e-Prime - Advances in Electrical Engineering, Electronics and Energy最新文献

{"title":"Neural Prophet driven day-ahead forecast of global horizontal irradiance for efficient micro-grid management","authors":"Stephen Oko Gyan Torto ,&nbsp;Rupendra Kumar Pachauri ,&nbsp;Jai Govind Singh","doi":"10.1016/j.prime.2024.100817","DOIUrl":"10.1016/j.prime.2024.100817","url":null,"abstract":"<div><div>This study introduces an innovative approach to day-ahead solar irradiance forecasting, utilizing the NeuralProphet model—a deep learning-based extension of the Prophet tool—to effectively manage the complexities of time-series data in solar energy prediction. Recognizing the critical role of accurate solar irradiance predictions in optimizing the operation of multi-vectored energy hubs, this research integrates NeuralProphet's advanced neural network components, including its trend and seasonality modules, to enhance forecasting accuracy. The innovative integration of NeuralProphet's trend, seasonality, and autoregressive components allows for superior performance in forecasting compared to traditional models. When the model's performance is compared to historical solar irradiance data, it is evident how well it captures underlying trends in comparison to more conventional approaches. In contrast, Dataset 1 has a daily forecast MAE for the model that is about 38.6 % lower than Dataset 2, but Dataset 1 has weekly and monthly forecast MAEs that are 6.25 % and 5.6 % higher, respectively. Better day ahead accuracy is also shown by the daily forecast MAPE for Dataset 1 being 45.1 % lower than for Dataset 2. Furthermore, Dataset 1 has a daily R² value of 99.5 %, while Dataset 2 has a value of 99.0 %. This suggests that Dataset 1 has 0.5 % more accurate day ahead forecasts. There is a 0.1 % increase in accuracy as evidenced by the weekly R² values for Dataset 1, which is 98.4 %, while Dataset 2 is 98.3 %. The R² for monthly projections shows that Dataset 1 has a 0.5 % poorer accuracy over longer time horizons, with 95.6 % for Dataset 1 and 96.1 % for Dataset 2. These results demonstrate the model's potential to optimize the operation of energy hubs by accurately forecasting GHI, contributing to more efficient micro-grid management and a reduction in dependency on fossil fuels. The findings demonstrate that deep learning techniques can be integrated into renewable energy forecasting, offering substantial benefits for the design and management of future energy systems..</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"10 ","pages":"Article 100817"},"PeriodicalIF":0.0,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced thermal modeling of power transformers: A comparison of bond graph and IEEE methods considering external environmental factors","authors":"Vinit Mehta ,&nbsp;Jayashri Vajpai","doi":"10.1016/j.prime.2024.100812","DOIUrl":"10.1016/j.prime.2024.100812","url":null,"abstract":"<div><div>The optimal and secure operation of electrical power system is largely affected by the reliability of power transformers in operational and economic terms. The continuous monitoring of power transformer is crucial for ensuring the quality of electrical power supply. Hence, the thermal modeling of power transformer is very essential to prevent their failure. This paper aims to design thermal models of operating power transformer by considering the two external influencing parameters of solar irradiation and wind flow. This paper presents a Bond Graph (BG) method-based design of thermal models for power transformer under operating condition by comparison with the results obtained from IEEE Std. based thermal models and also with the practical readings. The models have been implemented on a 5MVA, 33/11 kV power transformer running at 33 kV Substation, Sardarpura, Jodhpur, by initially considering the input hourly dataset of load and ambient temperature. The designed thermal models were subsequently updated by integrating the impact of solar radiation and wind incident on the surface of power transformer. Comparative study of all the designed thermal models has been done that indicates improved accuracy of the model if the impact of solar radiation and wind flow are included. Also, the effectiveness of the BG based thermal models in accurately predicting the system behaviour validates their applicability for real world engineering applications.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"10 ","pages":"Article 100812"},"PeriodicalIF":0.0,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating renewable energy communities and Italian UVAM project through renewable hydrogen chain","authors":"Giulio Raimondi ,&nbsp;Giuseppe Spazzafumo","doi":"10.1016/j.prime.2024.100819","DOIUrl":"10.1016/j.prime.2024.100819","url":null,"abstract":"<div><div>Renewable energy communities (RECs) in Italy could play an important role in increasing the stock of electric renewable generation in the coming years. Their impact on the electric grid could be non-negligible. At the same time with increased electric generation from renewables, a greater need for electric national grid balancing is expected, preferably based on zero-emission energy storage. Based on currently existing entities in Italian regulation framework (i.e. REC and UVAM project), the present work proposes an original