Machine Learning and Data Mining Applications in Power Systems
This Special Issue was intended as a forum to advance research and apply machine-learning and data-mining methods to facilitate the development of modern electric power systems, grids and devices, and smart grids and protection devices, as well as to develop tools for more accurate and efficient pow...
Furkejuvvon:
| Materiálatiipa: | Online |
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| Giella: | eaŋgalasgiella |
| Almmustuhtton: |
MDPI - Multidisciplinary Digital Publishing Institute
2022
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| Fáttát: | |
| Liŋkkat: | ONIX_20220621_9783036541778_124 |
| Fáddágilkorat: |
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| _version_ | 1869515119827877888 |
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| collection | Directory of Open Access Books |
| description | This Special Issue was intended as a forum to advance research and apply machine-learning and data-mining methods to facilitate the development of modern electric power systems, grids and devices, and smart grids and protection devices, as well as to develop tools for more accurate and efficient power system analysis. Conventional signal processing is no longer adequate to extract all the relevant information from distorted signals through filtering, estimation, and detection to facilitate decision-making and control actions. Machine learning algorithms, optimization techniques and efficient numerical algorithms, distributed signal processing, machine learning, data-mining statistical signal detection, and estimation may help to solve contemporary challenges in modern power systems. The increased use of digital information and control technology can improve the grid’s reliability, security, and efficiency; the dynamic optimization of grid operations; demand response; the incorporation of demand-side resources and integration of energy-efficient resources; distribution automation; and the integration of smart appliances and consumer devices. Signal processing offers the tools needed to convert measurement data to information, and to transform information into actionable intelligence. This Special Issue includes fifteen articles, authored by international research teams from several countries. |
| format | Online |
| id | doab-20.500.12854ir-84546 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-845462024-04-11T15:10:39Z Machine Learning and Data Mining Applications in Power Systems Leonowicz, Zbigniew Jasiński, Michał virtual power plant (VPP) power quality (PQ) global index distributed energy resources (DER) energy storage systems (ESS) power systems long-term assessment battery energy storage systems (BESS) smart grids conducted disturbances power quality supraharmonics 2–150 kHz Power Line Communications (PLC) intentional emission non-intentional emission mains signalling virtual power plant data mining clustering distributed energy resources energy storage systems short term conditions cluster analysis (CA) nonlinear loads harmonics, cancellation, and attenuation of harmonics waveform distortion THDi low-voltage networks optimization techniques different batteries off-grid microgrid integrated renewable energy system cluster analysis K-means agglomerative ANFIS fuzzy logic induction generator MPPT neural network renewable energy variable speed WECS wind energy conversion system wind energy frequency estimation spectrum interpolation power network disturbances COVID-19 time-varying reproduction number social distancing load profile demographic characteristic household energy consumption demand-side management energy management time series Hidden Markov Model short-term forecast sparse signal decomposition supervised dictionary learning dictionary impulsion singular value decomposition discrete cosine transform discrete Haar transform discrete wavelet transform transient stability assessment home energy management binary-coded genetic algorithms optimal power scheduling demand response Data Injection Attack machine learning critical infrastructure smart grid water treatment plant power system n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities This Special Issue was intended as a forum to advance research and apply machine-learning and data-mining methods to facilitate the development of modern electric power systems, grids and devices, and smart grids and protection devices, as well as to develop tools for more accurate and efficient power system analysis. Conventional signal processing is no longer adequate to extract all the relevant information from distorted signals through filtering, estimation, and detection to facilitate decision-making and control actions. Machine learning algorithms, optimization techniques and efficient numerical algorithms, distributed signal processing, machine learning, data-mining statistical signal detection, and estimation may help to solve contemporary challenges in modern power systems. The increased use of digital information and control technology can improve the grid’s reliability, security, and efficiency; the dynamic optimization of grid operations; demand response; the incorporation of demand-side resources and integration of energy-efficient resources; distribution automation; and the integration of smart appliances and consumer devices. Signal processing offers the tools needed to convert measurement data to information, and to transform information into actionable intelligence. This Special Issue includes fifteen articles, authored by international research teams from several countries. 2022-06-21T08:41:34Z 2022-06-21T08:41:34Z 2022 book ONIX_20220621_9783036541778_124 9783036541778 9783036541785 https://directory.doabooks.org/handle/20.500.12854/84546 eng application/octet-stream Attribution 4.0 International https://mdpi.com/books/pdfview/book/5530 https://mdpi.com/books/pdfview/book/5530 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-0365-4178-5 10.3390/books978-3-0365-4178-5 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783036541778 9783036541785 314 Basel open access |
