Computer Science Research on Smart Grid Information System Architecture Cao Junwei) 2) Wan Yuxin 3 Tu Guojun Zhang Shuqing 4) Xia Ai 3 Liu Xiaofei Chen Zhen 12 Lu Chao 4) Tsinghua University Institute of Information Technology, Beijing 100084) 2) (Tsinghua Trust Science With technology countries.
The smart grid mainly solves the following problems: ensuring grid security, stability and reliability while improving equipment utilization. Due to the high coupling of the power grid system and improper dispatch control, a single fault can cause cascading failures, and even cause large-scale power outages and equipment damage, resulting in inestimable direct and indirect losses. Therefore, the reliability requirements of the grid system are very high. The intelligent scheduling of the smart grid is to solve the problem of collecting, transmitting, analyzing and processing wide-area information on the basis of ensuring security and reliability.
Realize the interaction between power generation and electricity use. The basic feature of the grid is the balance between power generation and electricity use. From the perspective of the network user, the user can obtain the operating parameters of the power grid (such as the cost of power and the power consumption of various devices) through the intelligent power network, thereby adjusting the power usage of the power. For the power grid system, an accurate load model can be constructed according to the power consumption information of the power equipment, thereby effectively improving the power supply efficiency. The construction of the traditional power grid is based on the one-way thinking of the transmission-transmission f, and a large amount of redundancy causes waste. The smart grid is based on a high-real-time (tens of milliseconds) measurement communication system, which can achieve power generation load balance through real-time control. Thereby, the hot spare can be reduced and the stability of the system can be improved.
Intermittent renewable energy access. New energy mainly refers to wind power and photovoltaic power generation. China's wind power resources are mainly concentrated in the northwestern region, and these areas are also areas with abundant solar energy resources.
However, China's power demand is concentrated in the central and eastern regions, so China's new energy power must be transmitted long distances to reach the load zone. This requires the grid to be optimally configured for new energy generation across the country. At the same time, due to the randomness and intermittent nature of new energy power generation, if it is directly integrated into the power grid, it may affect the overall stability of the power grid system. If wind power generation may be disconnected from the network due to objective meteorological reasons, it will cause instantaneous imbalance of the power system, which in turn will affect the overall stability.
It can be seen that the smart grid needs to solve the bottlenecks of traditional grid information systems in information collection, transmission, processing and sharing, and the solution of these problems depends on the evolving Internet of Things technology. The core technology of the Internet of Things covers physical state perception, information representation, information transmission and information processing from the sensor network to the upper application system. It will play an important role in communication, security and upper-layer applications in the smart grid information system. Function: Sensor network technology can be used for data acquisition and information acquisition of communication devices such as smart meters; real-time and secure communication technologies can be used for transmission of grid operating parameters, real-time transmission of grid operation and maintenance data and power generation load data; data The storage and information representation technology 6 can be used for storage, management, query and organization of massive data of the power grid; the data distributed processing and the arbitrary scheduling technology can be used for power system security stability analysis, real-time deployment of energy flow after new energy access. The development of the Internet of Things technology has enabled the power system to be integrated into the computer digital environment from a relatively phase 1 Cao Junwei, etc.: Intelligent grid multiplication system architecture research, closed self-sufficient control system, while improving the stability of the grid, making wind, electric energy, etc. Energy is easily integrated into the smart grid information system for unified planning and scheduling.
Drawing on the information technology architecture of the Internet of Things, this paper proposes the architecture of the smart grid from the perspective of information technology. Section 2 summarizes the definition of smart grid; Section 3 introduces the current status of smart grid development at home and abroad, major technical difficulties and challenges, and proposes a smart grid information system architecture; Section 4, Section 6 details the infrastructure of the Smart Grid Information System, Support platform and application system; Section 7 summarizes and looks forward to the future research direction of smart grid.
2 Smart grids define smart grids, usually referred to as modern grid systems that incorporate modern information systems into traditional grid networks. Therefore, the power grid has better controllability and observability, and solves the problems of low energy utilization, poor interaction, and difficulty in analyzing safety and stability of traditional power systems. At the same time, based on real-time regulation of energy flow, it is convenient for distributed new energy generation and distribution. Access and use of energy storage systems.
The first significant feature of the smart grid is its considerable performance. That is, by means of information network technology, real-time monitoring of information of each node of the power system.
For example, IBM defines the first level of the three levels of smart grid as real-time, comprehensive and detailed monitoring of information, eliminating blind spots in monitoring. “Tsinghua University proposed “CCCP†in the 1980s (communication, computer and control technology in the power system) Applying the concept, the smart grid is the integration and interaction of the two networks of the traditional power system network and the power information network. The same definition also includes related concepts.
Another feature of the smart grid is the dynamic interaction between the two sides of the power generation. That is to use the real-time acquisition of grid power generation information and user information for optimal scheduling. From the point of view of the network users, the goal of the smart grid is to co-ordinate all power resources to provide more stable power to the network users in a cheaper way. For example, Duke Energy proposed that in the smart grid environment, network users can observe their own power consumption in real time and adjust their own electricity habits to reduce costs. At the same time, power companies can deploy according to users' needs. Supply and price guidance to guide users' needs, reducing total energy consumption. The European Smart Grid Strategic Development Plan proposes that the smart grid should integrate all the users, generators and two-way equipment connected to the grid, and strengthen the control of the power generation side through intelligent monitoring, communication and self-healing technologies, and provide users with more information. And electricity optimization programs to reduce the impact of the power system on the environment, improve the reliability and safety of power supply.
The third feature of the smart grid is its high reliability. That is, it can be automatically recovered from the system oscillation, and the system is alarmed and adjusted in advance for the system instability trend. For example, the US Department of Energy defines smart grids with features such as system oscillation self-recovery, high robustness, and security. The third level of the three levels of smart grid defined by IBM is to conduct advanced analysis based on information integration to achieve the goal of improving reliability, reducing costs, and improving revenue and efficiency.
Based on the above viewpoints, we define the smart grid as follows: Smart grid is a comprehensive composite system integrating sensing, communication, calculation, decision-making and control built on the basis of traditional power grid. The operation status of the node resources and equipment, hierarchical management and power allocation, to achieve a high degree of integration of energy flow, information flow and industrial labor, improve the operational stability of the power system, in order to maximize the efficiency of equipment utilization, Improve safety and reliability, save energy and reduce emissions, improve the quality of power supply for users, and improve the utilization efficiency of renewable energy. The most important goal of the smart grid is to reduce energy consumption costs, improve the quality of residential electricity consumption, and reduce the operating cost of electricity, thereby promoting the development of the national economy.
3 Status and Challenges of Smart Grid Development 3.1 Development Status of Smart Grid at Home and Abroad In 2001, the CIN/SI project was launched, and a modeling, simulation, analysis and synthesis tool was developed to establish high robustness, high adaptability and control. Reconstructed networked power systems and infrastructure, introduced in June 2001 by "Wred", is an earlier reference to the construction of smart energy networks. After that, the American Electric Power Research Institute launched the IntelUGrul project and released the IntelUGml1 architecture in 2004. GE, Cisco, and Lucent participated in the research and development of the project. The project aims to integrate energy systems and control information systems in power systems, and to provide implementation steps and technical guidance on how to build smart grids from the perspectives of power information systems and service models. In 2003, the US Department of Energy released the grid 2030 Blue Dragonfly and in the same year led the establishment of the GridWise2 Alliance, which aims to promote the integration of traditional power systems and information technology to build a new smart grid. At present, members include IBM, Sco, West Gate, GE, Microsoft, Samsung and more than 140 companies in the energy and information fields. In March 2008, Xcel Energy Corporation of the United States announced the establishment of a smart grid city pilot project in Boulder, Colorado. Currently, 23,000 intelligent monitoring devices have been installed to provide users with more convenient and stable power supply and help users save money. Electricity costs. In May 2011, the United States established a new smart grid pilot in Maui, Hawaii. In general, the development of smart grid technology in the United States focuses on the integration of communication technology, control technology and power system, while emphasizing the interaction between network users and grid systems. The US Department of Energy's Smart Grid Report 2009 indicates that building a smart grid system should be carried out in six areas: transmission systems, distributed energy, power distribution systems, information networks, management, and financial environments.
The construction plan of the European smart grid began in 2004. At the first International Conference on Renewable Energy and Distributed Energy Integration, industry and research stakeholders proposed the idea of ​​establishing a future European power network technology platform. In 2005, with the support of the European Commission, Europe established the Smart Grid European Technology Platform to provide planning for the development of European power networks in 2020 and beyond. The organization released the European Smart Grid Design Blueprint in 2006, proposing that the smart grid must include four objectives: flexibility, accessibility, reliability and economy. The accessibility section specifically mentions renewable energy and Access to efficient low-carbon capacity. At the end of 2008, the organization released the European Smart Grid Strategic Development Plan and released the most comprehensive version in April 2010. The European smart grid development was prioritized into six levels, covering grid optimization, distributed energy, and information and communication technologies. To market operations and other aspects. All targets will be completed around 2020, with the first phase of the goal (optimizing grid operations and usage) in 2008 2012 to address grid operation, safety and market-oriented energy flow control issues in a distributed environment. In April 2009, Sakamoto announced the “Sakamoto Development Strategy and Economic Long-Term Planâ€, which includes solar power grid-connected, future smart grid power grid test, and electric vehicle fast charging device, which are closely related to the smart grid. The Sakamoto Electric Business Association said in July 2009 that it will fully develop the "Spirit Edition Smart Grid". South Korea released the "Green Energy Industry Strategy" in 2008 and launched the "Korean version of the Smart Grid".
Imagine.
