根据电力系统的各种量测信息,智能电网采用状态估计得出电网当前的运行状态,因此精确的状态估计对维持智能电网的合法操作至关重要。虚假数据注入攻击可以篡改由数据采集与监控系统采集到的测量信息,对电网状态估计造成安全威胁。现有...根据电力系统的各种量测信息,智能电网采用状态估计得出电网当前的运行状态,因此精确的状态估计对维持智能电网的合法操作至关重要。虚假数据注入攻击可以篡改由数据采集与监控系统采集到的测量信息,对电网状态估计造成安全威胁。现有多数虚假数据注入攻击是基于已知电网拓扑结构,而在未知电网拓扑结构的情况下构造高性能的虚假数据注入攻击更具有现实意义。提出一种盲在线虚假数据注入攻击方法,采用核主成分分析（kernel principal component analysis,KPCA）在尽可能多的保留数据内部非线性关系的情况下,把测量数据向量通过核函数投影到高维空间,在高维空间对测量数据进行线性变换,因此可求得近似电网拓扑结构矩阵,并且该方法只需要使用少量的测量值便可构造在线攻击。最后在IEEE 14节点和118节点标准测试系统中进行大量仿真实验,并与完美攻击、随机攻击和其他盲攻击进行比较分析,验证了所提攻击方法的有效性。展开更多
The building sector and its heating and cooling represents one of the major consumer of energy worldwide. Simultaneously, the share of fluctuating generation of renewable energies in the energy mix increases. Therefor...The building sector and its heating and cooling represents one of the major consumer of energy worldwide. Simultaneously, the share of fluctuating generation of renewable energies in the energy mix increases. Therefore storage and demand side management technologies are required. The new adaptive and predictive control algorithm for thermally activated building systems （TABS） based on multiple linear regression （AMLR） presented in this paper enables the application of demand side management （DSM） strategies. Based on simulations, different strategies have been compared with each other. By applying the AMLR algorithm, electricity energy cost savings of 38% could be achieved compared to the conventional control strategy for TABS, while increasing the thermal comfort. At the same time, thermal energy demand can be reduced in the range between 4% to 8%, and pump operation time from 86% to 89%.展开更多
文摘根据电力系统的各种量测信息,智能电网采用状态估计得出电网当前的运行状态,因此精确的状态估计对维持智能电网的合法操作至关重要。虚假数据注入攻击可以篡改由数据采集与监控系统采集到的测量信息,对电网状态估计造成安全威胁。现有多数虚假数据注入攻击是基于已知电网拓扑结构,而在未知电网拓扑结构的情况下构造高性能的虚假数据注入攻击更具有现实意义。提出一种盲在线虚假数据注入攻击方法,采用核主成分分析（kernel principal component analysis,KPCA）在尽可能多的保留数据内部非线性关系的情况下,把测量数据向量通过核函数投影到高维空间,在高维空间对测量数据进行线性变换,因此可求得近似电网拓扑结构矩阵,并且该方法只需要使用少量的测量值便可构造在线攻击。最后在IEEE 14节点和118节点标准测试系统中进行大量仿真实验,并与完美攻击、随机攻击和其他盲攻击进行比较分析,验证了所提攻击方法的有效性。
基金supported by the Ministry of Science,Research and Arts(MWK)of Baden-Württemberg,Germany,as part of a Ph.D.scholarship
文摘The building sector and its heating and cooling represents one of the major consumer of energy worldwide. Simultaneously, the share of fluctuating generation of renewable energies in the energy mix increases. Therefore storage and demand side management technologies are required. The new adaptive and predictive control algorithm for thermally activated building systems （TABS） based on multiple linear regression （AMLR） presented in this paper enables the application of demand side management （DSM） strategies. Based on simulations, different strategies have been compared with each other. By applying the AMLR algorithm, electricity energy cost savings of 38% could be achieved compared to the conventional control strategy for TABS, while increasing the thermal comfort. At the same time, thermal energy demand can be reduced in the range between 4% to 8%, and pump operation time from 86% to 89%.
