2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE)最新文献_第2页

Assessment of the Economic Viability of Nuclear-Renewable Hybrid Energy Systems: Case for Ghana 核-可再生混合能源系统经济可行性评估:加纳案例

2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE) Pub Date : 2022-08-10 DOI: 10.1109/SEGE55279.2022.9889765

M. A. Nyasapoh, S. Gyamfi, S. K. Debrah, Hossam Gaber, N. Derkyi

{"title":"Assessment of the Economic Viability of Nuclear-Renewable Hybrid Energy Systems: Case for Ghana","authors":"M. A. Nyasapoh, S. Gyamfi, S. K. Debrah, Hossam Gaber, N. Derkyi","doi":"10.1109/SEGE55279.2022.9889765","DOIUrl":"https://doi.org/10.1109/SEGE55279.2022.9889765","url":null,"abstract":"Developing economies spend a greater proportion of their GDP on the importation of fossil fuels to ensure sustainable electricity generation. However, the use of fossil fuels has negative environmental consequences that hinder sustainable development. Therefore, clean energy solutions are required to address the challenges of sustainable development. The flexible operation and load-following mode of some nuclear power plants serve as backup to intermittent renewables. Based on the Ghana Renewable and Nuclear Power agenda, the integration of nuclear and renewable energy for electricity generation is essential for sustainable development. The study undertakes a financial performance analysis of nuclear and renewable hybrid energy systems (N-R HES) using the HOMER software for optimization analysis. The study results show that the proposed grid-tied N-R HES has an NPV of US${$}$770,661, US${$}$763,007 and US${$}$763,065 for Site I, Site II, and Site III, respectively. Compared to Ghana’s 2021 tariff rate, the cost of energy (COE) is expensive for the lifeline consumer (0.05USD/kWh) but cheap for the bulk commercial consumer (0.2 USD/kWh). Therefore, the economic viability analysis recommends a novel alternative to stimulate commercial activities, especially small and medium enterprises (SMEs), while serving as future clean energy solutions for Ghana and the West African sub-region.","PeriodicalId":338339,"journal":{"name":"2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117186011","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}

引用次数: 1

Assessment of Functional Risks for Engineering Adaptive Smart Grid Applications 工程自适应智能电网应用的功能风险评估

2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE) Pub Date : 2022-08-10 DOI: 10.1109/SEGE55279.2022.9889752

W. Renz, J. Sudeikat, J. Backes, Kolja Eger

{"title":"Assessment of Functional Risks for Engineering Adaptive Smart Grid Applications","authors":"W. Renz, J. Sudeikat, J. Backes, Kolja Eger","doi":"10.1109/SEGE55279.2022.9889752","DOIUrl":"https://doi.org/10.1109/SEGE55279.2022.9889752","url":null,"abstract":"Established engineering procedures for developing smart grid applications adopt the Use-Case Methodology in combination with the Smart Grid Architecture Model (SGAM). This methodology has so far been adapted to include risk assessment for guaranteeing system security i.e. non-functional requirements. Recent work on engineering use cases that require specific adaptivity processes to make the system resilient against unexpected, rare events indicated the necessity to refine the established methodologies. In this paper, we propose an extension to the established engineering methodology that guides development teams to quantify such functional risks during requirements engineering phase. This enables inferring the suitable operating principles and system architectures for appropriate adaptive application designs. For demonstration, we consider the risks that arise from operating a virtual power plant under rare environmental conditions that are usually treated by manual trading activities. The methodology is validated in a case study for risk-aware balancing of renewable energy via flexible prosumers thereby reproducing the ad-hoc workflow used for particular flexibility use cases in earlier work. Altogether, we show how, at design time, the use of the proposed methodology supports the development of risk-aware adaptive systems.","PeriodicalId":338339,"journal":{"name":"2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE)","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122344851","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}

引用次数: 1

SEGE 2022 Cover Page SEGE 2022封面页

2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE) Pub Date : 2022-08-10 DOI: 10.1109/sege55279.2022.9889767

引用次数: 0

Applications of Blockchain Methodologies for Microgrid Energy Transactions While Maintaining User Privacy and Data Security – A Review 区块链方法在微电网能源交易中的应用，同时维护用户隐私和数据安全——综述

2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE) Pub Date : 2022-08-10 DOI: 10.1109/SEGE55279.2022.9889755

P. Ghosh, Rand Kato, Danielle Taana Smith, L. McKnight

引用次数: 0

Digital Twin of Radio-Mesh Smart Meter Communication for Outage Management Using a Multi-agent System 基于多智能体系统的无线网格智能电表通信中断管理的数字孪生

2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE) Pub Date : 2022-08-10 DOI: 10.1109/SEGE55279.2022.9889773

