Electric Power Resources Research Articles

Optimized operation strategy for energy storage charging piles based on multi-strategy hybrid improved Harris hawk algorithm

In response to the issues arising from the disordered charging and discharging behavior of electric vehicle energy storage Charging piles, as well as the dynamic characteristics of electric vehicles, we have developed an ordered charging and discharging optimization scheduling strategy for energy storage Charging piles considering time-of-use electricity prices. The decision variables include the charging and discharging prices, states, and power of electric vehicles. We have constructed a mathematical model for electric vehicle charging and discharging scheduling with the optimization objectives of minimizing the charging and discharging costs of electric vehicles and maximizing the revenue of Charging piles. To address the challenges of multivariable, multi-objective, and high-dimensional optimization in the proposed model, we propose a Multi-strategy Hybrid Improved Harris Hawk Algorithm (MHIHHO). In addition, to validate the optimization performance of the proposed algorithm, CEC benchmark test functions are employed to assess the algorithm's optimization accuracy, convergence speed, stability, and significance. Finally, optimization-based scheduling simulations are performed considering power constraints for energy storage charging and discharging at different time intervals, as well as discharge loads. The proposed method reduces the peak-to-valley ratio of typical loads by 52.8 % compared to the original algorithm, effectively allocates charging piles to store electric power resources during off-peak periods, reduces user charging costs by 16.83 %–26.3 %, and increases Charging pile revenue.

Demand and Forecast Analysis of Power New Energy under the Background of Carbon Peak Reachin

Electric power resources is directly related to the national development and social people’s livelihood of the energy industry, is to support the future economic transformation and improve the residents living standards of rigid demand, however, the power industry is the highest carbon dioxide emissions in China, the power industry accounts for the energy industry of carbon dioxide emissions more than 40%. Under the background of the increasing demand for power resources in the current social development, the carbon dioxide emissions of the power industry are directly related to whether China can achieve the goal of reaching the national carbon emission peak by 2030. The article will summarize the driving factors of carbon emission reduction in the power industry through scenario analysis, combining the social electricity demand, power structure adjustment and the coal consumption of power generation standards, and improve the new energy generation technologies such as offshore wind power and hydropower to achieve the carbon emission of the power industry to reach the carbon peak standard. The article mainly achieves carbon emission reduction in the power industry through offshore wind power and distributed photovoltaic technologies, optimizes the power supply structure, and achieves the carbon peak target by 2030.

Research on the Operation Optimization of Aggregate Resources under the Dual Factors of Power Grid and Economy

Under the influence of power grid and economy, the operation optimization of aggregate resources has high practical value and significance. For the problems of the existing aggregate resource operation optimization methods, this paper presents a completely new optimization method, considering the economic factors of power output, grid line transmission, grid stability, transformer capacity, energy storage charging and discharge loss, grid transmission loss, transformer loss and production arrangement of adjustable resource aggregate, and combined with the idea of electric power translation in the operation of the load device. By adopting a mixed-integer linear programming model (Mixed-Integer Linear Programming, MILP), the operation optimization problem of the aggregate resource is transformed into a mathematical planning problem to be solved, which effectively avoids the start-stop delay of the load device, and shortens the time taken to adjust power supply and demand, reduces the construction cost and operation and maintenance cost of the aggregate, and realizes the optimal allocation of electric power resources, improves the sustainable energy utilization rate and the stability of the power system, and provides a new direction for the continuous development and progress of the power system.

Research on Reliability of Distribution Network Power Engineering Technology

With the progress of society, electric power resources have become an indispensable part of people's production and life. The power system composed of four parts, namely, power plant, transmission network, distribution network and users, is an important part of China's power grid, supporting the transmission and use functions of China's power grid. Therefore, ensuring the stable and continuous operation of the power system helps to build a strong transmission network in China, improve the transmission efficiency and efficiency of the power grid, and further improve the maturity of the power engineering technology of the distribution network. Therefore, this paper studies the reliability of distribution network power engineering technology.