| spellingShingle | virtual power plant (VPP) power quality (PQ) global index distributed energy resources (DER) energy storage systems (ESS) power systems long-term assessment battery energy storage systems (BESS) smart grids conducted disturbances power quality supraharmonics 2–150 kHz Power Line Communications (PLC) intentional emission non-intentional emission mains signalling virtual power plant data mining clustering distributed energy resources energy storage systems short term conditions cluster analysis (CA) nonlinear loads harmonics, cancellation, and attenuation of harmonics waveform distortion THDi low-voltage networks optimization techniques different batteries off-grid microgrid integrated renewable energy system cluster analysis K-means agglomerative ANFIS fuzzy logic induction generator MPPT neural network renewable energy variable speed WECS wind energy conversion system wind energy frequency estimation spectrum interpolation power network disturbances COVID-19 time-varying reproduction number social distancing load profile demographic characteristic household energy consumption demand-side management energy management time series Hidden Markov Model short-term forecast sparse signal decomposition supervised dictionary learning dictionary impulsion singular value decomposition discrete cosine transform discrete Haar transform discrete wavelet transform transient stability assessment home energy management binary-coded genetic algorithms optimal power scheduling demand response Data Injection Attack machine learning critical infrastructure smart grid water treatment plant power system n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities Machine Learning and Data Mining Applications in Power Systems |
| title | Machine Learning and Data Mining Applications in Power Systems |
| title_full | Machine Learning and Data Mining Applications in Power Systems |
| title_fullStr | Machine Learning and Data Mining Applications in Power Systems |
| title_full_unstemmed | Machine Learning and Data Mining Applications in Power Systems |
| title_short | Machine Learning and Data Mining Applications in Power Systems |
| title_sort | machine learning and data mining applications in power systems |
| topic | virtual power plant (VPP) power quality (PQ) global index distributed energy resources (DER) energy storage systems (ESS) power systems long-term assessment battery energy storage systems (BESS) smart grids conducted disturbances power quality supraharmonics 2–150 kHz Power Line Communications (PLC) intentional emission non-intentional emission mains signalling virtual power plant data mining clustering distributed energy resources energy storage systems short term conditions cluster analysis (CA) nonlinear loads harmonics, cancellation, and attenuation of harmonics waveform distortion THDi low-voltage networks optimization techniques different batteries off-grid microgrid integrated renewable energy system cluster analysis K-means agglomerative ANFIS fuzzy logic induction generator MPPT neural network renewable energy variable speed WECS wind energy conversion system wind energy frequency estimation spectrum interpolation power network disturbances COVID-19 time-varying reproduction number social distancing load profile demographic characteristic household energy consumption demand-side management energy management time series Hidden Markov Model short-term forecast sparse signal decomposition supervised dictionary learning dictionary impulsion singular value decomposition discrete cosine transform discrete Haar transform discrete wavelet transform transient stability assessment home energy management binary-coded genetic algorithms optimal power scheduling demand response Data Injection Attack machine learning critical infrastructure smart grid water treatment plant power system n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities |
| topic_facet | virtual power plant (VPP) power quality (PQ) global index distributed energy resources (DER) energy storage systems (ESS) power systems long-term assessment battery energy storage systems (BESS) smart grids conducted disturbances power quality supraharmonics 2–150 kHz Power Line Communications (PLC) intentional emission non-intentional emission mains signalling virtual power plant data mining clustering distributed energy resources energy storage systems short term conditions cluster analysis (CA) nonlinear loads harmonics, cancellation, and attenuation of harmonics waveform distortion THDi low-voltage networks optimization techniques different batteries off-grid microgrid integrated renewable energy system cluster analysis K-means agglomerative ANFIS fuzzy logic induction generator MPPT neural network renewable energy variable speed WECS wind energy conversion system wind energy frequency estimation spectrum interpolation power network disturbances COVID-19 time-varying reproduction number social distancing load profile demographic characteristic household energy consumption demand-side management energy management time series Hidden Markov Model short-term forecast sparse signal decomposition supervised dictionary learning dictionary impulsion singular value decomposition discrete cosine transform discrete Haar transform discrete wavelet transform transient stability assessment home energy management binary-coded genetic algorithms optimal power scheduling demand response Data Injection Attack machine learning critical infrastructure smart grid water treatment plant power system n/a thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology thema EDItEUR::K Economics, Finance, Business and Management::KN Industry and industrial studies::KNB Energy industries and utilities |
| url | ONIX_20220621_9783036541778_124 |