This paper describes a micro-grid system and its monitoring system. This micro-grid system consists of generation systems, consumer electrical equipments, auxiliary equipments and the monitoring system. All the equipm...This paper describes a micro-grid system and its monitoring system. This micro-grid system consists of generation systems, consumer electrical equipments, auxiliary equipments and the monitoring system. All the equipments have 485 communication interfaces. In order to monitor and manage this micro-grid system, we built a monitoring system, which contains modular instrument system and industrial personal computer. In order to keep real time, we adopt some measures in software and hardware. We adopt LABVIEW and its program modules in software and adopt modular instrument system in hardware. Supporting by the software and hardware, the micro-grid system can be safe and stable.展开更多
This paper presents an algorithm based on Thevenin equivalent network for voltage stability evaluation. The proposed algorithm provides a technique for online predicting the largest possible margin to voltage collapse...This paper presents an algorithm based on Thevenin equivalent network for voltage stability evaluation. The proposed algorithm provides a technique for online predicting the largest possible margin to voltage collapse of an electrical power system. An online maximum loadability determination algorithm is developed by transforming the impedance margin, obtained from the Thevenin equivalent network, into the loading margin at each of the load buses in a power system. Furthermore, the proposed algorithm also takes system load trends into account for practical applications. The effectiveness of the proposed algorithm is tested on the IEEE 14 and 57 bus test systems. Simulation results have shown that the proposed algorithm is useful and practical for online voltage instability monitoring.展开更多
The state-of-the-art query techniques in power grid monitoring systems focus on querying history data, which typically introduces an unwanted lag when the systems try to discover emergency situations. The monitoring d...The state-of-the-art query techniques in power grid monitoring systems focus on querying history data, which typically introduces an unwanted lag when the systems try to discover emergency situations. The monitoring data of large-scale smart grids are massive, dynamic and highly dimensional, so global query, the method widely adopted in continuous queries in Wireless Sensor Networks(WSN), is rendered not suitable for its high energy consumption. The situation is even worse with increasing application complexity. We propose an energy-efficient query technique for large-scale smart grids based on variable regions. This method can query an arbitrary region based on variable physical windows, and optimizes data retrieve paths by a key nodes selection strategy. According to the characteristics of sensing data, we introduce an efficient filter into the each query subtree to keep non-skyline data from being retrieved. Experimental results show that our method can efficiently return the overview situation of any query region. Compared to TAG and ESA, the average query efficiency of our approach is improved by 79% and 46%, respectively; the total energy consumption of regional query is decreased by 82% and 50%, respectively.展开更多
The most important elements of “intellectual networks” (Smart Grid) are the systems of monitoring the parameters of electrical equipment. Information-measuring systems (IMS), which described in this paper, were prop...The most important elements of “intellectual networks” (Smart Grid) are the systems of monitoring the parameters of electrical equipment. Information-measuring systems (IMS), which described in this paper, were proposed to use together with rapid digital protection against short-circuit regimes in transformer windings. This paper presents an application’s experience of LVI-testing, some results of the use of Frequency Response Analysis (FRA) to check the condition of transformer windings and infra-red control results of electrical equipment. The LVI method and short-circuit inductive reactance measurements are sensitive for detecting such faults as radial, axial winding deformations, a twisting of low-voltage or regulating winding, a losing of winding’s pressing and others.展开更多
After the attacks on September 11, 2001 and the follow-up risk assessments by utilities across the United States, securing the water distribution system against malevolent attack became a strategic goal for the U.S. E...After the attacks on September 11, 2001 and the follow-up risk assessments by utilities across the United States, securing the water distribution system against malevolent attack became a strategic goal for the U.S. Environmental Protection Agency. Following 3 years of development work on a Contamination Warning System (CWS) at the Greater Cincinnati Water Works, four major cities across the United States were selected to enhance the CWS development conducted by the USEPA. One of the major efforts undertaken was to develop a process to seamlessly process “Big Data” sets in real time from different sources (online water quality monitoring, consumer complaints, enhanced security, public health surveillance, and sampling and analysis) and graphically display actionable information for operators to evaluate and respond to appropriately. The most significant finding that arose from the development and implementation of the “dashboard” were the dual benefits observed by all four utilities: the ability to enhance their operations and improve the regulatory compliance of their water distribution systems. Challenge: While most of the utilities had systems in place for SCADA, Work Order Management, Laboratory Management, 311 Call Center Management, Hydraulic Models, Public Health Monitoring, and GIS, these systems were not integrated, resulting in duplicate data entry, which made it difficult to trace back to a “single source of truth.” Each one of these data sources can produce a wealth of raw data. For most utilities, very little of this data is being translated into actionable information as utilities cannot overwhelm their staffs with manually processing the mountains of data generated. Instead, utilities