business model to create a storage of dispatchable renewable hydrogen to be used for balancing National electric grid. Hydrogen production is from excess of renewables in RECs constituted in the same area. UVAM project allows to access the ancillary services market with the minimum capacity of 1 MW that appears appropriate to the proposed scenario. Based on current technical-economic constraints of the technologies involved (electrolysis and both fuel cell and internal combustion engine fed by hydrogen), proposed business model is not day-present economic feasible: the return on investment is never positive. The cost forecasts available for 2035 indicate that the business model will be likely sustainable, with a net present value becoming positive for configurations with more than 3000 people involved in the RECs, with a photovoltaic penetration condition of 1.8 kWp/capita. This research work suggests an original business model for managers of RECs with an excess of renewables generation.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"10 ","pages":"Article 100819"},"PeriodicalIF":0.0,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Forecasting thermoelectric power generation through utilization of waste heat from building cooling systems based on simulation","authors":"Catur Harsito ,&nbsp;Riyadi Muslim ,&nbsp;Eki Rovianto ,&nbsp;Yudi Kurniawan ,&nbsp;Fathin Muhammad Mahdhudhu","doi":"10.1016/j.prime.2024.100821","DOIUrl":"10.1016/j.prime.2024.100821","url":null,"abstract":"<div><div>The transformation of sustainable energy use is one of the main challenges facing the world today. Waste heat from industrial processes and conventional power plants is one form of energy waste that is often wasted. In this context, research on thermoelectric energy conversion systems is a very relevant and important topic to research. This research investigates about the potential for utilizing thermoelectric elements with stacked materials that utilize waste heat from building cooling systems. Numerical simulation was chosen to carry out further analysis regarding the potential energy produced and the efficiency of the materials used. Three-dimensional design and ANSYS is used as a three-dimensional simulation analysis tool. The research results show that thermoelectric systems with stacked materials have the potential to produce energy from waste heat. Material <em>(Cu₂Se⁺, BiTe⁺) (Bi₂S₃^-, CuFeS^-)</em> with 10 mm legs has the highest output power of 32.82 mW whereas <em>(PbSe⁺, BiTe⁺) (Bi₂S₃^-, AgInSe^-)</em> with a leg length of 20 mm has the highest efficiency value of 25.97%, and a power value of 6 .92mW. Full system research can produce values ​​that more closely resemble actual conditions.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"10 ","pages":"Article 100821"},"PeriodicalIF":0.0,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Convolutional neural network approach for fault detection and characterization in medium voltage distribution networks","authors":"Atefeh Pour Shafei ,&nbsp;J.Fernando A. Silva ,&nbsp;J. Monteiro","doi":"10.1016/j.prime.2024.100820","DOIUrl":"10.1016/j.prime.2024.100820","url":null,"abstract":"<div><div>Power outages significantly impact the power industry by disrupting social welfare and economic stability. Still, existing methods for fault detection face challenges due to load and network topology, conditions, and installed equipment. However, recent advances in artificial intelligence (AI) are enabling researchers to create alternative approaches for fault detection and location strategies. Therefore, this paper introduces a novel method for detecting, classifying, and locating faults in power systems through voltage waveform analysis using a convolutional neural network (CNN) integrated with the Piecewise Function Put Together (PFPT) algorithm for fault detection and fault zone localization in a power distribution network. Utilizing Park's transformation, noise reduction PFPT sine fitting, and CNNs, the proposed method distinguishes between 'healthy' and 'faulty' conditions. Simulation results reveal that while the voltage Park's vector time behavior of a healthy system remains stable, it exhibits circular or mixed patterns under faulty conditions. These patterns enable the identification of four types of short circuit faults—single-line-to-ground (LG), line-to-line (LL), line-to-line-to-ground (LLG), and three-line (3L) faults—by analyzing 3D voltage Park's waveforms at network buses. The study validates fault type identification through the observation of rotating Park vectors from sine fitting of time-based voltage waveforms. By converting 3D voltage waveforms into high-resolution images, the method utilizes a CNN for fault recognition, achieving an accuracy of 93.1%. This innovative approach underscores the robustness and precision of combining traditional electrical engineering techniques with modern AI.