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This paper first presents a review of the current technology in power system protection and control, including the protective relays, local controls and system controls. Then, this paper presents a couple of typical scenarios to illustrate the possible problems with the existing technology. Next, this paper proposes the vision of a self-healing pro...
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... even though this is initially a frequency stability problem, the final consequence is a voltage collapse. Figure 5 shows the gradual process based on the above analysis. A possible solution to the above problem is to develop a fast and efficient approach to dynamically analyze the system state in real-time or in 5-minute look-head mode. ...
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... A SHePS must be able to perform a) protection, or detection and isolation of a fault; and b) restoration, in which all of the healthy parts of the system are re-energized. A great deal of work has been done on SHePS [2][3][4][5][6], and FLISR-type SHePS [7] are commercially available (for example, see [8] and [9]). ...
In self-healing, self-assembling power systems, in which adjacent microgrids may autonomously connect to one another (i.e., self-network), it is necessary to ensure that adjacent microgrids connect only when their voltages are sufficiently well-synchronized in magnitude and phase. In many cases, a standard synchronization check function can achieve this, but in self-healing power systems that rely on local measurements only (either due to lack of communications or due to a communications outage), situations arise in which two line relays form the boundary between two microgrids, and, because they cannot share data, neither can prevent the other from reclosing. It is thus necessary to ensure via the line relays' timing functions that they do not close at the same time, because if one closes first then the other can go to synchronization check. This paper describes a self-healing power systems concept utilizing only local measurements, describes and demonstrates how asynchronous connection of adjacent microgrids can occur, and then proposes a simple process for assigning "tagged" time delays to the line relays such that no two adjacent line relays have the same reclosure time delay. This "tagged timer" process is demonstrated via PSCAD simulation using the IEEE 13-bus distribution test circuit and manufacturer-specific, code-based inverter models.
... A SHePS must be able to perform several critical power system functions, including a) protection, which includes detection of faults and isolation of faulted parts of the system; and b) restoration of service, in which all of the undamaged parts of the system are re-energized. SHePS have been extensively reported on in the literature [2][3][4][5][6], and Fault Location, Isolation and System Restoration (FLISR)-type SHePS [7], such as those described in [8] and [9], are commercially available today. ...
Self-healing power systems can provide significant resilience benefits. However, most self-healing power systems concepts rely on data sharing via communications that may be cost-prohibitive or that could become unreliable during contingency events. Self-healing, or self-assembly, via local measurements only would have some significant advantages, if sufficient performance can be achieved. This paper presents simulations demonstrating the use of a specific set of techniques to achieve self-assembly and self-healing in the IEEE 13-bus distribution test circuit, using only local measurements, when energized only by distributed inverter-based resources. Black start, fault isolation, and system restoration are demonstrated. The inverter-based resources are represented by manufacturer-specific code-based models. The results indicate that the performance of the local-measurements-only system can be comparable to other techniques, in the cases tested.
... A considerable amount of work has been done on various types of SHePS over the last two decades [2][3][4][5][6], and some SHePS techniques are mature; one SHePS technology, commonly called Fault Location Isolation and Service Restoration (FLISR) [7], is commercially available (for example, see [8] and [9]). Today's SHePS technologies typically address the two engineering challenges described above via sharing of data over a high-speed communications network [10,11], between devices and a central controller (a centralized architecture) or between devices directly (a distributed architecture). ...
Self-healing or self-assembling power systems that rely on local measurements for decision making can provide significant resilience benefits, but they also must include safeguards that prevent the system from self-assembling into an undesirable configuration. One potential undesirable configuration would be the formation of closed loops for which the system was not designed, a situation that can arise any time that two intentional-island systems can be connected in more than one place, e.g. if tie-line breakers are included in the self-assembling system. This paper discusses the unintentional loop formation problem in self-assembling systems and presents a method for mitigating it. This method involves calculating the correlation or the mean absolute error (MAE) between the two local frequency measurements made on either side of a line relay. The correlation and MAE between these frequencies changes significantly between the loop and non-loop cases, and this difference can be used for loop detection. This paper presents and explains the method in detail, presents evidence that the method's underlying assumptions are valid, and demonstrates in PSCAD two implementations of the method. The paper concludes with a discussion of the strengths and weaknesses of the proposed method.
... Currently, the main approach for system control and decision making is centralized. The most common application of centralized control is in the generation and transmission systems, where the measurements are assembled in a Supervisory Control and Data Acquisition (SCADA) system, whose data are used by operators to monitor, control and optimize the control of the field devices, processing information and transmitting control commands [26]. In a centralized approach in substations, the system may be controlled by intelligent electronic devices (IEDs) [23]. ...
... In this paper the communication system is not discussed but the information given by it is used in LabVIEW software to develop Virtual Power Protection System (VPPS). VPPS system not only secures the system but also control the power system [11,12]. ...
This paper presents Virtual power protection system (VPPS) for control and automatic healing of Power System. VPPS is a system that can be implemented in control centre to detect any system abnormalities in a power system. In a self-healed power system, unplanned outages and abnormalities could be prevented through better prediction, analysis and control. Recognition and diagnosis of fault conditions has a significant role that may prevent disturbances extension and spreading to other healthy parts of the power system. The VPPS is developed in NI LabVIEW environmentwhich analyses different types of power system faults like over/under voltage, over/under frequency, short circuit and line to ground faults etc. and automatically protects and heals the systems.The simulation results are presented to illuminate the effectiveness of the VPPS under different abnormal condition of power system.
