Operation Of System Research Articles

Optimizing loss functions for improved energy demand prediction in smart power grids

In this paper, our aim is to improve the accuracy and effectiveness of energy demand forecasting, particularly within modern electricity transmission systems and smart grid technology. To achieve this, we developed a hybrid approach that combines machine learning, representation learning, and other deep learning techniques. This approach is based on extracting essential features, including time-based attributes, identifiable trends, and optimal lags. The outcome of our investigation is the observation that triplet losses demonstrate remarkable accuracy, particularly when employed with a larger margin size and for longer prediction lengths. This finding signifies a substantial improvement in the precision and reliability of energy demand forecasting within modern electricity transmission systems. Our research not only improves predictive modeling in the power grid but also demonstrates the practical use of advanced analytics in addressing renewable energy integration challenges, refining energy demand forecasting for efficient management, system operation, and market analysis.

Virtual testbed for development and evaluation of power system digital twins and their applications

Digital twins (DTs) show considerable promise for development of applications and solutions across a diverse range of power system services. Ensuring these applications function as intended without causing disruptions or unexpected issues requires comprehensive testing prior to practical deployment. However, current approaches to power system digital twin (PSDT) application development and testing experience significant obstacles, including limitations and risks associated with accessing real-world power systems, models and data. This article introduces a virtual testbed based on the concept of a virtual physical twin (VPT), that replaces the need for access to a physical twin (PT), as a platform designed to remove the heavy reliance on online data flows and provide a close to real-world environment. A testbed enables simultaneous development and testing of DTs and their related applications in a realistic, interactive, and safe setting without impact on the operation of the actual power system. A complete workflow for PSDT testbed implementations is proposed, with all necessary steps from concept to the eventual connection to the physical system. To validate the practical implementation steps, utility, and value of the testbed, a real-time transient stability analysis with two artificial intelligence algorithms is provided. The proposed testbed is expandable and adaptable, promoting the development of advanced and intelligent PSDTs. The key benefit of the testbed is that it enables the development of DT and its application closely in a realistic environment without affecting the operation of PT.

Performance Improvement of Predictive Voltage Control for Interlinking Converters of Integrated Microgrid

Voltage quality in Renewable Energy System may be harmed by varying power demand and fluctuating energy source outputs. The model predictive voltage (MPV) control approach is suggested in this study. The proposed control strategy enables appropriate power interactions between the AC and DC subgrids while sharing power fluctuations in a coordinated way. Both the AC and DC subgrids support each other in accordance with their normalized relative changes in AC frequency and DC voltage, respectively. A typical photovoltaic (PV) wind-battery-based hybrid AC/DC microgrid is modelled and investigated, and the usefulness of the proposed scheme is validated under the renewable energy variations and load perturbations. MATLAB/Simulink has validated the efficacy of the suggested strategy. A set of comparative tests was conducted between conventional Proportional-Integral (PI) control, Sliding Mode Control (SMC) strategies, and a novel Model Predictive Voltage Control (MPV) approach under diverse conditions. The aim was to comprehensively assess the advantages of the proposed MPV method. Results demonstrate that, in contrast to traditional PI and SMC control strategies, the MPV technique exhibits distinct benefits in terms of superior control performance and achieves exceptionally low Total Harmonic Distortion (THD) values. Ultimately, the proposed solution not only raises the performance standard but also ensures the stable operation of the Renewable Energy System (RES).

Experimental investigation of the small-scale prototype of the dew point water recovery system

The article presents experimental investigation of the Dew Point Water Recovery (DPWR) system designed for clean water recovery using the dew point cooling phenomenon. The technology is a novel distillation process which allows for highly efficient water recovery. It is a first distillation technology which allows for water distillation through direct contact with atmospheric air. The authors designed, built, and tested an original prototype of a laboratory-scale DPWR system to verify its basic operating principles and perform performance analysis. It was shown that on average 10 × 10−6 m3 of clean water could be recovered from each cubic meter of the supply air with an average GOR of 1.9. Although the operation of the DPWR system requires electricity to drive fans, pumps and other associated equipment, the actual driving force of the system is thermal energy. The average thermal energy demand of the DPWR system was 370 kWh/m3, and more than half of this energy was based on the thermodynamic potential of the supply air. Based on experimental data, the mathematical model of the DPWR system was verified and it was found that the average relative discrepancy in predicting air temperature did not exceed 8%, and in predicting air humidity: 5%. The conducted experiments confirmed that the proposed DPWR system is feasible and has the potential to fill the technological gap in terms of a low-energy and easily accessible water recovery method.

