Recently, smart grid solutions have started to extend the visibility of the electrical grid to the entire network; including high voltage transmission lines, medium voltage distribution networks, and the low voltage n...Recently, smart grid solutions have started to extend the visibility of the electrical grid to the entire network; including high voltage transmission lines, medium voltage distribution networks, and the low voltage networks to households. The typical data monitored includes： voltage, current, phase, and power measurements, together with network events and alarms. This paper analyses the key challenges facing smart grid solutions in providing effective access to large volumes of sensory data that is distributed over a large geographic area. A case study is described that outlines how the use of geospatial technology together with Web 2.0 technologies may be applied to improve user access and control to this data. The results show that a geospatial solution provides an effective mechanism for visualizing telemetry data monitored within the smart grid.展开更多
This paper presents a novel transient current differential algorithm for earth fault detection in unearthed （isolated） and compensated neutral medium voltage （MV） networks. The proposed algorithm uses the transien...This paper presents a novel transient current differential algorithm for earth fault detection in unearthed （isolated） and compensated neutral medium voltage （MV） networks. The proposed algorithm uses the transient residual currents, which are very sensitive for earth faults detection. The transient values of residual currents are calculated for each feeder in the network and used as an earth fault indicator. The flow of residual currents is investigated. It is found that the residual current for the faulted feeder is equal to the summation of all residual currents for all other healthy feedersl Based on this investigation, a differential technique is proposed. A percentage restrain performance is proposed to ensure the selectivity and security of the algorithm. The transient algorithm is very sensitive for earth fault incidence. To apply the proposed algorithm, the residual currents can be measured easily by one sensor for each feeder with no need to voltage measurement. The proposed algorithm is less dependent on the fault resistance and the faulted feeder parameters. The network is simulated by ATP/EMTP program. Different fault conditions are covered in the simulation process： different fault inception angles, fault locations and fault resistances.展开更多
This paper studies an existing 13.8 kilovolt distribution network which, serves an oil production field spread over an area of approximately 60 kilometers square, in order to locate any fault that may occur anywhere i...This paper studies an existing 13.8 kilovolt distribution network which, serves an oil production field spread over an area of approximately 60 kilometers square, in order to locate any fault that may occur anywhere in the network using fuzzy c-mean classification techniques. In addition, Sections 5 and 6 introduce two different methods for normalizing data and selecting the optimum number of clusters in order to classify data. Results and conclusions are given to show the feasibility for the suggested fault location method. Suggestion for future related research has been provided in Section 8.展开更多
文摘Recently, smart grid solutions have started to extend the visibility of the electrical grid to the entire network; including high voltage transmission lines, medium voltage distribution networks, and the low voltage networks to households. The typical data monitored includes： voltage, current, phase, and power measurements, together with network events and alarms. This paper analyses the key challenges facing smart grid solutions in providing effective access to large volumes of sensory data that is distributed over a large geographic area. A case study is described that outlines how the use of geospatial technology together with Web 2.0 technologies may be applied to improve user access and control to this data. The results show that a geospatial solution provides an effective mechanism for visualizing telemetry data monitored within the smart grid.
文摘This paper presents a novel transient current differential algorithm for earth fault detection in unearthed （isolated） and compensated neutral medium voltage （MV） networks. The proposed algorithm uses the transient residual currents, which are very sensitive for earth faults detection. The transient values of residual currents are calculated for each feeder in the network and used as an earth fault indicator. The flow of residual currents is investigated. It is found that the residual current for the faulted feeder is equal to the summation of all residual currents for all other healthy feedersl Based on this investigation, a differential technique is proposed. A percentage restrain performance is proposed to ensure the selectivity and security of the algorithm. The transient algorithm is very sensitive for earth fault incidence. To apply the proposed algorithm, the residual currents can be measured easily by one sensor for each feeder with no need to voltage measurement. The proposed algorithm is less dependent on the fault resistance and the faulted feeder parameters. The network is simulated by ATP/EMTP program. Different fault conditions are covered in the simulation process： different fault inception angles, fault locations and fault resistances.
文摘This paper studies an existing 13.8 kilovolt distribution network which, serves an oil production field spread over an area of approximately 60 kilometers square, in order to locate any fault that may occur anywhere in the network using fuzzy c-mean classification techniques. In addition, Sections 5 and 6 introduce two different methods for normalizing data and selecting the optimum number of clusters in order to classify data. Results and conclusions are given to show the feasibility for the suggested fault location method. Suggestion for future related research has been provided in Section 8.
