WSEAS Transactions on Power Systems最新文献

{"title":"Congestion Management in Power Transmission Lines with Advanced Control Using Innovative Algorithm","authors":"Bala Saibabu Bommidi, Baddu Naik Bhukya, Swarupa Rani Bondalapati, Hemanth Sai Madupu","doi":"10.37394/232016.2022.17.35","DOIUrl":"https://doi.org/10.37394/232016.2022.17.35","url":null,"abstract":"It can be challenging to allocate all the necessary power to a supply in a modern power system if the power lines are overloaded. The conventional power system, monitored by flexible AC transmission system (FACTS) controllers, is one answer to this issue because it can increase the electrical power system's ability to deal with rapid variations in working circumstances. The advanced interline power flow controller using a constriction factor-based particle swarm optimization (CFBPSO) algorithm (AIPFC) was proposed in this paper as an optimal power flow control for controlling congestion in transmission lines. When comparing the performance of single-line and multi-line FACTS controllers, the latter is shown to be more effective overall. This paper presents a comprehensive model of an advanced interline power flow controller (AIPFC) and explores the effect of situating the controller in the most advantageous physical location. To address OPF concerns when using state-of-the-art IPFC, a novel algorithm, CFBPSO, is proposed. A traditional IEEE 30 bus test system is used to verify the proposed method. A standard IEEE 30 bus test system is used to verify the accuracy of the proposed method. In their paper, the researchers show that their proposed algorithm works by showing that the value of the objective function goes down.","PeriodicalId":38993,"journal":{"name":"WSEAS Transactions on Power Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44261057","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}

{"title":"Analysis of 3-Phase Symmetrical and Unsymmetrical Fault on Transmission Line using Fortescue Theorem","authors":"Fsaha Mebrahtu Gebru, Ayodeji Olalekan Salau, Shaimaa H. Mohammed, S. Goyal","doi":"10.37394/232016.2022.17.32","DOIUrl":"https://doi.org/10.37394/232016.2022.17.32","url":null,"abstract":"This paper investigates the major faults affecting the transmission of electrical energy after power has been generated from the power generating station. In a 3-phase transmission line, faults arise due to numerous causes such as aircraft, line breaks due to the excessive loading, heavy winds, trees falling across the lines etc. The faults faced in a 3-phase transmission line are broadly categorized into two main parts, namely: unsymmetrical faults and symmetrical faults. Furthermore, there is another classification of faults in 3-phase transmission lines such as: shunt type of faults and series type of faults, but this paper discusses the shunt type of faults which create short circuit on single line to ground (L-G) faults between two conductors or line to line (L-L) faults, or double line to ground (LL-G) or (triple) three line to ground (LLL-G) faults. This was achieved using the Fortescue Theorem on MATLAB software. The results show that the single L-G faults occur more frequently followed by the L-L faults, LL-G faults, and LLL-G faults. This study is essential to evaluate the power reliability and stability of power transmission lines.","PeriodicalId":38993,"journal":{"name":"WSEAS Transactions on Power Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44141422","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}

{"title":"New Procedure for Estimation of Power Fundamental Phasor Parameters in Presence of Decaying DC Components","authors":"Dimitrije Rozgic, P. Petrović","doi":"10.37394/232016.2022.17.29","DOIUrl":"https://doi.org/10.37394/232016.2022.17.29","url":null,"abstract":"The paper proposes a new algorithm for the estimation of the fundamental phasor in a power system, based on the removal of exponentially decaying DC components (DDCs). These components, as well as high-order harmonics and noise components, have a considerable effect on accuracy and speed of convergence in numerical and digital relays – speed of the protection relay operation. A Discrete Fourier Transform (DFT) based approach with a modified Prony method was used to calculate and remove the unwanted effect of DDCs in a time interval slightly longer than the period of the fundamental harmonics. The proposed procedure offers the possibility to estimate the parameters of unwanted DDCs in a simpler and analytically more precise way, thus facilitating its program implementation. The algorithm offers the ability to easily adjust the response speed - detection time. This flexibility of the algorithm provides a compromise in terms of response speed as well as expected reliability and security of fault detection. The developed procedure enables the monitoring of the very demanding dynamics of the current signal in short-circuit conditions, and thus the estimation of the phasor parameters of the energy signal so that the relay protection can respond to this emergency in the most adequate (adaptive) way - it becomes more precise and faster in its response. The algorithm has low numerical and computational complexity while maintaining its high performance even in conditions of a very strong noise signal. The simulation results for different test signals demonstrate high precision in the estimation of the fundamental phasor of the proposed algorithm.","PeriodicalId":38993,"journal":{"name":"WSEAS Transactions on Power Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47690096","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}

