Electrical Load Distribution Research Articles

Energy hub management for integrated energy systems: A multi-objective optimization control strategy based on distributed output and energy conversion characteristics

To improve the comprehensive utilization efficiency of energy, a multi-objective optimization control strategy applied to the energy hub (EH) within the system is proposed to address the electrical and thermal load distribution of the integrated energy system (IES) and the low-carbon economic operation. First, a model of the electrical and thermal energy outputs is established based on the characteristics of the IES network and the multidimensional “load parameter” evolution law. Moreover, a distributed control strategy is proposed that utilizes the information interaction between neighboring EHs to accurately share the electrical and thermal loads, which reduces the communication burden of the system while avoiding overloads. Furthermore, to coordinate the optimal operation of the devices within the hub, based on the energy conversion characteristics of the EH, a multi-objective optimization model is proposed that considers low-carbon and economic aspects to realize efficient energy use. Simulation results show that the proposed strategy effectively improves the robustness of the system while realizing proportional load distribution and low-carbon economic operation. Under the same load, when focusing on system economics, the operating cost is 2.182/¥ lower than when focusing on low-carbon systems, but carbon emission is 1.6753/kg CO2 higher.

RETRACTED: Optimum operation of energy hub by considering renewable resources by considering risk tolerance and risk taking with Teaching–learning-based optimization

Amidst growing concerns over climate change, the conventional energy landscape faces critical challenges associated with fossil fuel usage. In response, this study explores alternative approaches by investigating an energy hub system leveraging wind turbine-generated power. This hub integrates seamlessly with electricity and natural gas grids, offering a comprehensive energy supply encompassing electricity, natural gas, and thermal loads. The research strategy encompasses a multi-pronged approach. A Time-of-Use (TOU) load management program optimizes the distribution of electrical and thermal loads. To address the unpredictability of wind speed, the information gap decision theory (IGDT) is introduced to manage risk and deviations effectively. The central objective involves optimizing the energy hub's operations, focusing on minimizing operational costs and emissions. To address this intricate challenge, the study employs the Teaching–Learning-Based Optimization (TLBO) method. This advanced technique concurrently optimizes cost and environmental impact, exemplifying its efficacy in the energy hub context. The research culminates in demonstrating the TLBO algorithm's swift convergence, highlighting its aptitude for addressing complex cost and emission optimization dynamics. In sum, this study offers innovative insights into sustainable energy systems, where economic and environmental considerations converge harmoniously.

An Empirical Performance Assessment of Infrared Thermography for Real-time Monitoring of Electrical Systems in the Coco Fibre Industry

The quality of the electrical network, which includes MV panels, DBs, MCBs, sub-circuits with fuse units, and electrical motors for machine tools, determines production in any sector. Most drive systems employ inductionmotors. System temperature indicates health. Excess temperature is rarely detected due to breakdown. This case study presents real-time data for a leading coir industry from each electrical circuit and motor in several machine tools. Every section is thermographed and compared to the allowed temperature range. Thermographic analysis is non-contact and uses fewer meters and instruments. A harmonic analyzer measures THD using data from the full testing period. Modern energy audits save 10–15% on energy. Suggestions include modest restructuring of electrical network load distribution, little investment in capacitor banks in each section of induction motors, and thorough analysis and corrective measures based on customer needs.

Research on electrical load distribution using an improved bacterial foraging algorithm

This paper proposes an improved bacterial foraging algorithm for electrical load distribution to impro-ve power plants’ efficiency and reduce energy consumption costs. In the chemotaxis stage, the adaptive step size is introduced to accelerate the random search speed compared with the traditional algorithm. In the replication stage, a hybrid crisscross operator is proposed to replace the traditional binary replication method in the algorithm to ensure the diversity of the population and improve the efficiency of the algorithm. The adaptive dynamic probability is used instead of the initial fixed probability to improve the global search performance of the algorithm. The mathematical model of electrical load distribution in a natural power plant is established, and the improved bacterial foraging algorithm is used to solve the model. Through comparative analysis of two power plant unit experiments, it is proved that the results of the improved algorithm can reduce 3.671% and 1.06% respectively compared with the particle swarm optimization algorithm, and 7.26% and 1.37% respectively compared with the traditional bacterial foraging algorithm, which can significantly reduce the coal consumption of the power plant.

