Pub Date : 2022-07-06DOI: 10.1109/IYCE54153.2022.9857521
Anna Judit Molnár, Botond Szücs
Due to climate change, global sustainability goals have been defined to reduce emissions and encourage the transformation of the entire energy sector. The current, fossil fuel-based electricity generation will be replaced by renewable energy sources. This analysis discusses the predictable effects of the National Energy- and Climate Plan, from the aspects of energy production, import demand, and carbon dioxide emission and the problematics of the renewable energy's overproduction to give a scope of future challenges, such as the necessity of an energy storage system and the volatile operation of renewable energy generation.
{"title":"The effects of increasing solar energy sources in the Hungarian electricity system","authors":"Anna Judit Molnár, Botond Szücs","doi":"10.1109/IYCE54153.2022.9857521","DOIUrl":"https://doi.org/10.1109/IYCE54153.2022.9857521","url":null,"abstract":"Due to climate change, global sustainability goals have been defined to reduce emissions and encourage the transformation of the entire energy sector. The current, fossil fuel-based electricity generation will be replaced by renewable energy sources. This analysis discusses the predictable effects of the National Energy- and Climate Plan, from the aspects of energy production, import demand, and carbon dioxide emission and the problematics of the renewable energy's overproduction to give a scope of future challenges, such as the necessity of an energy storage system and the volatile operation of renewable energy generation.","PeriodicalId":248738,"journal":{"name":"2022 8th International Youth Conference on Energy (IYCE)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126975184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-06DOI: 10.1109/IYCE54153.2022.9857545
R. A. Pózmán, L. Székely, R. Cselkó
In 2019, Covid-19 pandemic appeared and affected the health of humanity. The virus can spread between people in various ways, but mostly from infected liquid particles. A fundamental method of defense is the use of a face mask in public, however, the efficiency of wearing a mask can be influenced by a number of factors. Most of the masks have a classification based on its filtration efficiency. There are three categories, the FFP1, FFP2 and FFP3, where FFP means „filtering facepiece”. All the 3 types can filter particles down to the size of 0.6 micrometer, but the FFP1's efficiency is 80%, the FFP2's 94%, while the FFP3's reaches 99%. In the USA they use the same categories, but call it KN80, KN95 and KN100. The problem is that the commonly used textile masks do not have a classification, which means that these cannot protect the wearer from being infected. The aim of our research is to improve the filter efficiency of masks, and we have described in this paper the first phase, the construction and testing of the laboratory model. Two cases were considered, with one needle and five needle solutions. During the experiments, the electrode distance was varied. When using more needles, the nanofibers covered a larger area, but there was a greater roughness between the fibers generated. Considering that electrospinning starts after a critical electric field strength, some calculations were performed in COMSOL model.
{"title":"Examination of electric field distribution in a laboratory-built electrospinning device","authors":"R. A. Pózmán, L. Székely, R. Cselkó","doi":"10.1109/IYCE54153.2022.9857545","DOIUrl":"https://doi.org/10.1109/IYCE54153.2022.9857545","url":null,"abstract":"In 2019, Covid-19 pandemic appeared and affected the health of humanity. The virus can spread between people in various ways, but mostly from infected liquid particles. A fundamental method of defense is the use of a face mask in public, however, the efficiency of wearing a mask can be influenced by a number of factors. Most of the masks have a classification based on its filtration efficiency. There are three categories, the FFP1, FFP2 and FFP3, where FFP means „filtering facepiece”. All the 3 types can filter particles down to the size of 0.6 micrometer, but the FFP1's efficiency is 80%, the FFP2's 94%, while the FFP3's reaches 99%. In the USA they use the same categories, but call it KN80, KN95 and KN100. The problem is that the commonly used textile masks do not have a classification, which means that these cannot protect the wearer from being infected. The aim of our research is to improve the filter efficiency of masks, and we have described in this paper the first phase, the construction and testing of the laboratory model. Two cases were considered, with one needle and five needle solutions. During the experiments, the electrode distance was varied. When using more needles, the nanofibers covered a larger area, but there was a greater roughness between the fibers generated. Considering that electrospinning starts after a critical electric field strength, some calculations were performed in COMSOL model.","PeriodicalId":248738,"journal":{"name":"2022 8th International Youth Conference on Energy (IYCE)","volume":"2 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114020320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-06DOI: 10.1109/IYCE54153.2022.9857518
K. Krawiec, Oliver Kraft, R. Jahn
Transactive Energy Systems (TES) represent a new approach to achieve an optimal utilisation of distributed energy resources (DER) as well as realising a better integration of prosumers. As transactive participants, producers, consumers and prosumers take part in achieving a dynamic and efficient grid operation based on economic and control mechanisms. A key challenge of realising TES is to enable a decentralised structure. With the gaining popularity of Distributed Ledger Technologies (DLT) and especially Blockchain in the year 2017, this trend has also gained traction in the field of TES to build a decentralised system. However, even before the aforementioned DLT approaches from 2017 onwards, there have been functioning TES implementations that are not based on DLT. It is also important to note that with all the advantages that the use of DLT brings, there are also new challenges linked with. The objective of this paper is to analyse, whether the use of DLT for TES is scientifically plausible or can be identified as a temporal hype. At first, the foundations of TES as well as the basic principles of using DLT for TES are being presented. Furthermore, different implementations of TES with and without the use of DLT are being shown. On this basis a comparative analysis of regular TES as well as TES based on DLT is executed. Within this framework an assessment of the effectiveness of using DLT for TES is formed.
