Research On Privacy Preserving Issues In Smart Grids

As the next-generation energy network solution,smart grid technology can effectively im-prove the stability,reliability,and economy of the power system,by integrating modern advanced communications,computing and control technologies into the conventional power generation,transmission,distribution and consumption sectors.In order to realize the real-time monitoring and optimization control of the power grid,the smart grid needs to collect the fine-grained data of the energy users,meanwhile.a large amount of data needs to be communicated among the op-erators to ensure the security and stability of the power system under the distributed smart grid architecture,which inevitably gives rise to a series of privacy issues.Related researches show that these data will potentially expose personal privacy information such as energy user’s lifestyle and income status,and critical sensitive parameters such as power generation cost and electricity demand of the operator.In addition,in recent years.cyber security accidents and privacy leak incidents related to the power system have been frequently reported around the world,which has made the issue of privacy preserving of smart grids a hot topic for the governments,academia,and industry.At the present stage,a large number of research efforts have emerged both at home and abroad,trying to propose corresponding privacy preserving strategies to achieve data security in the smart grid from different aspects and perspectives such as anonymization,encryption,load scheduling,and trusted computing.However,existing works are still faced with problems such as high upfront investment,high computing and communication pressure,and data accuracy decline.In view of the shortcomings of existing researches on the privacy preserving in smart grid,this thesis combines the latest research results in this direction of recent years,and takes the privacy preserving issues of smart grids as the core.From three aspects of privacy preserving for the power consumption side,privacy incentive mechanism for utilities,and privacy protection for power providers,effective privacy preserving strategies are proposed to provide effective privacy protection services for all participants of the power system.The main work and contributions are summarized as follows1.Research on privacy preserving load scheduling for continuous loads.In consideration of the problems of big upfront investment and poor economic performance of existing works,we innovatively incorporate both thermostatically controlled load and home batteries into the framework of privacy preserving load scheduling,thereby the privacy preserving margin is increased and the dependence of algorithm performance on battery capacity is reduced We formulate this as a convex optimization problem to minimize the weighed sum of fi-nancial cost,the deviation from the pre-defineed load profile,and the user dissatisfaction.In order to solve the problem effectively and make full use of the redundant computing capaci-ty of household appliances,we decompose the primal problem into a series of subproblems through dual decomposition,and design a stochastic gradient based two-level iterative dis tributed algorithm.The performance of the proposed algorithm is verified by simulations2.Research on privacy preserving load scheduling involving discrete loads.Based on the pre-vious study,we further incorporate discrete loads into the framework of privacy preserving load scheduling.To tackle the NP-hard problem of mixed integer programming introduced by discrete loads,we propose a randomized algorithm to solve the primal problem effi ciently,which can achieve higher computing efficiency at the expense of certain optimality Furthermore,we derive the upper bound of the algorithm’s sub-optimality through rigorous theoretical derivation,and prove the convergence of the algorithm.Simulation results are presented to verify the effectiveness and feasibility of the proposed algorithm,as well as to investigate the influence of key parameters on the performance.3.Research on privacy-preserving incentive mechanism for utility companies based on contract theory.An incentive mechanism based on contract theory to resolve this conflict among the energy users’ privacy requirement,utility companies’ welfare,and laws and regulation,s.In this mechanism,the utility company can provide multiple privacy contracts to energy users without knowing the specific privacy requirement of the users,and maximize the utility’s system performance while satisfying the diversity of privacy requirement.We adopt the concept of differential privacy to quantify the privacy preserving level,and comprehensively consider factors such as the performance of energy theft detectors,data aggregation accuracy,and privacy budget in system performance.Through rigorous theoretical derivation,the number of constraints in mechanism design is reduced,and the computational efficiency is effectively improved.The validity and feasibility of the proposed mechanism are verified by simulations4.Resear-ch on privacy preserving distributed optimal power flow.Aiming at privacy preserv-ing issue in distributed optimal power flow,we propose a privacy-preserving Alternating Direction Method of Multipliers(ADMM)based distributed OPF algorithm by adding s-tochastic noise into the communication messages between neighbor buses and introducing secure function.which can effectively prevent leakage of sensitive information of each oper-ator without affecting the optimality of the algorithm.The analysis on the convergence and optimality of the proposed algorithm is provided through rigorous theoretical derivation,and the validity and feasibility of the proposed algorithm are verified by simulationsIn the end,the thesis is concluded and some possible future research directions are discussed.