Regulation of the Concept of "Electric Energy Power" in Acts of International Law and Decisions of International Judicial Instances

The subject of the study is the peculiarities of the regulation of the legal category "electric energy (power)" in international acts (regulatory and judicial). The object of the study is recognized as the international foundations of the legal regulation of the concept of "electric energy (power)", reflected in the sources of international law and in the decisions of international judicial bodies. The purpose of the scientific article is to substantiate the need to unify the norms of international law with a reflection of the generally recognized position regarding the concept of "electric energy (power)" and the formation of the author's vision of the definition of this term.The author examines in detail the positions regarding the understanding of this term in international acts of various international organizations and judicial instances, emphasizes the importance of international unification in this direction, expresses the author's position on the meaning of the dynamically developing spheres of activity and economy of each modern state. Each State is called upon not only to provide its citizens and their collective entities with electric power resources on a safe and uninterrupted basis, but also to implement these functions in international relations regulated by acts of international law. The importance of the unification of the concept of "electric energy (power)" as a tool for the approximation of the legislation of individual countries aimed at fst)" in the acts of international law is designed to ensure both energy security and the identity of national legal regulation by including in the sources of law to the maximum extent textually and essentially similar from a legal point of view categories and their definitions. A special contribution of the author is to conduct a detailed analysis of numerous acts of international law (normative, judicial), which include in their content the concept of "electric energy (power)", the characteristics of various positions, carrying out their comparative characteristics. The novelty of the research is reflected in the formation of an opinion regarding the understanding of the legal category "electric energy (power)", its reflection in the author's definition.

MPoW: How to Make Proof of Work Meaningful

Proof of Work (PoW), which is a consensus algorithm for blockchain, entails a large number of meaningless hash calculations and wastage of electric power and computational resources. In 2021, it is estimated that the PoW of Bitcoin consumes as much electricity as Pakistan's annual power consumption (91TWh). This is a serious problem against sustainable development goals. To solve this problem, this study proposes Meaningful-PoW (mPoW), which involves a meaningful calculation, namely the application of a genetic algorithm (GA) to PoW. Specifically, by using the intermediate values that are periodically generated through GA calculations as an input to the Hashcash used in Bitcoin, it is possible to make this scheme a meaningful calculation (GA optimization problem) while maintaining the properties required for PoW. Furthermore, by applying a device-binding technology, mPoW can be ASIC resistant without the requirement of a large memory. Thus, we show that mPoW can reduce the excessive consumption of both power and computational resources.

Machine learning predictive model for electronic slurries for smart grids

Electricity is a fundamental energy that is essential to the growth of industrialization and human livelihood. Electric power resources can be used to meet living and production needs more steadily, effectively, and intelligently with the help of an intelligent power grid. The accuracy and stability of component requirements have increased due to the rapid growth of intelligent power networks. One of the fundamental components for component production is electronic slurry, so optimizing electronic paste’s properties is crucial for smart grids. In the field of materials science, the process of discovering new materials is drawn out and chance-based. The traditional computation process takes a very long time. Scientists have recently applied machine learning techniques to anticipate material properties and hasten the creation of novel materials. These techniques have proven to offer amazing benefits in a variety of fields. Machine learning techniques, such as the cross-validated nuclear ridge regression algorithm to predict double perovskite structure materials and the machine learning algorithm to predict the band gap value of chalcopyrite structure materials, have demonstrated excellent performance in predicting the band gap value of some specific material structures. The performance value of other structural materials cannot be predicted directly by this targeted prediction model; it can only forecast the band gap value of a single structural material. This study presents two model techniques for dividing data sets into element kinds using regression models and dividing data sets into clusters using regression models, both of which are based on the fundamental theory of physical properties, band gap theory. This plan is more efficient than the classification-regression model. The MAE dropped by 0.0455, the MSE dropped by 0.0425, and the R2 rose by 0.022. The effectiveness of machine learning in forecasting the material band gap value has increased, and the model trained by this design strategy to predict the material band gap value is more reliable than previously.

Research on Power Material Demand Forecasting Strategy Based on Prophet Algorithm

The rapid economic growth has promoted the development of China’s electric power industry, which has gradually expanded the demand scale of electric power materials. Only by accurately forecasting the demand situation of electric power resources can the electric power field develop in a better direction. Based on this, this paper expounds the current situation of power material demand forecasting, then introduces the basic introduction of Prophet algorithm, and then puts forward the power material demand forecasting strategy based on Prophet algorithm, and verifies the application effect of this forecasting strategy through experimental analysis. Through the experimental analysis, it can be seen that the prediction strategy can get very accurate results, and has high practicability, so it can be applied to practical work.

