On Intelligent Monitoring And Early Warning System For Power Systems Based On Accurate Meteorology And GIS

Electricity is a special industry that guarantees national security and maintains the lifeline of the national economy.Whether its operation is stable has a greater impact on society.In recent years,with global warming,severe weather,such as severe storms,and prolonged droughts,extreme cold,extreme heat,and freezing rain and snow have occurred frequently,it offers great threats to the safe and stable operation of the power grid;At the same time,my country proposes to build an energy system with renewable energy as the mainstay,and achieve the goal of "carbon peak and carbon neutrality" in the field of energy utilization.Therefore,analyzing the impact of weather changes on the production and operation of the power grid,comprehensively using tools such as power grid GIS and artificial intelligence,and researching and Improving grid monitoring and early warning capabilities is essential to ensure the safe and stable operation of the grid.The work of this paper mainly includes the following aspects:(1)On the basis of realizing the correlation between meteorological data and power grid equipment,carry out precise processing such as "meteorological fitness scanning" and "meteorological information customization of important equipment" on power grid operating equipment to realize the organic integration of meteorological information,electrical equipment and grid GIS information.(2)A method for forecasting wind and light output based on precise weather is proposed,and an artificial neural network model optimized based on the L-M algorithm is trained to achieve accurate forecasting of new energy power.The system uses realtime weather data to correct the predicted values of wind power and photovoltaic output to improve the level of new energy consumption and ease the pressure on the power grid.(3)Use meteorological data to accurately process the results,push the meteorological information that affects the operation of important equipment to control operators in real time,and display it graphically.According to the calculation result of Spearman's correlation coefficient,early warning of line tripping in districts and counties during thunderstorms.Carry out real-time weather monitoring for the whole process of maintenance work.When there is a weather forecast result that affects the maintenance operation,the alarm information will be sent to the control and operation personnel in time to remind the maintenance personnel to arrange the work progress reasonably;after the line failure,the fault location and the line GIS information are combined to realize the rapid location of the fault point and the fault After the power grid operation risks are comprehensively analyzed and judged,the staff on duty are prompted to adopt pre-control measures to improve the automation level of fault handling.The main work and innovations of this paper are as follows:1)Propose a neural network prediction model optimized based on the LM algorithm,which shortens the time required for wind power and photovoltaic output prediction and improves the prediction accuracy;According to the real-time weather information data,the new energy output prediction is carried out to enable wind and photovoltaic power generation.2)Propose a total data analysis method based on the power grid GIS platform,which fully integrates geographic information,meteorological data,power grid facilities and other data,and accurately matches power grid equipment with realtime meteorological information,predicts accuracy,and achieves Lean power grid dispatch;3)exploited a smart monitoring and early warning system for power grid dispatch based on precise weather and power grid GIS information,and applied it to scenarios such as maintenance and power grid fault warning and analysis.Relevant research results have been initially used in the Shandong Power Grid Dispatching Center with good results.