In China, in May 2009, the State Grid Corporation of China proposed the development plan of China's smart grid, which will promote the construction of China's smart grid in three phases and plan to build a unified smart grid in 2020; from the grid itself to security and stability, energy scheduling, Eight aspects of user interaction and new power applications give the characteristics of China's future smart grid. North China Power Grid Corporation announced the pilot community in April 2009. In 2008, China Southern Power Grid Corporation became a wide-area damping control system, which is the world's first wide-area closed-loop intelligent control system that has been successfully implemented. The system is based on wide-area closed-loop control that is adaptive by the synchronized phasor measurement unit. As of 2009, China has imported more than 1,000 PMU nodes in Northeast China, North China, Central China, Jiangsu, East China, Henan, Yunnan, Lizhou, Guangdong and South China, and established more than 10 WAMS central stations, covering 500kV substations. And major power plants, more than the United States in this regard.
There are also a number of units in the university that are conducting research on smart grids. For example, the team led by Academician Han Yingjun of Tsinghua University has achieved certain results in the monitoring of wide-area power grids, and solved the key technical problems in the wide-area damping control project, and proposed cooperation with Sifang Group. A power system security early warning, defense and control system construction scheme based on wide area information. The team led by Academician Yu Xinxin of Tianjin University has made certain progress in the distributed generation function system, and put forward the technical idea of ​​connecting the distributed generation function system of solar energy, wind energy and small water energy into the large power grid in the form of microgrid. Improve energy transmission efficiency and power transmission stability and reliability, improve power quality and reduce costs.
Overall, the current research on smart grids focuses on the access of distributed energy and the interaction of power generation. The research work of smart grids in China focuses on the information acquisition and stability control of large grid systems, which is compatible with China's power network. Strong characteristics are related.
3.2 Status and main problems of grid information system The existing grid information system (power secondary system) mainly refers to the power dispatching automation network and its energy management system EMS (Energy Management System), distribution network management system DMS (Distribution Management System) and wide area monitoring System WAMS. Energy management system mainly includes data acquisition (Acquisition), automatic power generation control system AGC (AutomaticGamControl) and power state estimation system; distribution network management system mainly includes distribution automation system DAS (Dstrbuion Information System) and demand side management system DSM ( DemandSideManagement), etc.; and the wide-area monitoring system consists of a synchronous phase angle measuring unit PMU, real-time acquisition of the main data of the grid. The EMS and DMS systems all rely on the remote control unit RTU (RemoteTerminalUnit) and its data acquisition and monitoring system SCADA. The main problem is that the data acquisition time is too long, reaching the sub-second level, which cannot meet the real-time requirements of high-efficiency applications such as the power grid. Wide area control, energy scheduling, etc. WAMS Phase 1 Cao Junwei et al.: The response time of the smart grid multiplication system architecture research system is on the order of 100 milliseconds, but the WAMS system relies on the construction of the power private network, and the input cost is relatively high. Currently there is no PMU below the domestic 110kV voltage level. Node deployment. In addition, the existing grid information system only collects and controls data for the distribution of electric field stations and high-power electrical equipment, and cannot obtain real-time information of the load. The energy allocation is also based on offline prediction. This has caused four major problems facing the existing power network: (1) the important parameters of the power system are random, time-varying, and unobtrusive, which makes the power system prediction and scheduling difficult; (2) the true electrode limit of the transmission line is unknown, often Relying on great conservativeness for reliability, resulting in low line utilization; (3) for faults in long-distance transmission, it is impossible to accurately know the fault information, such as the location and severity of the fault, often adopting a tentative approach to deal with the fault, resulting in a large amount of equipment redundancy; (4) The power system cannot be stored actively, the reactive power cannot be dynamically balanced, the load cannot interact, and the hot standby causes waste.
In order to solve the above problems, a large number of sensing devices, such as smart meters and PMU units, need to be added, and the addition of sensing devices means that the amount of real-time data is large, and the real-time transmission and processing of power system data under large data volume needs to be utilized. Advanced information, communication, networking and computing technologies are the issues that smart grid information systems need to address. Based on this, we propose the following structure of the smart grid information system.
3.3 Smart Grid Information System Architecture The proposed smart grid information system architecture, as shown in Figure 2, mainly includes three parts: the smart grid information system infrastructure, the smart grid information system support platform and the smart grid information system application system.
Schematic diagram of smart grid information system architecture Smart grid information system infrastructure mainly refers to the hardware foundation of building smart grid, while smart grid information system support platform mainly refers to the software infrastructure of building smart grid, on top of which is to achieve the goal of smart grid construction Various types of applications. The above three platforms will be explained separately below.
4 Smart Grid Information System Infrastructure The smart grid information system infrastructure is the hardware foundation for building a smart grid, including the main links of the power system and the control, measurement equipment and communication network.
4 1 Power system control and measurement equipment First, the composition of the power system is briefly introduced. The power system is mainly composed of six parts: power generation, transmission, power transformation, power distribution, power consumption and dispatch. Power generation includes traditional hydropower, thermal power and new nuclear energy, wind energy and solar power generation. The control of power generation is mainly for frequency regulation of generators, voltage amplitude adjustment, synchronous phase and active reactive power regulation, and generator output. The voltage is generally in the range of 1135 kV. The transmission link connects the main generators and load centers in the grid system to form the backbone network of the grid system, usually operating at the highest voltage level (eg 220kV or more). Commonly used transmission technologies include high-voltage direct current transmission and flexible alternating current transmission. The substation link becomes a secondary distribution process of power, connecting substations and substations, and some large industrial loads may directly access the substation system.
The voltage level of the substation system is generally between 69138 kV. Through the transformer ratio and reactive power compensation equipment for the substation, the grid system can control the reactive power and voltage of the grid. The distribution link is the most integrated into the conversion of electric energy to individual users. The distribution system is divided into a primary distribution system and a secondary distribution system. The primary distribution system mainly supplies small industrial electricity, and the voltage level is 434 secondary. The electrical system is used for electricity for residents and businesses, with a voltage rating of 120240V.
The power system measurement equipment is the basis for building a smart grid. The implementation of the smart grid depends on the application and deployment of the sensor. Currently, the sensors in the smart grid include the grid operation and maintenance measurement system and the personal user measurement system. The grid operation and maintenance measurement system is mainly used to collect electrical information of power system units such as transmission and distribution lines, power plants, and motor sides. Commonly used remote network devices such as SCADA systems, RTUs and PMUs in the WAMS system have measurements. , communication, control and other functions, the measurement unit is widely used in energy management systems (EMS), but its main disadvantage is that the data sampling frequency is low, can not get the dynamic information of the grid operation in time; each RTU unit is not synchronized The clock and the acquired data are out of sync. Compared with the RTU unit, the PMU adds phase angle measurement; it has a GPS timing unit for higher measurement accuracy; at the same time, the measurement frequency is higher, on the order of tens of milliseconds. The personal user measurement system is mainly used to measure personal power usage, such as smart meters. The main function of the smart meter (SmartMeter) is to obtain the power-saving and energy-saving suggestions for the user by obtaining the power consumption data of different power-consuming devices of the user and combining with the operation of the power grid, and the information flow is transmitted in both directions. Smart meters should have the following functions: two-way communication; automatic data collection; power outage management; dynamic billing management; demand response for load control.
At present, in the field of smart meter development, there are two main ideas: (1) using multiple acquisition devices to directly collect data from the appliance; 2) using a collection device to collect data, and then using a classification algorithm to identify the data. One of the drawbacks of the first idea is that each appliance needs to be equipped with sensing equipment, which is costly, and some electrical appliances are difficult to install and require additional communication protocols and equipment to support data collection. Relatively speaking, the cost of the second idea is relatively low, mainly based on the pattern recognition algorithm to classify the electrical characteristics of the electrical appliances, and thus analyze the power consumption of different electrical appliances. For the second method, it is important to use the sensor to obtain which type of data, because the selection of features has a great influence on the efficiency of the pattern recognition algorithm. At present, the existing design has the advantages and disadvantages of the measurement scheme of Table 1. The difference between the active power and the reactive power and high-power electrical appliances is large, which is advantageous for distinguishing (1) not suitable for small-power appliances (2) similar electrical appliances cannot be distinguished (3) implementation is complicated, It is necessary to simultaneously measure the power and reactive power and current characteristics and start-up characteristics. It is easy to distinguish similar electrical appliances. (1) Inaccurate measurement of high-current electrical appliances. (2) Professionals need to install transient voltage and noise characteristics. (1) Easy installation, any socket Can be used for installation () can be used to distinguish similar appliances (1) each user needs to retrain (2) requires high adoption rate (above MHz) to measure continuous high frequency voltage characteristics requires higher sampling frequency (50 power control equipment is realized The carrier of the smart grid target, the main operating parameters of the grid system are frequency, voltage, phase, active power, reactive power. To achieve the control of the above parameters, the control object of the grid system includes all levels of power generation units, power transmission and transformation systems, Power distribution system. The main control equipment is RTU unit and various intelligent electronic equipment (IntelligentElectronicDevice
4.2 Power System Communication Network Communication network is an important infrastructure for smart grids. The wide-area measurement system WAMS, the Wide Area Protection System (WAPS), and the Wide Area Control System WACS (Wide Area Control System) in the smart grid all depend on the communication architecture. Due to the diversity and dispersion of the grid system, there is no unified system architecture for the grid system. Considering the current networking mode and future application requirements of the smart grid, we believe that the bottom-up architecture of the smart grid communication network system is as shown in Figure 3.
According to the smart grid communication network system, the smart grid communication network can also be viewed as two parts: 1) The power state monitoring network consisting of the grid state measurement unit PMU and RTU. The number of nodes in the domain is small. (2) An information network composed of individual user measurement units, which is characterized by a large number of nodes and high scalability requirements.
