an online access to exchange your research work, technical notes & surveying results 8.125. It is crucial for state-maintained smart substations. 7, no. However, the error metric is not given, which leads to inefficient results. Therefore, this paper aims to systematically review the existing application of machine learning methods on power system resilience enhancement, to expand the interest of researchers and scholars in this topic, and to jointly promote the application of artificial intelligence in the field of power systems. Substation equipment is briefly described in terms of its energy-related functions, classifications, and uses. This metric is assessed for both strategies by using the below equation. Simulation and experimental hardware show how deep modulation can converge to viable communications links, using the same machine intelligence, in vastly different channels. Initially, when several trials yield the same outcome with little variation, precision is necessary. Evaluating substation equipment overhaul efficacy tests the plans execution. An intelligent substation maintenance management system is needed because of a lack of a clear distinction between intelligent and conventional substation methods. The LSTM framework is shown in Figure 3. Compared to current methods, ours takes 250 seconds in training. The long-term accumulation of test/patrol examination data, malfunction records, and servicing documentation are what make up the bulk of the textual data for power transformers. Document indexing is the process of selecting the right collection of keywords from the entire corpus of documents and giving weights to such keywords for every individual text, thereby converting all files into a vector of keyword weights. K. Sun, T. Jing, X. The direct methods involve acquiring an NX core sample and using sophisticated laboratory procedures to determine UCS. In this paper, a multi-objective resilient PMU placement (MORPP) problem is formulated, and solved by a modified Teaching-Learning-Based optimization (MO-TLBO) algorithm. These three functions have been integrated into a console-type nuclear power plant monitoring and control system as a validation test bed. grid resilience have also been discussed in this paper. These techniques can deal with difficult tasks faced by applications in modern large power systems with even more interconnections installed to meet increasing load demand. These figures are shown below. B. There are new technological tools and theoretical concepts for the repair and control of power equipment owing to AIs advancements in performance, accuracy, and self-learning capacity in the detection, forecasting, improvement, and judgment jobs. Independent operation and maintenance produce additional contradictions. Chen et al. International Journal of Trend in Scientific Research and Development - IJTSRD having Here, =forget gate during the time (t), =input gate during t, =output gate during t, =candidates of input to be stored at t, =memory cells at t, ht=hidden state at t, Xt=input vectors at t, =bias vector of forget gate, =bias vector of input gate, =bias vector of output gate, and =bias vector of candidates of the input. . In order to expand its applicability in the near future, it is necessary to improve the surface properties of the porous structure. J2021155. AI techniques have become popular for solving different problems in power systems like control, planning, scheduling, forecast, etc. Power systems are still vulnerable to large-scale blackouts caused by extreme natural events or man-made attacks. distribution systems and the monitoring of apparatus. Considering human resource utilization efficiency, time cost, transit cost, and the constant reduction of operational people under large-scale operation and maintenance, smart substations may increase operation and maintenance efficiency (Wang et al. This paper lists the literature related to artificial intelligence applications to power systems and notes the artificial . This determines how precise our results are when comparing to other conventional results. With massive possibility and room for improvement in AI, the inspiration for researching them are apparent, and literally, hundreds of papers have been published, discussing the findings of hybrid AI for condition monitoring purposes. A number of select systems are described briefly and application areas suggested include security assessment, operator training, and planning. The fitness F of GA-based HCNN-individual TLSTM and MAPE (mean absolute percentage error) was also created as an inverse relationship; thus, the MAPE is used to determine individual fitness, allowing for an evaluation of the models effectiveness and the establishment of the final attribute values. The three distinctive life-cycle phases, design, control, and maintenance are correlated with one or more tasks to be addressed by AI, including optimization, classification, regression, and data structure exploration. The abstract may be rewritten to highlight AI deployment in specific fields. Furthermore, both the training and testing datasets have the best recall rate compared to previous approaches. The aim of the paper is to investigate the possibility of using artificial intelligence in photovoltaic energy production forecasting. Y. Z. Zhang, S. Zhang, and J. Hu, Calculation model of operation and maintenance costs of a substation project in electricity market environment, in Proceedings of the 2021 IEEE 4th International Conference on Computing, Power and Communication Technologies (GUCON), pp. The validation tests in which, The growing numbers of application areas for artificial intelligence (AI) methods have led to an explosion of domain-specific accelerators that could support every new machine learning (ML) algorithm advancement, clearly highlighting the need for a capability to quickly and automatically transition from algorithm definition to hardware implementation and explore design space along a variety of SWaP (size, weight and Power). 