Experimental Investigation of Bladeless Power Generator from Wind-induced Vibration

The power harvester unit from flow-induced vibration (FIV) was designed to harness energy from low flow velocity based on the magnetostrictive effect on the galfenol (Fe – Ga alloy) strip induced by the oscillating bluff body. This study aimed to investigate the cross-section variation’s effect on the FIV characteristics and the magnetostrictive material’s performance for the bladeless power generator. The generator model’s vibration characteristics and performance tests were conducted in the wind tunnel test using the wind-receiving unit (WRU) variation. The results showed that the resonance reduced-velocity (Vr) were around 3.7 and 4.0 for rectangular and circular cylinders, respectively. Furthermore, the effect of rectangular depth variation on the power generation output is linear to the test models’ displacement rate and vibration frequency. The harvester’s maximum power generation was 5.25 mW, achieved using the rectangular prism with depth D = 0.4H. The power coefficient was also evaluated for different wind-receiving models. The harvester model lit up 54 LED lamps in the wind tunnel test. The voltage output is sufficient to provide electric power resources for an IoT system, sensor, and wearable or wireless devices. The harvester model successfully generated a voltage signal under the initial field test with an ambient wind velocity of 0.9 – 2.71 m/s. Therefore, this study recommends the development of bladeless power generators in the future.

Multi-Technology Driven R&D Cost Improvement Scheme and Application Utility of EESP in Energy-Intensive Manufacturing Industry

Facing the sustainable use of electric power resources, many countries in the world focus on the R&D investment and application of electrochemical energy storage projects (i.e., EESP). However, the high R&D cost of EESP has been hindering large-scale industrial promotion in the energy-intensive manufacturing industry represented by the tobacco industry. Reducing and controlling the R&D cost has become an urgent problem to be solved. In this context, this paper innovatively proposes a multi-technology driven R&D cost improvement scheme, which integrates WBS (i.e., Work Breakdown Structure), EVM (i.e., Earned Value Method), BD (i.e., Big Data), and ML (i.e., Machine Learning) methods. Especially, the influence of R&D cost improvement on EESP application performance is discussed through mathematical model analysis. The research indicates that reducing EESP R&D costs can significantly improve the stability of EESP power supply, and ultimately improve the application value of EESP in energy-intensive manufacturing industries. The R&D cost management scheme and technical method proposed in this paper have important theoretical guiding values and practical significance for accelerating the large-scale application of EESP.

Evaluating the cost-effectiveness of the «SMART MONITORING» system for the equipment of Russian railways infrastructure facilities

The article proposes economic justification of application of SMART MONITORING system for surveillance of equipment of Russian Railways (RZhD) infrastructure facilities. The paper analyzes the costs of electricity in the operation of heat curtains and equipment with high-energy consumption. SMART MONITORING system allows to perform digital transformation of signals from analog sensors of temperature, humidity and other climatic parameters, to accumulate, systematize and present in a convenient form for further processing. The article illustrates possible applications of the system for monitoring and analyzing the operation of various groups of equipment providing the life cycle of buildings and structures of Russian Railways. Thearticle shows the ratio of costs for the creation of the system SMART MONITORING and the resulting savings in resources. Application of SMART MONITORING system will give an opportunity to save electric power and labor resources. The system allows to get the detailed analytics of electric power expenses, due to which it is possible to make the mode of operation of electric equipment optimal and has the functionality, which allows to calculate different parameters. The authors conclude that this surveillance system will significantly improve the efficiency of electrical equipment, using modern industry approaches to solve the problems of its operation, namely IoT technologies and cloud storage and data processing technologies.

Impact of spatial misallocation of electric power resources on economic efficiency and carbon emissions in China.

The relationship between resource misallocation and productivity has become a hot topic in recent years, but few studies examined the impact of spatial misallocation of electric power resources (SMEPRs) on economic efficiency and carbon emissions. Here, we constructed a calculation model of SMEPRs that can measure both the misallocation degree and direction and uncovered the spatiotemporal evolvement mechanism of SMEPRs. On this basis, we explored the impact of SMEPRs on regional economic efficiency and carbon emissions using panel data from 29 provinces in China from 1988 to 2017. The results demonstrate that the high level of SMEPRs in China shows complex spatiotemporal characteristics and significantly affects the regional economic efficiency and carbon emissions. Specifically speaking, first, SMEPRs present the characteristics of the coexistence of excessive and insufficient allocation among provinces and regions, the increasing extent of misallocation in the eastern and western regions, and the gradual decline in the central region; second, SMEPRs have a strong negative effect on the regional economic efficiency and carbon emissions by affecting regional industrial structures, which indicates that SMEPRs are an important factor restricting the high-quality development of regional economies. The research is conducive to the development of resource misallocation theory. Moreover, the research observations offer fresh insights to upgrading the high-quality and green development of China's power sector and promoting regional economic transformation and ecological sustainability.

