Analyzing grid frequency behavior in response to weather variations: A statistical approach

The transition towards carbon neutrality in the Nordic Power System (NPS) by 2035/40 intensifies the integration of Renewable Energy Sources (RES), especially wind and solar power. This change introduces significant challenges in maintaining the balance between electricity demand and generation, imp...

Descripción completa

Detalles Bibliográficos
Autor: Gonzalez Morales, Jenny Marcela
Tipo de recurso: tesis de maestría
Fecha de publicación:2024
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/425939
Acceso en línea:https://hdl.handle.net/2117/425939
Access Level:acceso abierto
Palabra clave:Electric power system stability
Renewable energy sources
Energy policy
Sistemes de distribució d'energia elèctrica--Estabilitat
Energies renovables
Política energètica
Àrees temàtiques de la UPC::Energies::Recursos energètics renovables
id ES_88639b0d8ee457f9530dfd10f3151ede
oai_identifier_str oai:upcommons.upc.edu:2117/425939
network_acronym_str ES
network_name_str España
repository_id_str
dc.title.none.fl_str_mv Analyzing grid frequency behavior in response to weather variations: A statistical approach
title Analyzing grid frequency behavior in response to weather variations: A statistical approach
spellingShingle Analyzing grid frequency behavior in response to weather variations: A statistical approach
Gonzalez Morales, Jenny Marcela
Electric power system stability
Renewable energy sources
Energy policy
Sistemes de distribució d'energia elèctrica--Estabilitat
Energies renovables
Política energètica
Àrees temàtiques de la UPC::Energies::Recursos energètics renovables
title_short Analyzing grid frequency behavior in response to weather variations: A statistical approach
title_full Analyzing grid frequency behavior in response to weather variations: A statistical approach
title_fullStr Analyzing grid frequency behavior in response to weather variations: A statistical approach
title_full_unstemmed Analyzing grid frequency behavior in response to weather variations: A statistical approach
title_sort Analyzing grid frequency behavior in response to weather variations: A statistical approach
dc.creator.none.fl_str_mv Gonzalez Morales, Jenny Marcela
author Gonzalez Morales, Jenny Marcela
author_facet Gonzalez Morales, Jenny Marcela
author_role author
dc.contributor.none.fl_str_mv Valderrama Ángel, César Alberto
Golzar, Farzin
Luka, Smajila
dc.subject.none.fl_str_mv Electric power system stability
Renewable energy sources
Energy policy
Sistemes de distribució d'energia elèctrica--Estabilitat
Energies renovables
Política energètica
Àrees temàtiques de la UPC::Energies::Recursos energètics renovables
topic Electric power system stability
Renewable energy sources
Energy policy
Sistemes de distribució d'energia elèctrica--Estabilitat
Energies renovables
Política energètica
Àrees temàtiques de la UPC::Energies::Recursos energètics renovables
description The transition towards carbon neutrality in the Nordic Power System (NPS) by 2035/40 intensifies the integration of Renewable Energy Sources (RES), especially wind and solar power. This change introduces significant challenges in maintaining the balance between electricity demand and generation, impacting grid frequency stability, a critical parameter that indicates the reliability of the power system. Despite extensive research on RES integration, there is a lack of studies examining the direct impact of weather conditions on grid frequency and frequency containment reserve (FCR) activation in the NPS. This study investigates how weather phenomena can influence grid frequency stability and the activation of FCR, aiming to model these relationships using statistical algorithms. A literature review explored the theoretical background of NPS frequency control services, weather-dependent generation sources, prominent weather parameters, and existing statistical modelling approaches. The review identified wind speed and air temperature as crucial weather parameters in the NPS influencing generation variability and demand fluctuations. Besides, the research suggested the need for advanced models to capture complex, nonlinear relationships between these weather variables and grid frequency. A dual-phase analysis was involved in the methodology, utilising historical data from 2017 to 2022. Long-term analysis involved collecting and preparing datasets on grid frequency, wind speed, and air temperature, ensuring data quality through synchronisation, cleaning, and handling missing values. The methodology combined descriptive statistical measures, exploratory data analysis (EDA), and time-series modelling using AutoRegressive Integrated Moving Average with eXogenous variables and Seasonal AutoRegressive Integrated Moving Average with eXogenous variables (ARIMAX/SARIMAX) within the Box-Jenkins framework. In the short-term analysis, Non-Deterministic Frequency Deviations (NDFDs) from 2022 were focused on utilising high-resolution data to capture disturbance events. Criteria for disturbances were defined, and key frequency quality indicators such as the Rate of Change of Frequency (RoCoF) were calculated. Reliability analysis was conducted by calculating the Time to Failure (TTF) and Mean Time Between Disturbances (MTBD), allowing for the assessment of the grid’s resilience