4 2.1 Personal User Network The personal user measurement unit often connects through the local area network and then accesses the WAN. The local area network composed of the smart meter connection includes the home area network HAN (HomeAreaNetwork) and the available networking modes include a wireless network and a BPL (Broadband OverPowerLine) network. Among them, the wireless network is used to construct a smart grid personal user LAN. The existing standards include the Zgbee1 protocol and the OpenHAN protocol. Both of the above protocols operate on the basis of the IEEE 802. 15.4 wireless network standard. Zgbee protocol is a common networking technology in wireless sensor networks. It is mostly used in the construction of low-speed short-range wireless networks. A scheme based on Zgbee to construct personal user LAN is given. OpenHAN is a wireless network networking protocol designed specifically for home power systems. In 2008, the first edition of the networking requirements document was released by the Open Smart Grid User Group (OSGUG) (OpenSmartGridUsersGroup) and revised in 2010. The networking structure for constructing a personal user LAN is either a star network or a mesh network. The main disadvantage of the star network is that the central node has a heavy burden and there is a single point of failure problem. The mesh network is more common in the structure of the wireless sensor network. Due to its better self-healing characteristics, the mesh network is actually used to construct the phase one. Cao Junwei et al.: The smart grid multiplication system architecture studies the individual user power information network, but the nodes near the centralized node (AccessPmnt) are the bottleneck of the mesh network.
42.2 Power backbone communication network The smart grid backbone communication network networking mode can be divided into two categories. The first type is the combination of power network and information network, that is, the communication carrier itself is an element in the power network, including based on GroundWre) Media self-supporting overhead cable ADSS (A11DielectricSelfSupporting). The second category is the separation of the architecture of the smart grid information network from the power network, that is, the use of an additional network architecture power system information network. In this mode, there are also different information network architectures, which can be roughly divided into three types, namely, optical fiber, wireless signal, and leased band competition. At present, the common practice is that the backbone network is constructed by fiber, and the edge network is transmitted by wireless.
The use of power network elements to construct an information network model is conducive to cost savings, but it is easy to cause the power system and information system to be coupled to each other. The failure of the power network will lead to the failure of the information network. The separation mode can solve the above problems and make the smart grid information network architecture more free. However, in the separation mode, the information network must separately select the transmission carrier, which needs to balance the cost and transmission performance. In particular, power system equipment has a wide distribution range. Some remote areas do not have the conditions for constructing optical fiber or wireless networks, and require additional transmission methods. For example, based on the transmission architecture model of cognitive radio CRCCogmtveRado, the benefit of cognitive radio lies in Find the white space suitable for communication from the frequency band of a specific area, and use the transmission belt to compete without affecting the existing communication system. The IEEE 802.22 protocol defines a white space search method. At present, the 802.22 protocol has been deployed in video video, and it can be used to construct information networks in remote areas through CR technology.
The existing power system network communication protocols include the IEC60870, IEC61850, and IEC61970 protocol groups. Since the above protocol groups are mainly constructed for different types of data networks, this section will not be described, and will be further described in Section 6.
42.3 Main Indicators of Smart Grid Communication Network The two main indicators for the construction of smart grid communication network are network stability and network delay. Different network construction methods will inevitably lead to different network characteristics. How to select the construction scheme of smart grid communication network is an important issue in the field of smart grid research.
There are two ideas for discussing the delay and stability of smart grid networks: (1) From the perspective of network topology and protocol itself, such as the study of the network with dedicated competition and sharing competition in the separation information network architecture mode. Performance and its influencing factors; 2) Study the transmission performance of smart grid from the perspective of information theory, such as the analysis of the channel capacity required for smart grid wireless communication to ensure the requirements of secure communication. On the basis of network performance analysis, considering the impact of power system communication delay on control performance is a problem that networked control systems need to solve. However, current networked control systems usually analyze for a single network and are not popular.
As mentioned above, the current power information network is usually built by a private network. However, due to the cost constraints of dedicated deployment, the dedicated band competition is often not very large, and in this case, the shared band competition model can often obtain a larger channel. Capacity, which means better transmission delay performance, but the problem is that the stability of the delay under the shared-band model is greatly affected by network conditions. If the background noise ratio is high, the network delay and packet will rise rapidly. . Based on TCP/IP, the smart grid WAMS and WAMC models were built, and the network delay and packet conditions after adding background noise and QoS mechanism in the shared band competition mode were analyzed. At the same time, the situation of different competitions under the shared competition model was compared. At present, China's smart grid adopts a private network construction mode, but due to cost constraints, it is limited to 220kV and above. How to ensure the real-time and stability of transmission in the case of sharing a competitive network will be a difficult point.
For the personal user measurement network, it is characterized by a large number of network nodes, but the amount of data of a single node is limited. In addition, the network is mostly built by wireless. How to collect these data and ensure the real-time performance of the data is needed for the smart grid. problem. A smart meter measurement system model based on compression sensing technology is proposed for the personal user measurement system. The wireless access method is adopted. On the other hand, with the increasing number of wide-area monitoring nodes, the existing power information The network is gradually unable to meet the system requirements, and the pressure of the large data volume on the competition is also likely to cause delays. If the power system raw data itself can be compressed, the system can reduce the need for competition. A measurement system model based on matrix singular value decomposition is proposed for grid operation and maintenance measurement system. By analyzing the degree of coupling of the grid connection to determine which data needs to be transmitted between the areas, the size of the data to be transmitted is reduced.
The main difference between smart grid communication transmission and traditional information transmission is that the dynamic of the system is strong. The difficulty of smart grid communication lies in its high stability requirement for network delay and time delay. The main problem faced by traditional power grid communication control systems, such as SCADA systems, is that the delay is too large. How to balance the cost and performance according to the limitations of physical conditions is also a difficult problem for the main computer journal of smart grid research in the future. In addition, how to ensure the confidentiality and security of the smart grid data channel is also a problem to be solved.
424 Smart grid upper-layer application network With the promotion of distributed generation and energy storage technology, from the perspective of power supply and use, the self-organization characteristics of the grid will be strengthened, and the grid will exhibit self-production and sales characteristics within the local area. For example, the power used by users in the future may be partly from the supply of large power grids, while the other part comes from the power generated by new energy sources in its vicinity. The loss of transmission and distribution in this mode will be reduced and will help to reduce the load on the large grid. The network model of this self-organized power supply network is consistent with the content distribution network CDN (ContentDeliveryNetwork). The power supply mode similar to Internet Cache and P2P may also be generated in the power grid, that is, through the hybrid vehicle PHEV (PlugrinHybrid ElectricVehicle) and electric The car EV came to act as a Cache, and a similar idea was put forward in 2004. This paper believes that the upper-layer application network of the smart grid can be constructed by using overlay network technology and information center network technology. ) is a virtual network based on current TCP/IP architecture Internet communication. It improves communication reliability and service quality on TCP/IP networks by deploying a set of nodes on the existing communication infrastructure. Coverage networks provide the foundation for network communications for the diversity of smart grid applications. For example, the load balancing problem in the microgrid system can be solved by the P2P model. With the algorithm of P2P technology in distributed resource discovery, the system can quickly acquire the data of power consumption and power generation of each node, and then perform the deployment. If regional information such as address is added to the node description, the system can reduce transmission loss according to the principle of nearby supply. An agent-based microgrid transmission and distribution deployment model is described. In addition, P2P technology can be applied in many aspects such as power pricing system, intelligent protection system, and intelligent unloading. Coverage network technology can also be used to improve the security and latency performance of smart grids. By setting up a security hub (hub), the data concentrator can select a secure data forwarding node by means of authentication or the like. And the use of overlay network technology can help improve the overall reliability of the network, and should not cause single point failure.
(InformationCentricNetwor-kmg, ICN) is one of the important achievements of the current future Internet architecture research. The basic idea is to separate the information object from the network location, and to apply the early warning analysis based on the important role of the publish/subscribe model. The challenge of communication and security. In addition, grid state measurement is often directed to large grid components or loads. The number of local area is relatively limited and the performance of the measurement unit is high. However, the system often adopts a centralized management mode, which results in excessive load on the central node of the system. The competitive constraints are obvious.
Since the 1990s, the intelligent meter reading equipment (AMR) has gradually begun to apply the pilot, but AMR has only become a remote acquisition and billing function of data, and does not have the function of regulating the user's power consumption behavior. Pass to pass. The Advanced Metering Infrastructure (AMI), which is composed of Smart Meters (SMM), can realize the two-way transmission of information flow. The smart meter and AMI system are the basis for building a smart grid. Compared with the grid state measurement, the personal measurement system is characterized by a large number in a small area and high scalability requirements; at the same time, it requires real-time data and security.
The smart grid measurement system is the basis for the realization of the smart grid, and the power data collection function is realized. Existing measurement systems include SCADA systems, WAMS systems, and AMI systems. The SCADA system and the WAMS system are combined to collect power state data and the AMI is collected into individual user data. The SCA-DA system is not very real-time and is gradually being replaced by the WAMS system. The AMI is still in development and has not yet formed a forming plan. On the other hand, the role of the smart grid measurement system depends on the data analysis processing system. The smart grid data representation and storage architecture will be analyzed below.
