Volume 25, Issue 1

With the progress of society, the supply of electricity has become an inevitable choice for the development of all walks of life. The stability, safety, and economic dispatch of the electric energy system directly impact the entire country’s economic development, from national defense, military, and even people’s daily life, all closely associated with the smooth running of the network. In the aspect of power grid planning and operation, the economic security dispatching problem of power system is a very typical optimization problem. The problem is how to maximize the operating cost of the system under the premise of satisfying the system’s load limit and safety and stability. Due to the rapid development of power technology, the research on power system security and economic planning is essential. As an important means to promote China’s energy structure adjustment and promote the supply side structural reform, the regional spot electricity market is playing an increasingly important role in building a resource optimization allocation mechanism, improving China’s energy resource allocation efficiency, and promoting social and economic development. However, the development of China’s regional spot power market is still in its infancy, and the transaction price of the regional spot power market is quite different from that of other countries. It was given these problems, this article discusses the use of particle swarm algorithms for secure and economic scheduling of power systems in the context of securely reading blockchains and distributed data. The research results showed that: The introduction of environmental pollution penalty programs improved the priority dispatch of wind and photovoltaic power when considering environmental penalty programs and backup penalties for wind and photovoltaic power. The setting of the coefficient of the environmental penalty term depended on the designer’s emphasis on the priority scheduling of wind power and photovoltaic (PV) power generation (PG), and the standby capacity penalty clause achieved reasonable dispatch and utilization of wind power and PV PG, which reduced the dramatic fluctuations and intermittent volume of the system, and facilitated safe and consistent operation of the network. The research of this paper shows the positive relationship between the blockchain and distributed data security reading algorithm and the clearing method of regional spot power market, and points out a new method for its development.

The development of modern society requires not only attention to development methods and efficiency, but also correct evaluation of various environmental issues that arise during development, to achieve optimal social development without damaging the ecological environment. Intelligent power systems utilize new energy technologies, energy storage technologies, and smart grid technologies. Against this development background, how to achieve sustainable, environmentally friendly, and Low Carbon (LC) development in the power system operation, which has been at the center of China’s national economic construction and development system, has become a common concern for all participants. Therefore, this paper proposed a study on supporting role of intelligent power systems based on LC and environmental protection. In the new era, the target functions to be achieved by smart grids can provide the necessary support for the construction and development of LC power systems, and its importance is self-evident. Based on this reality, this article took LC power systems as the research object and combined the analysis of the functions of smart grids to discuss clean energy power systems. The experimental results showed that the Power Generation (PG) capacity of thermal PG increased from 280.4 billion kWh to 289.7 billion kWh. The increase in wind PG from 2.5 billion kWh to 5.5 billion kWh showed that although clean energy accounted for a small proportion, the power system was still dominated by traditional PG. However, clean energy PG is increasingly being valued. At the end of this article, corresponding rectification suggestions were also proposed, with the purpose of helping to optimize the development and improvement of LC power systems.

Electric energy is the most commonly used energy in people’s daily life. In the process of use, how to improve the utilization rate of resources, so as to achieve the purpose of energy saving and environmental protection of power resources is a very significant work. The power grid is crucial in the transmission of electricity, and the energy consumption of substations is a major factor affecting the operation cost. Therefore, it is a key condition to ensure the stable operation of the power grid to scientifically calculate its energy consumption and formulate appropriate energy-saving measures. After consulting a large number of relevant documents and data, it has been found that many researchers have provided new ideas for the calculation of energy consumption and the study of energy-saving measures in substations. This article was adding its own understanding and taking it as the direction and basis. In the introduction, the research significance of substation energy consumption calculation was introduced, and then the academic research and analysis were carried out on the two key sentences of substation energy consumption calculation and analysis and the research of multi-objective artificial bee colony (ABC) algorithm in substation. In the method part, a constructive algorithm theory was proposed, and the application of the algorithm in substation energy consumption was proposed to provide a theoretical basis for the energy consumption calculation and energy conservation measures research of substations based on multi-objective ABC algorithm. At the end of the article, a simulation comparison experiment was carried out and the experiment was summarized and discussed. Firstly, the performance of the two algorithms was analyzed. Then, through the first selection of power plant T and Y, it was concluded that the resistivity of the cable in the distribution room in power plant Y was much higher than the average value based on the experimental results. Therefore, it was taken as the sample subject of the following experiments and analyzed again. For the second time, the analysis of district power plant Y showed that through simple calculation, the average energy efficiency difference of the distribution room before and after use was 3.1. Finally, it was analyzed that the ABC algorithm could not only improve the energy efficiency of the distribution room in the power plant, but also improve the effective efficiency of its power station. It shows that this kind of algorithm is effective and worthy of further study.