{"title":"A comparative analysis of using Distributed Ledger Technologies for Transactive Energy Systems","authors":"K. Krawiec, Oliver Kraft, R. Jahn","doi":"10.1109/IYCE54153.2022.9857518","DOIUrl":"https://doi.org/10.1109/IYCE54153.2022.9857518","url":null,"abstract":"Transactive Energy Systems (TES) represent a new approach to achieve an optimal utilisation of distributed energy resources (DER) as well as realising a better integration of prosumers. As transactive participants, producers, consumers and prosumers take part in achieving a dynamic and efficient grid operation based on economic and control mechanisms. A key challenge of realising TES is to enable a decentralised structure. With the gaining popularity of Distributed Ledger Technologies (DLT) and especially Blockchain in the year 2017, this trend has also gained traction in the field of TES to build a decentralised system. However, even before the aforementioned DLT approaches from 2017 onwards, there have been functioning TES implementations that are not based on DLT. It is also important to note that with all the advantages that the use of DLT brings, there are also new challenges linked with. The objective of this paper is to analyse, whether the use of DLT for TES is scientifically plausible or can be identified as a temporal hype. At first, the foundations of TES as well as the basic principles of using DLT for TES are being presented. Furthermore, different implementations of TES with and without the use of DLT are being shown. On this basis a comparative analysis of regular TES as well as TES based on DLT is executed. Within this framework an assessment of the effectiveness of using DLT for TES is formed.","PeriodicalId":248738,"journal":{"name":"2022 8th International Youth Conference on Energy (IYCE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130173205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-06DOI: 10.1109/IYCE54153.2022.9857538
L. Rácz, Áron Molnár, B. Németh
Recently, several new challenges have emerged in the electricity system that needs to be addressed appropriately by system operators. The flexible, resilient operation of the grid requires knowledge of the real-time relationships of power line conductors. This paper aims to present the thermal behavior of high voltage conductors based on international project experience. Given that the results of special sensors with different thermal monitoring approaches are available, the conductor's radial and longitudinal temperature variation and magnitude can be presented. The thermal state of the conductor can be traced not only by measurement but also by calculations of physical models. In this paper, the measurement results of the two sensors are compared with the estimates of a physical model. In the light of the results, guidelines can be formulated that will result in more reliable and accurate thermal modeling and transfer capacity calculations.