during different seasons and Frequency Containment Reserve for Disturbance (FCR-D) activation. Throughout both phases, various probability distribution functions were fitted to the frequency deviation data, with the Johnson SU distribution emerging as the best fit. This distribution effectively captured the skewness and heavy tails observed. The study shows that extreme weather conditions, especially during winter, cause increased frequency deviations and frequent FCR-D activations, indicating that traditional time-series models are insufficient for forecasting. The results emphasise the need for advanced modelling methods, real-time monitoring, and adaptive frequency control strategies due to the variability caused by RES integration. This research provides practical options for maintaining grid reliability and stability in the evolving energy context of the NPS.
publishDate 2024
dc.date.none.fl_str_mv 2024
2024-10-25
2025
2025-03-11
dc.type.none.fl_str_mv master thesis
http://purl.org/coar/resource_type/c_bdcc
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/425939
url https://hdl.handle.net/2117/425939
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universitat Politècnica de Catalunya
publisher.none.fl_str_mv Universitat Politècnica de Catalunya
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869412548101537792
spelling Analyzing grid frequency behavior in response to weather variations: A statistical approachGonzalez Morales, Jenny MarcelaElectric power system stabilityRenewable energy sourcesEnergy policySistemes de distribució d'energia elèctrica--EstabilitatEnergies renovablesPolítica energèticaÀrees temàtiques de la UPC::Energies::Recursos energètics renovablesThe transition towards carbon neutrality in the Nordic Power System (NPS) by 2035/40 intensifies the integration of Renewable Energy Sources (RES), especially wind and solar power. This change introduces significant challenges in maintaining the balance between electricity demand and generation, impacting grid frequency stability, a critical parameter that indicates the reliability of the power system. Despite extensive research on RES integration, there is a lack of studies examining the direct impact of weather conditions on grid frequency and frequency containment reserve (FCR) activation in the NPS. This study investigates how weather phenomena can influence grid frequency stability and the activation of FCR, aiming to model these relationships using statistical algorithms. A literature review explored the theoretical background of NPS frequency control services, weather-dependent generation sources, prominent weather parameters, and existing statistical modelling approaches. The review identified wind speed and air temperature as crucial weather parameters in the NPS influencing generation variability and demand fluctuations. Besides, the research suggested the need for advanced models to capture complex, nonlinear relationships between these weather variables and grid frequency. A dual-phase analysis was involved in the methodology, utilising historical data from 2017 to 2022. Long-term analysis involved collecting and preparing datasets on grid frequency, wind speed, and air temperature, ensuring data quality through synchronisation, cleaning, and handling missing values. The methodology combined descriptive statistical measures, exploratory data analysis (EDA), and time-series modelling using AutoRegressive Integrated Moving Average with eXogenous variables and Seasonal AutoRegressive Integrated Moving Average with eXogenous variables (ARIMAX/SARIMAX) within the Box-Jenkins framework. In the short-term analysis, Non-Deterministic Frequency Deviations (NDFDs) from 2022 were focused on utilising high-resolution data to capture disturbance events. Criteria for disturbances were defined, and key frequency quality indicators such as the Rate of Change of Frequency (RoCoF) were calculated. Reliability analysis was conducted by calculating the Time to Failure (TTF) and Mean Time Between Disturbances (MTBD), allowing for the assessment of the grid’s resilience during different seasons and Frequency Containment Reserve for Disturbance (FCR-D) activation. Throughout both phases, various probability distribution functions were fitted to the frequency deviation data, with the Johnson SU distribution emerging as the best fit. This distribution effectively captured the skewness and heavy tails observed. The study shows that extreme weather conditions, especially during winter, cause increased frequency deviations and frequent FCR-D activations, indicating that traditional time-series models are insufficient for forecasting. The results emphasise the need for advanced modelling methods, real-time monitoring, and adaptive frequency control strategies due to the variability caused by RES integration. This research provides practical options for maintaining grid reliability and stability in the evolving energy context of the NPS.Universitat Politècnica de CatalunyaValderrama Ángel, César AlbertoGolzar, FarzinLuka, Smajila20242024-10-2520252025-03-11master thesishttp://purl.org/coar/resource_type/c_bdccNAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/masterThesisapplication/pdfhttps://hdl.handle.net/2117/425939reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/4259392026-05-27T15:37:01Z
score 15,81155