Linus Meyer, Kasper L. Jørstad, Lasse Kappel Mortensen, Athila Q. Santos, Karsten Handrup, H. Shaker

{"title":"Digital Twin of Radio-Mesh Smart Meter Communication for Outage Management Using a Multi-agent System","authors":"Linus Meyer, Kasper L. Jørstad, Lasse Kappel Mortensen, Athila Q. Santos, Karsten Handrup, H. Shaker","doi":"10.1109/SEGE55279.2022.9889773","DOIUrl":"https://doi.org/10.1109/SEGE55279.2022.9889773","url":null,"abstract":"With more distributed energy resources and electrification of the transport and heating sector, higher loads and more stress are imposed on the consumer side of the power grid, leading to higher fault risks. Therefore, an increasing need for innovative outage management solutions in the low voltage area of the power grid arises. However, testing new outage management methods in real-world power grids involves high risk and complexity. A virtual test environment to simulate outages on the grid can erase this risk and reduce complexity, enabling the development of new and innovative outage management strategies. This paper proposes a digital twin representation of a generalized radio-mesh smart meter network. The digital twin serves as a virtual test environment for further research and development of fault detection and diagnosis methods. As the European commission plans to finish a mass roll-out of smart meters for its member states by 2030, existing smart meter infrastructure is utilized by integrating their currently unused features, such as the last gasp feature. Modeling the radio-mesh network was subject to a variety of complex principles such as communication blind spots, package collision, and limited communication range. A validation of the behavior of the digital twin was carried out by comparing the simulated transmission time of the smart meter packages with transmission time data obtained in an experiment. Identical times were recorded, thus the results confirmed an accurate representation of the real system.","PeriodicalId":338339,"journal":{"name":"2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132566036","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}

引用次数: 1

Validating IEEE 1547 Capabilities of DER Inverter Model Using a Real-Time Simulated Inverter Laboratory Testbed 利用实时仿真逆变器实验室测试平台验证DER逆变器模型的IEEE 1547性能

2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE) Pub Date : 2022-08-10 DOI: 10.1109/SEGE55279.2022.9889756

N. Ninad, Eugene Desjardins-Couture, Estefan Apablaza-Arancibia

引用次数: 0

Energy Systems Condition Monitoring: Dynamic Principal Component Analysis Application 能源系统状态监测:动态主成分分析应用

2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE) Pub Date : 2022-08-10 DOI: 10.1109/SEGE55279.2022.9889774

Henrik Alexander Nissen Søndergaard, H. Shaker, B. Jørgensen

{"title":"Energy Systems Condition Monitoring: Dynamic Principal Component Analysis Application","authors":"Henrik Alexander Nissen Søndergaard, H. Shaker, B. Jørgensen","doi":"10.1109/SEGE55279.2022.9889774","DOIUrl":"https://doi.org/10.1109/SEGE55279.2022.9889774","url":null,"abstract":"Faults are estimated to cause 30 percent and 40 percent of energy consumption in building energy systems and district heating systems, respectively. It is therefore critical to detect these faults as early as possible to decrease this unnecessary waste of energy. Faults can also lead to lowered comfort of the customers. To detect these faults a data-driven methodology is applied, which utilizes dynamic principal component analysis (DPCA) for a generalized representation of the data, by projecting it into a subspace. In conjunction with DPCA, two multivariate statistical methods are applied for process condition monitoring: Hotelling’s T2 statistics and Q statistics. For fault diagnosis sensor contribution plots are utilized. The methodology has been applied to two cases: A district heating substation and a study space in a building in Denmark, with accompanying results and discussions. The methodology has proven to be easy to implement for both cases, showing that is exceptionally generalized and scalable. Furthermore, it has been able to detect known faults and identify the sensors responsible for the faults, in the data from the two cases. It has the potential to be adopted in real-time, however, more testing is necessary with other known faults.","PeriodicalId":338339,"journal":{"name":"2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127936785","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}

引用次数: 1

Demand Response Strategy of a Virtual Power Plant for Internal Electricity Market 面向内部电力市场的虚拟电厂需求响应策略

2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE) Pub Date : 2022-08-10 DOI: 10.1109/SEGE55279.2022.9889759