Research on High Voltage Cable Condition Detection Technology based on Wireless Sensor Network

The development and progress of modern society cannot be achieved without the support of electric power resources, and at present, electric power is the most important energy source to promote social development and maintain human life. As a key unit under the power distribution and transmission system, the high-voltage cable of the power grid will undertake the task of supplying power resources to the whole power grid. Therefore, based on the transmission line fault diagnosis framework of Wireless Sensor Networks (WSN), a high-voltage cable path condition monitoring scheme using LoRa technology is proposed. Three high-voltage cable condition monitoring periods are proposed according to the difference of high-voltage cable fault rate, and the delay and energy consumption of the high-voltage cable monitoring system are optimized by multi-objective particle swarm algorithm reality. The experimental results show that the proposed high-voltage cable detection technology can switch the working mode according to different environments, and the data communication packet loss rate is less than 5%, while the detection platform has excellent delay performance and energy saving effect. The high-voltage cable status detection solution can effectively solve the problem of blind high-voltage cable channels in high mountain areas of China. The research content has important reference value for the detection of China’s power grid circuit system.

Laser-irradiated graphene-polymer contact electrification as a sustainable power source in metal-free triboelectric nanogenerator

Triboelectric nanogenerators (TeNGs) show exceptional promise for converting wasted mechanical energy into electrical energy. The present study briefly demonstrates the use of highly conducting laser-irradiated graphene (LIG) film as a current collector in an exciting class of metal-free TeNGs. The LIG film with fused structure was developed via a two-step method- electrochemical deposition followed by laser-irradiation method. The encapsulation of polymers like PVA and PEO via spin coating process on the fused structure of LIG film provides a composite matrix with higher conductivity associated with LIG and the triboelectric effects generated from polymers as well as from the carbon source. The structural and the surface properties of the polymer-coated LIG film were examined by XRD, Raman, FT-IR and drop size analyzer techniques. As a result, the resulting sandwich-type metal-free TeNGs deliver an open-circuit voltage (VOC) of 10 V and a maximum short circuit current (ISC) of 10 μA over a very small scale TeNGs (1.5 × 1.5) cm2. The LIG-Polymer TeNG device is influenced by the electrostatic induction mechanism and provides a new avenue for multifunctional electric power resources.

Spatial and temporal characteristics of China’s water footprint of energy and its matching relationship with water resources

Energy and water resources are very important for human survival and social development. Energy and water footprint can reflect the real occupation of water resources in the process of energy production. Based on the energy and water footprint evaluation model, this paper calculates the life cycle water footprint of fossil energy and power production in 30 provinces (cities and autonomous regions) in China, studies the temporal and spatial pattern evolution characteristics of China’s raw coal, crude oil, natural gas, hydropower and thermal power from 2004 to 2016, and analyzes the spatial matching relationship between China’s energy and water footprint and water resources. The results show that: (1): during the study period, the water footprint of fossil energy increases first and then decreases with 2012 as the boundary. The rapid growth of hydropower water footprint promotes the continuous growth of power water footprint. (2): In terms of spatial pattern, the water footprint of fossil energy increases in the West and decreases in the East with the Huhuanyong line as the boundary, and the Inner Mongolia, Shanxi and Shaanxi region as the high-value concentration area; in the power water footprint, there is a significant spatial boundary between hydropower water footprint and thermal power water footprint. The rapid growth of hydropower water footprint has gradually formed a high-value concentration area of power water footprint in the Yangtze River Basin, the Pearl River Basin and the southeast coast. (3): The spatial matching degree of energy and water footprint and water resources fluctuates and declines in the pattern of high in the south and low in the north. The spatial matching degree of fossil energy and water footprint is lower than that of electric power and water resources. The energy water contradiction between raw coal production and thermal power generation is the most prominent. One third of the country has the problem of energy water mismatch. North China with high energy and water footprint has great pressure on energy water matching. The contradiction between energy production and water resources allocation still exists. Truly reflect the matching relationship between energy and water footprint and water resources, help to optimize the comprehensive management of energy and water resources, and provide a quantitative basis for maximizing the energy water synergy.

