Gross electricity consumption forecasting using LSTM and SARIMA approaches: A case study of Türkiye

Energy, Год журнала: 2023, Номер 284, С. 128575 - 128575

Опубликована: Авг. 1, 2023

Язык: Английский

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System strength shortfall challenges for renewable energy-based power systems: A review

Renewable and Sustainable Energy Reviews, Год журнала: 2023, Номер 183, С. 113447 - 113447

Опубликована: Июнь 30, 2023

Renewable energy sources such as wind farms and solar power plants are replacing conventional coal-based synchronous generators (SGs) to achieve net-zero carbon emissions worldwide. SGs play an important role in enhancing system strength a make it more stable during voltage/frequency disruptions. However, traditional coal-fired being decommissioned many parts of the world, owing stringent environmental regulations low levelized cost renewables. Consequently, maintaining renewable energy-dominated has become major challenge, without adequate mitigation techniques, can potentially cause widespread outages. This paper provides overview its measurement techniques with large number (RESs), for example farms. The review includes approaches, future challenges.

Язык: 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, Год журнала: 2024, Номер 22, С. 102188 - 102188

Опубликована: Май 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.

Язык: Английский

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A prediction approach with mode decomposition-recombination technique for short-term load forecasting

Sustainable Cities and Society, Год журнала: 2022, Номер 85, С. 104034 - 104034

Опубликована: Июль 6, 2022

Язык: Английский

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Uncertainty avoidance and acceptance of the digital payment systems: a partial least squares-structural equation modeling (PLS-SEM) approach

Global Knowledge Memory and Communication, Год журнала: 2023, Номер unknown

Опубликована: Апрель 26, 2023

Purpose The purpose of this study is to investigate the determinants that likely influence intention using digital payment systems such as Jordan Mobile Payment (JoMoPay) system among public sector employees in Jordan. To achieve current study, authors developed a new research model based on extended unified theory acceptance and use technology (UTAUT2), with one Hofstede’s cross-cultural dimension scales [uncertainty avoidance (UA)] provide further understanding JoMoPay Design/methodology/approach A partial least squares-structural equation modeling approach was used analyze data collected by self-administration from 270 working Jordanian located Amman city, capital city Because most main sectors are because cost time considerations, applied non-probability sampling purposive technique. Findings empirical results reveal evident drivers behavioral significantly positively influenced social influence, UA, performance expectancy, price value effort expectancy; therefore, H1 , H2 H3 H5 H6 were supported. Conversely, show no significant relationship between facilitating conditions system, hence, related hypothesis ( H4 ) not Practical implications beneficial information Central Bank other service providers about employee intentions adopt increase decision-makers’ knowledge factors have an important impact UTAUT2 model. Social enable policymakers understand will enhance savings, investments living standards, create job opportunities well reduce poverty, paper money printing cost, risks transportation risk human errors. Originality/value outcomes obtained help both practitioners researchers elucidate situation employees, them formulate plans expedite adoption process case UA.

Язык: Английский

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A hybrid prediction interval model for short-term electric load forecast using Holt-Winters and Gate Recurrent Unit

Sustainable Energy Grids and Networks, Год журнала: 2024, Номер 38, С. 101343 - 101343

Опубликована: Март 12, 2024

Язык: Английский

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A multi-granularity hierarchical network for long- and short-term forecasting on multivariate time series data

Applied Soft Computing, Год журнала: 2024, Номер 157, С. 111537 - 111537

Опубликована: Март 24, 2024

Язык: Английский

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Ethical & Legal Concerns of Artificial Intelligence in the Healthcare Sector

Опубликована: Янв. 28, 2024

All major sectors are rapidly embracing AI technology to provide rapid and quality services patients. Along with opportunities, the integration of in healthcare has some ethical legal challenges. The present paper aims discuss concerns integrating into Jordanian system. Focus-group discussion (FGD), a qualitative method, was applied collect primary data from six participants. Results show that government is proactive core sectors, including healthcare. There provisions promote secure safe AI-driven services. However, system does not have special law could regulate AI-system. It highly recommended laws should be much more comprehensive, training ethics priority

Язык: Английский

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Distributionally robust optimization scheduling of port energy system considering hydrogen production and ammonia synthesis

Heliyon, Год журнала: 2024, Номер 10(5), С. e27615 - e27615

Опубликована: Март 1, 2024

In order to effectively address the uncertainty risks of port energy system caused by intermittence and fluctuation renewable energy, this paper proposes a scheduling method for based on distributionally robust optimization (DRO) considering ammonia synthesis after hydrogen production water electrolysis (P2H2A), uses real data from Tianjin Port example analysis. The calculation results show that 1 h selected interval P2H2A is reasonable, it can ensure reaction transitions smoothly new steady state, temperature pressure converter meet safety constraints. two-stage DRO be divided into pre-scheduling in day-ahead stage rescheduling intraday stage, which improve capacity anti-risk stochastic overcome conservatism optimization, consider economy robustness. Moreover, decision transformed prediction error function, result result, between cost optimization. As Wasserstein distance-based sphere radius increases, gradually deviates risk neutral leans towards averse When remains constant, variance decreases as number scenarios promote fuzzy set converge true distribution. greater than 15, will no longer fluctuate significantly, time range 1200 s–6600 s. It demands time. Therefore, model has outstanding advantages computing flexibility Port's scheduling, using energy.

Язык: Английский

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Solar photovoltaic generation and electrical demand forecasting using multi-objective deep learning model for smart grid systems

Cogent Engineering, Год журнала: 2024, Номер 11(1)

Опубликована: Апрель 20, 2024

The growing of the photovoltaic (PV) panel's installation in world and intermittent nature climate conditions highlights importance power forecasting for smart grid integration. This work aims to study implement existing Deep Learning (DL) methods used PV electrical load forecasting. We then developed a novel hybrid model made Feed-Forward Neural Network (FFNN), Long Short Term Memory (LSTM) Multi-Objective Particle Swarm Optimization (MOPSO). In this work, is long-term will consider meter data, socio-economic demographic data. generation by considering climatic data such as solar irradiance, temperature humidity. Moreover, we implemented these deep learning on two datasets, first one consumption collected from meters installed at consumers Douala. second management center performances models are evaluated using different error metrics Root Mean Square Error (RMSE) Absolute (MAE) regression (R). proposed gives RMSE, MAE R 1.15, 0.75 0.999 respectively. results obtained show that effective both prediction outperforms other FFNN, Recurrent (RNN), Decision Tree (DT), Gated Unit (GRU) eXtreme Gradient Boosting (XGBoost).

Язык: Английский

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