], the transition to such facilities have been shown to be insufficiently to meet the projections of future energy demands. Moreover, convincing arguments require that more than 50% of the existing non-renewable energy reserves, especially coal, the cheapest and most abundant of all fossils will have to be left untapped to combat climate change [16].…”

Section: Waste Heat Recovery Technologies and Sustainable Energy Developmentmentioning

confidence: 99%

Waste Heat Recovery Technologies: Pathway to Sustainable Energy Development

Oyedepo

Fakeye

2021

Journal of Thermal Engineering

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The aim of this study was to review the significant of waste heat recovery technologies as means of achieving sustainable energy development. Most developing nations of the World are faced with the enormous release of industrial waste heat of low temperature grade to the environment. Unlike material waste that is clearly visible, waste heat can be difficult to identify and evaluate both in terms of quantity and quality. Hence, understanding the availability of waste heat, and the ability to recover it, offer great opportunity to reduce energy costs and associated environmental impacts. Utilizing low-grade energy from waste heat sources is considered to offer a significant contribution to improving overall energy efficiency in the energy-intensive industrial sectors. The concept of industrial waste heat is explained, potential sources of waste heat from industries are identified, and the technologies available for waste heat recovery are presented in this study. From the review study, it is shown that about 72% of the global primary energy consumption is lost after conversion, while 63% of the considered waste heat streams arise at a temperature below 100 °C in which electricity generation has the largest share followed by transportation and manufacturing industry. The results of this study reveals that considerable amount of waste heat can be technically and economically recovered through sustainable technologies with prospective capacity for the much desired sustainable energy development. Specifically, in-depth utilization of waste heat resources can effectively moderate the rate of depletion of the fossil fuels and sufficiently reduce toxic emissions to within acceptable limits that are compatible to the projected time of full deployment of renewable energy (RE) source.

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Section: Waste Heat Recovery Technologies and Sustainable Energy Developmentmentioning

confidence: 99%

Waste Heat Recovery Technologies: Pathway to Sustainable Energy Development

Oyedepo

Fakeye

2021

Journal of Thermal Engineering

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“…1 However, solar energy has begun to compete for a convenient location as a source of clean energy and a pillar of sustainable development in many countries of the world. 2 The use of solar energy has been promoted in various applications, 3,4 including the thermal heating of water for domestic and industrial purposes, 5 the heating of air for comfort conditions, 6 ventilation using the Trombe wall, 7 and solar distillation. 8,9 In the production of electricity, there are several distinctive and suitable methods for the production of electric power such as the solar chimney, 10 concentrated power stations, 11 and photovoltaic (PV).…”

Section: Introductionmentioning

confidence: 99%

“…Today, environmentally friendly, clean technologies, particularly solar energy, are being used as an appropriate solution to overcome pollution difficulties and to address stable energy saving crises 1 . However, solar energy has begun to compete for a convenient location as a source of clean energy and a pillar of sustainable development in many countries of the world 2 . The use of solar energy has been promoted in various applications, 3,4 including the thermal heating of water for domestic and industrial purposes, 5 the heating of air for comfort conditions, 6 ventilation using the Trombe wall, 7 and solar distillation 8,9 .…”

Section: Introductionmentioning

confidence: 99%

Evaluation ofPVoutput in terms of environmental impact based on mathematical and artificial neural network models

Kazem

2020

Int J Energy Res

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This paper presents different prediction models for a grid-connected photovoltaic (GCPV) system based on long-term data sets. A 1.4 kW GCPV installed in Sohar, Oman, where measurements of the electrical and environmental parameters are taken every second for 5 years (from May 2014 to April 2019) to reduce uncertainty and improve the proposed model's accuracy. The highest power and energy measured from the GCPV are 1180 W and 245.8 kWh, respectively. Mathematical regression and cascade-feed forward propagation (CFNN) models for PV current, voltage, and power were proposed in terms of environmental impact. A NeuroSolutions package was used to propose GCPV models for electrical quantities. An evaluation criterion is defined, in this study, to assess the system's performance. The proposed models show excellent agreement with the measured experimental data. However, CFNN shows a superior accuracy compared with empirical and regression proposed models. The two models have proposed a dispute, but the model relating the solar irradiation and ambient temperature to GCPV current is more accurate. To evaluate and validate the proposed CFNN models, mean square error, MAE, root mean square error, and R 2 metrics have been used as a criterion and compared with different artificial neural networks models in the literature. The proposed CFNN is found to give the most accurate results in terms of MSE = 0.0007, MAE = 0.4310, and RMSE = 0.0290 and highest accuracy R 2 = 0.9999, which shows the effectiveness and feasibility of the proposed models.

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“…Increasing environmental concerns and depleting conventional energy reserves has been major global challenge of this century [1,2]. Hybrid RES based generation is supposed to feed major future energy demand [3]. Power extension of grid to isolated regions is associated with technical and economical limitation.…”

Section: Introductionmentioning

confidence: 99%

Feasibility Study of Standalone Hybrid Wind-PV-Battery Microgrid Operation

Kumar

Palwalia

2018

Technol Econ Smart Grids Sustain Energy

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This paper presents techno-economic analysis of hybrid wind-PV-battery based microgrid in standalone mode for technical university campus located in north-west Indian state Rajasthan. Generation unit consists of NPS100C-21 wind turbine, Tata TS250 PV module, Leonics Appolo series converter and Cellcube series battery bank. Hourly wind profile, solar data and electrical load of previous one year has been used to simulate thousands of cases to obtain optimal microgrid operation in terms of cost and number of generating units. Converter unit regulates voltage in AC and DC bus-bar. Battery acts as active power source and backup unit to meet additional power demand when wind-PV generation is deficit. This paper aims to find a feasible solution to make university campus free from fossil fuel based energy sources. Simulation results have been established under varying meteorological conditions and load data. Site lies in low wind region and maximum wind penetration is observed to be 19.5%. COE of considered generation unit is obtained as $0.238 with renewable fraction of 100%. Obtained optimal generation unit is competitive with grid extension in terms of techno-economic feasibility.

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Waste Energy for Life Cycle Assessment

Cited by 9 publications

References 194 publications

Waste Heat Recovery Technologies: Pathway to Sustainable Energy Development

Waste Heat Recovery Technologies: Pathway to Sustainable Energy Development

Evaluation ofPVoutput in terms of environmental impact based on mathematical and artificial neural network models

Feasibility Study of Standalone Hybrid Wind-PV-Battery Microgrid Operation

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