5.2 Data Representation and Storage System 52.1 Smart Grid Data Representation Since the grid system equipment is jointly produced by a number of different manufacturers, how to describe the grid system itself and uniformly manage the data generated by these heterogeneous devices is the key to realizing the smart grid information network. one. The representation of the power grid system includes the naming of the data collected by the power system, the definition of the data, the description of the device, the representation of the relationship between the devices, and the representation of the communication model.åŒæ ·ï¼Œæ™ºèƒ½ç”µç½‘çš„æ•°æ®è¡¨ç¤ºå¯ä»¥åˆ’分为电力系统数æ®è¡¨ç¤ºå’Œä¸ªäººç”¨æˆ·æ•°æ®è¡¨ç¤ºä¸¤ç±»ï¼Œå¦‚圄5所示（圄ä¸ä¸ŽPMUã€RTU相连模型为电力系统数æ®è¡¨ç¤ºæ¨¡åž‹ï¼›ä¸ŽSmartMeter相连模型为个人用户数æ®è¡¨ç¤ºæ¨¡åž‹ï¼‰æ™ºèƒ½ç”µç½‘æ•°æ®è¡¨ç¤ºæ¨¡åž‹ç›®å‰ï¼Œç”µåŠ›ç³»ç»Ÿæ•°æ®æè¿°å·²æœ‰çš„å¸¸ç”¨æ¨¡åž‹æ ‡å‡†åŒ…æ‹¬IEC60870å议组①ã€IEC61850å议组②ã€IEC61970å议组③以åŠæ£åœ¨åˆ¶å®šçš„IEC61968å议组④。其ä¸IEC60870å议组是较早（19901995年）制定的电力系统自动化å议组，其通信模型和数æ®æ¨¡åž‹é€‚用于采用专用通信线路æ建的点对点通信网络，目å‰æ£åœ¨é€æ¥è¢«æ›¿æ¢ã€‚ IEC61850å议组是æè¿°å˜ç”µç«™å†…é€šä¿¡ç½‘ç»œå’Œç³»ç»Ÿæ ‡å‡†ä½“ç³»çš„å议组，于1999å¹´å‘布。å议采用了é¢å‘对象的数æ®å»ºæ¨¡æ–¹æ³•ï¼Œå®žçŽ°äº†å¯¹æ•°æ®çš„自我æè¿°ï¼Œä¼ è¾“çš„æ•°æ®è‡ªå·±å¸¦æœ‰è¯´æ˜Žæ–‡ä»¶ï¼Œä½¿å¾—æ•°æ®ä¼ 输时ä¸éœ€è¦å†å®žçŽ°è¿›è¡Œè§„约和转æ¢ï¼Œä»Žè€Œå…·å¤‡äº†é¢å‘æœåŠ³çš„特点，而IEC60870å议组下数æ®ä¼ 输时需è¦æ”¶å‘åŒæ–¹äº‹å…ˆå¯¹æ•°æ®åº“进行规约IEC61970å议组åŠIEC61968å议组å‡é’ˆå¯¹ç”µç½‘调度管ç†ç³»ç»Ÿï¼Œå…¶ä¸IEC61970å议组主è¦é¢å‘EMS（能é‡ç®¡ç†ç³»ç»Ÿï¼‰ã€‚而IEC61968主è¦é¢å‘DMS（é…电管ç†ç³»ç»Ÿï¼‰ï¼Œä¸Šè¿°ä¸¤ä¸ªå议组å‡é‡‡ç”¨äº†é€šç”¨ä¿¡æ¯æ¨¡åž‹CIM.CIM模型也是采用é¢å‘对象的方法æ述电网模型åŠå…¶æ•°æ®ï¼Œå¯ç”¨UML图æ¥è¡¨ç¤ºç”µåŠ›ç³»ç»Ÿç»„件间的继承ã€è¿žæŽ¥å…³ç³»åŠèµ„æºå±žè®¡ç®—机å¦æŠ¥æ€§ï¼ŒåŒæ—¶CIM模型还定义了CIM/XML文件，使得CIM模型å¯é€šè¿‡XMLè¿›è¡Œä¼ é€’ï¼Œè¿™æ ·ä¸åŒçš„应用系统就å¯ä»¥ç›´æŽ¥ç›¸äº’é€šä¿¡ï¼Œå› æ¤CIM模型å¯ç”¨äºŽç”µåŠ›ç³»ç»Ÿçš„应用集æˆã€‚åŒæ—¶ï¼ŒCIM还具有元数æ®æ述管ç†çš„功能，å¯ç”¨äºŽç”µç½‘æ•°æ®ä»“库的建立。采用CIM模型对电力系统åŠå…¶æ•°æ®è¿›è¡Œå»ºæ¨¡æ˜¯æž„建智能电网信æ¯ç½‘的趋势，å‡æ出了基于CIM模型的智能电网信æ¯å…±äº«å¹³å°è®¾è®¡æ–¹æ¡ˆã€‚
就以智能电表为å•å…ƒçš„个人用户数æ®è€Œè¨€ï¼Œå·²æœ‰æ•°æ®æ¨¡åž‹æœ‰DLMS/COSEMæ¨¡åž‹ï¼Œå…¶å¯¹åº”çš„å›½é™…æ ‡å‡†ä¸ºIEC62056å议组①。DLMS对智能电表数æ®çš„读å–ã€è®¡è´¹å’Œè´Ÿè½½æŽ§åˆ¶è¿›è¡Œäº†è§„约，COSEM涵盖了DLMSè§„çº¦çš„ä¼ è¾“ä¸Žç”¨æˆ·å±‚è§„èŒƒã€‚
5.2.2智能电网数æ®å˜å‚¨æ¨¡åž‹æ™ºèƒ½ç”µç½‘具有å¯é 性è¦æ±‚高和数æ®æµ·é‡çš„特点，这è¦æ±‚智能电网数æ®çš„å˜å‚¨å¿…须设置必è¦çš„冗余和备份机制；åŒæ—¶ç”µç½‘æ•°æ®çš„å˜å‚¨æ¨¡åž‹å¿…须满足快速查找和处ç†è¦æ±‚ï¼›è€Œç”±äºŽæ™ºèƒ½ç”µç½‘åº”ç”¨å¤šæ ·ï¼Œä¸åŒåº”用实时性è¦æ±‚也ä¸ç›¸åŒï¼Œç”±æ¤æ™ºèƒ½ç”µç½‘çš„æ•°æ®å˜å‚¨ä¹Ÿå¯åˆ†ä¸ºåœ¨çº¿æ•°æ®å’Œå®žæ—¶æ•°æ®ä¸¤ç§æ¨¡å¼ã€‚
ç›®å‰ä¸»è¦æœ‰4ç§æ™ºèƒ½ç”µç½‘æ•°æ®å˜å‚¨æ–¹æ¡ˆï¼šç¬¬1类方案为多个数æ®é›†ä¸å™¨ï¼Œå•ä¸€æŽ§åˆ¶å¤„ç†èŠ‚ç‚¹åŠ ä¸Šåˆ©ç”¨å…³ç³»æ•°æ®åº“的集ä¸å˜å‚¨ã€‚å…¶ä¸æ¯ä¸ªæ•°æ®é›†ä¸å™¨è´Ÿè´£ä»Žä¸€å®šæ•°é‡çš„é‡æµ‹è®¾å¤‡ä¸èŽ·å–æ•°æ®ã€‚ç›®å‰æˆ‘国电网系统ä¸çš„广域控制模型与之类似；第2类方案与第1类方案类似，但将集ä¸å¼å˜å‚¨æ‹†åˆ†ä¸ºåˆ†å¸ƒå¼æ•°æ®åº“å˜å‚¨ã€‚第3类方案å–消了利用关系型数æ®åº“çš„å˜å‚¨æ¨¡å¼ï¼Œæ出了基于XML的〈关键å—，值〉模型，并且采用类似MapReduce的算法对数æ®åº“进行æ“作；第4类方案采用分布å¼æ–‡ä»¶ç³»ç»Ÿä¸Žæ•°æ®åº“结åˆçš„æ–¹å¼å˜å‚¨æ•°æ®ï¼Œå³æ•°æ®åº“ä¸å˜å‚¨çš„ä¸æ˜¯åŽŸå§‹çš„电网数æ®ï¼Œè€Œæ˜¯æ•°æ®çš„索引，原始数æ®ä»¥æ–‡ä»¶çš„å½¢å¼å˜åœ¨äºŽæ•°æ®é›†ä¸èŠ‚点上，该方å¼ç±»ä¼¼äºŽæœç´¢å¼•æ“Žå¯¹ç½‘页的æœç´¢ã€‚结åˆæ™ºèƒ½ç”µç½‘ä¸å®¶åºç”µåŠ›æ•°æ®çš„å˜å‚¨å’Œè´¦å•è®¡ç®—这一应用对上述4类方案的并å‘处ç†èƒ½åŠ›å’Œå¤„ç†æ—¶é—´è¿›è¡Œäº†ä»¿çœŸå¹¶ç»™å‡ºäº†ç»“以åŠé’ˆå¯¹å®¶åºæœˆè´¦å•çš„计算时间。结果表明方案3çš„å¯æ‰©å±•æ€§è¾ƒå·®è€Œæ–¹æ¡ˆ4的处ç†æ—¶é—´è¾ƒé•¿ï¼Œæ–¹æ¡ˆ1和方案2类似。