{"title":"Investigation of power line conductors' thermal behavior","authors":"L. Rácz, Áron Molnár, B. Németh","doi":"10.1109/IYCE54153.2022.9857538","DOIUrl":"https://doi.org/10.1109/IYCE54153.2022.9857538","url":null,"abstract":"Recently, several new challenges have emerged in the electricity system that needs to be addressed appropriately by system operators. The flexible, resilient operation of the grid requires knowledge of the real-time relationships of power line conductors. This paper aims to present the thermal behavior of high voltage conductors based on international project experience. Given that the results of special sensors with different thermal monitoring approaches are available, the conductor's radial and longitudinal temperature variation and magnitude can be presented. The thermal state of the conductor can be traced not only by measurement but also by calculations of physical models. In this paper, the measurement results of the two sensors are compared with the estimates of a physical model. In the light of the results, guidelines can be formulated that will result in more reliable and accurate thermal modeling and transfer capacity calculations.","PeriodicalId":248738,"journal":{"name":"2022 8th International Youth Conference on Energy (IYCE)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126586779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-06DOI: 10.1109/IYCE54153.2022.9857524
Dávid Kalmár, D. Szabó, G. Göcsei, B. Németh
The establishment of a dynamic line rating (DLR) system by using smart grid technologies with advanced meteorological and line monitoring sensors makes the electric power system more flexible. By developing a DLR-based system, it can lead to many benefits, including transmission capacity growth and an increased security of supply at consumers side, while the reliability of the network also can be enhanced. Accordingly, there is an opportunity not only constantly monitoring the transmission lines' load but also the thermal state of the conductors, on which based different types of degradation can be detected, even prevented. To get a more comprehensive picture of a power line, the aging of such parts like fittings, jumpers and conductors can be considered through monitoring the weather parameters, line loading and thermal state of the line elements. In addition, the sag of the overhead line spans is one of the most important factors in connection with the available transmission capacity. Thus, a case study was conducted in which the permanent degradation of the conductors was examined based on sag monitoring. This study summarizes the aging models of power line elements, which practical application is shown via a case study.
{"title":"Extension of dynamic line rating models with the effect of conductor aging","authors":"Dávid Kalmár, D. Szabó, G. Göcsei, B. Németh","doi":"10.1109/IYCE54153.2022.9857524","DOIUrl":"https://doi.org/10.1109/IYCE54153.2022.9857524","url":null,"abstract":"The establishment of a dynamic line rating (DLR) system by using smart grid technologies with advanced meteorological and line monitoring sensors makes the electric power system more flexible. By developing a DLR-based system, it can lead to many benefits, including transmission capacity growth and an increased security of supply at consumers side, while the reliability of the network also can be enhanced. Accordingly, there is an opportunity not only constantly monitoring the transmission lines' load but also the thermal state of the conductors, on which based different types of degradation can be detected, even prevented. To get a more comprehensive picture of a power line, the aging of such parts like fittings, jumpers and conductors can be considered through monitoring the weather parameters, line loading and thermal state of the line elements. In addition, the sag of the overhead line spans is one of the most important factors in connection with the available transmission capacity. Thus, a case study was conducted in which the permanent degradation of the conductors was examined based on sag monitoring. This study summarizes the aging models of power line elements, which practical application is shown via a case study.","PeriodicalId":248738,"journal":{"name":"2022 8th International Youth Conference on Energy (IYCE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128844110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-06DOI: 10.1109/IYCE54153.2022.9857522
Sindu Daniarta, A. Imre, P. Kolasiński
Natural gas refers to a mixture of the hydrocarbons such as Methane, Ethane, Propane, Butane, and other substances. One of the advantages of this fuel is that it emits relatively low amounts of pollutants; therefore, it appears to be more environmentally friendly than coal or oil. Large amounts of natural gas can be transported via pipelines (as pressurized gas) or alternatively in the liquid phase by tankers (as liquefied natural gas or LNG). A liquefaction of natural gas, which produces LNG at around $-162 ^{circ}mathrm{C}$ from ambient temperature, requires a lot of energy. The LNG needs to be regasified and warmed up to ambient temperature to utilize this fuel. During vaporization, some of the energy used for liquefaction can be restored. One of the ways to do that is the application of a direct expander, where part of this “cold energy” can be recovered (to produce the electricity) from this LNG during regasification. Since the composition of the LNG in selected countries (e.g., Algeria, Australia, Malaysia, Nigeria, Oman, Qatar, Trinidad and Tobago) is different, the gasification process and the energy recovery will differ as well. This work presents a comparative analysis of energy recovery from LNG by direct expander with different gas compositions. Comparing the recoverable energies from the typical LNGs used in the listed countries, the most energy can be recovered from the LNG produced in Trinidad and Tobago (which consists of 96.9% Methane, 2.7% Ethane, 0.3% Propane, and 0.1% Butane).