A novel hybrid-fuzzy logic based UVC technique for solar-PV/grid integrated water-pumping system

The continual depletion of fossil fuels and increased green-house emissions are persuading the consumers to install micro-renewable energy sources-based water pumping system. Among numerous energy sources, the solar-PV plays a significant role in water pumping application due to its virtuous, environment friendly, noise-free and abundant nature, so on. Along with solar-PV, the grid integrated system enables the continuous operation of water pumping system during varying temperature and irradiance conditions, and also delivers available solar-PV energy to grid during non-functional of pumping system. The above operations are carried by using bidirectional inverter which is controlled by using unit-vector control (UVC) technique. It consists of proportional-integral controller, which is not suited for regulation of DC-link voltage at desired level because of improper selection of gain values. In this work, an intelligent hybrid-fuzzy logic based UVC technique evidences the intelligent knowledge base for better regulation of DC-link voltage and power-flow of bidirectional inverter. The performance and operation of proposed hybrid-fuzzy logic control UVC technique for solar-PV/Grid integrated water-pumping system is evaluated under various operating cases by using MATLAB/Simulink tool; simulated results are conferred with superlative comparisons.

Voltage stability index: a review based on analytical method, formulation and comparison in renewable dominated power system

In an interconnected complex power system network voltage stability evaluation is indispensable to guarantee secure power system operation. To further increase the system performance and to make the system safer assessment, the voltage stability improvement is obligatory. In the various literature different voltage security assessment method using the voltage stability index has been presented. Different lists proposed in literature can be utilized to realize the weak buses and weak transmission lines to enacting the countermeasures against issues of voltage insecurity. Additionally, the arrangement and measuring of inexhaustible assets, on the web and disconnected observing of force framework and the measure of load to be shed at whatever point essential. This paper shows a survey on the different voltage stability index from various perspectives. The audit results on various record gives a far and wide logical to perceive the impending works in this field and to choose the best index for variety of applications such as voltage security assessment, renewable energy integration, distributed generation (DG) placement and sizing, online monitoring of the power system, and shedding of load.

A Multi-Satellite Space Environment Risk Prediction and Real-Time Warning System for Satellite Safety Management

In response to the need for a space security situation assessment during orbit, the multi-satellite space environmental risk prediction and early warning system is based on the detection results of the space weather payload of the Fengyun 4A and 4B satellites, as well as the prediction results of the National Space Weather Center, for the first time. By comprehensively utilizing some open-source data, it is the first time that we have achieved a 24 h advanced prediction of the space environment high-energy proton, low-energy particle, and high-energy electron risks for the safety of the Fengyun-series high-orbit satellites, and a real-time warning of satellite single-event upset, surface charging, and deep charging risks. The automation system has preliminarily achieved an intelligent space risk assessment for the safety of multiple stationary meteorological satellites, effectively improving the application efficiency of the space environmental data and the products of Fengyun-series satellites. The business status is stable in operation, and the resulting error between the predicted results of various risk indices and the measured data was less than one level. The warning accuracy was better than 90%. This article uses the system for the first time, to use Fengyun satellite data to, accurately and in a timely manner, predict and warn us about the low-energy particles and surface charging high-risk levels of the Fengyun 4A and 4B satellites during the typical space weather event on 21 April 2023, in response to the impact of complex spatial environmental factors on the safety of Fengyun-series high-orbit satellites. The construction and operation of a multi-satellite space environmental risk prediction and early warning system can provide a reference for the safety work of subsequent satellite ground system operations.

Optimal operation of flexible interconnected distribution grids based on improved virtual synchronous control techniques

With distributed energy sources connected to the distribution grid on a large scale for distributed photovoltaic power randomness, this paper proposes a flexible interconnection system optimization operation strategy. First, the virtual synchronous control technology is improved to improve the DC bus voltage stability; second, it analyzes the system operation mode to judge the output logic of PV and storage units, takes DC bus power balance as the underlying logic, and puts forward the power coordination optimization strategy and fault power supply restoration strategy with full consideration of factors such as the load balance degree of the distribution station area, the economic operation of the main transformer, and the amount of power lost in the faulty station area. It also establishes a multi-objective optimization model to obtain the power commands of each port and achieves the power flexibility mutualization of the flexible interconnected system through the accurate regulation of the soft normally open point (SNOP). Finally, a simulation model of the flexible interconnection system is built using MATLAB/Simulink to verify the effectiveness of the proposed optimization strategy.