Optimal Load Distribution of CHP Based on Combined Deep Learning and Genetic Algorithm

In an effort to address the load adjustment time in the thermal and electrical load distribution of thermal power plant units, we propose an optimal load distribution method based on load prediction among multiple units in thermal power plants. The proposed method utilizes optimization by attention to fine-tune a deep convolutional long-short-term memory network (CNN-LSTM-A) model for accurately predicting the heat supply load of two 30 MW extraction back pressure units. First, the inherent relationship between the heat supply load and thermal power plant unit parameters is qualitatively analyzed, and the influencing factors of the power load are screened based on a data-driven analysis. Then, a mathematical model for load distribution optimization is established by analyzing and fitting the unit’s energy consumption characteristic curves on the boiler and turbine sides. Subsequently, by using a randomly chosen operating point as an example, a genetic algorithm is used to optimize the distribution of thermal and electrical loads among the units. The results showed that the combined deep learning model has a high prediction accuracy, with a mean absolute percentage error (MAPE) of less than 1.3%. By predicting heat supply load variations, the preparedness for load adjustments is done in advance. At the same time, this helps reduce the real-time load adjustment response time while enhancing the unit load’s overall competitiveness. After that, the genetic algorithm optimizes the load distribution, and the overall steam consumption rate from power generation on the turbine side is reduced by 0.488 t/MWh. Consequently, the coal consumption rate of steam generation on the boiler side decreases by 0.197 kg (coal)/t (steam). These described changes can greatly increase the power plant’s revenue by CNY 6.2673 million per year. The thermal power plant used in this case study is in Zhejiang Province, China.

Modeling of static reliability assessment in dielectric elastomer transducers subject to electric loads

In recent years, Dielectric Elastomer Transducers (DETs) have been of top-notch interest as an alternative solution to conventional mechatronic transduction systems, thanks to their features as low-cost and affordable materials, silence operation, low-power consumption, and high level of energy density. Generally, in their most uncomplicated layout, these devices form an electrostatic system, composed of a Dielectric Elastomer (DE) membrane, embedded between two opposite compliant electrodes, constituting a highly deformable capacitor capable of transforming electrical energy into mechanical and vice versa. However, DETs applicability is strongly affected by several engineering constraints. One of their principal failure modes is related to the electrical breakdown of the DE membrane, which occurs when an applied input electrical load exceeds the dielectric strength of the DE. In order to address this problem, the materials and the input load conditions must be chosen appropriately to assure a desired lifetime of operation. For this purpose, this work proposes a preliminary static reliability assessment procedure to evaluate the failure probability of a DET for static events as the electrical breakdown, with specific electric input load conditions. The resulting reliability model comprises the stochastic comparison of the dielectric strength of the DE material with the extreme values distribution of electrical loads in a specific period, aiming to forecast the reliability evaluation for a more extended period, multiple of the original one.

Features of the Multi-Criteria Optimization Mathematical Model of the Thermal and Electrical Loads Distribution at a Combined Heat and Power Plant with a Mixed Equipment Composition

The features of the mathematical model of multi-criteria optimization of the distribution of current thermal and electrical loads at a combined heat and power plant with a mixed composition of equipment based on traditional heating units and a heating CCGT are considered. The previously proposed mathematical apparatus for solving the problem of multi-criteria optimization at a thermal power plant is analyzed. It is shown that with a mixed composition of equipment, along with the criteria of efficiency and environmental friendliness, it is also necessary to take into account the factors of reliability and mobility (maneuverability). The substantiation of the choice of reliability and mobility criteria for optimizing the operation modes of a thermal power plant is given. Approaches to solving the multi-criteria task are considered. The description of the features of the algorithm for solving the optimization problem is given in relation to thermal power plants with a mixed composition of equipment, including heating turbines of the T type and PGU.