å¦ä¸€æ–¹é¢ï¼Œç”±äºŽæ™ºèƒ½ç”µç½‘æ•°æ®åº”用类型数é‡ä¸å¯é¢„æœŸï¼Œå®¹æ˜“é€ æˆæ•°æ®ç»Ÿä¸€ç®¡ç†çš„困难。将智能电网数æ®æŠ½è±¡ä¸ºåŽ†å²æ¨¡å¼ã€å®žæ—¶æ¨¡å¼å’Œæœªæ¥æ¨¡å¼è¿›è¡Œå»ºæ¨¡ï¼Œè€Œä¸æ˜¯æŒ‰ç…§åº”用类型对数æ®å˜å‚¨è¿›è¡Œå»ºæ¨¡ç®¡ç†ã€‚å…¶ä¸å®žæ—¶æ•°æ®ç®¡ç†ä¸»è¦é’ˆå¯¹å®žæ—¶æ•°æ®åˆ†æžçš„需求，利用内å˜æ•°æ®åº“进行å˜å‚¨ã€‚历å²æ¨¡å¼ä¸»è¦é’ˆå¯¹åŽ†å²æ•°æ®çš„å˜å‚¨ã€æŸ¥æ‰¾ï¼Œé‡‡ç”¨æ—¶åºæ•°æ®åº“进行å˜å‚¨ã€‚而未æ¥æ¨¡å¼ä¸»è¦ç”¨äºŽå˜å‚¨æœªæ¥çš„å¯èƒ½å‘生的设备的å˜åŒ–ï¼Œä¾‹å¦‚åŠ å‘电机ç‰ã€‚在æ¤åŸºç¡€ä¸Šï¼Œä¸Šå±‚应用å¯ä»¥æŒ‰éœ€èŽ·å–和管ç†å¼‚æž„æ•°æ®åº“，从而解决异构数æ®æ¨¡åž‹çš„管ç†é—®é¢˜ã€‚æ¤å¤–，还有探讨在é‡æµ‹ç³»ç»ŸAMI和数æ®ç®¡ç†ç³»ç»ŸDMS（DataManagementSystem）之间构建统一数æ®é›†æˆä¸é—´å±‚MDI（MeterDataIntegration：59.从而使得AMI系统和DMS系统之间得到解耦，用于解决由于数æ®æ¨¡åž‹å’Œé€šä¿¡åè®®çš„å¼‚æž„æ€§é€ æˆæ•°æ®å˜å‚¨å’Œç®¡ç†çš„困难。
æ•°æ®å˜å‚¨æ¨¡åž‹é€‰å–çš„ä¸åŒå°†å¯¼è‡´æŸ¥æ‰¾ã€èŽ·å–和数æ®å¤„ç†æ¨¡å¼çš„ä¸åŒï¼ŒåŒæ—¶ä¹Ÿä¼šå¼•èµ·ç³»ç»Ÿå“应时间的区别，如何为智能电网选å–åˆé€‚çš„å˜å‚¨æ¨¡åž‹ï¼Œå°†æ˜¯æœªæ¥æ™ºèƒ½ç”µç½‘ç ”ç©¶ä¸çš„一个é‡è¦æ–¹å‘。
5.2.3基于云计算的智能电网数æ®å˜å‚¨ä»Žç³»ç»Ÿå®žçŽ°ä¸Šæ¥çœ‹ï¼Œç‰©è”网系统的æ建ä¾èµ–于云计算平å°ï¼Œäº‘计算平å°ä¸ºç‰©è”网应用æ供了计算和å˜å‚¨èµ„æºã€‚作为物è”网的一个典型实例，云计算技术与智能电网的结åˆæ˜¯å¿…然趋势。如æ出了基于云模型的数æ®ç®¡ç†å’Œå¤„ç†æ¨¡åž‹ï¼Œå°†æ™ºèƒ½ç”µç½‘æ•°æ®åˆ†å¸ƒå¼å˜å‚¨åœ¨ç”µç½‘çš„å„个节点，然åŽä»¥æœåŠ³çš„å½¢å¼å°†æ•°æ®æ供出æ¥ä¾›åº”用访问获å–。云å˜å‚¨æœ‰åŠ©äºŽè§£å†³æ™ºèƒ½ç”µç½‘æ•°æ®å˜å‚¨çš„æµ·é‡æ€§å’Œå¯é 性问题。
OpenPDC是目å‰å·²ç»æŒ‰å…¥è¿è¡Œçš„一个智能电网数æ®å¤„ç†ç³»ç»Ÿï¼Œå…¶å®žçŽ°åŸºäºŽå¼€æºå¹³å°Hadoop.该系统应用对象为时间åºåˆ—æ•°æ®æµï¼Œå³æ•°æ®æºä¸ºç»è¿‡GPS授时的数æ®æµã€‚应用背景å³ä¸ºæ™ºèƒ½ç”µç½‘ä¸çš„WAMS系统，由于WAMSç³»ç»Ÿçš„é‡‡æ ·é¢‘çŽ‡ä¸ºæ¯ç§’30次，当WAMS系统的åå•å…ƒPMUæ•°é‡åŠ 时，会产生大é‡çš„æ•°æ®ã€‚ç›®å‰è¯¥é¡¹ç›®ç®¡ç†äº†åŒ—美东部约120个PMUçš„æ•°æ®ä¿¡æ¯ï¼Œå¹³å‡æ•°æ®é‡çº¦ä¸ºæ¯å°æ—¶1.5GB.截至2009年我国仅在220kV电压ç‰çº§ä»¥ä¸Šç”µåŠ›ç³»ç»Ÿéƒ¨ç½²çš„PMUå•å…ƒä¸ªæ•°å·²ç»è¾¾åˆ°1000以上，å†è€ƒè™‘个人用户实时产生的数æ®ï¼Œå¯ä»¥é¢„è§æœªæ¥æ™ºèƒ½ç”µç½‘çš„æ•°æ®é‡æ˜¯éžå¸¸å·¨å¤§çš„。在这ç§èƒŒæ™¯ä¸‹ï¼Œé›†ä¸çš„æ•°æ®å˜å‚¨æ¨¡å¼å°†å¯¹ç½‘ç»œé€ æˆå·¨å¤§çš„压力，采用分布å¼å˜å‚¨æˆä¸ºä¸€ç§å¿…然。åŒæ—¶ç”±äºŽç”µç½‘稳定性的è¦æ±‚，数æ®æœ¬èº«å˜åœ¨å†—余备份的需求。云计算平å°çš„分布å¼æ–‡ä»¶ç³»ç»Ÿå¯ä»¥ä¸ºæ¤æ供解决方案，且有助于æ高电网系统的安全性。
1期曹军å¨ç‰ï¼šæ™ºèƒ½ç”µç½‘å€æ¯ç³»ç»Ÿä½“ç³»ç»“æž„ç ”ç©¶å¦‚ä½•å°†äº‘å˜å‚¨åº”用于智能电网还å˜åœ¨ä¸å°‘问题尚待解决。首先，虽然已有æåŠæœªæ¥ç”µç½‘çš„å˜å‚¨æ¨¡åž‹ï¼Œä½†å°šæ— 较æˆç†Ÿçš„方案，数æ®é‡‡ç”¨æ•°æ®åº“å˜å‚¨è¿˜æ˜¯ä»¥æ–‡ä»¶å½¢å¼å˜å‚¨ä»æœ‰äº‰è®®ã€‚其次，由于电网系统å˜åœ¨å¤šæ ·æ€§çš„特点，ä¸åŒé‡æµ‹ç³»ç»Ÿçš„æ•°æ®æ ¼å¼å¹¶ä¸ç»Ÿä¸€ï¼Œä¾‹å¦‚ä¸åŒåŽ‚家的RTUæ•°æ®æ ¼å¼éƒ½ä¸ç›¸åŒï¼Œå¦‚何构建统一数æ®æ¨¡åž‹çš„问题也需è¦è§£å†³ã€‚æ¤å¤–，失去时效性的大é‡æ•°æ®éœ€è¦è¿ç§»å¤‡ä»½ï¼Œå¹¶ä¸”è¿™ç§è¿ç§»æ˜¯é¢‘ç¹å‘生的，这ç§æƒ…况下ä¿è¯å˜å‚¨ç³»ç»Ÿçš„è¿è¡Œæ•ˆçŽ‡æˆä¸ºéš¾ç‚¹ã€‚æ¤å¤–æŸäº›åº”用对于电网数æ®çš„获å–有时间é™åˆ¶ï¼Œåˆ†å¸ƒå¼æ–‡ä»¶ç³»ç»Ÿçš„æŸ¥æ‰¾æ•ˆçŽ‡æ— æ³•æ»¡è¶³å…¶éœ€æ±‚ã€‚
总体æ¥çœ‹ï¼Œå°½ç®¡äº‘计算的分布å¼å˜å‚¨å¹³å°å’Œå¹¶è¡Œå¤„ç†æ¨¡åž‹é€‚åˆæœªæ¥æ™ºèƒ½ç”µç½‘分散性ã€å¯é 性ã€å®‰å…¨æ€§å’Œæ•°æ®æµ·é‡æ€§çš„需求，但ä¾ç„¶å˜åœ¨åº”用障ç¢ã€‚
