Recursive Fourier algorithm is a commonly used digital signal processing algorithm for protection relays. Its characteristic is to use the last calculation result to calculate the current result. Its calculation efficiency is very high. However, the recursive algorithm has a memory effect. Errors caused by accidental factors will be kept and be difficult to detect, bringing hidden dangers to the operation of the protection device. In this paper, a fault-tolerant mechanism suitable for recursive algorithm is proposed to eliminate the memory effect and prevent irrecoverable calculation deviation caused by occasional or accumulated errors, thus effectively preventing such problems from causing misoperation or failure of protection devices.

With the proposal of China’s “dual carbon” goal and the construction of a novel power system, how to reduce the total carbon emissions of power generation enterprises and increase the share of renewable energy generation is an important issue facing China at present. In this paper, the conventional electric energy market trading paradigm is improved, and an optimization model for electricity trading considering carbon markets and renewable energy quota system is proposed. The optimization model is constructed with the goal of minimum carbon emissions of power generation enterprises and minimum customer purchase cost of electricity, and the model is solved by using the Cplex solver. The optimized trading paradigm is compared with the conventional electric energy market trading paradigm, and the case analysis verifies that the optimization model corresponding to the trading paradigm in this article can well decline the carbon emission and customer purchase cost of electricity.

In order to improve the efficiency of identification and diagnosis of distribution network line faults and improve the reliability of power supply, this paper adopts a method based on wavelet entropy to construct a distribution network line operating condition characteristic gene bank. Firstly, the distribution network line simulation model is built to extract the operation data, and then, combined with the effective simulation data, the feature extraction algorithm model based on wavelet entropy is built, and finally, the characteristic gene bank is developed based on the feature data. The simulation results show that the feature extraction algorithm and characteristic gene bank based on wavelet entropy can effectively identify and diagnose a variety of operating conditions of distribution network lines, which meets the requirements of sustainable development of distribution network.

This paper aims to explore the application of isolation technology in high voltage design of energy storage systems (ESS), with a focus on analyzing the characteristics of optical isolation, magnetic isolation, and capacitive isolation technologies and their performance in different application scenarios. By combining technical comparison, application analysis, and case studies, this paper elaborates in detail on the application of isolation technology in improving system safety, reducing electromagnetic interference, achieving signal and energy transmission, and facilitating measurement and control in high voltage environments. The results indicate that reasonable selection of isolation technologies can effectively improve the safety and reliability of high voltage energy storage systems, providing theoretical basis and practical guidance for the design and optimization of high voltage energy storage systems.

With the growth of renewable energy and the increase of low carbon demand, alumina industry is facing the challenge of optimizing energy consumption. Targeting industrial production at high renewable energy ratios, it is optimized through electric energy substitution and demand response. In this paper, other green power real-time regulation is taken as the object of demand response, and a multi-objective demand response model of alumina production electricity consumption is established on the basis of guaranteeing that the rate of wind and light abandonment is minimized, and with the goal of satisfying the system economy and guaranteeing the output. The normal boundary intersection (NBI) method and nondominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ) are used to optimize and solve the model. According to the analysis results of actual cases, the NBI algorithm performs better in reducing the electricity cost and the rate of power abandonment, with a cost reduction of 73% and a rate of power abandonment of 16.65 percentage points, compared to 70% and 15.65 percentage points, respectively, for NSGA-Ⅱ.

The assignment of work orders is an essential part of the power operation and maintenance management system. Timely and accurate assignment methods can effectively improve the efficiency of work order circulation. Based on in-depth analysis of the characteristics of work order management in the field of power operation and maintenance, this article proposes an automatic assignment model for power operation and maintenance work orders based on fit degree. The model adopts criteria importance though intercrieria correlation (CRITIC) weighting method and fuzzy comprehensive evaluation to calculate the compatibility between operation and maintenance personnel and work orders, determine the optimal candidate for work order assignment, and then achieve automatic assignment of work orders. The practical application results show that compared to manual assignment, this automatic assignment model can effectively improve the efficiency and accuracy of work order assignment.

In order to solve the problem of high redundancy and low positioning accuracy of traditional cable fault location spectrum data, this paper proposes a high precision cable fault location method based on chirp-Z transform (CZT). Firstly, according to the transmission line theory, the distribution parameters and reflection coefficient characteristics of the fault cable are analyzed. Then, CZT is performed on the real part of the reflection coefficient. Finally, iterative filtering is used to denoise and obtain the cable fault location spectrum. The results show that the fault point recognition error of the proposed method is 0.025%~0.275%. Compared with fast Fourier transform (FFT), the proposed method has the advantages of refined location spectrum, high resolution, low redundancy and high fault location accuracy.

The grounding wire is an important equipment for ensuring the personal safety of power operators. Traditional grounding wire lacks informationization and intelligent management methods. There is no closed-loop management method for the extraction and return of grounding wire, which can easily lead to misconnection, no connection, and without returning, bringing huge risks to the safe and stable operation of the power grid. This article focuses on the Internet of Things (IoT) and intelligent transformation of grounding wire, grounding wire cabinet, and grounding pile. The design covers the full-process control system architecture covering the “cloud-network-edge-end”, and the full-process control system of grounding wire and intelligent monitoring device are developed. Through the method of edge IoT proxy cross regional collaboration, the consistency of the real-time status of grounding wire, grounding wire cabinet and grounding pile and business data between the security Ⅳ region and the Internet region is achieved. Based on cross regional collaboration of data, cross regional data collection and panoramic monitoring of grounding wire are achieved to ensure accurate grounding connection, improving the safety and work efficiency of on-site operators, and providing guarantees for the safe and stable operation of the power grid.

This article analyzes the characteristics of single phase grounding faults and cross line grounding faults in the same tower double circuit line, as well as the impact of zero sequence mutual inductance on grounding distance protection, in response to the misoperation fault of under range longitudinal distance protection during a cross line grounding fault on the same tower double circuit line. It is concluded that the additional impedance caused by zero sequence mutual inductance is the fundamental reason for the reduction of grounding distance protection range and the refusal of protection. In order to solve the problem, an adaptive zero sequence mutual inductance compensation method is proposed. The new method based on the adjacent zero sequence current injection and local auxiliary judgement can enable the compensation adaptively. The performance of the proposed method is evaluated based on the real time digital simulation system, and results show that this method is valid.

In the context of “dual carbon” goal, integrated photovoltaic storage and charging station (IPSCS) can effectively solve the problem of independent operation of multiple types of flexible resources. To enhance the collaborative consumption capacity of source load and reduce carbon emissions, this paper proposes a multi-timescale day-ahead operation strategy for IPSCS that considers carbon emission stratification and source load interaction. Firstly, hybrid prediction model and Monte Carlo method are applied to historical data to derive typical photovoltaic output and electric vehicle load scenarios, respectively. Secondly, the objective function of the mathematical model of the operation strategy of the integrated station is minimum comprehensive planning cost, minimum carbon emission, and maximum utilization of new energy. The model is solved using an improved whale optimization algorithm (IWOA) incorporating an opposition-based learning strategy and diversity variation processing. Finally, the rationality and effectiveness of the proposed strategy are verified through case analysis.