Prospects and Challenges of the Machine Learning and Data-Driven Methods for the Predictive Analysis of Power Systems: A Review

Energies, Journal Year: 2023, Volume and Issue: 16(10), P. 4025 - 4025

Published: May 11, 2023

The use of machine learning and data-driven methods for predictive analysis power systems offers the potential to accurately predict manage behavior these by utilizing large volumes data generated from various sources. These have gained significant attention in recent years due their ability handle amounts make accurate predictions. importance particular momentum with transformation that traditional system underwent as they are morphing into smart grids future. transition towards embed high-renewables electricity is challenging, generation renewable sources intermittent fluctuates weather conditions. This facilitated Internet Energy (IoE) refers integration advanced digital technologies such Things (IoT), blockchain, artificial intelligence (AI) systems. It has been further enhanced digitalization caused COVID-19 pandemic also affected energy sector. Our review paper explores prospects challenges using provides an overview ways which constructing can be applied order them more efficient. begins description role operations. Next, discusses systems, including benefits limitations. In addition, reviews existing literature on this topic highlights used Furthermore, it identifies opportunities associated methods, quality availability, discussed. Finally, concludes a discussion recommendations research application future grid-driven powered IoE.

Language: Английский

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Artificial intelligence and machine learning approaches in composting process: A review

Bioresource Technology, Journal Year: 2023, Volume and Issue: 370, P. 128539 - 128539

Published: Jan. 3, 2023

Language: Английский

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A Comprehensive Review of the Current Status of Smart Grid Technologies for Renewable Energies Integration and Future Trends: The Role of Machine Learning and Energy Storage Systems

Energies, Journal Year: 2024, Volume and Issue: 17(16), P. 4128 - 4128

Published: Aug. 19, 2024

The integration of renewable energy sources (RES) into smart grids has been considered crucial for advancing towards a sustainable and resilient infrastructure. Their is vital achieving sustainability among all clean sources, including wind, solar, hydropower. This review paper provides thoughtful analysis the current status grid, focusing on integrating various RES, such as wind grid. highlights significant role RES in reducing greenhouse gas emissions traditional fossil fuel reliability, thereby contributing to environmental empowering security. Moreover, key advancements grid technologies, Advanced Metering Infrastructure (AMI), Distributed Control Systems (DCS), Supervisory Data Acquisition (SCADA) systems, are explored clarify related topics usage technologies enhances efficiency, resilience introduced. also investigates application Machine Learning (ML) techniques management optimization within with techniques. findings emphasize transformative impact advanced alongside need continued innovation supportive policy frameworks achieve future.

Language: Английский

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Going green with artificial intelligence: The path of technological change towards the renewable energy transition

Oeconomia Copernicana, Journal Year: 2023, Volume and Issue: 14(4), P. 1059 - 1095

Published: Dec. 30, 2023

Research background: The twin pressures of economic downturn and climate change faced by countries around the world have become more pronounced over past decade. A renewable energy transition is believed to play a central role in mitigating economic-climate paradox. While architectural computational power artificial intelligence particularly well suited address challenges massive data processing demand forecasting during transition, there very scant empirical assessment that takes social science perspective explores effects AI development on transition. Purpose article: This paper aims answer two key questions: One is, how does software promote or inhibit shift consumption towards renewables? other under what policy interventions positive effect promoting consumption? Methods: We employ dataset 62 economies covering period 2011–2020 analyze impact where possible confounders, including political characteristics time-invariant elements, are controlled using fixed-effects estimation along with specified covariates. Findings & value added: can renewables. There suggestive evidence core mechanism linking such relationship tends lie improving innovation performance environmental monitoring rather than green computing. Government support for R&D technologies found be significantly beneficial harnessing Compared non-market-based policies, market-based policies significant moderating between

Language: Английский

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The role of energy communities in electricity grid balancing: A flexible tool for smart grid power distribution optimization

Renewable and Sustainable Energy Reviews, Journal Year: 2023, Volume and Issue: 187, P. 113742 - 113742

Published: Sept. 16, 2023

The unpredictability of renewable energy systems can affect the stability electricity grid, causing voltage and frequency imbalances. In this work, a suitable methodology based on peer-to-peer scheme applied to communities is developed implemented in simulation tool useful for investigating management strategies decision-making aims. model discretizes community its users into multiple control volumes, taking account various technologies. It incorporates balances individual as well entire community, considering prosumers, consumers, storage systems, electric vehicles. Moreover, enables exploration different solutions grid regulation optimization distributed resources. Additionally, predict demand one day ahead, facilitating organization availability minimize interactions flatten demand. objective functions, including self-consumption, self-sufficiency, grid-balancing factors, evaluate performance communities. To show capability model, it will be adopted optimize an investigated community. As result, increase self-consumption from 59.4 83.9 MW h/year achieved. Furthermore, balancing was achieved by guaranteeing non-fluctuating load providing 1.46 7.71 upward downward regulation. These findings illustrate positive impact dispatching integration sources importance further studying topic ensure stability.

Language: Английский

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Community-based virtual power plants’ technology and circular economy models in the energy sector: A Techno-economy study

Renewable and Sustainable Energy Reviews, Journal Year: 2023, Volume and Issue: 192, P. 114189 - 114189

Published: Dec. 23, 2023

Language: Английский

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Review of applications of artificial intelligence (AI) methods in crop research

Journal of Applied Genetics, Journal Year: 2024, Volume and Issue: 65(2), P. 225 - 240

Published: Jan. 13, 2024

Language: Английский

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Quantifying the benefits of shared battery in a DSO-energy community cooperation

Applied Energy, Journal Year: 2023, Volume and Issue: 343, P. 121105 - 121105

Published: May 5, 2023

Local energy communities are forming as a way for prosumers and consumers to invest in distributed renewable sources, community storage share electricity. Meanwhile, several distribution grids have voltage problems at certain hours of the year. consisting generation units might be valuable flexible assets that system operator (DSO) can make use of. This article aims study how battery an provide services grid, by creating linear optimisation model which includes power flow constraints degradation model. First, we investigate operation impacts nearby buses. We find when including model, limits violated much less than not Next, differs cooperates with active DSO use, quantify should remunerate community. get 15 € per year due increase electricity costs, equals 0.12%, compared is providing service. Finally, sensitivity analysis performed determine parameters more important consider. violations grid sensitive replacement cost, electric vehicle charging peak average spot price, while remuneration from cost. For small sizes low power-to-energy ratio, able improve all

Language: Английский

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Prediction of the rate of penetration in offshore large-scale cluster extended reach wells drilling based on machine learning and big-data techniques

Ocean Engineering, Journal Year: 2023, Volume and Issue: 285, P. 115404 - 115404

Published: July 25, 2023

Language: Английский

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Total and thermal load forecasting in residential communities through probabilistic methods and causal machine learning

Applied Energy, Journal Year: 2023, Volume and Issue: 351, P. 121783 - 121783

Published: Sept. 4, 2023

Indoor heating and cooling systems largely influence the power demand of residential buildings can play a significant role in Demand Side Management for energy communities. We propose novel method probabilistic forecasting total load community its base thermal components, combining conformalized quantile regression causal machine learning techniques, using only aggregate consumption environmental conditions data. applied proposed methods to dataset Germany, which includes separate measurements electricity domestic system consumption. The results show that produces day-ahead hourly forecasts outperform benchmarks components are not more accurate than but also close accuracy achievable with models trained directly on individual component T-learner resulted most effective among disaggregation terms accuracy, simplicity, potential extension.

Language: Английский

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