5.3分æžä¸Žå†³ç–系统智能电网按入实际è¿è¡ŒåŽï¼Œé¢ä¸´çš„å¦ä¸€ä¸ªå·¨å¤§æŒ‘战就是海é‡æ•°æ®çš„处ç†èƒ½åŠ›ã€‚由于智能电网既è¦æ»¡è¶³ä¸ªäººç»œç«¯ç”¨æˆ·ä¸Žç”µç½‘系统的交互需求，也è¦æ»¡è¶³ç”µç½‘控制系统对电网稳定性的控制需求，未æ¥æ™ºèƒ½ç”µç½‘ä¸æœ‰ä¸¤å¤§ç±»åº”用需è¦æµ·é‡æ•°æ®å¤„ç†æŠ€æœ¯çš„支撑。第一类是智能电网稳定è¿è¡Œç›‘æŽ§ç³»ç»Ÿï¼Œå®ƒæ ¹æ®é‡æµ‹ç³»ç»ŸèŽ·å–到的数æ®è¿›è¡ŒåŠ¨æ€å®‰å…¨è¯„ä¼°DSA（DynamicSecurityAssessment），ä¿è¯ç”µç½‘è¿è¡Œç¨³å®šï¼Œä»¥åŠç”µç½‘系统出现故障åŽæ¢å¤ç³»ç»Ÿã€‚第二类是智能销售和消费系统，它通过实时电价自动平衡电能的供应和消耗，如微软开å‘çš„Googleçš„PowerMeter系统②该类应用多与微网系统相结åˆï¼Œè€ƒè™‘新能æºå¦‚风能ã€å¤ªé˜³èƒ½æŽ¥å…¥åŽåˆ†æ•£å‘电资æºçš„利用问题。æ¤å¤–，考虑智能电网数æ®çš„æµ·é‡æ€§ï¼Œæ™ºèƒ½ç”µç½‘分æžå†³ç–系统与云计算技术的结åˆæ˜¯æœªæ¥è¶‹åŠ¿ï¼Œå› æ¤æœ¬æ–‡è®¤ä¸ºæœªæ¥æ™ºèƒ½ç”µç½‘分æžå†³ç–系统结构如圄6所示。
智能电网分æžå†³ç–系统5 31智能电网分æžå†³ç–需求对于第一类应用，第一是è¦è§£å†³ç”µç½‘稳定性的判定问题电力系统的稳定性分为é™æ€ç¨³å®šå’Œæš‚æ€ç¨³å®šä¸¤ç±»ï¼Œå…¶ä¸æš‚æ€ç¨³å®šæ述的是电网出现大扰动åŽçš„é²æ£’性，比如出现çŸè·¯æ•…éšœã€çŸçº¿ä»¥åŠå‘电机çªç„¶æ‘”è´Ÿè·ç‰ç‰ï¼Œå¦‚2003å¹´ç¾ŽåŠ å¤§åœç”µäº‹æ•…已有的电力系统暂æ€ç¨³å®šè¯„估方法（TSA）å¯ä»¥åˆ†ä¸ºä¸¤å¤§ç±»ï¼Œä¸€ç±»æ˜¯åŸºäºŽæ•°å¦æ¨¡åž‹çš„方法，包括时域仿真法，å³é€šè¿‡å»ºç«‹ç”µåŠ›ç³»ç»Ÿå„元件的微分方程，å†é€šè¿‡æ•°å€¼æ–¹æ³•æ±‚解å„状æ€é‡çš„时间特性；基于Lyap稳定判æ®çš„能é‡å‡½æ•°æ³•ã€æ‰©å±•ç‰é¢ç§¯æ³•ä»¥åŠåŠ¨æ€å®‰å…¨åŸŸæ³•ã€‚å¦ä¸€ç±»æ˜¯åŸºäºŽæ•°æ®æœ¬èº«çš„模å¼è¯†åˆ«æ–¹æ³•ï¼ŒåŒ…括神ç»ç½‘络ã€æ”¯æŒå‘é‡æœºã€é—ä¼ ç®—æ³•ç‰å¤šç§æ–¹æ³•ã€‚å…¶ä¸ç¬¬ä¸€ç±»æ–¹æ³•é¢ä¸´ä¸¤ä¸ªä¸»è¦å›°éš¾ï¼šä¸€æ˜¯å®žé™…电力系统规模很大，往往最åŽå˜æˆå‡ å¹²é˜¶çš„å¾®åˆ†æ–¹ç¨‹æ±‚è§£ï¼Œæ— æ³•æ»¡è¶³å®žæ—¶æ€§è¦æ±‚ï¼›å¦ä¸€æ–¹é¢ï¼Œç”±äºŽç”µåŠ›è´Ÿè·æ¨¡åž‹æœ¬èº«å°±æ˜¯ä¸å¯çŸ¥çš„，现有分æžæ–¹æ³•å¾€å¾€é‡‡ç”¨ä¼°è®¡å’Œç»éªŒçš„方法给定负è·çš„å‚数，ä¸ç²¾ç¡®ï¼Œå¦‚何对电网负è·å‚数进行在线辨识也是未æ¥æ™ºèƒ½ç”µç½‘亟需解决的问题。而第二类方法åŒæ ·é¢ä¸´å½“系统规模较大时，数æ®é›†æ•°é‡è¿‡å¤§çš„问题，如何进行特å¾é€‰å–和压缩目å‰å°šæ— 统一的模å¼ã€‚å¦ä¸€æ–¹é¢ï¼Œåœ¨èŽ·å–到电网故障信æ¯åŽï¼Œå¦‚何迅速é‡æ–°é…置电网结构使电网系统é‡å½’稳æ€æ˜¯ç¬¬äºŒä¸ªéœ€è¦è§£å†³çš„问题。已有的方法包括å¯å‘å¼ç®—法ã€ä¸“家系统ã€æ•°å€¼è®¡ç®—ã€è½¯ä»¶ä»¿çœŸåŠå¤šçº§ä»£ç†ç‰ã€‚å…¶ä¸é™¤å¤šçº§ä»£ç†ä¹‹å¤–的系统å‡åŸºäºŽé›†ä¸å¼æž¶æž„建立，当系统规模较大时会出现计算瓶颈。
通过智能电表获å–到用户用电数æ®åŽï¼Œæ™ºèƒ½ç”µç½‘çš„å¦ä¸€é¡¹åŠŸèƒ½æ˜¯å¯¹ç”¨æˆ·ç”¨ç”µè¡Œä¸ºè¿›è¡Œé¢„测和建议，充分利用分布å¼èƒ½æºå‘电能力，并通过电力使用时间的è¿ç§»é™ä½Žå³°å€¼ä½¿ç”¨æ—¶é—´æ®µç”µåŠ›ç³»ç»ŸåŽ‹åŠ›ï¼Œè¿›è€Œæ高电力系统è¿è¡Œæ•ˆçŽ‡ã€‚å…¶æ ¸å¿ƒæ€æƒ³æ˜¯åˆ©ç”¨å®žæ—¶ç”µä»·è°ƒèŠ‚用户行为。该类应用通常分三æ¥å®žçŽ°ï¼šï¼ˆ1ï¼‰æ ¹æ®ç”¨æˆ·æ•°æ®æž„建行为模型并进行预测。
（2）ä¸å¿ƒå¤„ç†å•å…ƒèŽ·å–用户数æ®è¿›è¡Œå…¨å±€ä¼˜åŒ–ï¼ˆå±žäºŽå¤šç›®æ ‡ä¼˜åŒ–é—®é¢˜ï¼‰ï¼Œä¾‹å¦‚å¯¹äºŽå•ä¸ªç”¨æˆ·æ¥è¯´ä¼˜åŒ–ç›®æ ‡æ˜¯æœ€å°è´¹ç”¨ï¼Œè€Œå¯¹äºŽç”µåŠ›ç³»ç»Ÿæ¥è¯´ä¼˜åŒ–ç›®æ ‡æ˜¯ç”µåŠ›ç³»ç»Ÿè¿è¡Œç¨³å®šæ€§å’Œæ•ˆçŽ‡ã€‚
（3）实时控制系统控制电器开关已有的实现方案多基于多级代ç†ï¼ˆagentbased），计算机å¦æŠ¥æ¯çº§ä»£ç†è¿›è¡Œå‡ºä»·ï¼ˆéœ€è¦/å‘出的总电力åŠä»·æ ¼ï¼‰ï¼Œå†é€çº§æ±‡æ€»ç”±æœ€é«˜çº§ä»£ç†è¿›è¡Œä¼˜åŒ–ï¼Œå¦‚ç»™å‡ºçš„å®žæ—¶å®šä»·ç®—æ³•å°±æ˜¯è¿™æ ·ä¸€ç§æ–¹æ³•ã€‚结åˆç”µå†°ç®±çš„用电控制实例进行了说明。æ®ï¼Œè¯¥ç±»ä¼˜åŒ–问题属于NPèŠ«å…¨é—®é¢˜ï¼Œå› æ¤å¤šé‡‡ç”¨å¯å‘å¼ç®—法求解。æ¤å¤–，如ä¸è€ƒè™‘用户å‘电网ä¸é€ç”µçš„问题，则å¯ä»¥åˆ©ç”¨çº¿æ€§è§„划方法求解。
5 32基于云计算的智能电网数æ®å¤„ç†ç”±äºŽç”µç½‘系统规模大ã€èŠ‚点多，特别是智能电表得到的数æ®éœ€è¦å®žæ—¶è§„划和调度，这需è¦å¤§é‡çš„计算资æºè¿›è¡Œåˆ†æžå¤„ç†ï¼Œæ™ºèƒ½ç”µç½‘æ•°æ®å¤„ç†ä¸Žäº‘计算技术的结åˆæˆä¸ºå¿…然。