In recent years, with the development of smart grids, people have increasingly high requirements for the safety, stability, and reliability of smart grid operation. In actual operation, smart grids require real-time monitoring and control, while for low-voltage power lines, power line carrier communication is required for data transmission. However, in practical applications on site, the low-voltage power line environment is complex, with ground faults, electrical equipment interference, and other situations that can affect communication quality and reliability, leading to a decrease in the effectiveness of real-time monitoring and control. The research in this paper is based on a complex low voltage platform simulation platform to restore the on-site complex substation communication environment. The purpose is to improve the efficiency of automatic meter reading systems by using various communication methods in low-voltage substations, such as wireless public network point-to-point data transmission, optical fiber communication data transmission, power line carrier data transmission, etc. Automatic meter reading systems are an important means of low voltage substation communication. This article experimentally tested the maximum personnel allocation for meter reading using low voltage carrier communication technology, which was 8 people smaller than the maximum personnel allocation for traditional meter reading, and the minimum personnel allocation was 8 people smaller than the traditional meter reading personnel allocation. The electricity accuracy of meter reading using low voltage carrier communication was up to 96 %, while the electricity accuracy of traditional meter reading was 70 %. The maximum accuracy of line loss statistics for low voltage carrier communication technology meter reading was 90 %, while the maximum accuracy of line loss statistics for traditional meter reading was 68 %. The frequency of load anomalies found in low-voltage carrier communication meter readings within a month ranged from 30 to 60 times, while the traditional meter readings concentrated on 10–25 times. From these data, it is clear that communication meter reading in low-voltage station areas has advantages over traditional meter reading.

The world population is growing with more understanding of technical and social changes. Limited energy reserves and exponential demand growth have created a serious concern in all sectors including automobile sector. Electric vehicles (EVs) develop better means of transportation as it suppress to the adverse effects in using conventional ways of transportation. Among all the energy requirements, the automobile sector demands almost 21 %. It is a matter of concern because of limited energy reserves. Concerning all the adverse effects of using conventional ways of transportation, scientists and engineers are working on electric vehicles. Intensive research has been going on for decades to make electric vehicles a substitute for conventional transportation systems with the same reliability. The merit for EV charging infrastructure is an indispensable metric that plays a pivotal role in assessing the efficacy and progress of electric vehicle charging networks. This metric encompasses a range of critical factors, including the density and geographical distribution of charging stations, the charging speed and capacity, the utilization rates, the availability of alternative charging options (e.g., fast charging, slow charging), and the integration of optimization technologies for optimal energy management. Apart from technical advancements, the researchers are working on the challenges related to their mass adoption in current distribution system. For large-scale deployment of EVs, reliable and sustainable charging infrastructure needs to be developed. But the charging station placement problem is a complex problem. Charging stations must be placed in the distribution network in such a way that the negative impacts of the placement of charging stations on the operating parameters of the distribution network are minimal. The various aspects to gain deeper insights into the strengths and weaknesses of existing charging infrastructure, and to propose innovative solutions for further enhancing the efficiency, accessibility, and sustainability of EV charging networks. The location of the charging station is important and must consider the effect of EV charging demand at existing system with overall charging station placement cost. Therefore, the Voltage Reliability Power loss (VRP) Index (that integrates effect of important parameters such as voltage variation, reliability, and power loss) using Discrete Particle Swarm Optimization (DPSO) is minimized including overall charging station cost as an important constraint for this proposed algorithm. This overall charging station cost includes land cost, installation cost, and energy demand cost by electric vehicles. The results are compared with new discrete versions of different PSO techniques, namely, Standard-Discrete Particle Swarm Optimization (S-DPSO) and Passive Congregation Discrete Particle Swarm Optimization (PC-DPSO) optimization techniques. Highlights – Site selection of charging station at an economically viable location for electric vehicle users with minimum effect on the existing distribution network. – Site selection of charging station considering existing distribution substations, road congestion, and voltage stability of the distribution network bus. – Utilization of fuzzy inference algorithm for selecting a potential location. – Calculation of the land required for establishing a fast or a slow rate charging station based on FAME-India (Faster Adoption and Manufacturing of Electric and Hybrid Vehicles in India), a government of India initiative for faster adoption of EVs. – Optimization of a cost function for commissioning EV stations including the cost of land, charging time, cost of energy, and number of vehicles charging points.

This paper presents the evolution of bidirectional electric vehicle charger for G2V (i.e., Grid-to-Vehicle) and V2G (i.e., Vehicle-to-Grid) utility. Electric vehicle are growing day by day in the area of transportation. As more electric vehicles hit the road to maintain the need for charging, bidirectional charging becomes essential. Bidirectional charging in electrical vehicles facilitates users to either make energy flow to the vehicle or flow from the vehicle. The proposed design allows users to make economic gains from electric vehicle with other exciting advantages. Particularly unidirectional charging solution restricts the user to use energy for charging only applications whereas, this paper proposed a control strategy for bidirectional charging of electric vehicles. Hence electric vehicles could be potentially used as a source during an emergency like power outages, grid failure, or whenever there is an excess load on grid and user needs more energy. Additionally, this paper uses an integration of buck and boost converter to develop a bidirectional vehicle charger. The performance of bidirectional converter with control algorithm is verified by simulation on MATLAB Simulink.