Research and application of power equipment monitoring and fault diagnosis

Power equipment monitoring and fault diagnosis are important parts of power system operation and maintenance. By monitoring the status and performance parameters of power equipment in real time, and timely discovering and diagnosing potential fault problems, the reliability, safety and economy of the power system can be improved. At present, this research has made significant progress, but there are still some research gaps that need to be further explored and resolved. Through the research and application of power equipment monitoring and fault diagnosis, this paper aims to improve the reliability, safety and economy of power grid, reduce the risk of failure, optimize equipment operation and maintenance strategies, and improve power supply quality and user satisfaction. Condition monitoring and fault diagnosis are very important for the normal operation of the power system equipment, which can not only strengthen the fault diagnosis of the power system equipment, but also avoid the problem of large-scale paralysis caused by the failure of the power system equipment.

Air-conditioning load characteristics and grey box predicting model in subway stations

With the continuous expansion of metro, energy conservation of air-conditioning system in subway stations draws the attention of the whole world. Most of the researches are focused on improving the energy efficiency of the system, while the load characteristics of subway stations are paid little attention. The inaccurate load prediction in the designing of air-conditioning system results in redundancy and low operating efficiency. Therefore, accurately predicting the air-conditioning load is crucial for energy saving in subway stations. In this paper, an innovative three-stage subway air-conditioning load test method was proposed and implemented in nine subway stations in Qingdao. Based on the test data, the special air-conditioning load characteristics of subway stations as underground buildings were analyzed. The results showed that electrical equipment load accounted for the largest part, reaching 53.7 %, while only 42 % of the equipment power was converted into air-conditioning load. The positive role of the envelope should not be ignored, especially in the case of entrance and exit walls, which bore almost all of the fresh air load. Based on the three-stage test, a grey box model was established and the error was validated to be within 6 %. With this model, the load of air-conditioning system can be calculated by inputting passenger flow, power of electrical equipment and public area. This paper provides a reference for the design and operation of air-conditioning system in subway stations.

CONCEPT SOLUTION OF AUTONOMOUS IOT SMART HIVE AND OPTIMIZATION OF ENERGY CONSUMPTION USING ARTIFICIAL INTELLIGENCE

In this paper the authors present a conceptual solution for an autonomous smart beehive with a focus on energy efficiency; the hive's existence is based on artificial intelligence. The hive is equipped with an advanced system for monitoring the entry and exit of bees, as well as for collecting data on the weather inside and around the hive. Using an array of sensors controlled by Espressif ESP32 and Arduino Mega microcontroller boards, the hive continuously optimizes the operation of the ventilation system and other components, monitoring energy consumption and adapting to changing conditions. Special accents in the work are dedicated to the monitoring of the solar panel and, consequently, the capacity of the battery for independent power supply of the system, as well as the application of artificial intelligence to predict meteorological changes and optimize energy efficiency. This paper provides a comprehensive overview of the solutions and technologies that enable the autonomous and energy-efficient functioning of the Smart Hive.

Key issues in Japan's public health centers to prepare for future pandemics: a text mining study using a topic model.

In Japan, over 450 public health centers played a central role in the operation of the local public health system in response to the COVID-19 pandemic. This study aimed to identify key issues for improving the system for public health centers for future pandemics. We conducted a cross-sectional study using an online questionnaire. The respondents were first line workers in public health centers or local governments during the pandemic. We solicited open-ended responses concerning improvements needed for future pandemics. Issues were identified from these descriptions using morphological analysis and a topic model with KHcoder3.0. The number of topics was estimated using Perplexity as a measure, and Latent Dirichlet Allocation for meaning identification. We received open-ended responses from 784 (48.6%) of the 1,612 survey respondents, which included 111 physicians, 330 nurses, and 172 administrative staff. Morphological analysis processed these descriptions into 36,632 words. The topic model summarized them into eight issues: 1) establishment of a crisis management system, 2) division of functions among public health centers, prefectures, and medical institutions, 3) clear role distribution in public health center staff, 4) training of specialists, 5) information sharing system (information about infectious diseases and government policies), 6) response to excessive workload (support from other local governments, cooperation within public health centers, and outsourcing), 7) streamlining operations, and 8) balance with regular duties. This study identified key issues that need to be addressed to prepare Japan's public health centers for future pandemics. These findings are vital for discussions aimed at strengthening the public health system based on experiences from the COVID-19 pandemic.