prefer to provide their staffs with actionable information that is easily understood and provides the basis for rapid decision-making. Smart grid systems were developed so utilities can essentially find the actionable needle in the haystack of data. Utilities can then focus on rapidly evaluating the new information, compare it known activities occurring in the system, and identify the correct level of response required. Solution: CH2M HILL was engaged to design, implement, integrate, and deploy a unified spatial dashboard/smart grid system. This system included the processes, technology, automation, and governance necessary to link together the disparate systems in real time and fuse these data streams to the GIS. The overall solution mapped the business process involved with the data collection, the information flow requirements, and the system and application requirements. With these fundamentals defined, system integration was implemented to ensure that the individual systems worked together, eliminating need for duplicate data entry and manual processing. The spatial dashboard was developed on top of the integration platform, allowing the underlying component data streams to be visualized in a spatial setting. Result: With the smart grid system in place, the utilities had a straightforward method to determine the true operating conditions of their systems in real time, quickly identify a potential non-compliance problem in the early stages, and improve system security. The smart grid system has freed staff to focus on improving water quality through the automation of many mundane daily tasks. The system also plays an integral role in monitoring and optimizing the utilities’ daily operations and has been relied on during recovery operations, such as those in response to recent Superstorm Sandy. CH2M HILL is starting to identify the processes needed to expand the application of the smart grid system to include real-time water demands using AMI/AMR and real-time energy loads from pumping facilities. Once the smart grid system has been expanded to include Quality-Quantity-Energy, CH2M HILL can apply optimization engines to provide utility operations staffs with a true optimization tool for their water systems.展开更多
This paper presents a preliminary study of developing a novel distributed adaptive real-time learning framework for wide area monitoring of power systems integrated with distributed generations using synchrophasor tec...This paper presents a preliminary study of developing a novel distributed adaptive real-time learning framework for wide area monitoring of power systems integrated with distributed generations using synchrophasor technology. The framework comprises distributed agents (synchrophasors) for autonomous local condition monitoring and fault detection, and a central unit for generating global view for situation awareness and decision making. Key technologies that can be integrated into this hierarchical distributed learning scheme are discussed to enable real-time information extraction and knowledge discovery for decision making, without explicitly accumulating and storing all raw data by the central unit. Based on this, the configuration of a wide area monitoring system of power systems using synchrophasor technology, and the functionalities for locally installed open-phasor-measurement-units (OpenPMUs) and a central unit are presented. Initial results on anti-islanding protection using the proposed approach are given to illustrate the effectiveness.展开更多
The Smart Grid has three main characteristics, which are to some degree antagonistic. These characteristics are: provision of good power quality, energy cost reduction and improvement in the reliability of the grid. T...The Smart Grid has three main characteristics, which are to some degree antagonistic. These characteristics are: provision of good power quality, energy cost reduction and improvement in the reliability of the grid. The need to ensure that they can be accomplished together demands a much richer ICT monitoring and control network than the current system. In this paper we particularly investigate the design and deployment of the ICT system in the urban environment, specifically in a university campus that is embedded in a city, thus it represents the Neighbourhood Area Network (NAN) level of the Smart Grid. In order to design an ICT infrastructure, we have introduced two related architectures: namely communications network architecture and a software architecture. Having access to the characteristics of a real NAN guides us to choose appropriate communication technologies and identify the actual requirements of the system. To implement these architectures at this level we need to gather and process information from environmental sensors (monitoring e.g. temperature, movement of people and vehicles) that can provide useful information about changes in the loading of the NAN, with information from instrumentation of the Power Grid itself. Energy constraints are one of the major limitations of the communication network in the Smart Grid, especially where wireless networking is proposed. Thus we analyse the most energy efficient method of collecting and sending data. The main contribution of this research is that we propose and implement an energy efficient ICT network and describe our software architecture at the NAN level, currently very underdeveloped. We also discuss our experimental results. To our knowledge, no such architectures have yet been implemented for collecting data which can provide the basis of Decision Support Tools (DSTs).展开更多
文摘This paper describes a micro-grid system and its monitoring system. This micro-grid system consists of generation systems, consumer electrical equipments, auxiliary equipments and the monitoring system. All the equipments have 485 communication interfaces. In order to monitor and manage this micro-grid system, we built a monitoring system, which contains modular instrument system and industrial personal computer. In order to keep real time, we adopt some measures in software and hardware. We adopt LABVIEW and its program modules in software and adopt modular instrument system in hardware. Supporting by the software and hardware, the micro-grid system can be safe and stable.
