Research On Operation And Maintenance Strategy Of Photovoltaic Power Generation System Based On State Prediction

In recent years,with the rapid advancement of distributed photovoltaic power generation systems in my country,distributed photovoltaic power stations that have been built have gradually exposed problems such as low maintenance technology and management level,insufficient professionalism and intensification,and low efficiency.It has become one of the bottlenecks restricting the stable and healthy development of distributed photovoltaic power plants.In order to effectively improve the availability and power generation efficiency of photovoltaic power plants,it is of great significance to study the state assessment methods and intelligent maintenance strategies of photovoltaic power generation systems.Based on the above research background,the main work of this thesis is as follows.(1)Aiming at the problem that the operating environment of photovoltaic arrays is complex and the operating status affects its power generation efficiency and service life,a new method based on combined weight and Markov Chain Monte Carlo(MCMC)dynamic simulation is proposed used to evaluate the status of photovoltaic arrays.Firstly,the failure probability about evaluation system of photovoltaic module string units is constructed under the premise of considering the impact of environmental factors on the evaluation indicators,combined with the G1 and entropy weight to combine the weights of the evaluation indicators and obtain the failure probability of photovoltaic modules string unit.Then by establishing the relationship between random variables and evaluation indicators,using MCMC to simulate the state of the photovoltaic array.It laid the foundation for the intelligent maintenance of photovoltaic power generation systems.(2)In view of the high cost of regular maintenance of the photovoltaic power generation system and the problem that the real-time status of the system cannot be fully utilized to dynamically adjust the maintenance strategy,a new dynamically combined maintenance strategy of photovoltaic system based on associative set and availability is proposed by considering the influence of equipment operation status and weather factors.Firstly,an associative set is established according to the structural and functional correlation of the equipment,and the maintenance strategy set is determined based on this unit.Then,the states of the equipment and associative set are predicted by the improved Markov state transition model and their availability is calculated.In the stage of equipment maintenance decision-making,the lowest maintenance cost and the highest availability are the goals.The maintenance time and way of equipment is determined by the mode factor and the equipment status.In the optimization stage of associative set maintenance strategy,a joint maintenance decision set based on the economic and structural correlation of equipments is established,so the best maintenance strategy for the system is determined.Finally,the influence of environmental factors on maintenance cost and system availability is analyzed.The economy and effectiveness of the model are verified.(3)Aiming at the problem that the maintenance method based on the status information of the photovoltaic power generation system cannot effectively reflect the influence of the comprehensive correlation of the components on the maintenance strategy,on the basis of optimizing maintenance cost and availability,a new maintenance strategy for two-layer optimization of photovoltaic power generation systems based on component dependencies and availability is proposed.Firstly,the comprehensive correlation of components in the system is analyzed,the influence of failure correlation on maintenance strategy is verified by introducing failure correlation strength.Then,the availability of the system and components is modeled by improving the Markov model.Finally,the idea of opportunistic maintenance is introduced and the upper-level optimization model that aiming at the lowest maintenance cost is established by considering the economic correlation.The highest availability of the system is taken as the objective function,and the limit of the availability of components is used as a constraint to establish a lower-level optimization model for verification.By introducing the weather availability rate to analyze its influence on the maintenance cost and the change rate of system availability.Thus,the economy and universality of the model are verified,as well as the specific influence of weather factors on the formulation of maintenance strategies.