Operation Of Power Grid Equipment Research Articles

A logical reasoning-based method for sensing the operating status of equipment

Grid equipment monitoring is to achieve comprehensive perception, rapid analysis and accurate disposal of grid operation status. As the scale of the grid continues to expand, many problems such as low efficiency in single point-based alarming, complicated and difficult process, irregular work norms, etc., have occurred in the current operating mode, which greatly restricts the improvement of management level of monitoring operation. Based on the correlation between substation monitoring information and monitoring equipment operation, we establish the correspondence between primary equipment such as main transformer, busbar, line and capacitor and the corresponding telemetry such as current, voltage, active power, reactive power and frequency. Then we analyze the occurrence mechanism of power grid equipment operation events, sense the equipment operation status, and realize timely and accurate sense and push of equipment operation defects and faults, thereby improving operational efficiency of monitoring devices.

Research on Intelligent Monitoring and Maintenance Technology of Substation Based on Digital Twin

The design, research and development, test, operation and maintenance of power grid substation equipment are relatively independent. Related problems in each link cannot be comprehensively managed from the perspective of the full life cycle of equipment. Operation and maintenance personnel need to face data monitoring, network monitoring, equipment monitoring, business system monitoring, fault diagnosis and repair and other business scenarios. There are many types of information, complex association relationship, abstract and inefficient operation and maintenance information, “man-machine-object” can not be two-way cooperation and interaction, fault diagnosis and troubleshooting difficulties. Digital substation intelligent monitoring operational digital twin applications, digital intelligent substation operations provide operational monitoring service ability, realize the grid digital substation twin modeling and environment reconstruction, false or true merged superposition, two-way coordinated interaction, twin intelligence operations and panoramic visual monitoring, field devices for power grid operation maintenance, resource scheduling, and construction planning to provide guidance, Fully guarantee the safe and reliable operation of power grid equipment, realize the full life cycle management of power grid equipment, and improve the level of intelligence, visualization and digitalization of power grid.

Function orientation and typical application scenarios of the Internet of Things construction for power transmission and transformation equipment

In recent years, power grid enterprises have continuously promoted the construction of intelligent operation inspection system. Pilot applications of various equipment status sensors, online monitoring devices, intelligent wearable devices, mobile terminals and Beidou navigation satellite system have been gradually carried out. The configuration range of intelligent equipment such as UAV and robot has been continuously expanded, and big data analysis technology, artificial intelligence diagnosis technology have also been preliminarily applied. With the continuous development and breakthrough of key technologies such as edge computing and wireless transmission, it provides favorable conditions for the intelligent, diversified and ecological development of the construction and application of the IOT for power transmission and transformation equipment. This paper mainly introduces the overall architecture and functional positioning of the construction of power transmission and transformation IOT, and combined with the business needs of some typical application scenarios in the operation of power grid equipment, to promote the integrated application of IOT technology and power grid equipment operation and inspection business, and also establish an open, shared and symbiotic IOT ecosystem of power transmission and transformation equipment, so as to lay the foundation for intelligent equipment management.

Optimization Method of Power Equipment Maintenance Plan Decision-Making Based on Deep Reinforcement Learning

The safe and reliable operation of power grid equipment is the basis for ensuring the safe operation of the power system. At present, the traditional periodical maintenance has exposed the abuses such as deficient maintenance and excess maintenance. Based on a multiagent deep reinforcement learning decision-making optimization algorithm, a method for decision-making and optimization of power grid equipment maintenance plans is proposed. In this paper, an optimization model of power grid equipment maintenance plan that takes into account the reliability and economics of power grid operation is constructed with maintenance constraints and power grid safety constraints as its constraints. The deep distributed recurrent Q-networks multiagent deep reinforcement learning is adopted to solve the optimization model. The deep distributed recurrent Q-networks multiagent deep reinforcement learning uses the high-dimensional feature extraction capabilities of deep learning and decision-making capabilities of reinforcement learning to solve the multiobjective decision-making problem of power grid maintenance planning. Through case analysis, the comparative results show that the proposed algorithm has better optimization and decision-making ability, as well as lower maintenance cost. Accordingly, the algorithm can realize the optimal decision of power grid equipment maintenance plan. The expected value of power shortage and maintenance cost obtained by the proposed method is $71.75$ $MW·H$ and $496000$ $yuan$.

Research on Identification and Measurement Methods of Influencing Factors of Investment in Operation and Maintenance

Operation and maintenance investment is an important part of the capital expenditure of power grid enterprises. In recent years, affected by multiple profit-cutting factors such as the macroeconomic downturn, the slowdown in electricity growth, the implementation of transmission and distribution price reform requirements, the narrowing of electricity price space, and the state's phased reduction of electricity cost policies, the profitability of power grid companies has dropped significantly, and power grid investment. The capacity was significantly weakened, and the operating pressure was unprecedented. Identifying and measuring the influencing factors of power grid operation and maintenance investment is an important supporting role for enterprises to formulate scientific and reasonable investment strategies for power grid equipment operation and maintenance. Therefore, this paper first applies the fish-bone method, combined with the current status of equipment operation and maintenance management of power grid enterprises, and scientifically identifies the factors that affect the investment level of operation and maintenance; then, based on the grey correlation theory, analyzes the degree of influence of each influencing factor.

