Research On Privacy Protection Strategy For Smart Meter Users In Smart Grid

A large number of high-precision power consumption data in the smart grid brings convenience to the management of the power grid,but high-precision data also poses a threat of user privacy leakage.After the third party obtains the user’s electricity information recorded by the smart meter,the data mining technology can be used to obtain the use of the appliance,and then the user’s behavior habits are inferred,resulting in user privacy leakage.In this paper,the privacy protection of smart meter users in smart grid is studied.Taking home micro grid as the research object,the charging and discharging of battery is mainly used to hide the real data of users’ electricity consumption.Two privacy protection methods are proposed,which are cooperated by solar panel and electrolytic water hydrogen generation equipment.Standardized mutual information and power loss rate are used as evaluation indexes of privacy protection effect and power loss respectively.This paper proposes a TTB algorithm based on target tracking.When the meter data truly reflects the demand for electricity,the electricity meter can be used to estimate the electricity consumption of the appliance.The TTB algorithm tracks the preset target by controlling the meter reading,decoupling the coupling relationship between the meter reading and the power demand,and achieving the effect of protecting the user’s privacy.The simulation results show that the TTB algorithm can save the user’s electricity bill while achieving better privacy protection when selecting the appropriate tracking target.Due to the limitation of battery’s charging and discharging power and capacity,the battery can’t provide enough privacy protection for users when it reaches the boundary condition.In order to solve this problem,this paper proposes a hybrid algorithm based on noise addition and differential privacy protection theory,which uses the charge and discharge of battery to inject noise into the real power consumption data when the battery does not reach the limit boundary,and uses the power consumption characteristics of small household electrolytic water hydrogen production equipment when the battery reaches the limit boundary.The simulation results show that this method can greatly reduce the standard mutual information between the real power consumption data and the data recorded by the meter.In terms of practicability,this protection method can achieve good privacy protection effect under the condition of low power loss rate.Although some extra expenses are needed,the privacy of users is well protected.Both protection methods proposed in this paper can achieve good privacy protection.Between them,the HBNA algorithm is better than the TTB algorithm in privacy protection.However,the cost of the HBNA algorithm to reduce the privacy leakage rate is to increase the electricity bill,and the TTB algorithm has the effect of saving electricity.