å·²æœ‰ç ”ç©¶å·¥ä½œæŽ¢è®¨æ™ºèƒ½ç”µç½‘ä¸Žäº‘è®¡ç®—æŠ€æœ¯çš„ç»“åˆï¼Œå¦‚将云计算的分布å¼æ•°æ®å˜å‚¨æ¨¡åž‹å’Œå¹¶è¡Œå¤„ç†æ¨¡åž‹ç”¨äºŽå˜å‚¨ç”µç½‘æ•°æ®ï¼Œå¯¹æ•°æ®å集进行并行处ç†å†æ±‡æ€»å¤„ç†ç»“果。上文æ到的Hohm系统就是基于云计算平å°çš„ä¸è¶³ä¹‹å¤„在于其处ç†ç®—法è¦æ±‚æ•°æ®å集之间互ä¸ç›¸å…³ï¼Œæ¯ä¸ªæ•°æ®å集å¯ä»¥ç‹¬ç«‹è¿›è¡Œè¿ç®—处ç†ï¼Œæ™ºèƒ½ç”µç½‘ä¸çš„æŸäº›åº”用符åˆè¿™ç§è¿ç®—模å¼ï¼Œæ¯”如实时电价计算。但还å˜åœ¨ä¸€ç±»åº”用，需è¦è·¨åŒºåŸŸçš„æ•°æ®åˆ†æžæ‰èƒ½ç»™å‡ºç»“果，数æ®å集之间ä¸èƒ½è§£è€¦ï¼Œå¦‚调度ã€å‘电负è·å¹³è¡¡ã€ç”µç½‘应急报è¦ã€‚è¿™ç§æƒ…况下简å•çš„云计算模型并ä¸èƒ½è¿›è¡Œå¤„ç†ã€‚电网的物ç†ç‰¹æ€§æ˜¯ç³»ç»Ÿæœ¬èº«çš„å…³è”性较强（电力系统之间å˜åœ¨ç”µæ°”连接），也å³æ„味ç€æ•°æ®å˜åœ¨å…³è”性，是å¦å¯ä»¥æ”¹è¿›å¹¶è¡Œç®—法，é™ä½Žä¼ 输和计算的资æºæ¶ˆè€—，是未æ¥æ™ºèƒ½ç”µç½‘ç ”ç©¶çš„ä¸€ä¸ªæ–¹å‘，如å‰æ–‡æ到的通过分æžç”µç½‘连接的耦åˆå±‚度æ¥é™ä½Žæ•°æ®ä¼ 输é‡ã€‚æ¤å¤–，如何在æ¾è€¦åˆç³»ç»Ÿæ¨¡åž‹ä¸‹ä¿è¯ç³»ç»Ÿå¤„ç†æ€§èƒ½ï¼Œæ»¡è¶³å¤„ç†æ—¶é™è¦æ±‚，也是难点。
5.4控制与执行系统智能电网包括电能的å‘ã€è¾“ã€å˜ã€é…ã€ç”¨ç‰5个环节以åŠåˆ†å¸ƒå¼æ–°èƒ½æºçš„æŽ¥å…¥å’Œä½¿ç”¨ï¼Œæ‰€ä»¥å…¶æŽ§åˆ¶ç³»ç»Ÿåœ¨ä¼ ç»Ÿçš„åŽ‚ç«™å¼æŽ§åˆ¶ç³»ç»Ÿä¸ŠåŠ 入了é¢å¤–的分布å¼é¢‘率ã€åŠŸçŽ‡ã€ç”µåŽ‹ã€ç›¸ä½ã€è´Ÿè·æ˜¯ç”µåŠ›ç³»ç»Ÿçš„主è¦å‚数，电网系统频率下é™ã€ç”µåŽ‹ä¸‹é™ã€å‘电机失效ã€è¿‡è´Ÿè·éƒ½ä¼šé€ æˆç”µåŠ›ç³»ç»Ÿäº‹æ•…ç”šè‡³å´©æºƒã€‚ä¼ ç»Ÿçš„ç”µåŠ›ç³»ç»ŸæŽ§åˆ¶ä¸»è¦é’ˆå¯¹ä»¥ä¸Šå‚数进行调控，具体包括稳定控制ã€ç”µåŽ‹åŠæ— 功功率控制ã€é¢‘率åŠæœ‰åŠŸåŠŸçŽ‡æŽ§åˆ¶ã€é…电网控制ã€æŸ”性交æµè¾“电控制，在新能æºå¤§é‡å¼•å…¥åŽï¼Œåˆ†å¸ƒå¼èƒ½æºå¦‚ä½•ä¸Žä¼ ç»Ÿç”µç½‘ç»“åˆæ˜¯æœªæ¥æ™ºæ™ºèƒ½æŽ§åˆ¶æ‰§è¡Œç³»ç»Ÿèƒ½ç”µç½‘需è¦è§£å†³çš„é‡ç‚¹é—®é¢˜ï¼Œå› 为新能æºæŽ¥å…¥å¾€å¾€ä¼šç»™ç”µç½‘带æ¥æ–°çš„安全稳定问题。在电压åŠæ— 功功率控制方é¢ï¼Œå·²æœ‰ç®—法包括优化问题求解的梯度类算法ã€ç‰›é¡¿æ³•ã€äºŒæ¬¡è§„划法ã€çº¿æ€§è§„划法以åŠæ¨¡æ‹Ÿé€€ç«ç®—法ã€é—ä¼ ç®—æ³•ã€èšç¾¤ç®—法åŠäººå·¥ç¥žç»ç½‘络ç‰å¤šç§æ–¹æ³•ã€‚频率åŠåŠŸçŽ‡æŽ§åˆ¶æ–¹é¢ï¼Œå·²æœ‰ç®—法包括ç»å…¸çš„IP控制ã€é²æ£’控制ã€ç¥žç»ç½‘络ã€é—ä¼ ç®—æ³•åŠçº¿æ€§è§„划法ç‰ã€‚而é…电网控制方é¢ï¼Œå·²æœ‰ç®—法包括整数规划法ã€åˆ†æ”¯å®šç•Œæ³•ã€æ··åˆæ•´æ•°æ³•ã€äººå·¥æ™ºèƒ½å’Œå¯å‘å¼ç®—法以åŠåŸºäºŽå¤šä»£ç†ç³»ç»Ÿçš„方法。柔性交æµè¾“电控制主è¦åŸºäºŽé™æ¢æ— 功补å¿å™¨ASVCã€å¯æŽ§ä¸²è”电容器补å¿TCSCã€å¯æŽ§ç§»ç›¸å™¨TCPSåŠç»¼åˆæ½®æµæŽ§åˆ¶å™¨UPFC.电力系统稳定控制和分布å¼èƒ½æºå‘电控制的方法将在6.2节åŠ6.3节进行详细论述，在æ¤ä¸åšè®¨è®ºã€‚
从系统构架上æ¥çœ‹ï¼Œä¼ 统电网的控制模å¼å¤šé‡‡ç”¨é›†ä¸å¼çš„构架。所谓集ä¸æŽ§åˆ¶å°±æ˜¯æ‰€æœ‰é‡‡é›†åˆ°çš„æ•°æ®ç»Ÿä¸€å‘é€è‡³æ•°æ®ä¸å¿ƒè¿›è¡Œé›†ä¸å¤„ç†å¹¶ç»™å‡ºæŽ§åˆ¶å馈，而分散ç–略指将大电网按区域划分，æ¯ä¸ªåŒºåŸŸæœ‰è‡ªå·±çš„控制ä¸å¿ƒï¼ŒæŽ§åˆ¶ä¸å¿ƒä¹‹é—´é€šè¿‡å…±äº«æ•°æ®å®žçŽ°å¯¹æ•´ä¸ªç³»ç»Ÿçš„控制。从系统性能上æ¥çœ‹ï¼Œé›†ä¸å¼æŽ§åˆ¶å¾€å¾€ä¼šå¯¹ä¸»èŠ‚点产生过大的处ç†åŽ‹åŠ›å’Œå¸¦ç«žåŽ‹åŠ›ï¼ŒåŒæ—¶ä¹Ÿå®¹æ˜“é€ æˆå•ç‚¹å¤±æ•ˆï¼Œæ‰€ä»¥æœªæ¥ç”µç½‘的控制结构会é€æ¥å‘分散结构过渡；å¦ä¸€æ–¹é¢ï¼Œéšç€æ–°èƒ½æºçš„引入，未æ¥ç”µç½‘将是许多分散的微电网的集åˆï¼Œåˆ†1期曹军å¨ç‰ï¼šæ™ºèƒ½ç”µç½‘å€æ¯ç³»ç»Ÿä½“ç³»ç»“æž„ç ”ç©¶å¸ƒå¼æŽ§åˆ¶çš„应用是一ç§å¿…然。æ¤å¤–，分散å¼çš„控制模型下由于数æ®æ— éœ€èŠ«å…¨åœ¨å¹¿åŸŸèŒƒå›´å†…ä¼ é€’ï¼Œå¯¹äºŽå‡å°‘网络延时和ä¿è¯ç½‘络稳定性也å¯èƒ½äº§ç”Ÿç§¯æžä½œç”¨ï¼Œå¦‚在信æ¯ç½‘构架采用OPGWç»„ç½‘æ–¹æ³•ä¸‹ç ”ç©¶äº†é›†ä¸å’Œåˆ†æ•£æŽ§åˆ¶ç–略下电网系统的延时和稳定性。从结果上看，分散控制的平å‡å»¶æ—¶æ›´å°ä¸”方差更å°ï¼Œæ„味ç€ç½‘络的稳定性更好。
本节对实现智能电网的4个é‡è¦æ”¯æ’‘å¹³å°è¿›è¡Œäº†åˆ†æžã€‚为了实现智能电网对电力的稳定控制ã€èƒ½æºçš„实时调é…以åŠæ–°èƒ½æºçš„接入ç‰ç›®æ ‡ï¼Œéœ€è¦æž„建基于智能电网基础设施和支撑平å°çš„应用体系。下é¢ç€é‡ä»Žå‘电侧ã€ç”µç½‘侧和用电侧这3æ–¹é¢å¯¹æ™ºèƒ½ç”µç½‘ä¿¡æ¯ç³»ç»Ÿåº”用体系进行介ç»ã€‚
6智能电网信æ¯ç³»ç»Ÿåº”用体系6.1å‘ç”µä¾§åº”ç”¨ç”±äºŽä¼ ç»ŸåŒ–çŸ³èƒ½æºçš„ä¸å¯å†ç”Ÿæ€§åŠå¯¹çŽ¯å¢ƒé€ æˆçš„å½±å“，绿色能æºå³æ–°èƒ½æºå‘电以åŠéšä¹‹äº§ç”Ÿçš„微网系统æ£é€æ¸æˆä¸ºæœªæ¥ç”µç½‘系统å‘展的趋势。
