Pub Date : 2022-05-09DOI: 10.1109/energycon53164.2022.9830375
N. Tasmurzayev, B. Amangeldy, Z. Baigarayeva, M. Mansurova, B. Resnik, G. Amirkhanova
The article is given to the issue of guideline of hotness supply and cooling in the room. A robotized framework for checking the unique attributes of such sensors is depicted, which is a product and equipment complex for setting up a test seat and dissecting the boundaries of sensors for dynamic temperature control and cooling. The framework fills the roles of controlling the Google Coral USB Accelerator, designing the ADC (Analog-digital converter) and deciding the sufficiency recurrence and stage recurrence qualities of temperature sensors, switches, leak sensors and cooling taking into account the latest values from temperature and humidity sensors, fixing attributes and monitoring in SCADA (Supervisory Control And Data Acquisition) Genesis64 program. The plan of the test seat, the summed-up calculation of the framework activity and the screen type of the program activity are introduced. The product of the robotized framework for temperature control and cooling in the room is created based on SCADA Genesis 64 programs and technologies with OPC UA (Unified Architecture) and ModBUS TCP data receive protocol.
本文讨论了室内供热与制冷的指导原则问题。描述了用于检查此类传感器独特属性的机器人框架，该框架是用于设置测试座和剖析动态温度控制和冷却传感器边界的产品和设备综合体。该框架用于控制Google Coral USB加速器，设计ADC(模数转换器)，根据温度和湿度传感器的最新值确定温度传感器、开关、泄漏传感器和冷却的充分重复和阶段重复质量，并在SCADA (Supervisory Control and Data Acquisition) Genesis64程序中固定属性和监控。介绍了试验台的布置、框架活度的汇总计算和程序活度的筛分类型。基于SCADA Genesis 64程序，采用OPC UA (Unified Architecture)和ModBUS TCP数据接收协议，实现了室内温度控制和冷却的机器人框架产品。
{"title":"Improvement of HVAC System Using the Intelligent Control System","authors":"N. Tasmurzayev, B. Amangeldy, Z. Baigarayeva, M. Mansurova, B. Resnik, G. Amirkhanova","doi":"10.1109/energycon53164.2022.9830375","DOIUrl":"https://doi.org/10.1109/energycon53164.2022.9830375","url":null,"abstract":"The article is given to the issue of guideline of hotness supply and cooling in the room. A robotized framework for checking the unique attributes of such sensors is depicted, which is a product and equipment complex for setting up a test seat and dissecting the boundaries of sensors for dynamic temperature control and cooling. The framework fills the roles of controlling the Google Coral USB Accelerator, designing the ADC (Analog-digital converter) and deciding the sufficiency recurrence and stage recurrence qualities of temperature sensors, switches, leak sensors and cooling taking into account the latest values from temperature and humidity sensors, fixing attributes and monitoring in SCADA (Supervisory Control And Data Acquisition) Genesis64 program. The plan of the test seat, the summed-up calculation of the framework activity and the screen type of the program activity are introduced. The product of the robotized framework for temperature control and cooling in the room is created based on SCADA Genesis 64 programs and technologies with OPC UA (Unified Architecture) and ModBUS TCP data receive protocol.","PeriodicalId":106388,"journal":{"name":"2022 IEEE 7th International Energy Conference (ENERGYCON)","volume":"314 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121532078","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 : 2022-05-09DOI: 10.1109/energycon53164.2022.9830193
A. Koduah, G. Svinkunas
The use of matrix converters (MC) as interfaces between the grid and the traditional doubly fed induction generators (DFIG) in wind power applications introduces high harmonic frequencies of which traditional passive filters may not be suitable for attenuation. This paper analyses the harmonic frequencies generated by the MC and proposes a hybrid harmonic filter (HHF) for harmonic and power factor compensation in the grid side of the MC. The HHF achieved 1.02% THD% of the fundamental 50Hz with little to no impact to the dynamic stability of the MC. The results were simulated and confirmed with MATLAB/Simulink simulation software.