... Presently, the protection and control settings are configured as fixed values based on offline studies [23], [26]. In the future, these settings should be configured in real time in a proactive and adaptive approach to better utilize the generation and transmission asset when the system is not stressed and to better protect the system under extremely stressed conditions [27]. ...
A modern power grid needs to become smarter in order to provide an affordable, reliable, and sustainable supply of electricity. For these reasons, considerable activity has been carried out in the United States and Europe to formulate and promote a vision for the development of future smart power grids. However, the majority of these activities emphasized only the distribution grid and demand side leaving the big picture of the transmission grid in the context of smart grids unclear. This paper presents a unique vision for the future of smart transmission grids in which their major features are identified. In this vision, each smart transmission grid is regarded as an integrated system that functionally consists of three interactive, smart components, i.e., smart control centers, smart transmission networks, and smart substations. The features and functions of each of the three functional components, as well as the enabling technologies to achieve these features and functions, are discussed in detail in the paper.
... Presently, the protection and control settings are configured as fixed values based on offline studies [23], [26]. In the future, these settings should be configured in real-time in a proactive and adaptive approach such that it will better utilize the generation and transmission asset when the system is not stressed and to better protect the system under extremely stressed conditions [27]. ...
Modern power grid is required to become smarter in order to provide an affordable, reliable, and sustainable supply of electricity. Under such circumstances, considerable activities have been carried out in the U.S. and Europe to formulate and promote a vision for the development of the future smart power grids. However, the majority of these activities only placed emphasis on the distribution grid and demand side; while the big picture of the transmission grid in the context of smart grids is still unclear. This paper presents a unique vision for the future smart transmission grids in which the major features that these grids must have are clearly identified. In this vision, each smart transmission grid is regarded as an integrated system that functionally consists of three interactive, smart components, i.e., smart control centers, smart transmission networks, and smart substations. The features and functions of each of the three functional components as well as the enabling technologies to achieve these features and functions are discussed in detail in the paper.
... The research effort in the area of power grid computing primarily focuses on algorithms and models used in power grid computing tasks by reducing the execution time while enhanc-ing accuracy. Li et al. [12] present a vision to better utilize the real-time information through the next generation monitoring and communication technology to perform a much faster online security analysis. [9] and [11] propose improved algorithms for state estimation and load forecasting, respectively. ...
Blackouts in our daily life can be disastrous with enor- mous economic loss. Blackouts usually occur when appro- priate corrective actions are not effectively taken for the initial contingency, resulting in a cascade failure. There - fore, it is critical to complete those tasks that are running power grid computing algorithms in the Energy Manage- ment System (EMS) in a timely manner to avoid blackouts. This problem can be formulated as guaranteeing end-to-end deadlines in a Distributed Real-time Embedded (DRE) sys- tem. However, existing work in power grid computing runs those tasks in an open-loop manner, which leads to poor guarantees on timeliness thus a high probability of black- outs. Furthermore, existing feedback scheduling algorith ms in DRE systems cannot be directly adopted to handle with significantly different timescales of power grid computing tasks. In this paper, we propose a hierarchical control so- lution to guarantee the deadlines of those tasks in EMS by grouping them based on their characteristics. Our solu- tion is based on well-established control theory for guar- anteed control accuracy and system stability. Simulation results based on a realistic workload configuration demon- strate that our solution can guarantee timeliness for power grid computing and hence help to avoid blackouts.
... HE present technology in power system operation such as state estimation and contingency analysis was initially developed back to 1960s. The technology advance in communication, computing and power system algorithms has made it possible to re-think the way to perform real-time monitoring and control [1][2][3][4]. The typical present technology of monitoring and control may be briefly summarized as follows: ...
... The present technology lacks the coordination of protection and control systems [1][2]. Each component takes actions based on its own decision. ...
This paper presents a vision of the next generation monitoring, assessment and control functions in a future control center, which will be fully automated, decentralized and based on wide-area measurement. The paper points out the technology and infrastructure gaps to fill to fully implement future control centers, as well as a roadmap towards the proposed vision. This vision is expected to be a critical part of the future smart transmission grid.
In the quest for an adaptable, dependable, and sustainable energy supply, the modern power grid necessitates a transformative upgrade towards intelligence. While substantial efforts have been devoted to envisioning and advancing smart power grids in the United States and Europe, the focus has predominantly centered on the distribution grid and demand-side management, leaving the holistic perspective of the transmission grid within the context of smart grids somewhat obscured. This paper proposes a distinct vision for the future of smart transmission grids, delineating their pivotal attributes. In this envisioned framework, each smart transmission grid emerges as a cohesive, integrated system comprising three interrelated smart components: smart control centers, smart transmission networks, and smart substations. The paper meticulously outlines the characteristics and functionalities of each of these three essential components, elucidating the enabling technologies necessary to realize their envisioned capabilities. By conceptualizing smart transmission grids as multifaceted systems driven by intelligent components, this vision underscores the potential for enhancing grid efficiency, reliability, and sustainability. Through the seamless integration of advanced control centers, transmission networks, and substations empowered by cutting-edge technologies, smart transmission grids aim to optimize grid operations, facilitate dynamic energy management, and foster resilience against emerging challenges and disruptions.