{"title":"Smart Grid Stability Prediction with Machine Learning","authors":"Gilliaert Daniel","doi":"10.37394/232016.2022.17.30","DOIUrl":"https://doi.org/10.37394/232016.2022.17.30","url":null,"abstract":"Smart grids refer to a grid system for electricity transmission, which allows the efficient use of electricity without affecting the environment. The stability estimation of this type of network is very important since the whole process is time-dependent. This paper aimed to identify the optimal machine learning technique to predict the stability of these networks. A free database of 60,000 observations with information from consumers and producers on 12 predictive characteristics (Reaction times, Power balances, and Price-Gamma elasticity coefficients) and an independent variable (Stable / Unstable) was used. This paper concludes that the Random Forests technique obtained the best performance, this information can help smart grid managers to make more accurate predictions so that they can implement strategies in time and avoid collapse or disruption of power supply.","PeriodicalId":38993,"journal":{"name":"WSEAS Transactions on Power Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41629183","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}

{"title":"Wind Power Forecasting using Artificial Neural Network","authors":"M. Obeidat, Baker N Al Ameryeen, A. Mansour, Hesham Al Salem, Abdullah Eial Awwad","doi":"10.37394/232016.2022.17.28","DOIUrl":"https://doi.org/10.37394/232016.2022.17.28","url":null,"abstract":"The electric energy generated from wind resources is now one of the most important sources in the electrical power system. Predicting wind speed is difficult because wind characteristics are unpredictable, highly variable, and dependent on many factors. This paper presents the design of an artificial neural network used in wind energy forecasting that has been trained using weather data that influences wind energy generation. Artificial Neural Network (ANN) has gained popularity in recent years due to its superior performance. The main objective of the developed model is to improve the forecasting of energy generated from wind farms. The developed system allows the power system operator to determine the best time to rely on the wind farm to produce power for the electrical system without affecting the stability of the system and reducing the cost of electricity generation due to the traditional method. The analysis is performed by investigating wind potential and collecting data from a highly recommended source. The heatmap, covariance and correlation methods are used to analyze the data, and then the data is used to build an Artificial Neural Network (ANN) in MATLAB 2020. The results show very high accuracy 99.9%.","PeriodicalId":38993,"journal":{"name":"WSEAS Transactions on Power Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41757218","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}

{"title":"Wind Turbine Energy Cost Optimisation Using Various Power Models","authors":"D. P. S, Vijila Moses, M. G, L. M.","doi":"10.37394/232016.2022.17.27","DOIUrl":"https://doi.org/10.37394/232016.2022.17.27","url":null,"abstract":"In modern times, the worldwide wind turbine installations have developed swiftly resulting in the decrease of green gas emissions. Though wind is a free gift of nature, it is expensive to harness this energy for useful applications like electricity generation. The cost of installation of the wind turbine at a particular station does not depend only on the wind resource, but also on the structure of the turbine and the energy conversion technology. The wind turbine Cost of Energy (CoE) is used to estimate the payback time for the return on the investment made by the wind farm owners for the turbine. Meticulous research is required to optimize the turbine CoE which will make wind a very competent source of energy. In this article, in order to minimize the wind turbine CoE, the wind speed is modelled using three different distributions namely, Dagum, Gamma and Weibull and the evaluation of the turbine Annual Energy Production (AEP) is carried out. Mathematical functions such as linear, quadratic and cubic have been used to model the wind power. For the cost analysis of the turbine, the price model which was established by United States, National Renewable Energy Laboratory (NREL) is employed. The comparative study of the proposed methodology have been done for six different stations. The turbine CoE model is an element of two factors, the rated power Pr of a turbine and the rated wind speed Vr of a turbine. Based on the results obtained, a broad recommendation to reduce the turbine CoE is presented. This study enables us to figure out the minimum turbine CoE among the three discussed mathematical distributions, the finest distribution for wind speed modelling and the optimum mathematical function for wind power modelling. The suitable size of the wind turbine also can be found by optimizing the rotor radius R of the turbine for each data.","PeriodicalId":38993,"journal":{"name":"WSEAS Transactions on Power Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42050504","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}

{"title":"Hybrid Ant Colony Robust Genetic Algorithm for Optimal Placement of Renewable Distributed Generation and Storage units in Distribution Networks","authors":"Vasco C. F. Santos, E. Gouveia","doi":"10.37394/232016.2022.17.26","DOIUrl":"https://doi.org/10.37394/232016.2022.17.26","url":null,"abstract":"This paper presents a multi-objective algorithm to support sizing and placement of Renewable Distributed Generation with storage units (RDG&S) in radial distribution networks. Two objectives are considered in the model, the first one is focused in the minimization of the RDG&S units capital costs and the second one in the minimization of system losses. This approach uses a hybrid Ant Colony Genetic Algorithm (ACGA) divided in two steps. At the first step of the approach an Ant Colony (AC) acts to face with the uncertainty of the problem and to deal with instabilities of the initial data. This way a good Pareto front, which is used to feed the initial population of da Genetic Algorithm (GA). At the second step, an Elitist Robust Genetic Algorithm with a secondary population is used, to characterize the non-dominated Pareto Optimal Frontier. In this algorithm the concept of robustness is operationalized in the computation of the fitness value assigned to solutions. The results presented in this approach demonstrates the real capabilities of the proposed algorithm to generate a well-spread and more robust effective non-dominated Pareto Optimal Frontier.","PeriodicalId":38993,"journal":{"name":"WSEAS Transactions on Power Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43973122","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}