Z. Ullah, Muhammad Baseer, Arshad, Muhammad Baseer Arshad

{"title":"Demand Response Strategy of a Virtual Power Plant for Internal Electricity Market","authors":"Z. Ullah, Muhammad Baseer, Arshad, Muhammad Baseer Arshad","doi":"10.1109/SEGE55279.2022.9889759","DOIUrl":"https://doi.org/10.1109/SEGE55279.2022.9889759","url":null,"abstract":"Operational challenges are expected when a large amount of wind and solar energy is added to the electricity system. It is necessary to introduce new technologies to allow more energy portfolio integration into power systems in order to compensate for the intermittent nature of renewable energy sources (RESs) such as wind and solar power due to their fluctuating nature. A possible solution to the problem of renewable energy integration in power market transactions is the idea of a virtual power plant (VPP). A VPP is a novel and smart approach of integrating distributed energy resources (DERs) such as demand response (DR) and energy storage system (ESS). A VPP could exploit DERs and demand-side participation to mitigate peak loads and thus sustain grid stability. This paper presents a DR strategy of a VPP for simulating energy transactions within the VPP internal electricity market. The method assesses the impact of the DR program on renewable energies integration aiming to minimize VPP operating costs over the short-term planning horizon. Stochastic programming theory is used to address the optimization problem while protecting the interests of the end users. Preliminary findings show that peak load has been reduced while the overall cost of operating has decreased.","PeriodicalId":338339,"journal":{"name":"2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122607217","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}

引用次数: 1

Distributed Residential Demand Response Using Building Mass and Electric Thermal Storage System 基于建筑质量和电蓄热系统的分布式住宅需求响应

2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE) Pub Date : 2022-08-10 DOI: 10.1109/SEGE55279.2022.9889758

Farshad Etedadi Aliabadi, K. Agbossou, N. Henao, S. Kelouwani, F. Laurencelle

{"title":"Distributed Residential Demand Response Using Building Mass and Electric Thermal Storage System","authors":"Farshad Etedadi Aliabadi, K. Agbossou, N. Henao, S. Kelouwani, F. Laurencelle","doi":"10.1109/SEGE55279.2022.9889758","DOIUrl":"https://doi.org/10.1109/SEGE55279.2022.9889758","url":null,"abstract":"The increment of energy demand in residential electric networks increases the energy cost and reduces the operating reliability. This behavior is accentuated in cold climate regions where most of the consumers use electric space heating systems. In this context, thermal energy storage systems can be used as flexibility sources to relieve power grid stress. However, it is necessary to design an effective demand response technique to take advantage of the maximum potential of thermal storage systems. This research aims to propose and evaluate a distributed demand response approach to control integrated passive building thermal storage and electric thermal storage systems (utilizing bricks as storage means). The proposed approach is implemented as a dynamic price-based and day-ahead scheduling optimization problem based on the game theory concept. The formulation expresses the consumer’s participation willingness in the demand response program and their associated financial incentives. A simulation is carried out to examine the electrical/thermal behavior of the system and reveal the effectiveness of the proposed method in flattening the aggregated demand profile, reducing costs, and ensuring the households’ comfort. The numerical results show the capability of the proposed algorithm to improve the peak-to-average ratio by 57.36% and decrease the peak demand by 57.3%, while reducing the total electricity cost by 24.19% and increasing the share of distributed energy resources.","PeriodicalId":338339,"journal":{"name":"2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE)","volume":"328 11-12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120928793","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}

引用次数: 2

Fast Grid State Estimation for Power Networks: An Ensemble Machine Learning Approach 电网状态快速估计:一种集成机器学习方法

2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE) Pub Date : 2022-08-10 DOI: 10.1109/SEGE55279.2022.9889763

Shadi Shahoud, Hatem Khalloof, Ragheed Khalouf, Clemens Düpmeier, H. Çakmak, Kevin Förderer, V. Hagenmeyer

{"title":"Fast Grid State Estimation for Power Networks: An Ensemble Machine Learning Approach","authors":"Shadi Shahoud, Hatem Khalloof, Ragheed Khalouf, Clemens Düpmeier, H. Çakmak, Kevin Förderer, V. Hagenmeyer","doi":"10.1109/SEGE55279.2022.9889763","DOIUrl":"https://doi.org/10.1109/SEGE55279.2022.9889763","url":null,"abstract":"For better managing modern power distribution networks with continuously and dynamically changing grid characteristic induced by e.g. adding new renewable generation or vehicle charging stations, state estimation solutions must be capable of dynamically adapting to such topology changes. However, these solutions use a hand-made static topology model as calculation basis which cannot be easily dynamically adapted to topology changes without editing the underlying network topology model. This process is time-consuming and computationally expensive especially for large grids. In the present paper, we address the problem of grid state estimation by proposing a new machine learning-based solution. It paves the road for generic, accurate and simple state estimation independent of the grid topology and with minimal number of grid parameters. To achieve this, four simulated datasets, namely Balanced Generation-Consumption, Unbalanced Generation, Unbalanced Consumption and Mixed datasets are created representing the most common cases existing in the grid. Unlike other research works in the field of grid state estimation, this work applies ensemble learning, namely boosting, bagging and stacking for predicting the grid state variables. The obtained results are very promising and show that our ensemble-based solution exhibits very good results in terms of time efficiency and accuracy.","PeriodicalId":338339,"journal":{"name":"2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126396535","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}

引用次数: 1