{"title":"A Comparative Study of Direct Expanders Utilizing Different Mixtures of Natural Gas","authors":"Sindu Daniarta, A. Imre, P. Kolasiński","doi":"10.1109/IYCE54153.2022.9857522","DOIUrl":"https://doi.org/10.1109/IYCE54153.2022.9857522","url":null,"abstract":"Natural gas refers to a mixture of the hydrocarbons such as Methane, Ethane, Propane, Butane, and other substances. One of the advantages of this fuel is that it emits relatively low amounts of pollutants; therefore, it appears to be more environmentally friendly than coal or oil. Large amounts of natural gas can be transported via pipelines (as pressurized gas) or alternatively in the liquid phase by tankers (as liquefied natural gas or LNG). A liquefaction of natural gas, which produces LNG at around $-162 ^{circ}mathrm{C}$ from ambient temperature, requires a lot of energy. The LNG needs to be regasified and warmed up to ambient temperature to utilize this fuel. During vaporization, some of the energy used for liquefaction can be restored. One of the ways to do that is the application of a direct expander, where part of this “cold energy” can be recovered (to produce the electricity) from this LNG during regasification. Since the composition of the LNG in selected countries (e.g., Algeria, Australia, Malaysia, Nigeria, Oman, Qatar, Trinidad and Tobago) is different, the gasification process and the energy recovery will differ as well. This work presents a comparative analysis of energy recovery from LNG by direct expander with different gas compositions. Comparing the recoverable energies from the typical LNGs used in the listed countries, the most energy can be recovered from the LNG produced in Trinidad and Tobago (which consists of 96.9% Methane, 2.7% Ethane, 0.3% Propane, and 0.1% Butane).","PeriodicalId":248738,"journal":{"name":"2022 8th International Youth Conference on Energy (IYCE)","volume":"1089 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116472163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-06DOI: 10.1109/iyce54153.2022.9857523
{"title":"8th International Youth Conference on Energy","authors":"","doi":"10.1109/iyce54153.2022.9857523","DOIUrl":"https://doi.org/10.1109/iyce54153.2022.9857523","url":null,"abstract":"","PeriodicalId":248738,"journal":{"name":"2022 8th International Youth Conference on Energy (IYCE)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124633516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-06DOI: 10.1109/IYCE54153.2022.9857544
Dávid Markovics, M. J. Mayer
The built-in capacity and therefore the importance of photovoltaic (PV) power generation is inevitably increasing in the past years resulting that it is less and less possible to turn a blind eye to the challenging problems that come with it. This article focuses on a practical issue regarding numerical weather prediction (NWP) based PV forecasting with machine learning, which is the effect of the training time. Most of the studies propose new high-level sophisticated algorithms which can reduce the errors with a given percentage, however few of them deals with practical questions regarding the training time therefore the operating time needed to reach the accuracy of physical models, and the optimal length of the training dataset is still generally unclear. This study is supposed to provide some suggestions introducing the test method and the results of the simulations that were done on 2-years data including spatial weather forecast and the power production of a Hungarian PV plant. Three fast but powerful ensemble methods, XGBoost, LightGBM and ExtraTrees regression were applied using different train length cases in the range of 2,4,6… 102 weeks, for all the 52 two-week intervals. This simulation allows to investigate not just the previously mentioned aspects, but also the seasonal difference and sensitivity for the forecasting accuracy. The results are shown in both day-ahead and intraday time horizons, where in case of latter, also some measured power values of the close-past has been added to the input variables.
{"title":"Investigating the effect of training time for machine learning based photovoltaic power forecasting","authors":"Dávid Markovics, M. J. Mayer","doi":"10.1109/IYCE54153.2022.9857544","DOIUrl":"https://doi.org/10.1109/IYCE54153.2022.9857544","url":null,"abstract":"The built-in capacity and therefore the importance of photovoltaic (PV) power generation is inevitably increasing in the past years resulting that it is less and less possible to turn a blind eye to the challenging problems that come with it. This article focuses on a practical issue regarding numerical weather prediction (NWP) based PV forecasting with machine learning, which is the effect of the training time. Most of the studies propose new high-level sophisticated algorithms which can reduce the errors with a given percentage, however few of them deals with practical questions regarding the training time therefore the operating time needed to reach the accuracy of physical models, and the optimal length of the training dataset is still generally unclear. This study is supposed to provide some suggestions introducing the test method and the results of the simulations that were done on 2-years data including spatial weather forecast and the power production of a Hungarian PV plant. Three fast but powerful ensemble methods, XGBoost, LightGBM and ExtraTrees regression were applied using different train length cases in the range of 2,4,6… 102 weeks, for all the 52 two-week intervals. This simulation allows to investigate not just the previously mentioned aspects, but also the seasonal difference and sensitivity for the forecasting accuracy. The results are shown in both day-ahead and intraday time horizons, where in case of latter, also some measured power values of the close-past has been added to the input variables.","PeriodicalId":248738,"journal":{"name":"2022 8th International Youth Conference on Energy (IYCE)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129855179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-06DOI: 10.1109/IYCE54153.2022.9857548
P. Vijayan
Load forecasting is one of the most important step to maintain demand-supply balance and stability in a power system. With the advent of artificial intelligence and machine learning tools, load forecasting/energy consumption prediction is conducted with increased accuracy. The application of several machine learning techniques to predict energy consumption has been reported. However, a detailed analysis of different techniques is beneficial to choose the right approach to specific cases. This paper presents a study of different prediction models in energy forecasting. The prediction models are implemented in Matlab. The training and testing results for the data set is presented.