ICRH operations during the JET tritium and DTE2 campaigns

The JET-ILW pure tritium and deuterium–tritium (DTE2) experimental campaigns took place in 2021–2022. Tritium (T) and deuterium–tritium (D–T) operations present challenges not encountered in present day tokamaks (Horton et al 2016 Fusion Eng. Des. 109–111 925–36). This contribution focuses on ion cyclotron resonance heating (ICRH) operations in tritium and deuterium–tritium plasmas, starting with a summary of the program of improvements to the ICRH system which spanned a few years prior to these experiments. Procedures were implemented to address specific constraints from tritium and deuterium–tritium operations (tritium safety and reduced access to the RF generator area) and increase the system reliability and power availability during plasma pulses. Operation of the upgraded real time RF power control system that maximises the launched power while taking into account limitations from the system or antenna coupling is described. We also report on the result from dedicated pulses performed to assess the potential harmful impact of the 2nd harmonic tritium resonance in the plasma, close to the inner wall, when using the standard central hydrogen minority ICRH scheme. During DTE2, the ITER-like antenna was not used because water leaked from an in-vessel capacitor into the vessel on day-2 of the experimental campaign. The lessons learnt from this incident are highlighted. Finally, the ICRH plant adjustments required to safely perform ion cyclotron wall cleaning discharges are described.

OPTIMAL LOCATION OF AN IDEAL TRANSFORMER UPFC MODEL USING OPF FIRST-ORDER SENSITIVITIES

This paper presents a screening technique for greatly reducing the computation involved in determining the optimal location of a unified power flow controller (UPFC) in a power system. The first-order sensitivities of the generation cost with respect to UPFC control parameters are derived. This technique requires running only one optimal power flow (OPF) to obtain UPFC sensitivities for all possible transmission lines. To implement a sensitivity-based screening technique for guidance in optimally locating a single UPFC in a power system, we propose a new UPFC model, wrach consists of an ideal transformer with a complex turns ratio and a variable shunt admittance. In this model, the UPFC control variables do not depend explicitly on UPFC input and output currents and voltages. Accordingly, this model does not require adding extra buses for UPFC input and output terminals. IEEE five-, 14- and 30-bus systems were used to frustrate the technique. Index Terms-Flexible ac transmission systems (FACTS), FACTS location, first-order sensitivity, optimal power flow (OPF), screening technique, unified power flow controller (UPFC), UPFC ideal transformer model, UPFC placement, UPFC uncoupled model. This study focuses on the development of an Ideal Transformer Unified Power Flow Controller (UPFC) model and its integration with Optimal Power Flow (OPF) first-order sensitivities analysis for determining optimal UPFC locations in power systems. The abstract outlines the significance of UPFCs in enhancing power system stability and efficiency by controlling voltage and power flow. It highlights the objectives of the research, including the development of the UPFC model, analysis of OPF first-order sensitivities, and their combined application for screening optimal UPFC locations. The study aims to contribute to the improvement of power system operation and control through strategic UPFC placement. The abstract provides a concise overview of the study, summarizing the key aspects of the research. It outlines the development of an ideal transformer Unified Power Flow Controller (UPFC) model, the analysis of Optimal Power Flow (OPF) first-order sensitivities, and their application in determining optimal locations for UPFC installation in power systems

Collaborative scheduling method of active-reactive power for rural distribution systems with a high proportion of renewable energy

Large-scale distributed renewable energy connected to the rural distribution network has given birth to a new rural distribution system with a high proportion of new energy typical characteristics, and the optimal scheduling of the new rural distribution system has become an important issue to ensure the safe and stable operation of the power grid. This paper proposes a method of active-reactive power collaborative optimization scheduling for rural power distribution system with a high proportion of renewable energy. Firstly, the active support capability evaluation model is established, and the active power support capability and reactive power support capability of rural power distribution system are quantitatively evaluated, which provides data basis and boundary conditions for the scheduling part. Then, considering power-loss cost, distribution network operation cost, and penalty cost, a method of active-reactive power collaborative optimization scheduling for rural power distribution systems with a high proportion of renewable energy is proposed. Finally, the active support capability evaluation and regulation platform of the rural power distribution system is built to provide technical support services for the safe and stable operation of the rural power distribution system. Given the problems of overload and overvoltage faced by rural power distribution systems with a high proportion of renewable energy, this paper aims to solve the key technical challenges of optimization and regulation of new rural power distribution systems. The results show that the optimized control method proposed in this paper has better security and economy, and is conducive to promoting the construction and operation of the new rural power distribution system.

