User Privacy Protection Strategy Based On Rechargeable Battery In Smart Grid

In smart grid,the high-precision power data brings convenience for demand side response management while brings threats to users’ privacy.The enemy can dig out what type of appliance is being in use from power usage data through data mining methods,thus speculating the user’s behavior pattern.By this means,the users’ privacy is leaked.In recent years,the frequent disclosure of smart grid privacy has attracted great attention from academia and industry.In this paper,we take the household micro-grid equipped with photovoltaic power generation device as the research object,and build a mathematical model to describe the energy flow relationship of it.We propose two privacy protection algorithms by using rechargeable battery to hide the real appliance load,and give the definitions of privacy leakage rate and electricity saving rate as the evaluation indexes of privacy protection effect and electricity saving effect respectively.In this paper,the TC algorithm is proposed based on curve tracking.By tracking the pre-defined curve,the TC algorithm decouples the coupling relationship between the reading of the meter and the power demand,thus protecting the users’ privacy.The simulation results show that,when the appropriate tracking curve value is selected,the TC algorithm can effectively protect the privacy but will increase the electricity fees.Fine-grained data leaks appliance loads information.From the perspective of increasing data granularity,the IDG algorithm is proposed to protect users’ privacy.This algorithm discretizes the readings of smart meters thus increasing data granularity.In the meanwhile,the battery is controlled to charge at a low price and discharge at a high price,thus saving costs.According to the different ways of choosing the value of the power drawn from the grid,the algorithm can be divided into RM-IDG algorithm with random choosing value method and BCM-IDG algorithm with best cost-saving choosing value method.Simulation results verify that,the BCM-IDG algorithm performs better cost-saving effect than the RM-IDG algorithm,while the RM-IDG algorithm performs better privacy protection effect than the BCM-IDG algorithm under the same data granularity.The two IDG algorithms provide the best privacy protection and electricity saving effects when the data granularity is maximized.