截至2008年，新能æºå å…¨çƒèƒ½æºæ¶ˆè€—的比例为19%，而且这一比例还在é€å¹´ä¸Šå‡ã€‚20042（）（）9年间，全çƒæ–°èƒ½æºå®¹é‡çš„长速度在æ¯å¹´10%60%之间。列出了至2020年世界å„国新能æºå‘电å 电网å‘电容é‡çš„预期百分比，其ä¸ä¸¹éº¦ã€ç‘žå£«çš„部分地区预计在2030å¹´å‰å¯ç”¨æ–°èƒ½æºå‘电芫全å–ä»£ä¼ ç»Ÿèƒ½æºå‘电。
本节ç€é‡å¯¹æ–°èƒ½æºå‘ç”µæŽ¥å…¥ä¼ ç»Ÿç”µç½‘åŽçš„控制管ç†å’Œèƒ½æºè°ƒåº¦é—®é¢˜è¿›è¡Œåˆ†æžï¼Œå¯¹äºŽä¼ 统电网的å‘电控制问题ä¸äºˆæ¶‰åŠï¼Œå› 为该类问题已ç»åœ¨ç”µåŠ›ç³»ç»Ÿé¢†åŸŸè¿›è¡Œè¿‡å¤šå¹´çš„ç ”ç©¶ã€‚
6.1.1新能æºæŽ¥å…¥ç®¡ç†å¹¿ä¹‰ä¸Šçš„新能æºåŒ…括å¯åˆ†æ´¾èƒ½æºï¼ˆcHspatchableenergy）和ä¸å¯åˆ†æ´¾èƒ½æºï¼ˆnondispatchableenergy），其ä¸æ°´ç”µç«™ã€ç”Ÿç‰©èƒ½å’Œåœ°çƒèƒ½å‡å±žäºŽå¯åˆ†æ´¾èƒ½æºï¼Œè€Œé£Žèƒ½ã€å¤ªé˜³èƒ½å’Œæ½®æ±èƒ½å‡å±žäºŽä¸å¯åˆ†æ´¾èƒ½æºã€‚划分的ä¾æ®åœ¨äºŽå¯åˆ†æ´¾èƒ½æºçš„能æºä¾›åº”基本是å¯æŽ§çš„，而ä¸å¯åˆ†æ´¾èƒ½æºåˆ™ç›¸å，例如风力å‘电ä¸é£Žçš„速度和时间是ä¸å¯æŽ§çš„。å¯åˆ†æ´¾èƒ½æºçš„接入管ç†ä¸ŽåŒ–石能æºå‘ç”µç³»ç»Ÿæ— æ˜Žæ˜¾ä¸åŒï¼Œè€Œä¸å¯åˆ†æ´¾èƒ½æºç”±äºŽèƒ½æºä¾›åº”的波动性，接入电网åŽä¼šå¯¹ç”µç½‘系统的稳定性出现影å“ã€‚å› æ¤ï¼Œä¸å¯åˆ†æ´¾èƒ½æºçš„接入管ç†é—®é¢˜å°†æ˜¯æœªæ¥æ™ºèƒ½ç”µç½‘å‘ç”µç³»ç»Ÿçš„ç ”ç©¶é‡ç‚¹ã€‚ç›®å‰ï¼Œä¸å¯åˆ†æ´¾èƒ½æºå‘电主è¦ä»¥é£ŽåŠ›å‘电ã€å…‰ä¼å‘ç”µå’Œç‡ƒæ–™ç”µæ± ä¸ºä¸»ã€‚æ®2009年的统计数æ®ï¼Œé£ŽåŠ›å‘电的容é‡é•¿æ¯”其余新能æºå‘电系统容é‡ä¹‹å’Œè¿˜è¦å¤šï¼Œå…¨çƒé£ŽåŠ›å‘电装机总容é‡è¾¾åˆ°160GW，而光ä¼å‘电则是长速度最快的新能æºå‘电系统。
å…‰ä¼å‘电系统和风力å‘电系统的主è¦ç‰¹ç‚¹åœ¨äºŽå…¶èƒ½æºä¾›åº”çš„é—´æ‡æ€§ï¼Œå› æ¤ä¼šé€ æˆå‘电输出电压ã€é¢‘率的波动。而这ç§æ³¢åŠ¨æ€§åœ¨æŽ¥å…¥ç”µç½‘åŽä¼šå¯¹ç”µç½‘系统的整体稳定性产生影å“。这ç§å‘电电压和频率的波动性表现为两类问题：一类是æ£å¸¸å‘电期间由于能æºä¾›åº”æ³¢åŠ¨é€ æˆçš„电能质é‡é—®é¢˜ï¼Œå¦‚风速时大时å°é€ æˆçš„电压ä¸ç¨³å®šï¼›äºŒæ˜¯èƒ½æºè¾“å…¥ä¸ç¨³å®šé€ æˆçš„能é‡è¾“出波动问题，如风力å‘电ä¸é£Žæœºè¾“出功率的波动，æžç«¯æƒ…况下风力过å°æˆ–过大为ä¿æŠ¤é£ŽåŠ›å‘电机会åœæ¢å‘电，å³åœæ¢è¾“出。为解决第一类问题，电力系统领域已进行了数åå¹´çš„ç ”ç©¶ï¼Œç›®å‰å·²æœ‰æ–¹æ³•å¤šåŸºäºŽç”µåŠ›ç”µå器件的应用，通过在风力å‘ç”µæœºå’Œç”µç½‘ä¹‹é—´åŠ å…¥å˜æµå™¨åŠç”µå®¹å™¨ç»„åˆç‰ç”µåŠ›ç”µå器件，以实现对电压抖动ã€é¢‘率抖动ã€æ— 功补å¿å’Œæœ‰åŠŸè¾“出ç‰å‘电系统关键å‚数的控制。例如风力å‘电机自20世纪80年代起ç»è¿‡äº†å››äº”代的改进，早期的风力电机速度ä¸å¯æŽ§ï¼Œé£Žæœºè¾“å‡ºä»…é€šè¿‡ä¸€ä¸ªæ— åŠŸè¡¥å¿çŽ¯èŠ‚å°±åŠ å…¥åˆ°å¤§ç”µç½‘ä¸ï¼Œå› æ¤é£ŽåŠ›çš„波动直接会输入到电网系统ä¸ï¼Œè€Œç›®å‰çš„å¯æŽ§å˜é€Ÿæ’频风力电机已å¯è¾ƒå¥½å®žçŽ°å¯¹é£Žæœºè¾“出的电能质é‡æŽ§åˆ¶ï¼Œè¯¦ç»†ä¿¡æ¯å¯ã€‚在电能质é‡æŽ§åˆ¶æ–¹é¢å·²æœ‰æŠ€æœ¯åŒ…括机械开关电容MSCsã€åŸºäºŽå¯æŽ§æ™¶é˜ç®¡çš„é™æ¢æ— 功补å¿SVCs以åŠé™æ¢åŒæ¥è¡¥å¿STATCOM在实现了在ä¸å¯åˆ†æ´¾èƒ½æºæŽ§åˆ¶åŸºç¡€ä¸Šï¼Œä¸å¯åˆ†é…能æºæŽ¥å…¥çš„稳定控制è¿è¡Œç›‘æŽ§ä¸Žä¸Šæ–‡è®ºè¿°ä¼ ç»Ÿç”µåŠ›ç³»ç»ŸæŽ§åˆ¶æ¨¡åž‹çš„ä¸€è‡´è€Œå¯¹äºŽä¸å¯åˆ†æ´¾èƒ½æºå‘电间æ‡æ€§é€ æˆçš„第2类问题，则更ä¾èµ–äºŽæ™ºèƒ½ç”µç½‘ä¼ æ„Ÿã€é‡æµ‹ã€é€šä¿¡å’Œæ•°æ®å¤„ç†çŽ¯èŠ‚的支撑圄8以风力å‘电为例æ述了智能电网信æ¯ç³»ç»Ÿå¯¹é£ŽåŠ›å‘电接入的管ç†ã€‚
ç›®å‰ï¼Œè§£å†³é£ŽåŠ›å‘电系统å¯èƒ½å‡ºçŽ°çš„输出ä¸ç¨³å®šé—®é¢˜ï¼Œä¸»è¦æœ‰ä¸¤æ¡æ€è·¯ï¼šä¸€æ˜¯é€šè¿‡é¢„测风场所在地的风力输出信æ¯ï¼Œç»“åˆè´Ÿè½½æµ‹çš„能æºéœ€æ±‚ä¿¡æ¯ï¼Œé€šè¿‡ä¸Žç”µèƒ½å˜å‚¨ç»“åˆçš„æ··åˆæ–°èƒ½æºå‘电系统进行实时调度，以实现稳定的å‘电输出但第1ç§æ€è·¯éœ€è¦å¤§é‡çš„分布å¼å˜å‚¨è®¾å¤‡ä¸Žé£Žç”µç³»ç»Ÿé…套建设，æˆæœ¬è¾ƒé«˜ï¼›äºŒæ˜¯é€šè¿‡å¯¹ç”µç½‘è´Ÿè·çš„实时控制ã€å¹³è¡¡é£ŽåŠ›å‘电输出和负载功率需求之间的关系，在风机输出å‡å°‘æ—¶å‡å°‘è´Ÿè·çš„使用，从而é™ä½Žå˜å‚¨è®¾å¤‡çš„规AirEnergyStorage）ã€è¶…级电容åŠç”µåŠ¨æ±½è½¦å‚¨èƒ½ç³»ä¾‹å¦‚就是采用抽水储能与新能æºå‘电系统结åˆçš„实例。系统ä¸åŒçš„å˜å‚¨ç³»ç»Ÿèƒ½é‡è½¬åŒ–效率ã€å»ºè®¾æˆæœ¬å’Œé€‚用模å¼éƒ½ä¸ç›¸åŒï¼Œè¯¦ç»†å†…容å¯ä»¥
Cement Bagging,Bag Of Mortar Mix,Big Bag Cement,1 Cubic Meter Cement Bags
Guangdong Yingtong Paper Co., Ltd , https://www.yingtongpacking.com