Research on the Application of Artificial Intelligence in Operation and Maintenance for Power Equipment

With the continuous deepening of the construction of the State Grid, more and more power grid equipment such as substations need to be repaired and maintained in a timely manner, which makes the workload and difficulty of the power grid equipment operation and maintenance personnel more and more difficult. Electricity is a necessity for our daily life and enterprise production. In order to ensure the rapid and stable economic development, reliable power supply must be provided, and the normal operation of power equipment is the key to safe and stable power supply. Due to the rapid development of cities, various problems have begun to appear in some power grid plans, coupled with the upgrading of power grid equipment and the implementation of new power grid plans, making the operation and maintenance of power grid equipment more and more difficult, and more and more challenges high. Therefore, this article first analyzes the process of intelligent state maintenance of power grids, analyzes the key technologies of artificial intelligence in the operation and maintenance of power equipment, and analyzes the application of artificial intelligence technology in the operation and maintenance of power equipment.

Talking about the significance of optimizing the condition evaluation standard of small power grid equipment such as voltage transformer

Power grid equipment condition evaluation and condition maintenance is a kind of operation and maintenance means with strong reliability, low cost and high efficiency in power grid equipment operation management. At present, when carrying out state assessment of power grid equipment such as, grounding devices, capacitors, reactors, because of the features of large number, frequent failures, complex and changeable operating environment, etc, existing state evaluation standards have obvious deficiencies, which makes it difficult to meet management needs. Optimizing state evaluation standards, formulating scientific and effective state evaluation guidelines are of great significance for improving equipment safety and ensuring safe and stable operation of power systems.

Effect of acid wet deposition on operation of power grid equipment in China

The distribution law of acid rain in China is counted, and the operation of power grid equipment in acid wet deposition area is investigated. It is found that southern China has the strongest acidity of precipitation in the country. The ratio of SO42-, N03-, NH4+, Ca2+ concentration in acid rain is higher. Acid rain causes serious corrosion of transmission line and transformation equipment in Shandong, Sichuan, Shanxi and Henan provinces of China. The acid rain and corrosion products aggravate the dissolution and chemical reaction of the original dry deposition pollution on the external insulation surface of power grid, which may lead to corrosive flashover.

MODERN INFORMATION TECHNOLOGIES IN THE CONTROL SYSTEMS FOR COMPLEX BIOTECHNICAL OBJECTS OF AGRICULTURAL APPOINTMENT

Background. In modern world, the tasks of forming appropriate control strategies for various biotechnical objects of agricultural purpose are aimed at minimizing energy costs. Traditional control systems for complex biotechnical objects in conditions of high energy costs are inefficient. It is proposed to develop energy-efficient intelligent control systems using, as a criterion of efficiency, enterprise profits and modern information technologies. Objective. The aim of the paper is the creation of energy efficient intelligent control systems based on the analysis of natural disturbances, biological component states, price policy, continuous monitoring of the power grid equipment operation mode parameters’ stability. Methods. The analysis of existing traditional control systems for complex biotechnical objects in conditions of high energy cost made it possible to identify effective solutions for improving the reliability of integrated power supply systems for the agro-industrial complex and developing energy-efficient control systems for complex biotechnical objects. Results. The solution to the problem of minimizing energy costs has been obtained, which contributes to an increase in the production profit in general, due to the formation of appropriate control strategies for electrical facilities that are components of technological equipment. Conclusions. The modern theory of automatic control makes it possible to develop, using information technologies, energy-efficient control systems for complex biotechnical objects on the basis of analysis of natural disturbances, states of the biological component, price policy in the market of marketable products, and continuous monitoring of the power network equipment operation mode parameters’ stability. Keywords: automatic; infocommunication; energy efficiency; electrotechnics; control; synchronization; monitoring.

An Integrated Power Grid Equipment Operation and Maintenance Solution Based on Big Data, Cloud Computing, the Internet of Things and Mobile Internet

The traditional operation and maintenance methods cannot meet the new demands of current grid operation and maintenance as it grows in both scale and complexity. Based on the analysis of the shortcomings of the existing methods, an integrated solution based on big data, cloud computing, the Internet of Things and mobile Internet is proposed in this paper. Internet of Things technologies such as RFID and wireless transmission are adopted to acquire and sense information of field equipment. Big data and cloud computing technologies are used to standardize field work management and supervise standard field work operation. Besides, a data exchange channel is built between maintenance site and control center via intelligent operation and maintenance terminals to enable data upload and interaction between maintenance site and control center.