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/energycon53164.2022.9830189
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}
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/energycon53164.2022.9830403
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/energycon53164.2022.9830493
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/energycon53164.2022.9830512
B. Bremdal, I. Ilieva, S. Puranik
Digitization and automation in the building sector are constantly increasing. Developments around the Internet of Things (IoT) also affect this industry. However, due to the lack of common standards, the development of building automation has been complicated, expensive, and slowly progressing. This paper presents an approach to increase the utilization of sensor data. The approach will help develop smart buildings where energy efficiency is increased and where better interaction with surrounding infrastructure is facilitated. The paper’s focus is on ontologies that make communication more intelligent, data labelling more efficient and utilization of collected and real-time data more expedient relative to the building's performance, area utilization and user experience. The idea is not to replace existing ontologies, but to create an overarching structure that connects essential concepts representing different perspectives of a building and interactions with surrounding infrastructure. We call this structure a hyper-ontology. The presented in the paper approach reflects ongoing work in the project DataCat.
{"title":"The Need for a Comprehensive Ontology for Smart Buildings","authors":"B. Bremdal, I. Ilieva, S. Puranik","doi":"10.1109/energycon53164.2022.9830512","DOIUrl":"https://doi.org/10.1109/energycon53164.2022.9830512","url":null,"abstract":"Digitization and automation in the building sector are constantly increasing. Developments around the Internet of Things (IoT) also affect this industry. However, due to the lack of common standards, the development of building automation has been complicated, expensive, and slowly progressing. This paper presents an approach to increase the utilization of sensor data. The approach will help develop smart buildings where energy efficiency is increased and where better interaction with surrounding infrastructure is facilitated. The paper’s focus is on ontologies that make communication more intelligent, data labelling more efficient and utilization of collected and real-time data more expedient relative to the building's performance, area utilization and user experience. The idea is not to replace existing ontologies, but to create an overarching structure that connects essential concepts representing different perspectives of a building and interactions with surrounding infrastructure. We call this structure a hyper-ontology. The presented in the paper approach reflects ongoing work in the project DataCat.","PeriodicalId":106388,"journal":{"name":"2022 IEEE 7th International Energy Conference (ENERGYCON)","volume":"5 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":"129827012","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/energycon53164.2022.9830231
M. L. Scala, M. Dicorato, G. Forte, C. Gadaleta, Chiara Giordano, M. Migliori, Davide Monno, E. Carlini
In the framework of energy transition, transmission network expansion planning process arises the need of effective and flexible tools to evaluate development options and their mutual influence, accounting for heterogenous though significant information. This paper aims to propose a new methodology developed by the Italian Transmission System Operator to identify and select the transmission network developments of higher importance for investment planning strategies. The presented approach involves the definition of alternatives by combination of network developments, by using a multi-criteria analysis involving technical and economic aspects. The method is tested on the Network Development Plan of Italian Transmission Network.
{"title":"Network development alternative analysis based on Analytic Hierarchy Process","authors":"M. L. Scala, M. Dicorato, G. Forte, C. Gadaleta, Chiara Giordano, M. Migliori, Davide Monno, E. Carlini","doi":"10.1109/energycon53164.2022.9830231","DOIUrl":"https://doi.org/10.1109/energycon53164.2022.9830231","url":null,"abstract":"In the framework of energy transition, transmission network expansion planning process arises the need of effective and flexible tools to evaluate development options and their mutual influence, accounting for heterogenous though significant information. This paper aims to propose a new methodology developed by the Italian Transmission System Operator to identify and select the transmission network developments of higher importance for investment planning strategies. The presented approach involves the definition of alternatives by combination of network developments, by using a multi-criteria analysis involving technical and economic aspects. The method is tested on the Network Development Plan of Italian Transmission Network.","PeriodicalId":106388,"journal":{"name":"2022 IEEE 7th International Energy Conference (ENERGYCON)","volume":"56 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":"130157612","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/energycon53164.2022.9830301
J. Hönen, J. Hurink, B. Zwart
Due to the increasing penetration of photovoltaic (PV) systems, electric vehicles (EV) and other smart devices on a household level, the role of consumers changes from pure consumption to production and storage of electricity. These prosumers will also directly participate in future electricity markets. To compensate for the small scale and the fluctuations in their demand and production, one promising approach for prosumers is to form small energy communities or microgrids, and participate in the electricity markets as one entity. A challenge for these microgrids is to find an optimal energy management strategy, mainly due to the uncertainty in electricity prices, in PV generation as Well as in the prosumer loads. To integrate this uncertainty into the planning, an adaptive robust optimization approach using linear decision rules is proposed in this paper. The linear decision rules allow for a delayed determination of some of the decisions and can therefore adapt to realizations of the uncertainty. Three different uncertainty scenarios are used to evaluate and compare the proposed approach in a case study and to get more structural insights into the efficiency of the approach.
{"title":"Robust Energy Management for a Microgrid","authors":"J. Hönen, J. Hurink, B. Zwart","doi":"10.1109/energycon53164.2022.9830301","DOIUrl":"https://doi.org/10.1109/energycon53164.2022.9830301","url":null,"abstract":"Due to the increasing penetration of photovoltaic (PV) systems, electric vehicles (EV) and other smart devices on a household level, the role of consumers changes from pure consumption to production and storage of electricity. These prosumers will also directly participate in future electricity markets. To compensate for the small scale and the fluctuations in their demand and production, one promising approach for prosumers is to form small energy communities or microgrids, and participate in the electricity markets as one entity. A challenge for these microgrids is to find an optimal energy management strategy, mainly due to the uncertainty in electricity prices, in PV generation as Well as in the prosumer loads. To integrate this uncertainty into the planning, an adaptive robust optimization approach using linear decision rules is proposed in this paper. The linear decision rules allow for a delayed determination of some of the decisions and can therefore adapt to realizations of the uncertainty. Three different uncertainty scenarios are used to evaluate and compare the proposed approach in a case study and to get more structural insights into the efficiency of the approach.","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":"121244786","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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