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"10 ","pages":"Article 100820"},"PeriodicalIF":0.0,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142539505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Biomedical device powered by triboelectric nanogenerator","authors":"Guru Prasad Murugan ,&nbsp;Abiudh Durairaj R ,&nbsp;Sharan Kishore R ,&nbsp;Dr. Manjula Devi R ,&nbsp;Dr. Jeyalakshmi Velusamy","doi":"10.1016/j.prime.2024.100811","DOIUrl":"10.1016/j.prime.2024.100811","url":null,"abstract":"<div><div>Biomedical devices play vital roles in health monitoring. Operability of these devices is hindered by their limited battery life. In vivo monitoring, diagnosis, and treatment have become challenging. The proposed Triboelectric Nanogenerator helps in overcoming the shackles of battery life. This article describes the process involved in the development of a healthcare device powered by triboelectric effect. In this work a contact-separation mode based triboelectric nanogenerator (TENG) has been used to power the device. TENG uses triboelectric phenomenon to transform mechanical energy into electrical energy. A contact-separation mode TENG operates through the interaction of two triboelectric materials. These materials act as an anode and a cathode, respectively, and develop opposite charges when brought into contact. Upon separation, the charged surfaces retain their individual charges, creating a potential difference between the materials. This difference generates an electrostatic field that drives the flow of electrons from one electrode to the other. As the electrons return, the field collapses, and the materials come back into contact, repeating the cycle. The device has been used to power a heart rate monitoring system. Experimental results demonstrate the output performance and long-term durability of the TENG device. Furthermore, future research, challenges and opportunities have been elaborated.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"10 ","pages":"Article 100811"},"PeriodicalIF":0.0,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of temperature and magnetic field on the density of surface states in semiconductor heterostructures","authors":"U.I. Erkaboev,&nbsp;N.Yu. Sharibaev,&nbsp;M.G. Dadamirzaev,&nbsp;R.G. Rakhimov","doi":"10.1016/j.prime.2024.100815","DOIUrl":"10.1016/j.prime.2024.100815","url":null,"abstract":"<div><div>In this article, the physical properties of the surface of the CdS/Si(p) material under the influence of a magnetic field were studied . The dependence of the density of surface states of the p-type Si(p) semiconductor on the magnetic field and temperature has been studied. For the first time, a mathematical model has been developed to determine the temperature dependence of the density of surface states of a semiconductor under the influence of a strong magnetic field. Mathematical modeling of processes was carried out using experimental values of the continuous energy spectrum of the density of surface states, obtained at various low temperatures and strong magnetic fields, in the band gap of silicon. The possibility of calculating discrete energy levels is demonstrated.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"10 ","pages":"Article 100815"},"PeriodicalIF":0.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535321","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A multi-layer constrained spectral k-embedded clustering methodology approach for intelligent partitioning of power grid to enhance resiliency in transmission networks","authors":"E Priya,&nbsp;J Preetha Roselyn","doi":"10.1016/j.prime.2024.100813","DOIUrl":"10.1016/j.prime.2024.100813","url":null,"abstract":"<div><div>The intentional controlled islanding by intelligent partitioning of the power grid is considered as essential to protect the grid from cascading events, faults, and High Impact Low Probability (HILP) events. To enhance the resilience, stability, and security of the power grid, the proposed model in this paper intentionally divides the affected power network into islands. This paper presents an intelligent partitioning approach to create an islanding solution through multilayer graphs using spectral clustering. The controlled islanding algorithm uses a multi-criteria objective function that considers the correlation coefficients among the frequency of the buses and minimal disturbances in the real and reactive power. The proposed control technique is implemented in two phases. The first phase employs correlation coefficients between frequency of the buses and modularity clustering to identify clusters of coherent buses. During the second stage, all nodes are categorised into groups using Multi-level constrained Spectral Clustering (ML-CSC) to determine the solution for Intentional controlled Islanding that satisfies bus coherency with the minimum level of disruptions to real and reactive power flows across the boundaries. The proposed algorithm for resolving the generator coherency issue and an intelligent islanding solution is demonstrated by simulation experiments conducted on an IEEE 39-bus transmission test system developed in DIGSILENT Powerfactory version 2023. The MATLAB version R2023a is used to construct the ML-CSC control method. The results demonstrated that the proposed ML-CSC algorithm substantially impacts the functioning of the power system, enabling the formation of intelligent islanding during abnormal conditions. Also, the results clearly show that instead of using single-layer spectral clustering, the multi-layer spectral clustering yields a better intentional islanding solution with minimum power flow mismatch which enhances the transient stability of the islands.