Economic Dispatch of CHP Units through District Heating Network’s Demand-Side Management

Optimisation of heat and electrical load distribution, where the objective function is the maximum efficiency of the CHP unit for a given load range, can be done considering the limitations of electrical power and the heat load. Simulating a real CHP unit with a district heating network shows that demand-side management can improve the overall economic efficiency of the CHP plant and increase the unit’s operating range in the electricity spot market. Economic dispatch makes it possible to determine a reasonable additional increase in the electric power of the CHP unit, and to optimise the supply temperature and mass flow of the district heating network. The results obtained and the analysis performed indicate that the proposed methodology provides logical results and can be used to calculate the efficiency indicators of the cogeneration of electrical and thermal energy. The problem of optimising the operating mode of the CHP unit was solved, which allows us to determine the optimal additional increase in the unit’s electrical load at a given heat load of consumers, which on average increases the CHP unit’s efficiency up to an additional 1.5%.

Optimization of Fuel Cost in Electric Power Systems using Harmony Search Algorithm

Fuel Cost Optimization emerges as an important issue in electrical load distribution systems. In this study, the performance of Harmony Search Algorithm, which has a significant place in the literature, has been observed for a sample problem in the field of fuel cost optimization. It is aimed to distribute the load provided by a three-unit power plant with minimum cost. Three restricted functions are defined in order to calculate the energy production cost per hour of three thermal power plants. For this reason, the problem has been solved by using equal weighted scalarization, one of the multi-objective optimization techniques and static penalty function with Harmony Search Algorithm. The obtained results are presented in comparison with the Lagrange solution and Artificial Bee Colony Algorithm, which were used to solve the same problem.

ВИЗУАЛИЗАЦИЯ ГЕОДАННЫХ СЕЗОННЫХ КОЛЕБАНИЙ МАГНИТНЫХ ПОЛЕЙ НА БАЗЕ ESRI ARCGIS

Energy objects, installations of high and ultra-high voltage, are considered man-made, dangerous objects in terms of the intensity of the electric and magnetic field distribution, which create ion shells in high-altitude zones and spread a certain radius on the territory of a residential area. In this regard, during the construction and commissioning of low-frequency power facilities, it is necessary to conduct a specific environmental analysis on the selected territory. One of the main sanitary and epidemiological requirements for the construction and commissioning of high – voltage power lines is to take into account changes in the daily and seasonal distribution of electrical loads along high-voltage power lines, which have a continuous dynamic characteristic that increases the level of electric and magnetic field strength. In turn, the development of information support for environmental problems of the territory based on GIS technologies makes it possible to record information about the ecological state of the territory at a specific time and present this state with a set of thematic environmental maps of various territorial or district entities. It should be noted that the above characteristics increase the advantage of geoinformation technologies as an information platform of the database, which will make it possible to obtain data for processing operational analyses and conclusions about the state of the environment around high-voltage power lines.

Electrical load distribution forecasting utilizing support vector model (SVM)

The significance of electrical load forecasting on the electrical distribution network has become eminent with the entry of energy sector and electrical market. This paper of research comprehends a model for forecasting the electrical load distribution. This paper highlights the forecasting on the electrical distribution system by taking into account the load ambiguities. Support Vector Machine (SVM), which is a machine learning algorithm is the prediction or forecasting model utilized in the proposed paper for forecasting the electrical load distribution. The ambiguities that impact the electrical load distribution are; cooling loads, indoor heat gains and cooling parameters are taken into account during the prediction. The demand for electrical load is impacted by many factors starting from the climatic conditions to the economic-socio influences. The proposed load prediction model is reliable, beneficial and an enhancing model for the conservation of electrical energy in the distribution network.

ELECTRICAL LOAD RELIABILITY ASSESSMENT USING ANALYTICAL METHOD, CASE STUDY: FUPRE 1 X 2.5MVA INJECTION SUBSTATION

This research work presents the reliability assessment of electrical load distribution system in Federal University of Petroleum Resources, Effurun (FUPRE), Warri using the Analytical method and ETAP software as the simulation tool to run the reliability assessment of the System. The analytical analysis was conceded out by using August 2018 – August 2019 historical data of Tetfund Classrooms Blocks, Hostels, College of Technology, Administration Block, Health Center, and College of Science Feeder obtained from the Benin Electricity Distribution Company [BEDC]. The results conceded revealed that College of Technology Injection Substation is the most reliable in the distribution network when compared to the other five substations around the institution premises as it recorded system indices of ASAI: 99.30, SAIFI: 1.10, SAIDI: 55.35, CAIDI: 123.04 in August 2018 to August 2019. Nevertheless, the total reliability indices of the six substations under investigation as obtained from the analysis, and it shows that availability of power to FUPRE distribution is very poor as compared with the benchmark of IEEE ASAI of 99.99 for distribution substation availability.

