Phasor measurement units(PMUs) can provide real-time measurement data to construct the ubiquitous electric of the Internet of Things. However, due to complex factors on site, PMU data can be easily compromised by inte...Phasor measurement units(PMUs) can provide real-time measurement data to construct the ubiquitous electric of the Internet of Things. However, due to complex factors on site, PMU data can be easily compromised by interference or synchronization jitter. It will lead to various levels of PMU data quality issues, which can directly affect the PMU-based application and even threaten the safety of power systems. In order to improve the PMU data quality, a data-driven PMU bad data detection algorithm based on spectral clustering using single PMU data is proposed in this paper. The proposed algorithm does not require the system topology and parameters. Firstly, a data identification method based on a decision tree is proposed to distinguish event data and bad data by using the slope feature of each data. Then, a bad data detection method based on spectral clustering is developed. By analyzing the weighted relationships among all the data, this method can detect the bad data with a small deviation. Simulations and results of field recording data test illustrate that this data-driven method can achieve bad data identification and detection effectively. This technique can improve PMU data quality to guarantee its applications in the power systems.展开更多
Efficient utilization of energy resources is essential for a developing country like India. The concept of smart grid （SG） can provide a highly reliable power system with optimized utilization of available resources...Efficient utilization of energy resources is essential for a developing country like India. The concept of smart grid （SG） can provide a highly reliable power system with optimized utilization of available resources. The present Indian power grid requires revolutionary changes to meet the growing demands and to make the grid smarter and reliable. One of the important requirements for SG is the instantaneous monitoring of the voltage, current and power flows at all buses in the grid. The traditional monitoring system cannot satisfy this requirement since they are based on nonlinear power flow equations. Synchro-phasor-measurement devices like phasor mea- surement units （PMUs） can measure the phasor values of voltages at installed buses. Consequently, the currents passing through all branches connected to that bus can be computed. Since the voltage phasor values at the neighboring buses of a bus containing the PMU can be estimated using Ohm＇s law, it is redundant to install PMUs at all the buses in a power grid for its complete observability. This paper proposes the optimal geographi- cal locations for the PMUs in southern region Indian power grid for the implementation of SG, using Integer Linear Programming. The proposed optimal geographical locations for PMU placement can be a stepping stone for the implementation of SG in India.展开更多
Conventional power grids across the globe are reforming to smart power grids with cutting edge technologies in real time monitoring and control methods. Advanced real time monitoring is facilitated by incorpor- ating ...Conventional power grids across the globe are reforming to smart power grids with cutting edge technologies in real time monitoring and control methods. Advanced real time monitoring is facilitated by incorpor- ating synchrophasor measurement units such as phasor measurement units （PMUs） to the power grid monitoring system. Several physical and economic constraints limit the deployment of PMUs in smart power grids. This paper proposes a pragmatic multi-stage simulated annealing （PMSSA） methodology for finding the optimal locations in the smart power grid for installing PMUs in conjunction with existing conventional measurement units （CMUs） to achieve a complete observability of the grid. The proposed PMSSA is much faster than the conventional simulated annealing （SA） approach as it utilizes controlled uphill and downhill movements during various stages of optimiza- tion. Moreover, the method of integrating practical phasor measurement unit （PMU） placement conditions like PMU channel limits and redundant placement can be easily handled. The efficacy of the proposed methodology has been validated through simulation studies in IEEE standard bus systems and practical regional Indian power grids.展开更多
基金supported by the National Key R&D Program (No.2017YFB0902901)the National Natural Science Foundation of China (No.51627811,No.51725702,and No.51707064)。
文摘Phasor measurement units(PMUs) can provide real-time measurement data to construct the ubiquitous electric of the Internet of Things. However, due to complex factors on site, PMU data can be easily compromised by interference or synchronization jitter. It will lead to various levels of PMU data quality issues, which can directly affect the PMU-based application and even threaten the safety of power systems. In order to improve the PMU data quality, a data-driven PMU bad data detection algorithm based on spectral clustering using single PMU data is proposed in this paper. The proposed algorithm does not require the system topology and parameters. Firstly, a data identification method based on a decision tree is proposed to distinguish event data and bad data by using the slope feature of each data. Then, a bad data detection method based on spectral clustering is developed. By analyzing the weighted relationships among all the data, this method can detect the bad data with a small deviation. Simulations and results of field recording data test illustrate that this data-driven method can achieve bad data identification and detection effectively. This technique can improve PMU data quality to guarantee its applications in the power systems.
文摘Efficient utilization of energy resources is essential for a developing country like India. The concept of smart grid （SG） can provide a highly reliable power system with optimized utilization of available resources. The present Indian power grid requires revolutionary changes to meet the growing demands and to make the grid smarter and reliable. One of the important requirements for SG is the instantaneous monitoring of the voltage, current and power flows at all buses in the grid. The traditional monitoring system cannot satisfy this requirement since they are based on nonlinear power flow equations. Synchro-phasor-measurement devices like phasor mea- surement units （PMUs） can measure the phasor values of voltages at installed buses. Consequently, the currents passing through all branches connected to that bus can be computed. Since the voltage phasor values at the neighboring buses of a bus containing the PMU can be estimated using Ohm＇s law, it is redundant to install PMUs at all the buses in a power grid for its complete observability. This paper proposes the optimal geographi- cal locations for the PMUs in southern region Indian power grid for the implementation of SG, using Integer Linear Programming. The proposed optimal geographical locations for PMU placement can be a stepping stone for the implementation of SG in India.
文摘Conventional power grids across the globe are reforming to smart power grids with cutting edge technologies in real time monitoring and control methods. Advanced real time monitoring is facilitated by incorpor- ating synchrophasor measurement units such as phasor measurement units （PMUs） to the power grid monitoring system. Several physical and economic constraints limit the deployment of PMUs in smart power grids. This paper proposes a pragmatic multi-stage simulated annealing （PMSSA） methodology for finding the optimal locations in the smart power grid for installing PMUs in conjunction with existing conventional measurement units （CMUs） to achieve a complete observability of the grid. The proposed PMSSA is much faster than the conventional simulated annealing （SA） approach as it utilizes controlled uphill and downhill movements during various stages of optimiza- tion. Moreover, the method of integrating practical phasor measurement unit （PMU） placement conditions like PMU channel limits and redundant placement can be easily handled. The efficacy of the proposed methodology has been validated through simulation studies in IEEE standard bus systems and practical regional Indian power grids.