Study of magnetic resonance coronary angiography based on functional magnetic resonance imaging

China's economic development depends on the stable operation of power system. Whether in industry or agriculture, electric power resources have covered all aspects of people's production and life. In particular, China's economy is developing at a high speed, and the demand for power resources is increasing day by day. Based on this actual demand, this paper takes 35kV Transmission Line as an example to analyze its safe operation and maintenance in detail, aiming to provide reference scheme for China's power industry and promote the healthy and stable operation of China's transmission line.

SMART ELECTRICITY CONSERVATION SYSTEM USING EFFICIENTNET

Conservation of electric resource has been one of the important challenges over the decades. Worldwide, many nations are struggling to conserve and to bridge the gap between the demand and production of the resource. Though many measures like several Government acts, replacing existing products with energy conserving products and many solar based systems are being invented and used in practise, the demand and the need to preserve the resource still persists. Hence, this paper focuses on a novel technique to conserve the electric resource using a deep learning technique. The system uses Convolutional Neural Networks to identify and localize humans in the CCTV footages using EfficientNet, a deep transfer learning model. The classifier processes and yields its output to an embedded Arduino microcontroller, after detecting the presence/absence of human. The microcontroller enables/disables the electric power supply in the area of human’s presence/absence, based on the classifier’s output respectively. The system achieves an accuracy percentage of 84.2% in detecting humans in the footages with the subsequent enabling/disabling of electric power resource to conserve electricity.

Concessionary Agreement as a Tool for Performing Innovative Activities by Electric Power Companies

The electrical power sector is a social and strategical significant economic area which provides all sectors of the economy and the population with electric power resources. Currently, the industry is characterized by a high level of worn-out fixed assets and an ever-increasing technical and technological backlog. The innovative development way is crucial for the electric power industry. It ensures the use of alternative energy sources, improves quality and reliability of power supply. In order to move the country from the export economy to the resource-innovative one, the interaction between the government and private electric power companies is required. The author has developed a concessionary mechanism based on public-private partnerships, contributing to innovative activities of electric power companies. The article provides a diagram of the procedure for concluding a concessionary agreement for performing innovative activities in the electric power industry. It allows us to study a competition procedure. The purpose of the concessionary mechanism is to achieve social and economic effects of investment and innovation processes in the electric power.

Mapping China’s Electronic Power Consumption Using Points of Interest and Remote Sensing Data

Producing gridded electric power consumption (EPC) maps at a fine geographic scale is critical for rational deployment and effective utilization of electric power resources. Brightness of nighttime light (NTL) has been extensively adopted to evaluate the spatial patterns of EPC at multiple geographical scales. However, the blooming effect and saturation issue of NTL imagery limit its ability to accurately map EPC. Moreover, limited sectoral separation in applying NTL leads to the inaccurate spatial distribution of EPC, particularly in the case of industrial EPC, which is often a dominant portion of the total EPC in China. This study pioneers the separate estimation of spatial patterns of industrial and nonindustrial EPC over mainland China by jointly using points of interest (POIs) and multiple remotely sensed data in a random forests (RF) model. The POIs provided fine and detailed information about the different socioeconomic activities and played a significant role in determining industrial and nonindustrial EPC distribution. Based on the RF model, we produced industrial, non-industrial, and overall EPC maps at a 1 km resolution in mainland China for 2011. Compared against statistical data at the county level, our results showed a high accuracy (R2 = 0.958 for nonindustrial EPC estimation, 0.848 for industrial EPC estimation, and 0.913 for total EPC). This study indicated that the proposed RF-based method, integrating POIs and multiple remote sensing data, can markedly improve the accuracy for estimating EPC. This study also revealed the great potential of POIs in mapping the distribution of socioeconomic parameters.

Research on energy autonomy system design of field patrol car based on solar energy

The Inner Mongolia Autonomous Region has abundant solar energy and electric power resources. Due to the long distance between cities, the transmission lines are too long, which leads to difficulties in line inspection. To overcome the problem of line inspection, a field patrol car using solar energy is studied in this paper, the energy system of which can complete the charge and discharge independently and then realize the inspection task.Revolving around the energy autonomy of solar-energy field inspection vehicle, this paper first selects the appropriate components and builds the energy-autonomy inspection system of the patrol car, according to its design requirements. Then the solar tracking algorithm and MPPT control algorithm are used to improve the conversion rate of solar panels, so that the fast charging can be realized. Finally, the hardware and software of the solar controller are designed, and the corresponding functions are debugged.