2, 2022. Multimodal machine learning analyses data from several modalities. [22]], CAD-IOMPSE [Song et al. In particular, we present a new MLIR dialect (part of the SODA frontend) that allows expressing spiking neural network features (e.g., available resources, spiking sequences, analog signal reading, etc.) Three objectives are considered in the MORPP problem, minimizing the number of PMUs, maximizing the system observability, and minimizing the voltage stability index. The patterns uncovered in the training dataset are applied to the test dataset by all prediction and classification algorithms. With the recent development in artificial intelligence technique, machine learning has shown a processing ability in computational, perceptual and cognitive intelligence. In this stage, the suggested techniques performance is evaluated, and a comparison analysis is computed by comparing it to some existing techniques (Text CNN [Chen et al. Many companies have forecast that the future of operation and supply chain management (SCM) may change dramatically, from planning, scheduling, optimisation, to transportation, with the presence of artificial intelligence (AI). engineers, students, and practitioners working in and around the world in many areas. This paper suggested a new HCNN-TLSTM technique to manage such operations and maintenance issues of the powerful hardware assets in the substation. The high exhaust heat temperature can be utilized by Heat Recovery Steam Generator (HRSG) to make superheated steam. B. Li and J. Liu, Research on remote intelligent platform and automatic monitoring system of transformer substations, in Proceedings of the 2021 IEEE International Conference on Emergency Science and Information Technology (ICESIT), pp. Primary procedures for smart substation maintenance. These examples show how to use K-LDA classification to classify a two-class situation. W. Wan, Y. Liu, X. Han, and H. Wang, Evaluation Model of Power Operation and Maintenance Based on Text Emotion Analysis, Mathematical Problems in Engineering, vol. important social need worldwide. The growth in electricity demand and the development of grid modernization have increased the complexity of power grid and driven the grid more vulnerable to extreme events like environmental disasters or man-made attacks. among professionals throughout the world in e-journals. Framework of prediction using genetic algorithm-based HCNN-TLSTM. Abstract: Out of the requirements of the operational monitoring systems of large steam power plants, this paper suggests a scheme for developing the intelligent control systems in steam power plants by using modern artificial intelligence techniques. Additionally, three areas of power equipment operation evaluation, maintenance training, and asset management are used to highlight the application of vector model data in substation operation and maintenance. The multimodal learning model integrates and learns multisource information from the model mechanism, not only splicing separate models and turning on their respective switches in different contexts. ANN is based on quite simple principles, but takes advantage of their mathematical nature, non-linear iteration to demonstrate powerful problem solving ability. This work proposes an approach to communications that is contrary to much traditional approaches in that processing, The objective of the development of an intelligent man-machine system for future nuclear power plants is enhancement of operational reliability by applying recent advances in cognitive science, artificial intelligence, and computer technologies. Like an attribute selection strategy, text analysis technologies frequently make use of this procedure. Improved diagnostic assessment and forecast results may provide a more reliable point of reference for equipment decision-making optimization, enhancing converter declarative programming still further. Finally, Dense creates a vector in the format specified, which is subsequently used in forecasting. Rahmat Izaizi B. Ismail1, Firas B. Ismail Alnaimi1 and Haidar F. AL-Qrimli2, Published under licence by IOP Publishing Ltd different heat sources, fossil fuel dominates here, although nuclear heat energy and solar heat energy are also used[2]. It is possible to use AI data analysis technologies, like expert systems and uncertainty reasoning as well as machine learning and intelligent optimum computations. So, it is being voracious or needy in quality or state. and Development Journal. S. Zhang, Y. Ye, and J. Yang, Prospects for the application of artificial intelligence (AI) technology in the power grid, in Proceedings of the Advancements in Mechatronics and Intelligent Robotics, pp. It is possible to forecast the state of an item of equipment by monitoring and evaluating its status. Substation equipment should be overhauled on schedule according to a company-wide strategy. In our two-class example, they show the direction of the primary eigenvector, which provides the most discriminating information. Based on an examination of the energy consumption data collecting technique, calculation foundation, and analysis method, the monitoring application of power equipment in the substation is developed. IJTSRD is a leading Open Access, Peer-Reviewed International Veracity is the proportion to which information is exact, accurate, and dependable. Incorporated in these are demands for ABSTRACT The geothermal power plant situated at Dholera, Gujarat like every power plant is designed for long term electricity generation. 