Monitoring Adjustment And Anomaly Diagnosis Of Power Consumption Process In Smart Grid

The continuous updated smart meters applied to smart grid systems can monitor and analyze the power consumption,and give a reasonable price in next time slots,so as to induce users to consume electricity more efficiently and wisely.We obtain the optimal power consumption,power supply and prices by establishing the social welfare maximization model balancing supply and demand in every time slot.However,in reality,the users’ reserved power consumption is often different from the optimal power consumption and power supply.In some time slots,the difference is considerably large,which may result in an anomalous power consumption process.Therefore,it is urgent to solve the problem of anomalous power consumption process.Under the above background,it is of great significance to research the power consumption process.The thesis researches the power consumption process from the aspect of system regulation.By comprehensively using the automatic process control method and fuzzy comprehensive evaluation method,the thesis constructs the theoretical system of power consumption process monitoring,adjustment and anomaly diagnosis.The monitoring and linear function based adjustment,quadratic function based adjustment,exponential function based adjustment,anomaly monitoring,diagnosis and classification adjustment of power consumption process are systematically studied to realize the stability and reliability of power consumption process.The main research work is as follows:Firstly,aiming at the problem of monitoring and adjusting users’ actual power consumption to make it close to the optimal power consumption,an automatic process control strategy based on linear function is proposed.First,the social welfare maximization model is solved.Next,taking the difference between the users’ reserved and the optimal power consumption as the process variable,using the exponential weighted moving average as the process controller to predict the power consumption difference in the next period through the change trend of historical data,the monitoring model is proposed.Then,the monitoring and linear function based adjustment algorithm is designed.Only when the exponential weighted moving average value of the difference exceeds the preset threshold,the price will be adjusted in the next period to reduce the adjustment frequency as much as possible.The proposed method can ensure the stability of the actual power consumption after adjustment.Finally,the example analysis results show that the actual power consumption after adjustment is closer to the optimal power consumption,and it runs smoothly to achieve the purpose of peak shaving and valley filling.Besides that,the parameters of monitoring threshold and regulation target are discussed,and two indicators to judge the regulation effect are proposed,adjustment frequency and standard error.Secondly,aiming at the problem of monitoring and adjusting users’ reserved power consumption to make it close to the optimal power consumption through less adjustment frequency,an automatic process control method based on quadratic function is proposed.First,the exponential weighted moving average is used as a controller to monitor the difference between the users’ optimal and reserved consumption requirement loads at the next time slot,and the model is established to monitor the difference.When the exponential weighted moving average value of the difference exceeds the preset threshold,it is regarded as anomaly and needs to be adjusted to the target value.Next,the adjustment algorithm is designed by the price demand response based on quadratic function.When the difference exceeds the upper bound of the threshold,the price is increased,and when the difference is lower than the lower bound of the threshold,the price is reduced.Then,four indicators are put forward to judge the adjustment effect: adjustment frequency,standard error,whole social welfare and profit.Finally,the example analysis results show that the four indicators of the proposed quadratic function based adjustment strategy are better than the adjustment strategy based on linear function.In addition,the actual power consumption runs smoothly and is close to the optimal power consumption.Thirdly,aiming at the problem of monitoring and adjusting the actual power consumption to make it close to the optimal power supply,an automatic process control method based on exponential function is proposed.First,the exponential weighted moving average is used as the controller to establish the monitoring model to monitor the difference between the actual power consumption and the optimal power supply.Then,the monitoring and adjustment algorithm based on exponential function is designed to obtain the stable actual power consumption.Finally,the example analysis results show that the three indicators of the proposed exponential function based adjustment strategy are better than the adjustment strategy based on linear function.At the same time,the actual power consumption is running close to the optimal power supply.Last but not least,aiming at the problem of formulating classification adjustment strategies for different reasons of the anomalous power consumption in smart grid,an adjustment and bound strategy of changing electricity price based on quadratic square root function is proposed.The strategy is a classification of adjustment based on automatic process control and fuzzy comprehensive evaluation to diagnose and adjust anomalies in monitoring users’ power consumption.First,the exponential weighted moving average is used as the control variable of automatic process control to determine the upper and lower boundaries for monitoring the actual power consumption,and the automatic process monitoring model is established.Next,the reasons for the anomalous power consumption are found out by using fuzzy comprehensive evaluation technology.Then,classification adjustment strategies are formulated for different reasons,and the adjustment model based on price demand response is established.Finally,example analysis results show that the proposed adjustment strategy of changing electricity price based on quadratic square root function is superior to the linear function adjustment strategy in terms of the four indicators.Applying fuzzy comprehensive evaluation method can effectively analyze the cause of the anomaly.Formulating classification of adjustment strategies can eliminate the anomalies and obtain regular and stable power consumption.To sum up,the research in the thesis enriches the theory of process monitoring adjustment and anomalous diagnosis for smart grid,and provides technical guidance for promoting the steady and reliable power consumption process.