文摘This paper presents an algorithm based on Thevenin equivalent network for voltage stability evaluation. The proposed algorithm provides a technique for online predicting the largest possible margin to voltage collapse of an electrical power system. An online maximum loadability determination algorithm is developed by transforming the impedance margin, obtained from the Thevenin equivalent network, into the loading margin at each of the load buses in a power system. Furthermore, the proposed algorithm also takes system load trends into account for practical applications. The effectiveness of the proposed algorithm is tested on the IEEE 14 and 57 bus test systems. Simulation results have shown that the proposed algorithm is useful and practical for online voltage instability monitoring.
基金Supported by National Natural Science Foundation Of China （60873235, 60473099）, Science-Technology Development Key Project of Jilin Province of China （20080318）, and Program of New Century Excellent Talents in University of China （NCET-06-0300）
基金The National Natural Science Foundation of China under Grant No.60402011the National Eleven Five-Year Scientific and Technical Support Plans of China under Grant No.2006BAH03B05~~
基金supported by the National Natural Science Foundation of China (NO. 61472072, 61528202, 61501105, 61472169)the Foundation of Science Public Welfare of Liaoning Province in China (NO. 2015003003)
文摘The state-of-the-art query techniques in power grid monitoring systems focus on querying history data, which typically introduces an unwanted lag when the systems try to discover emergency situations. The monitoring data of large-scale smart grids are massive, dynamic and highly dimensional, so global query, the method widely adopted in continuous queries in Wireless Sensor Networks(WSN), is rendered not suitable for its high energy consumption. The situation is even worse with increasing application complexity. We propose an energy-efficient query technique for large-scale smart grids based on variable regions. This method can query an arbitrary region based on variable physical windows, and optimizes data retrieve paths by a key nodes selection strategy. According to the characteristics of sensing data, we introduce an efficient filter into the each query subtree to keep non-skyline data from being retrieved. Experimental results show that our method can efficiently return the overview situation of any query region. Compared to TAG and ESA, the average query efficiency of our approach is improved by 79% and 46%, respectively; the total energy consumption of regional query is decreased by 82% and 50%, respectively.
文摘The most important elements of “intellectual networks” (Smart Grid) are the systems of monitoring the parameters of electrical equipment. Information-measuring systems (IMS), which described in this paper, were proposed to use together with rapid digital protection against short-circuit regimes in transformer windings. This paper presents an application’s experience of LVI-testing, some results of the use of Frequency Response Analysis (FRA) to check the condition of transformer windings and infra-red control results of electrical equipment. The LVI method and short-circuit inductive reactance measurements are sensitive for detecting such faults as radial, axial winding deformations, a twisting of low-voltage or regulating winding, a losing of winding’s pressing and others.
基金This work Science Foundation of China is supported by the National （No.60273085）, the State High-tech Research and Development Project （No.2001AA111081） and the ChinaGrid Project of China （No.CG2003-GA002）.