{"title":"Switching Harmonic Ripple Attenuation in a Matrix Converter-Based DFIG Application","authors":"A. Koduah, G. Svinkunas","doi":"10.1109/energycon53164.2022.9830193","DOIUrl":"https://doi.org/10.1109/energycon53164.2022.9830193","url":null,"abstract":"The use of matrix converters (MC) as interfaces between the grid and the traditional doubly fed induction generators (DFIG) in wind power applications introduces high harmonic frequencies of which traditional passive filters may not be suitable for attenuation. This paper analyses the harmonic frequencies generated by the MC and proposes a hybrid harmonic filter (HHF) for harmonic and power factor compensation in the grid side of the MC. The HHF achieved 1.02% THD% of the fundamental 50Hz with little to no impact to the dynamic stability of the MC. The results were simulated and confirmed with MATLAB/Simulink simulation software.","PeriodicalId":106388,"journal":{"name":"2022 IEEE 7th International Energy Conference (ENERGYCON)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131111440","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 : 2022-05-09DOI: 10.1109/energycon53164.2022.9830404
M. Montakhabi, J. Vannieuwenhuyze, P. Ballon
In this paper, we investigate how experts evaluate peer-to-peer (P2P), community self-consumption (CSC), and transactive energy (TE) market models compared to a traditional market model. The different models are evaluated on their capacities to generate different types of values in the electricity market. To facilitate the evaluations, we adopted the Analytic Hierarchy Process (AHP). The AHP is a quantitative multiple criteria decision-making tool facilitating experts to make a difficult choice between various options along a set of distinct evaluation criteria by a sequence of pairwise comparisons. So far, the AHP has not yet been applied in the context of energy transaction markets. Results show that experts prefer the community self-consumption and transactive energy market models because they might be most successful in generating green energy. These results help policy makers to better understand the heterogeneous capacities of the market models.
{"title":"Expert Recommendations on Energy Trading Market Models using the AHP model","authors":"M. Montakhabi, J. Vannieuwenhuyze, P. Ballon","doi":"10.1109/energycon53164.2022.9830404","DOIUrl":"https://doi.org/10.1109/energycon53164.2022.9830404","url":null,"abstract":"In this paper, we investigate how experts evaluate peer-to-peer (P2P), community self-consumption (CSC), and transactive energy (TE) market models compared to a traditional market model. The different models are evaluated on their capacities to generate different types of values in the electricity market. To facilitate the evaluations, we adopted the Analytic Hierarchy Process (AHP). The AHP is a quantitative multiple criteria decision-making tool facilitating experts to make a difficult choice between various options along a set of distinct evaluation criteria by a sequence of pairwise comparisons. So far, the AHP has not yet been applied in the context of energy transaction markets. Results show that experts prefer the community self-consumption and transactive energy market models because they might be most successful in generating green energy. These results help policy makers to better understand the heterogeneous capacities of the market models.","PeriodicalId":106388,"journal":{"name":"2022 IEEE 7th International Energy Conference (ENERGYCON)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133922320","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 : 2022-05-09DOI: 10.1109/energycon53164.2022.9830191
S. Schmitt, Iiro Harjunkoski, M. Giuntoli, J. Poland, Xiaoming Feng
The complexity of energy scheduling problems is increasing due to the energy transition. In recent research, Machine Learning (ML) has shown potential to contribute to the methodology for executing these tasks efficiently and reliably in future. This paper develops and compares three approaches for predicting binary decisions in Unit Commitment problems with network constraints: Two ML predictors using Random Forests and Graph Neural Networks are contrasted with a rule-based approach. On large datasets of realistic synthetic Unit Commitment problems, the performance criteria that need to be met for successful real-word application are evaluated: What is the speedup potential of using the predictions in the process? What is the risk of losing optimality or even feasibility? And what are the generalization capabilities of the predictors? We find that all three approaches have promising potential, each approach having its own pros and cons.
{"title":"Fast Solution of Unit Commitment Using Machine Learning Approaches","authors":"S. Schmitt, Iiro Harjunkoski, M. Giuntoli, J. Poland, Xiaoming Feng","doi":"10.1109/energycon53164.2022.9830191","DOIUrl":"https://doi.org/10.1109/energycon53164.2022.9830191","url":null,"abstract":"The complexity of energy scheduling problems is increasing due to the energy transition. In recent research, Machine Learning (ML) has shown potential to contribute to the methodology for executing these tasks efficiently and reliably in future. This paper develops and compares three approaches for predicting binary decisions in Unit Commitment problems with network constraints: Two ML predictors using Random Forests and Graph Neural Networks are contrasted with a rule-based approach. On large datasets of realistic synthetic Unit Commitment problems, the performance criteria that need to be met for successful real-word application are evaluated: What is the speedup potential of using the predictions in the process? What is the risk of losing optimality or even feasibility? And what are the generalization capabilities of the predictors? We find that all three approaches have promising potential, each approach having its own pros and cons.","PeriodicalId":106388,"journal":{"name":"2022 IEEE 7th International Energy Conference (ENERGYCON)","volume":"263 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115830812","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 : 2022-05-09DOI: 10.1109/energycon53164.2022.9830493
Caner Budak, Ulas Erdogan, Sinan Küfeoğlu
In this paper, the analysis of peer-to-peer energy trading with smart contracts, which are applications run on blockchains, is presented. The software architecture and algorithm of the smart contracts that run on the Ethereum Virtual Machine are mentioned. The smart contracts are applied transactions that guarantee the information of both parties in a peer-to-peer transmission and are verified by the logic structure that operates within itself and do not cause any vulnerabilities in the system. In addition, a software background with an instrument panel in the user interface and offering prices within the framework of the supply-demand relationship is presented. In addition to these, the paper aims to promote decentralisation by integrating renewable energy sources with the framework of peer-to-peer trading methods on a Blockchain.