67, no. Hence, precision is effective and plays a vital role in comparison. WiFi, WiMax, etc.) With increased competitiveness in power generation industries, more resources are directed in optimizing plant operation, including fault detection and diagnosis. Sun et al., Defect texts mining of secondary device in smart substation with GloVe and attention-based bidirectional LSTM, Energies, vol. (1) digital technology based on the application of semiconductor Available at SSRN: https://ssrn.com/abstract=4164367 or http://dx.doi.org/10.2139/ssrn.4164367 Download This Paper Open PDF in Browser Programming is the initial step. The LSTM uses a gate control technique to determine whether an input should be recalled or rejected, and it can use long-time sequence data to some extent. Abstract Carbon discharges from monetary movement proceed to rise and India is the third-biggest emitter among individual nations. An, and J. Hu, Application of power system vector model in substation operation and maintenance period, in Proceedings of the 2nd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2022), pp. If the LDA is merely a type of category, each type will require its own set of optimizing criteria. IJTSRD provides The genetic algorithm-based HCNN-TLSTM approach computes data produced from a convolutional neural network as a feed to LSTM to forecast time-series data. Dropout is a TLSTM feature that prevents problems with fitting. To guarantee the security of the substations hardware and surroundings, initially, physical labor was used to check substation hardware. [17] proposed 5G communication system architecture that is used in this study to implement wireless heterogeneous networking. To ensure this need is fulfilled, detailed investigations and developments are in progress on . In order to enhance power system resilience against outages and blackouts caused by extreme weather events or man-made attacks, it remains a major challenge to determine the optimal number and location of PMUs. [21]), which includes (1) profiles of power users, including geographical data, login details, and user types; (2) profiles of electricity substations; and (3) time-series data on user power usage. Then, B, Bk, Bm, Bo, R, Rk, Rm, and Ro are related weight matrices. Abstract. [8] examine power robots in domestic and international research and their structural characteristics and functions are analyzed for a variety of power applications, including overhead line inspection, substation inspection, live working of distribution lines, and cable channel power equipment inspection and maintenance. Assess substation maintenance. From this investigation, the proposed technique has the lowest MAPE (19.13%) compared with existing techniques. sensor technology, and standardized interfaces. Wang et al. electricity supply, deregulation, and global impact on the experienced operator crews participated were carried out in 1991 and 1992. The breakdown of power equipment can be characterized as either a good or bad event. [24]). Because of the distinctions between smart substation administration and traditional substation administration, Figure 1 depicts the six primary procedures used to carry out smart substation maintenance. Gradient fading is caused by gradually multiplying the weight matrix and the reciprocal of the tanh (from 0 to 1) function, which increases as the data interval (the indicated fixed length) grows longer. Rock strength, specifically the uniaxial compressive strength (UCS), is a critical parameter mostly used in the effective and sustainable design of tunnels and other engineering structures. Abstract The application of these techniques has been successful in many areas of power system engineering. The control center receives updates from the operational crew on the results of the overhaul. To realize this objective, the intelligent man-machine system, aiming to support a knowledge-based decision making process in an operator's supervisory plant control tasks, consists of three main functions, i.e., a cognitive model-based advisor, a robust automatic sequence controller, and an ecological interface. Second, recall is the percentage of pertinent instances that were found. expected: (1) reduced costs in remote surveillance in the field of [1]). Three distinct areas have been categorized validating the application of AI methods in power systems. The presented approach is conceived as a module of energy management and production planning of a photovoltaic power plant located in central part of Romania. For accuracy and F1 scores, Text CNN produced better results in (Chen et al. 2021, Article ID 2824689, 8 pages, 2021. The effectiveness of the proposed method is validated through, Traditional physical layer protocols (e.g. 295298, IEEE, Shanghai, China, May 2021. It is only a matter of eliminating words that appear in a large number of different documents throughout the corpus. Compliance with technical specifications for building smart laboratories and substations, as well as responses to requirements for building an IoT system, will be required. Here are the classes a priori probabilities. Salihu and Zayyanu [16] examined the samples taken from vegetable farms in Zamfara State, Nigeria, for thermodynamic and organophosphate agrochemicals. Artificial intelligence (AI) technology enables coming up with solutions because electricity business types and volumes are constantly expanding and developing. Physical fitness is used to select individuals for future generations. Abstract: Artificial intelligence is the science of automating intelligent behaviours currently achievable by humans. Equations (2) and (3) are used to calculate the scatter measurements. 143146, IEEE, December 2021. Zhang et al. the theory and practice along with knowledge sharing between researchers, developers, For both training and testing datasets, this metric is used to evaluate the accurateness of the new measurements reactions to proposed and present techniques, and this metric is expressed in percentage. Application of artificial intelligence in electrical power systems Abstract: In this paper, the application of heuristic and optimization algorithms based on artificial intelligence (AI) is investigated on electrical power systems. In this paper we discuss the support for such an integrated generation leveraging the SODA Synthesizer framework and its modular structure. Genhe is cold, while Xinjiang, Turpan, and Henan are hot. State Grids Three Collections and Five Majors have all been unattended smart substations. It is important to note that all of the information gathered throughout this technique gives details on equipment functioning conditions and problem propagation across the process. Stop words, such as articles and pronouns, are what they are called. The CAD-IOMPSE approach also generates superior accuracy, recall, and F-measure results (Song et al. DA-BiLSTM framework on basic power grid fault texts was applied to reduce misclassifications caused by data interruption (Li et al.