文摘After the attacks on September 11, 2001 and the follow-up risk assessments by utilities across the United States, securing the water distribution system against malevolent attack became a strategic goal for the U.S. Environmental Protection Agency. Following 3 years of development work on a Contamination Warning System (CWS) at the Greater Cincinnati Water Works, four major cities across the United States were selected to enhance the CWS development conducted by the USEPA. One of the major efforts undertaken was to develop a process to seamlessly process “Big Data” sets in real time from different sources (online water quality monitoring, consumer complaints, enhanced security, public health surveillance, and sampling and analysis) and graphically display actionable information for operators to evaluate and respond to appropriately. The most significant finding that arose from the development and implementation of the “dashboard” were the dual benefits observed by all four utilities: the ability to enhance their operations and improve the regulatory compliance of their water distribution systems. Challenge: While most of the utilities had systems in place for SCADA, Work Order Management, Laboratory Management, 311 Call Center Management, Hydraulic Models, Public Health Monitoring, and GIS, these systems were not integrated, resulting in duplicate data entry, which made it difficult to trace back to a “single source of truth.” Each one of these data sources can produce a wealth of raw data. For most utilities, very little of this data is being translated into actionable information as utilities cannot overwhelm their staffs with manually processing the mountains of data generated. Instead, utilities prefer to provide their staffs with actionable information that is easily understood and provides the basis for rapid decision-making. Smart grid systems were developed so utilities can essentially find the actionable needle in the haystack of data. Utilities can then focus on rapidly evaluating the new information, compare it known activities occurring in the system, and identify the correct level of response required. Solution: CH2M HILL was engaged to design, implement, integrate, and deploy a unified spatial dashboard/smart grid system. This system included the processes, technology, automation, and governance necessary to link together the disparate systems in real time and fuse these data streams to the GIS. The overall solution mapped the business process involved with the data collection, the information flow requirements, and the system and application requirements. With these fundamentals defined, system integration was implemented to ensure that the individual systems worked together, eliminating need for duplicate data entry and manual processing. The spatial dashboard was developed on top of the integration platform, allowing the underlying component data streams to be visualized in a spatial setting. Result: With the smart grid system in place, the utilities had a straightforward method to determine the true operating conditions of their systems in real time, quickly identify a potential non-compliance problem in the early stages, and improve system security. The smart grid system has freed staff to focus on improving water quality through the automation of many mundane daily tasks. The system also plays an integral role in monitoring and optimizing the utilities’ daily operations and has been relied on during recovery operations, such as those in response to recent Superstorm Sandy. CH2M HILL is starting to identify the processes needed to expand the application of the smart grid system to include real-time water demands using AMI/AMR and real-time energy loads from pumping facilities. Once the smart grid system has been expanded to include Quality-Quantity-Energy, CH2M HILL can apply optimization engines to provide utility operations staffs with a true optimization tool for their water systems.
文摘This paper presents a preliminary study of developing a novel distributed adaptive real-time learning framework for wide area monitoring of power systems integrated with distributed generations using synchrophasor technology. The framework comprises distributed agents (synchrophasors) for autonomous local condition monitoring and fault detection, and a central unit for generating global view for situation awareness and decision making. Key technologies that can be integrated into this hierarchical distributed learning scheme are discussed to enable real-time information extraction and knowledge discovery for decision making, without explicitly accumulating and storing all raw data by the central unit. Based on this, the configuration of a wide area monitoring system of power systems using synchrophasor technology, and the functionalities for locally installed open-phasor-measurement-units (OpenPMUs) and a central unit are presented. Initial results on anti-islanding protection using the proposed approach are given to illustrate the effectiveness.
文摘The Smart Grid has three main characteristics, which are to some degree antagonistic. These characteristics are: provision of good power quality, energy cost reduction and improvement in the reliability of the grid. The need to ensure that they can be accomplished together demands a much richer ICT monitoring and control network than the current system. In this paper we particularly investigate the design and deployment of the ICT system in the urban environment, specifically in a university campus that is embedded in a city, thus it represents the Neighbourhood Area Network (NAN) level of the Smart Grid. In order to design an ICT infrastructure, we have introduced two related architectures: namely communications network architecture and a software architecture. Having access to the characteristics of a real NAN guides us to choose appropriate communication technologies and identify the actual requirements of the system. To implement these architectures at this level we need to gather and process information from environmental sensors (monitoring e.g. temperature, movement of people and vehicles) that can provide useful information about changes in the loading of the NAN, with information from instrumentation of the Power Grid itself. Energy constraints are one of the major limitations of the communication network in the Smart Grid, especially where wireless networking is proposed. Thus we analyse the most energy efficient method of collecting and sending data. The main contribution of this research is that we propose and implement an energy efficient ICT network and describe our software architecture at the NAN level, currently very underdeveloped. We also discuss our experimental results. To our knowledge, no such architectures have yet been implemented for collecting data which can provide the basis of Decision Support Tools (DSTs).