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"10 ","pages":"Article 100813"},"PeriodicalIF":0.0,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142444832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coordination of smart inverter-enabled distributed energy resources for optimal PV-BESS integration and voltage stability in modern power distribution networks: A systematic review and bibliometric analysis","authors":"Olufunke Abolaji Balogun,&nbsp;Yanxia Sun,&nbsp;Peter Anuoluwapo Gbadega","doi":"10.1016/j.prime.2024.100800","DOIUrl":"10.1016/j.prime.2024.100800","url":null,"abstract":"<div><div>Integrating photovoltaic (PV) and battery energy storage systems (BESS) in modern power distribution networks presents opportunities and challenges, particularly in maintaining voltage stability and optimizing energy resources. This systematic review and bibliometric analysis investigates the coordination of smart inverter-enabled distributed energy resources (DERs) for enhancing PV-BESS integration and ensuring voltage stability. The study synthesizes recent advancements in smart inverter technologies, which provide grid support functions such as Volt/VAr control, and their applications in DER coordination. A comprehensive review of the literature is conducted to identify prevailing trends, research gaps, and emerging techniques in the field. Bibliometric analysis is employed to quantify the research landscape, highlighting key publications, citations, publications per country, and collaborative networks. The findings reveal that smart inverters play a crucial role in mitigating voltage violations and improving the hosting capacity of PV systems in distribution networks. Furthermore, optimal inverter settings, strategic placement of PV-BESS, and advanced control algorithms are identified as critical factors for effective DER integration. The study concludes by proposing future research directions, including the exploration of smart inverter interactions with legacy grid management systems and the development of robust algorithms for dynamic and adaptive DER coordination. This review serves as a valuable resource for researchers and practitioners aiming to enhance the stability and efficiency of power distribution networks through advanced DER management strategies.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"10 ","pages":"Article 100800"},"PeriodicalIF":0.0,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142444830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of an intelligent-based telemetry hexapod robotic system for surveillance of power system components","authors":"Oluwaseun O. Tooki ,&nbsp;Abdurrhman A. Aderinto ,&nbsp;Olawale M. Popoola","doi":"10.1016/j.prime.2024.100806","DOIUrl":"10.1016/j.prime.2024.100806","url":null,"abstract":"<div><div>A robot is an artificial system that performs specific programmed tasks to aid day-to-day human activities. Robot finds applications in industries for large-scale production, healthcare for computer-aided surgeries, security for surveillance of electrical power system equipment, and the military for carrying out dangerous reconnaissance. Most robotic systems employed for different operations use a wheeled mode of locomotion which has limitations over rough terrains and the issue of communication setup of the system. This work developed a hexapod, a six-legged robotic system, to overcome these identified challenges. The robot was developed in tandem with a telemetry system for surveillance. Although, automating the surveillance process using robotic systems has been in the works for some time. However, this work developed a telemetry hexapod robotic system for enhanced surveillance for the security of power systems equipment and other critical infrastructures using a Raspberry Pi for fast, secure data transmission, and precise system synchronization. An inverse kinematics approach was used to determine joint configurations for better positions of each endpoint. A digital camera was integrated into the robot to relay real-time images of adversaries of power system components intelligently. In addition, the system incorporates data processing capability. In the result obtained, the developed telemetry hexapod robotic system receives instructions over a distance slightly above 300 m. It establishes effective control of the telemetry system without any hindrance of a limited range as observed in Bluetooth-controlled systems. The system's performance includes an average efficiency of 98.2 %, latency of 0.48 s at the peak distance, and an endurance of 4 h. Further analysis of the system shows that the corresponding increase in the latency with the distance is negligible. The system performed better than other related systems considered in the literature. The correct implementation of the developed telemetry hexapod robotic system further enhances mobility, stability in rough terrain, reliable communication system. Also, it brings about a notable reduction in component theft in electrical power systems.</div></div>","PeriodicalId":100488,"journal":{"name":"e-Prime - Advances in Electrical Engineering, Electronics and Energy","volume":"10 ","pages":"Article 100806"},"PeriodicalIF":0.0,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142535319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}