Mindfulness networks: Analyzing associations with self‐compassion, other‐compassion, need fulfillment, and satisfaction in midlife married Canadians

AbstractInterest in mindfulness in the field of romantic relationships is growing. Drawing from a Self‐Determination Theory (SDT) perspective—which proposes that the basic psychological needs for autonomy, competence, and relatedness are foundational for well‐being—we attempted to map out the complex associations between mindfulness, self‐compassion, other‐compassion, basic need fulfillment in relationships, and increased relationship and sexual satisfaction. A sample of 640 midlife (40–59‐year‐old) married Canadians was recruited from a national panel. To test the associations at a systems‐level, we utilized psychological network analysis based on the premise that the relational and sexual effects of mindfulness are understood as part of a dynamic and multivariate network of associations with other variables. Need fulfillment in relationships (particularly relatedness needs) occupied a central position in the model, connecting mindfulness and self‐compassion with relationship satisfaction and sexual satisfaction. The findings underscored the major importance of SDT in relationships, and the overall structure of the network was consistent with growing theories of mindfulness in relationships. Future research employing longitudinal network models will aid in elucidating this system's operation over time.

Prediction Analysis of Deformation Characteristics During Construction and Operation of Tunnel Anchor Structure System in Soft Rock

Prediction Analysis of Deformation Characteristics During Construction and Operation of Tunnel Anchor Structure System in Soft Rock

Digital Twin and Simulation Analyses for Process Optimization of an Automated Guided Vehicle System

Development in industrial companies aims to digitize processes, ensure traceability and advance automation. Systems with automated guided vehicles (AGVs) can help meet these objectives. A core element of these systems is the higher-level system controller. When an AGV system is operated, some dynamic aspects appear. It is then to identify, that the previous specified rules for scheduling and routing of vehicles are not always proper and practical, which may result in waiting time of AGVs. That means the static performance requirements and the specifications based on them often lead to suboptimal results. A methodical problem-solving approach is to develop a digital twin as a reflection of reality and to carry out strategy analyses using simulation. For this purpose, a digital twin of the concerned AGV system with five vehicles and its technological environment is created using software of plant simulation. Various simulation scenarios are developed to simulate material flows by using different routing and scheduling rules and strategies. Drawing from the insights gained through the digital twin and simulation analyses, this study identifies novel scheduling and routing rules for the AGV system. These rules improve the overall efficiency and effectiveness of the system operations by easing traffic congestion, reducing transit time, and minimizing production downtime.

Insulator defect detection in transmission line based on an improved lightweight YOLOv5s algorithm

As one of the most important components on the transmission line, the insulator is prone to failure, which affects the safe operation of electrical power system. Hence, it is crucial to accurately detect the insulator defects for further maintenance in time. Recently, with the development of artificial intelligence and target detection algorithms, the insulator defect detection has received more and more attention. However, there are still existing some difficulties: insufficient samples and low detection accuracy. To improve the accuracy of insulator defect detection, this paper proposes an auto-detection method based on an improved lightweight YOLOv5s model. First, this paper introduces the basic network frame of YOLOv5s and proposes an improved algorithm by utilizing the GIoU loss function, Mish activation function, and CBAM module. Then, performs data enhancement in the insulator dataset to enhance the robustness of the model. Finally, trains and tests the improved YOLOv5s model, and compares it with traditional target detection algorithms. Compared with traditional target detection algorithms, the AP value of the proposed algorithm in detecting insulator defects can be improved by 5 %. The results demonstrate the improved algorithm proposed in this paper can effectively identify and position the insulator defects.

Optimizing power system operations: integrating FACTS and ESS through advanced algorithms

Optimizing power system operations: integrating FACTS and ESS through advanced algorithms