Social, environmental, and economic consequences of integrating renewable energies in the electricity sector: a review

Environmental Chemistry Letters, Journal Year: 2023, Volume and Issue: 21(3), P. 1381 - 1418

Published: March 24, 2023

Abstract The global shift from a fossil fuel-based to an electrical-based society is commonly viewed as ecological improvement. However, the electrical power industry major source of carbon dioxide emissions, and incorporating renewable energy can still negatively impact environment. Despite rising research in energy, consumption on environment poorly known. Here, we review integration energies into electricity sector social, environmental, economic perspectives. We found that implementing solar photovoltaic, battery storage, wind, hydropower, bioenergy provide 504,000 jobs 2030 4.18 million 2050. For desalinization, photovoltaic/wind/battery storage systems supported by diesel generator reduce cost water production 69% adverse environmental effects 90%, compared full fuel systems. potential emission reduction increases with percentage sources utilized. photovoltaic/wind/hydroelectric system most effective addressing climate change, producing 2.11–5.46% increase generation 3.74–71.61% guarantee share ratios. Compared single systems, hybrid are more reliable better equipped withstand impacts change supply.

Language: Английский

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Particle swarm optimization based LSTM networks for water level forecasting: A case study on Bangladesh river network

Results in Engineering, Journal Year: 2023, Volume and Issue: 17, P. 100951 - 100951

Published: Feb. 10, 2023

Floods are one of the most catastrophic natural disasters. Water level forecasting is an essential method avoiding floods and disaster preparedness. In recent years, models for predicting water levels have been developed using artificial intelligence techniques like neural network (ANN). It has demonstrated that more advanced sequenced-based deep learning techniques, long short-term memory (LSTM) networks, superior at hydrological data. However, historically, LSTM hyperparameters were based on experience, which typically did not produce best outcomes. The Particle Swarm Optimization (PSO) was utilized to adjust hyperparameter increase capacity learn data sequence characteristics. Utilizing observation from stations along Bangladesh's Brahmaputra, Ganges, Meghna rivers, model estimate flood dynamics. Nash Sutcliffe efficiency (NSE) coefficient, root mean square error (RMSE), MAE used assess model's performance, where PSO-LSTM outperforms ANN, PSO-ANN, in all stations. provides improved prediction accuracy stability improves varying lead times. findings may aid sustainable risk mitigation study region future.

Language: Английский

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A systematic review on automated human emotion recognition using electroencephalogram signals and artificial intelligence

Results in Engineering, Journal Year: 2023, Volume and Issue: 18, P. 101027 - 101027

Published: March 17, 2023

Language: Английский

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A Review of Hybrid Renewable Energy Systems: Architectures, Battery Systems, and Optimization Techniques

Eng—Advances in Engineering, Journal Year: 2023, Volume and Issue: 4(2), P. 1446 - 1467

Published: May 24, 2023

This paper aims to perform a literature review and statistical analysis based on data extracted from 38 articles published between 2018 2023 that address hybrid renewable energy systems. The main objective of this has been create bibliographic database organizes the content in different categories, such as system architecture, storage systems, auxiliary generation components used, software employed, addition showing algorithms economic reliability criteria for optimization these In total, have analyzed, compared, classified provide an overview current status simulation projects highlighting clearly appropriately relevant trends conclusions. A list also provided, which cover aspects required understanding HRESs.

Language: Английский

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Design and analysis of a solar-wind hybrid renewable energy tree

Results in Engineering, Journal Year: 2023, Volume and Issue: 17, P. 100958 - 100958

Published: Feb. 9, 2023

A hybrid tree is an artificial structure resembling a natural with branches on top of which are mounted solar modules or wind turbines. It can help supply power to mobile phones, laptops, electric vehicles, home appliances and lighting loads covering small large areas, be the best energy source for sustainable cities modern societies. This paper presents 3 kW design consisting 2 1 installed at Vaddeswaram, Andhra Pradesh (16.26°N 80.36°E) generate maximum using two-axis tracking system. Different designs applications trees available worldwide also presented. P–V I–V characteristics panels were obtained different irradiance temperature values. For turbine, speed co-efficient tip ratios studied. Power generation study was carried out tilt angles from 10° 20° panels. Structural optimisations performed validate whether withstand applied. The proposed solar-wind 4709 kWh/year system instead generating 3763 when fixed 18.25° angle.