{"title":"Smart Contract Development for Peer-to-Peer Energy Trading","authors":"Caner Budak, Ulas Erdogan, Sinan Küfeoğlu","doi":"10.1109/energycon53164.2022.9830493","DOIUrl":"https://doi.org/10.1109/energycon53164.2022.9830493","url":null,"abstract":"In this paper, the analysis of peer-to-peer energy trading with smart contracts, which are applications run on blockchains, is presented. The software architecture and algorithm of the smart contracts that run on the Ethereum Virtual Machine are mentioned. The smart contracts are applied transactions that guarantee the information of both parties in a peer-to-peer transmission and are verified by the logic structure that operates within itself and do not cause any vulnerabilities in the system. In addition, a software background with an instrument panel in the user interface and offering prices within the framework of the supply-demand relationship is presented. In addition to these, the paper aims to promote decentralisation by integrating renewable energy sources with the framework of peer-to-peer trading methods on a Blockchain.","PeriodicalId":106388,"journal":{"name":"2022 IEEE 7th International Energy Conference (ENERGYCON)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124487558","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 : 2022-05-09DOI: 10.1109/energycon53164.2022.9830232
Paula Bastida-Molina, I. N. Jiya, Van Khang Huynh
Cold countries with low irradiance values have typically used utility grid to support solar PV systems. However, the extended option is facing new challenges: the electricity tariffs increase and the expected high penetration of EVs, which can increase the pressure on the grid. In this research, a prototype simulation model of a solar PV-batteries-grid HRES to cover recharge of EVs was developed. The system was simulated in MATLAB®, with a control algorithm based on power balance between EVs load demand-solar PV generation, and the state of charge (SOC) of the batteries. The results indicate the suitability of the simulation model. It can select the appropriate support system according to the control algorithm. Moreover, the two scenarios presented for the case study reflect the importance of the initial SOC, since it will directly affect the availability of batteries for covering electricity shortfalls.
{"title":"Modelling a Hybrid Renewable Energy System for Recharging Electric Vehicles","authors":"Paula Bastida-Molina, I. N. Jiya, Van Khang Huynh","doi":"10.1109/energycon53164.2022.9830232","DOIUrl":"https://doi.org/10.1109/energycon53164.2022.9830232","url":null,"abstract":"Cold countries with low irradiance values have typically used utility grid to support solar PV systems. However, the extended option is facing new challenges: the electricity tariffs increase and the expected high penetration of EVs, which can increase the pressure on the grid. In this research, a prototype simulation model of a solar PV-batteries-grid HRES to cover recharge of EVs was developed. The system was simulated in MATLAB®, with a control algorithm based on power balance between EVs load demand-solar PV generation, and the state of charge (SOC) of the batteries. The results indicate the suitability of the simulation model. It can select the appropriate support system according to the control algorithm. Moreover, the two scenarios presented for the case study reflect the importance of the initial SOC, since it will directly affect the availability of batteries for covering electricity shortfalls.","PeriodicalId":106388,"journal":{"name":"2022 IEEE 7th International Energy Conference (ENERGYCON)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132633203","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 : 2022-05-09DOI: 10.1109/energycon53164.2022.9830280
Ye-Obong N. Udoakah, H. B. Sonder, L. Cipcigan
Electric Vehicle (EV) charging is classified into two major categories, depending on the type of chargers used. These are referred to as Alternating Current (AC) and Direct Current (DC) chargers. EVs' batteries are charged by an external source of electricity, such as the grid. Achieving the required charging voltage, charging current, and the charging power for the EV batteries requires power electronic interfaced technologies. AC charging requires an AC to DC converter, which is usually performed within the vehicle itself. DC charging, on the other hand, utilises an off-board converter to get DC power. The dynamic behaviour of power systems has changed drastically due to the increased usage of power electronic interfaced technologies. This paper presents different EV integration scenarios into a Nigerian distribution network feeder that serves both residential and commercial customers. The PSCADIEMTDC simulation software is used to investigate the impacts of different charger topologies from a grid perspective. The sizing of an appropriate filter is also proposed to help mitigate harmonic distortion introduced by various battery chargers in the network. The paper results bolster confidence in the ability of EVs and associated charging methods to be incorporated in different nations’ distribution network feeders via appropriate technologies while maintaining grid safety and reliability.
