By Fahrudin Mekic, ABB
Smart grid refers to electric power systems that enhance grid reliability and efficiency by automatically anticipating and responding to system disturbances. To achieve smart grid status at the power distribution system level, utilities have attempted various automatic technologies in the areas of system metering, protection and control. Within these technologies, automated power restoration is an important part of the puzzle.
Traditionally, electric utilities use the trouble call system to detect power outages. Specifically, when a fault occurs and customers experience power outages, they call and report the power outage. The distribution system control center then dispatches a maintenance crew to the field. The crew first investigates fault location and then implements the switching scheme(s) to conduct fault isolation and power restoration. This traditional power restoration procedure often takes several hours to complete, depending on how fast customers report the power outage and how quickly the maintenance crew can locate the fault point and conduct the power restoration.
In recent years, utilities deployed feeder switching devices, such as reclosers and circuit breakers, with intelligent electronic devices (IEDs) for protection and control applications. The automated capabilities of IEDs, such as measurement, monitoring, control and communications functions, make it practical to implement automated fault identification, fault isolation and power restoration. As a result, the power outage duration and the system reliability can be improved significantly.
Based on the information provided by IEDs, automated fault location identification and fault isolation are relatively easy to achieve. In contrast, automated power restoration is a challenging task, and many research efforts have been focused on tackling this application and studying the operating constraints, load balancing and other practical concerns.
Although some of the many proposed automated power restoration algorithms aim to provide a real-time solution, most of them are only suitable for planning analysis or were developed to be executed in the distribution control centers to aid system operators with appropriate decisions.
An online method for the automated power restoration application previously described exists. The method conducts an analysis to achieve back-feed power restoration–healthy load zones that have lost power that are restored through their boundary-tie switching devices from neighboring sources, with no reconfiguration beyond the tie devices under consideration. The back-feed restoration should not overload any part of the back-feeding network.
Requirements, Concepts and Methodologies
A restoration switching analysis (RSA) method produces a switching sequence that, when executed, will reach a valid post-restoration network that satisfies the following requirements: 1) it is radial; 2) no current violation exists at any network component; 3) no voltage violation exists at any network node.
Other optimization requirements are also considered. For example, losses can be minimized, and the back-feed transformer’s loading can be balanced.
A. Network Model. For the sake of method description, a simplified network model demonstrated here includes three types of components: sources, switching devices–switches that represent sectionalizers, load switches, circuit breakers and reclosers–and loads. Feeder conductors are assumed to be load attributes. Sources are assumed to have limited capacity (ampere rating) but constant voltage. Switches are assumed to have limited loading capability (in amperes), and circuit breakers and reclosers have unlimited current interruption capability. Loads are assumed to be constant, aggregated lumps that connect to switches over zero-impedance feeder conductors. The conductors have limited current carrying capability.
B. Network Connectivity. The connectivity of the network model must be known in order to achieve successful restoration. Data about the switching devices, loads and sources, as well as information about how these different components are connected, are required for the restoration method. Restoration by this method is most effective when multi-layered back-feed networks are present in the distribution system.
C. Restoration Validation Check. The restoration validation check confirms the validity of the post-restoration network configuration to ensure that the network is radial and all the currents and voltages are within the component limits. The restoration method produces radial post-restoration networks. Thus additional radiality checks are not necessary. A current violation check is performed as an integral part of the algorithm, based on the loading aggregation method described below. This check ensures that for all the network components the post-restoration loading currents are below their loading current limits.
D. Network Tracing-based Loading Aggregation. As stated earlier, back-feed power restoration should not overload any part of the back-feeding network. In the described method, this is achieved by recursive network tracing-based loading aggregation method: Start from a back-feeding source (usually a transformer), trace down all the network components it supplies, until the end of the tree structure is reached. When returning to the source, the tracing method sums up the loading current at each network component and if applicable, compared with its corresponding limit. The available capacity of a source can be calculated after the tracing goes back to the source.
E. Single-path and Multi-path Restoration. If a source can provide the restoration power over a single path to an out-of-service load zone, the restoration is called a single-path restoration. Otherwise, the out-of-service load zone may have to be split into two or more load zones to be back-feed, and the scenario is named as multi-path restoration. Both single-path and multi-path restorations may have to shed load in case the back-feed source capacity or feeder components’ loading capability is not sufficient.
Figure 1 shows a single-path full restoration example, where a fault at T-node L3 must be isolated by opening a forward-feed isolation switch R3 and two back-feed isolation switches R6 and R10. In this example, back-feed sources S3 and S4 both have sufficient capacity to pick up the out-of-service load on their corresponding restoration path and each tie switch R9 and R12 can be closed to achieve the restoration. The post-restoration circuit topology is shown in Figure 1(b).
Figure 2 shows a multi-path full restoration example, where a fault at load node L1 must be isolated by a forward-feed isolation switch R1 (in this case no forward restoration is required) and a back-feed isolation switch R2. In this example, none of the back-feed sources S2-S5 can completely pick up all the loads that are left unserved after fault isolation. Hence the algorithm splits the network into two parts by opening R13 and the out-of-service load restored by closing both R9 and R12 (from both S3 and S4). The post-restoration circuit topology is shown in Figure 2(b).
Figure 3 shows an extreme example where the splitting of the out-of-service load zones is still not enough. Following the fault at load L1, and its isolation by opening R1 and R2, none of the back-feed sources can pick up the out-of-service loads completely or even partially without violating the current capacity limits of those sources. Load L5 has to be shed in order to restore power to as many out-of-service loads as possible. The post-restoration circuit topology is shown in Figure 3(b). Note that the out-of-service load zone has to be split into three portions, according to the algorithm.
During the development of the algorithm, a physical circuit with three sources, five switches and three loads was set up (Figure 4) and a controller application was programmed.
In the circuit of Figure 4(a), because of the given source capacity, Figure 4(b), a fault at load L1 results in a splitting of the out-of-service network of L2, R3 and L3, by the opening of switch R3. Both tie switch R4 and R5 close to restore power to the out-of-service loads, as shown in Figure 4(c).
The fault detection and service restoration switching sequence in Figure 4(d) proves the effectiveness of the algorithm.
Achieving smart grid status at the power distribution system level has led to various attempts to upgrade system metering, protection and control. One key technology that has emerged as an important part of the smart grid puzzle is automated power restoration. Traditionally, electric utilities have used the trouble call system to detect power outages.
This article represents a deterministic algorithm that identifies a restoration strategy to restore the out-of-service load due to fault isolation while ensuring that the post-restoration network has a valid configuration. The algorithm is based on the concepts of network tracing, and it supports both single-path and multi-path restoration. In case the network components are too stressed and even the multi-path restoration cannot restore all the out-of-service loads, the algorithm tries to shed minimal load while restoring as many other loads as possible.
Fahrudin Mekic is global product manager with distribution automation for ABB. He has worked for ABB since 1996, where he has focused on power system protection and control in various engineering and managerial positions.