{"title":"Energy Consumption Prediction in Low Energy Buildings using Machine learning and Artificial Intelligence for Energy Efficiency","authors":"P. Vijayan","doi":"10.1109/IYCE54153.2022.9857548","DOIUrl":"https://doi.org/10.1109/IYCE54153.2022.9857548","url":null,"abstract":"Load forecasting is one of the most important step to maintain demand-supply balance and stability in a power system. With the advent of artificial intelligence and machine learning tools, load forecasting/energy consumption prediction is conducted with increased accuracy. The application of several machine learning techniques to predict energy consumption has been reported. However, a detailed analysis of different techniques is beneficial to choose the right approach to specific cases. This paper presents a study of different prediction models in energy forecasting. The prediction models are implemented in Matlab. The training and testing results for the data set is presented.","PeriodicalId":248738,"journal":{"name":"2022 8th International Youth Conference on Energy (IYCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130428647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-07-06DOI: 10.1109/IYCE54153.2022.9857536
Ádám Hadar, J. Csatár
Microgrids are going to take a major part of the future electricity distribution system, where they will form a local, controllable entity, consisting of various consumers, local energy producers and network energy storages. To be able plan, forecast and calculate the consumption and regulation energy values in advance by an algorithm - it is very important to have an accurate forecast, which takes the PV production too, into consideration. However, because of the low number of consumers and prosumers - the ordinary forecasting methods - which are applied in the transmission system-level consumption prediction - are not easily applicable in this situation, therefore a new approach is recommended. This paper focuses on developing such a method, that is capable of predicting a microgrid's electricity consumption in a D-1 and D-2 basis either from only the historical consumption data, or the history data and externalities. To do this, several real-life consumption data packages are analyzed and used to train a neural network. This network's parameters are subject to change throughout the process, according to the characteristics of the actual data, which is being predicted by it. Furthermore, in order to validate and evaluate the neural network's predictions - a classical ARIMA prediction model is also implemented and evaluated.
{"title":"Developing a residential consumption forecast method","authors":"Ádám Hadar, J. Csatár","doi":"10.1109/IYCE54153.2022.9857536","DOIUrl":"https://doi.org/10.1109/IYCE54153.2022.9857536","url":null,"abstract":"Microgrids are going to take a major part of the future electricity distribution system, where they will form a local, controllable entity, consisting of various consumers, local energy producers and network energy storages. To be able plan, forecast and calculate the consumption and regulation energy values in advance by an algorithm - it is very important to have an accurate forecast, which takes the PV production too, into consideration. However, because of the low number of consumers and prosumers - the ordinary forecasting methods - which are applied in the transmission system-level consumption prediction - are not easily applicable in this situation, therefore a new approach is recommended. This paper focuses on developing such a method, that is capable of predicting a microgrid's electricity consumption in a D-1 and D-2 basis either from only the historical consumption data, or the history data and externalities. To do this, several real-life consumption data packages are analyzed and used to train a neural network. This network's parameters are subject to change throughout the process, according to the characteristics of the actual data, which is being predicted by it. Furthermore, in order to validate and evaluate the neural network's predictions - a classical ARIMA prediction model is also implemented and evaluated.","PeriodicalId":248738,"journal":{"name":"2022 8th International Youth Conference on Energy (IYCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115236089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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