{"title":"Nigerian Distribution Network Feeder Impact Assessment with Integration of Electric Vehicles","authors":"Ye-Obong N. Udoakah, H. B. Sonder, L. Cipcigan","doi":"10.1109/energycon53164.2022.9830280","DOIUrl":"https://doi.org/10.1109/energycon53164.2022.9830280","url":null,"abstract":"Electric Vehicle (EV) charging is classified into two major categories, depending on the type of chargers used. These are referred to as Alternating Current (AC) and Direct Current (DC) chargers. EVs' batteries are charged by an external source of electricity, such as the grid. Achieving the required charging voltage, charging current, and the charging power for the EV batteries requires power electronic interfaced technologies. AC charging requires an AC to DC converter, which is usually performed within the vehicle itself. DC charging, on the other hand, utilises an off-board converter to get DC power. The dynamic behaviour of power systems has changed drastically due to the increased usage of power electronic interfaced technologies. This paper presents different EV integration scenarios into a Nigerian distribution network feeder that serves both residential and commercial customers. The PSCADIEMTDC simulation software is used to investigate the impacts of different charger topologies from a grid perspective. The sizing of an appropriate filter is also proposed to help mitigate harmonic distortion introduced by various battery chargers in the network. The paper results bolster confidence in the ability of EVs and associated charging methods to be incorporated in different nations’ distribution network feeders via appropriate technologies while maintaining grid safety and reliability.","PeriodicalId":106388,"journal":{"name":"2022 IEEE 7th International Energy Conference (ENERGYCON)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117315873","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 : 2022-05-09DOI: 10.1109/energycon53164.2022.9830403
Ibrahim Alkadi, A. A. Hamad, Faisal Aloufi
This paper presents the developed methodology to determine the most optimal solution to generate electricity in Saudi Arabia by conventional power generators. The analysis will consider all parameters and factors in the country that influence the decision-making process such as efficiency, cost, water utilization, greenhouse gas (GHG) emissions, and land use. The methodology utilizes the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), which is one of the Multicriteria Decision Analysis (MCDA) methods. This approach can support and assist power generation planning firms to adopt the most accurate generation system anywhere in the world. In this paper, the methodology is applied to Saudi Arabia, as the country has ambitious targets of relying more on environmentally friendly generation; such as renewables, natural gas turbines and nuclear power plants.
本文提出了发展的方法，以确定最优解决方案，以发电在沙特阿拉伯的传统发电机。该分析将考虑该国影响决策过程的所有参数和因素，如效率、成本、水利用、温室气体排放和土地利用。该方法采用了多准则决策分析(MCDA)方法之一的TOPSIS (Order of Preference by Similarity to Ideal Solution)。这种方法可以支持和协助发电规划公司在世界任何地方采用最精确的发电系统。在本文中，该方法适用于沙特阿拉伯，因为该国有更多地依赖于环保发电的雄心勃勃的目标;比如可再生能源、天然气涡轮机和核电站。
{"title":"A Novel Method to Identify the Best Conventional Power Generation Technology in Saudi Arabia","authors":"Ibrahim Alkadi, A. A. Hamad, Faisal Aloufi","doi":"10.1109/energycon53164.2022.9830403","DOIUrl":"https://doi.org/10.1109/energycon53164.2022.9830403","url":null,"abstract":"This paper presents the developed methodology to determine the most optimal solution to generate electricity in Saudi Arabia by conventional power generators. The analysis will consider all parameters and factors in the country that influence the decision-making process such as efficiency, cost, water utilization, greenhouse gas (GHG) emissions, and land use. The methodology utilizes the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), which is one of the Multicriteria Decision Analysis (MCDA) methods. This approach can support and assist power generation planning firms to adopt the most accurate generation system anywhere in the world. In this paper, the methodology is applied to Saudi Arabia, as the country has ambitious targets of relying more on environmentally friendly generation; such as renewables, natural gas turbines and nuclear power plants.","PeriodicalId":106388,"journal":{"name":"2022 IEEE 7th International Energy Conference (ENERGYCON)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116247057","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 : 2022-05-09DOI: 10.1109/energycon53164.2022.9830394
O. Abdel-Rahim, A. Chub, A. Blinov, D. Vinnikov
This paper suggests the implementation of the partial power converter for PV power processing instead of full power converter for better system efficiency and robustness. Processing a percentage of the total power, instead of processing the full power, improves system efficiency and reduces system cost and size. In this paper, an input parallel output series (PISO) buck-boost partial power converter is presented. The first stage of the system is controlled to ensure that PV panels are operating at the maximum power (MP). And the second resonant stage is controlled to fix the dc-bus voltage. Although the system has five-switches, four of them are operating in zero voltage and current switching, to eliminate switching losses of the system. Converter sharing percentage is adjusted to ensure optimum operation of the complete PV system. System analysis and simulation are demonstrated through the manuscript. Experimental and more comparative analysis will be presented in the final version.