In order to improve the security of power remote telemetry system, this paper studies the parameter identification method of power remote telemetry system based on real-time cross-section data and error-proof topology analysis. The method is based on a synchronization vector measurement unit. It uses the multi-source measurement method to fuse the real-time cross-section data of the power remote telemetry system, we reconstruct the fault-proof topology map of the power grid based on the fused real-time cross-section data. And according to the grid error prevention topology diagram, we set the grid line impedance parameters, calculate the sum and variance of voltage squares and so on. After the set parameters are established, the constraint conditions are divided, and the constraint conditions are transformed by linear function through quadratic programming. By judging whether the parameter identification function complies with its constraints, the parameter identification of the power remote telemetry system is realized. The experimental results show that this method can accurately obtain the real-time cross-section data of the power remote telemetry system. Moreover, it can accurately reconstruct the fault-proof topology of the power grid, and the maximum deviation of parameter identification is only 0.5223.

Predictive maintenance is required for Induction Motor (IM) to avoid sudden breakdown. In this paper, multimodal sensor data are used for prediction of the rotor slot width variation during runtime of IM. Moreover sensor data are visualized through visual image obtained using Scale Invariant Feature Transform (SIFT) and matching dictionary for various faults in motor such as overload, high speed, Broken Rotor bar (BRB), and unbalance magnetic pull. The multimodal sensor signals data acquired from different parts of three phase induction motor are analysed using various transforms such as Over Complete Rational Dilation Wavelet Transform (ORaDWT), Tuneable Q Wavelet Transform (TQWT), Polynomial Chirplet Transform (PCT) and Dyadic Wavelet Transform (Dyadic WT) for various fault conditions and rotor slot width mentioned during runtime condition of motor. The rotor slot width is predicted using Multiple Linear Regression (MLR), Polynomial Regression (PR), Logistic Regression (LR) and Soft-max Regression (SR) methods through the mean value and energy band of the acquired sensor signal. The Dyadic WT and SR perform better for rotor width prediction. The proposed method such as Dyadic WT and SR provides the prediction accuracy of about 95.2%. From experimental results the rotor slot width expansion more than 2% needs immediate attention to avoid breakdown of motor.

In this paper, a non-isolated DC–DC converter with three-winding coupled inductors and switched capacitor cells is introduced. More output voltage is acquired without imposing any extreme duty cycle and high turns ratio. With the help of a two-phase interleaved technique, the input current ripple is reduced efficiently. The leakage inductance of coupled inductors causes the reverse recovery problem of circuit diodes to be solved and alleviates them. Leakage energy is also absorbed by switched capacitor cells. One of the advantages of this converter is the reduction of voltage stress of power switches, which leads to a reduction of conduction losses. In this way, low-voltage rated power switches can be used. Creating soft-switching conditions on power switches and high efficiency are also the prominent features of this structure. Laboratory and experimental results were produced and presented by making a prototype of 350 W–18 V/480 V. Their analysis indicates the effective performance of the proposed topology.

This research paper represents the estimation and reduction of eddy current loss in a Magnetic Fault Current Limiter (MFCL). The nonlinear model of the device is established using electromagnetic coupled circuit supported by Finite Element Model. The current limiting performance of the MFCL is investigated by simulation study as well as laboratory testing. It is further observed that a significant amount of eddy current loss takes place inside the core and permanent magnet of the device. Different methods (shorting ring, lamination of permanent magnet and variation of magnet length) are proposed to reduce the eddy current. The advantages and disadvantages of these methods are discussed. Some design modifications are also proposed to minimize the temperature rise caused by the eddy current.

This paper presents the development of a new algorithm for the diagnosis of induction motor inter-turn short circuit and mixed combined fault detection based on the reduction Park’s vector modulus and discrete wavelet transform. The proposed method is based on a combination between the RPVM approach and DWT. This new signal of the RPVM is a cost-effective alternative implementation of the Extended Park’s Vector approach through monitoring only the fluctuations of the stator current zero-crossing times in the frequency domain. Using this technique, the characteristic frequency components of the fault are extracted from only one phase stator current when compared to Park’s vector modulus and Hilbert modulus. The main advantages of the RPVM signal are to acquire the values of a single-phase stator current to allow reducing the calculation complexity and for extracting features frequencies of the faults. Thus, the reduced amount of data samples must be stored and processed. This study investigates theoretically by using the proposed RPVM signal for performing to diagnose induction motor faults through the DWT method and processed via energy eigenvalue of energies. This proposed approach RPVM-DWT is validated experimentally to demonstrate its effectiveness in that the proposed algorithm reduces the computational cost and can be used in induction motor fault detections and identifications with different fault severity conditions.