Language: Английский

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Agroforest woody residual biomass-to-energy supply chain analysis: Feasible and sustainable renewable resource exploitation for an alternative to fossil fuels

Results in Engineering, Journal Year: 2023, Volume and Issue: 17, P. 101010 - 101010

Published: March 1, 2023

Agroforest woody residual biomass can play an essential role in the decarbonization of energy production and meeting targets imposed for carbon neutrality. However, due to constraints caused by some intrinsic characteristics, such as its low density, calorific value, high heterogeneity territorial dispersion, management hampers collection transport processes recovery. In this article, supply chain associated with recovery agroforestry is analyzed clarify positive negative points affecting viability feasibility projects. For purpose, a PEST SWOT analysis were carried out. It was identified that main are related economic aspects, which directly depending on optimization entire chain, from cutting operations, passing through intermediate tasks (which may or not add value), final destination

Language: Английский

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Optimal load forecasting and scheduling strategies for smart homes peer-to-peer energy networks: A comprehensive survey with critical simulation analysis

Results in Engineering, Journal Year: 2024, Volume and Issue: 22, P. 102188 - 102188

Published: May 3, 2024

The home energy management (HEM) sector is going through an enormous change that includes important elements like incorporating green power, enhancing efficiency forecasting and scheduling optimization techniques, employing smart grid infrastructure, regulating the dynamics of optimal trading. As a result, ecosystem players need to clarify their roles, develop effective regulatory structures, experiment with new business models. Peer-to-Peer (P2P) trading seems be one viable options in these conditions, where consumers can sell/buy electricity to/from other users prior totally depending on utility. P2P enables exchange between prosumers, thus provide more robust platform for This strategy decentralizes market than it did previously, opening up possibilities improving trade customers Considering above scenarios, this research provides extensive insight structure, procedure, design, platform, pricing mechanism, approaches, topologies possible futuristic while examining characteristics, pros cons primary goal determining whichever approach most appropriate given situation HEMs. Moreover, HEMs load framework simulation model also proposed analyze network critically, paving technical directions scientific researchers. With cooperation, age technological advancements ushering intelligent, interconnected, reactive urban environment are brought life. In sense, path living entails reinventing as well how people interact perceive dwellings larger city. Finally, work comprehensive overview challenges terms strategies, solutions, future prospects.

Language: Английский

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SCADA system dataset exploration and machine learning based forecast for wind turbines

Results in Engineering, Journal Year: 2022, Volume and Issue: 16, P. 100640 - 100640

Published: Sept. 13, 2022

Language: Английский

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A new approach to seasonal energy consumption forecasting using temporal convolutional networks

Results in Engineering, Journal Year: 2023, Volume and Issue: 19, P. 101296 - 101296

Published: July 17, 2023

There has been a significant increase in the attention paid to resource management smart grids, and several energy forecasting models have published literature. It is well known that plays crucial role applications including demand-side management, optimum dispatch, load shedding. A challenge grid managing forecasts efficiently while ensuring slightest feasible prediction error. type of artificial neural networks such as recurrent networks, are frequently used forecast time series data. However, due certain limitations like vanishing gradients lack memory retention sequential data should be modeled using convolutional networks. The reason they strong capabilities solve complex problems better than In this research, temporal network proposed handle seasonal short-term forecasting. computes outputs parallel, reducing computation compared Further performance comparison with traditional long terms MAD sMAPE proved model outperformed network.

Language: Английский

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Global LCOEs of decentralized off-grid renewable energy systems

Renewable and Sustainable Energy Reviews, Journal Year: 2023, Volume and Issue: 183, P. 113478 - 113478

Published: June 22, 2023

Recent global events emphasize the importance of a reliable energy supply. One way to increase supply security is through decentralized off-grid renewable systems, for which growing number case studies are researched. This review gives overview levelized cost electricity (LCOE) these autonomous range from 0.03 $2021/kWh over 1.00 worldwide. The average LCOEs 100% systems have decreased by 9% annually between 2016 and 2021 0.54 0.29 $2021/kWh, most likely due reductions in storage technologies. identifies discusses seven key reasons why frequently overestimated or underestimated research, how this can be prevented future. employed verify findings on assess where might deployed costs evolve.

Language: Английский

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