{"title":"Partial Buck-Boost Resonant Power Converter for Residential PV Applications","authors":"O. Abdel-Rahim, A. Chub, A. Blinov, D. Vinnikov","doi":"10.1109/energycon53164.2022.9830394","DOIUrl":"https://doi.org/10.1109/energycon53164.2022.9830394","url":null,"abstract":"This paper suggests the implementation of the partial power converter for PV power processing instead of full power converter for better system efficiency and robustness. Processing a percentage of the total power, instead of processing the full power, improves system efficiency and reduces system cost and size. In this paper, an input parallel output series (PISO) buck-boost partial power converter is presented. The first stage of the system is controlled to ensure that PV panels are operating at the maximum power (MP). And the second resonant stage is controlled to fix the dc-bus voltage. Although the system has five-switches, four of them are operating in zero voltage and current switching, to eliminate switching losses of the system. Converter sharing percentage is adjusted to ensure optimum operation of the complete PV system. System analysis and simulation are demonstrated through the manuscript. Experimental and more comparative analysis will be presented in the final version.","PeriodicalId":106388,"journal":{"name":"2022 IEEE 7th International Energy Conference (ENERGYCON)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116312060","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 : 2022-05-09DOI: 10.1109/energycon53164.2022.9830189
M. Gorobetz, A. Korneyev, L. Zemite
This study describes the developed method intended for dynamic modelling of a country’s economic and demographic processes related to the transport market, vehicle and fuel consumption. The method of prediction used in this model is artificial life. The situation of energy consumption for motor transport in Latvia is considered. The model being developed examines the factors influencing energy consumption in road transport. The model takes into account the influence of various factors on energy consumption in transport population, income rates, number of vehicles, countries of the region, taxes, economic factors. The energy forecasting model focuses on a set of planning and forecasting practices that take into account micro- and macroeconomic variables. Since forecasting is a scientific study of specific development prospects based on a system of qualitative and quantitative research aimed at identifying trends in the development of desired indicators, it is necessary to compile statistics on micro and macroeconomics. Data from various fields related to various scopes of human activity have been collected and analysed.
{"title":"Long-term Energy and Fuel Consumption Forecast in Private and Commercial Transport using Artificial Life Approach","authors":"M. Gorobetz, A. Korneyev, L. Zemite","doi":"10.1109/energycon53164.2022.9830189","DOIUrl":"https://doi.org/10.1109/energycon53164.2022.9830189","url":null,"abstract":"This study describes the developed method intended for dynamic modelling of a country’s economic and demographic processes related to the transport market, vehicle and fuel consumption. The method of prediction used in this model is artificial life. The situation of energy consumption for motor transport in Latvia is considered. The model being developed examines the factors influencing energy consumption in road transport. The model takes into account the influence of various factors on energy consumption in transport population, income rates, number of vehicles, countries of the region, taxes, economic factors. The energy forecasting model focuses on a set of planning and forecasting practices that take into account micro- and macroeconomic variables. Since forecasting is a scientific study of specific development prospects based on a system of qualitative and quantitative research aimed at identifying trends in the development of desired indicators, it is necessary to compile statistics on micro and macroeconomics. Data from various fields related to various scopes of human activity have been collected and analysed.","PeriodicalId":106388,"journal":{"name":"2022 IEEE 7th International Energy Conference (ENERGYCON)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114706420","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：