Smart Electric Grids Three-Phase Automatic Load Balancing Applications using Genetic Algorithms

Smart power grid is going to be the future grid. Conventional, renewable and alternate sources incorporating for power generation[1]. Smart Electrical Grids require nowadays a large interest in the electrical load distribution balancing problem. This problem is a well known for not having an optimal solution for large-scale systems, where the number of single phase consumers connected to three phase systems increases especially in very large-scale electrical distribution systems. This paper presents a new control technique for an automatic circuit phase change as well as an optimisation approach using Genetic Algorithms (GA) used to enhance the solution of electrical load distribution balancing problem. In the first part of the paper, the system under study is introduced, as well as the various solutions adopted. In the second part of the paper, a GA formulation and implementation of the solution is presented. The efficiency of the GA solution is also discussed.

A distributed EV charging strategy in an integrated energy system

Electric vehicles (EV) are viewed as an environmental-friendly travel device but bring the driver with range anxiety. One of the solutions to tackle this issue is to recharge at the fast charging station (FCS). Since the traffic flow of the transportation network and the operation condition of the fast charging station varies from time to time, it is important to implement real-time charging guiding for the EV drivers. In this paper, we propose a distributed guiding method to search for the best FCS with minimum sum of time cost and electricity purchasing cost. The EVs are viewed as a distribution of spatial and temporal electrical loads, which would affect the locational marginal price (LMP) of the FCS. The varied LMPs would also react upon the EV driver’s choice. The proposed guiding method utilizes the wireless communication technologies. Simulation test demonstrates the effectiveness of the proposed EV guiding method in an integrated energy system.

Electrical Design For Helium Purification and Supply System of RDE

The Experimental Power Reactor (RDE) is designed based on High Temperature Gas Cooled Reactor (HTGR) technology which uses helium gas as a coolant. Helium gas is suitable as a coolant for heat transfer in reactors with very high temperatures considering the characteristics of helium gas as an ideal gas / inert gas, unchanged in physical or chemical properties at very high relative temperatures, unreacted with gases / other substances. The sustainability of the helium supply should be maintained so that the reactor primary coolant system pressure remains stable. Hence the design of Electrical for Helium Purification and Supply System - RDE (HPS-RDE) should be developed. The purpose of this study was to develop a detailed RDE design in terms of optimal primary cooling design. The research method is separated into 3 steps, that is designing electrical system at HPS-RDE with component simulation, electrical load distribution analysis and electrical component specification on HPS-RDE system using ETAP software. The final result of this research is the result of analysis and layout of electric load distribution and electrical component specification in HPS-RDE.

GaN-Based Laser Wireless Power Transfer System.

The aim of this work is to present a potential application of gallium nitride-based optoelectronic devices. By using a laser diode and a photodetector, we designed and demonstrated a free-space compact and lightweight wireless power transfer system, whose efficiency is limited by the efficiency of the receiver. We analyzed the effect of the electrical load, temperature, partial absorption and optical excitation distribution on the efficiency, by identifying heating and band-filling as the most impactful processes. By comparing the final demonstrator with a commercial RF-based Qi system, we conclude that the efficiency is still low at close range, but is promising in medium to long range applications. Efficiency may not be a limiting factor, since this concept can enable entirely new possibilities and designs, especially relevant for space applications.