{"title":"Navigating the Prevailing Challenges of the Nigerian Power Sector","authors":"Eric Akpoviroro Obar, A. Touati, O. Adekanle, Benjamin O. Agajelu, Laince Pierre Moulebe, N. Rabbah","doi":"10.37394/232016.2022.17.24","DOIUrl":"https://doi.org/10.37394/232016.2022.17.24","url":null,"abstract":"The Nigerian power sector continues to suffer from the resource curse. With the abundance of natural and renewable energy resources, somehow the Nigerian power sector has failed to meet the energy demand. Over the years, lack of political will and inadequate investments as regards the generation, transmission and distribution of electricity have led to very costly outages. The frequent collapse of the national grid has led to use of diesel/gasoline generators as a stop gap measure for producing electricity. However, this approach significantly increases the cost of production of goods/services (especially with the Russia-Ukraine war) and pollutes the environment/ecosystem. The objective of this paper is to take and in-depth analysis of the problems of the Nigerian power sector beginning with the regulatory framework to the different actors of the Nigerian Electricity Supply Industry NESI (The Gas producers, The Nigerian Gas Company, The Generation Companies, The Transmission Company of Nigeria and the Distribution Companies). Our goal is to achieve a fundamental balance between the affordability, reliability and sustainability of electricity, otherwise known as the energy trilemma.","PeriodicalId":38993,"journal":{"name":"WSEAS Transactions on Power Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46727905","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}

{"title":"Reducing the Fluctuations Effect of the DC supply on the Three Phase Inverter using Intelligent Inverter Control","authors":"M. Obeidat, Osama Alsmeerat, A. Mansour, J. Abdallah","doi":"10.37394/232016.2022.17.23","DOIUrl":"https://doi.org/10.37394/232016.2022.17.23","url":null,"abstract":"In this paper, an Intelligent inverter control is used to reduce the noise, disturbances, and sudden jumps in DC bus voltage of the grid supplies a three-phase inverter. The system is modelled using Matlab/Simulink 2020. Many reasons cause fluctuations in a DC supply such as loose, corroded connections, or unregulated supply. The paper proposes a solution for fluctuations in DC supply of three phase voltage source inverter using two degree of freedom controllers Feeback FB and Feedforward FF. The results show that FB only can't solve the disturbances and sudden jumps of the DC voltage. Using both controllers FB and FF solve this problem and the performance such as overshoot, rise time, peak time, and settling time parameters are improved under different load conditions for ±15% fluctuation in DC supply","PeriodicalId":38993,"journal":{"name":"WSEAS Transactions on Power Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47077585","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}

{"title":"Performance Analysis of Hybrid Cryptography System for High Security and Cloud-Based Storage","authors":"R. Bhagyalakshmi, Roopashree D., S. K. N.","doi":"10.37394/232016.2022.17.25","DOIUrl":"https://doi.org/10.37394/232016.2022.17.25","url":null,"abstract":"Now a day, the security of the data is playing a major part in communication systems due to further bushwhackers between channels media. The security position depends on cache crucial and as per literature, advanced the bit size of the key, advanced the security and also larger data size comes major challenge task for the further process. Thus, the generation of crucial with the further size is a major grueling task and at present, the Advanced Encryption Standard (AES) is a better cryptography system where the encryption and decryption can perform with a fixed key. The literature says the holomorphic function is well-suitable for data size reduction. To address this issue, new Holomorphic grounded encryption and decryption and AES are combined to increase the security position. The alternate novelty is that variable crucial generation using Elliptic Wind Cryptography (ECC) due to its enlarged proportion of consideration in assiduity and experimenters. The ECC uses point addition and point doubling to induce 256 values and addition operations can be avoided. After the generation of the matrix, each matrix value is translated and decrypted using a Holomorphic algorithm. The proposed work has been designed using MATLAB 2017a, dissembled, and validated with different datasets in real decors. Cloud computing is expected to be considered one of the primary computing platforms in the field of storage and security as it possesses many advantages such as profitability, efficiency as well as lower implementation overheads. Contemporary cloud computing security algorithms are enhanced extensions of cryptography. Data privacy, as well as data protection, are the major areas of concern in Cloud computing. The cryptographic with holomorphic based data encryption and interchange of information is exchanged and then accumulated in the cloud through holomorphic encryption which uses point addition and doubling operation to ensure data confidentiality of owners as well as users. Proposed work novel hybrid algorithm based on the context of encryption and decryption and thus integrates cryptography hybrid techniques include modified 126-bit AES and ElGamal based ECC through splitting algorithm. The advantage of splitting the larger data in size into binary form and then processing for encryption and decryption leads to optimization of latency, increase throughput, and security. The proposed hybrid approach has better security towards information sharing as well as cloud storage intrusions. Based on obtained results in MATLAB 2017a software tool, the obtained results show that 43% improvement in throughput and 12% reduction in latency, and a 21% improvement in security level.","PeriodicalId":38993,"journal":{"name":"WSEAS Transactions on Power Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46179713","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}