Nearshore regional behavior of lightning interaction with wind turbines

The severity of lightning strikes on offshore wind turbines built along coastal and nearshore regions can pose safety concerns that are often overlooked. In this research study the behavior of electrical discharges for wind turbines that might be located in the nearshore regions along the East Coast of China and Sea of Japan were characterized using a physics-based model that accounted for a total of eleven different geometrical and lightning parameters. Utilizing the electrical potential field predicted using this model it was then possible to estimate the frequency of lightning strikes and the distribution of electrical loads utilizing established semi-empirical relationships and available data. The total number of annual lightning strikes on an offshore wind turbine was found to vary with hub elevation, extent of cloud cover, season and geographical location. The annual lightning strike rate on a wind turbine along the nearshore region on the Sea of Japan during the winter season was shown to be moderately larger compared to the lightning strike frequency on a turbine structure on the East Coast of China. Short duration electrical discharges, represented using marginal probability functions, were found to vary with season and geographical location, exhibiting trends consistent with the distribution of the electrical peak current. It was demonstrated that electrical discharges of moderately long duration typically occur in the winter months on the East Coast of China and the summer season along the Sea of Japan. In contrast, severe electrical discharges are typical of summer thunderstorms on the East Coast of China and winter frontal storm systems along the West Coast of Japan. The electrical charge and specific energy dissipated during lightning discharges on an offshore wind turbine was found to vary stochastically, with severe electrical discharges corresponding to large electrical currents of long duration.

Improving the efficiency of steam-turbine plants of different capacities

Important scientific and technical problem of increasing operational efficiency of steam-turbine plants by developing new technologies for solving problems of efficient distribution of thermal and electrical loads between turbines and network heaters of cogeneration turbines during the heating period is solved in the paper. The scientific principles and methods for solving problems of both the analysis of power plant states, and their synthesis (optimization), taking into account a large number of factors, affecting the indicators of thermal circuit elements in their interaction, thus providing modeling of energy systems of different configurations with the ability to include new elements are developed. Additional modules of mathematical model and software-computer complex for calculating thermal circuits to implement energy-saving measures are developed and introduced. Formulation and solution of the problem of determining rational operation modes of thermal circuits of low-capacity steam-turbine plants (confirmed by implementation acts) is first performed. For power units of industrial enterprises, expediency of building steam-turbine plants up the power steam boilers (confirmed by implementation acts) is shown. The optimum modes of heat output from cogeneration turbines T-100/120-130 and T-250/300-240 (confirmed by implementation acts) are determined. The obtained results have shown the feasibility of solving the energy-saving optimization problems through generating additional electric power from CHP turbine plants. To solve this problem, new methods, which allow to propose measures on saving fuel and energy resources without additional capital investment, are used.

Coupled field finite element analysis of pin-and-cap disk type insulator assembly

Extensive research has been done throughout the world on the performance of outdoor insulators and insulator assembly, in the area of structural, thermal and electrical analysis. These effects, i.e., structural, thermal and electric have been studied on individual basis only. That is only one effect is considered, however in the real field these effects should be considered simultaneously for the complete analysis of insulator and insulator assembly since these three effects are present at the same time. In this paper, coupled field structural-thermal-electrical finite element simulations are carried out by using a commercially available software package, which allow quantifying the effects of insulator assembly on when structural, thermal and electrical load distribution are considered simultaneously. The structural, thermal and electrical results are obtained for a single 11 kV cap-and-pin type ceramic disc type insulator assembly are analysed and presented. It is observed that under normal working conditions of an insulator assembly the structural, thermal and electrical loads are found mutually coupled, but not going to affect the structural, thermal and electrical characteristics of an insulator assembly and its components.

Simulation of Structural, Thermal and Electrical Load for High Voltage Ceramic Cap and Pin Disc Insulator Assembly

This paper studies mechanical- stress-strain, thermal- temperature distribution, electrical potential and electric field distribution for 11 kV, single ceramic cap and pin disc insulator assembly used for high voltage transmission and distribution systems. The coupled field finite element computer simulation is carried out by using a commercially available software package, which allows quantifying the effects of insulator assembly on where structural, thermal and electrical load distribution considered simultaneously. The simulation result shows stress concentration due to application of structural, thermal, and electrical load. The stress was maximum on pin and moderate on sealing material and disc. Similarly in electrical analysis, nodal electrical potential and electrical field distribution observed decreasing from bottom pin of insulator assembly to top cup end of insulator model. Remarkable stresses, temperature, electrical potential and electrical field rise was not observed at porcelain but mainly observed in critical areas like triple junction (pin-porcelain, porcelain-cup junction of insulator assembly), despite high tension, high temperature of conductor and high voltage-current. With continuous use of an insulator and varying environmental condition, this high tension, temperature and high voltage may cause small crack in sealing material and the insulator disc material. This may reduce performance or cause failure of an insulator without any prior notice.