Distribution Task Team

Use Case

The objective of Phase Identification is to recognize, track and report the connectivity and loading of Phases A,B,C through the distribution system so as to prevent excessive phase imbalance.

Background

Distribution system maps and models tend to lack reliable information about which single-phase laterals or individual customers are connected to which of the three phases. This connectivity information is not entirely static, since during restoration work such as repairs after a major storm, the phasing may be changed (deliberately or inadvertently). Historically, utilities have relied on manual notations from field crews about connectivity. In the absence of detailed records, owing to anecdotal reportings, an approximate balance – say, on the order of 10% difference in currents among phases – can usually be expected at the feeder head, but with no guarantees and occasional large departures.

Use Case

Disaggregation of net metered distributed generation (DG) from customer load uses high-precision measurements on the utility side of the meter to estimate the actual generation and amount of load offset behind the meter.

Background

When the distribution utility lacks access to separate load and generation telemetry from customer premises, net metered solar generation masks an unknown amount of load. This masked load implies a greater system exposure to contingencies. The masked load must be accounted for to assure adequate generation reserves in case of simultaneous tripping of many DG units, and to assure safe cold load pickup after an outage.

Use Case

Synchronized measurements at multiple locations throughout a distribution system during a fault can aid in the location of the fault and expedite service restoration.

Background

The vast majority of faults originate in distribution systems. The traditional means of locating a fault on a distribution system is for a utility employee to travel along the feeder where a protective device has operated, or where customers have reported an outage, and search for the fault visually (in the case of overhead lines) or with an underground fault locator.

Reducing the extent of this manual inspection would reduce both outage duration and cost to the utility. A common, simple approach for this is to estimate the fault location using measurements of the fault current and voltage at the substation and a feeder impedance model. However, multiple combinations of fault location and impedance may lead to the same quantities being recorded at the substation. Furthermore, the contribution of distributed generation (DG) to fault current, which is not directly observable from the substation, can lead to errors in fault location.

The accuracy of fault location can be improved by collecting synchronized measurements of current and/or voltage at additional locations throughout the system. Several approaches based on search, optimization, and state estimation techniques have been demonstrated to locate faults using distributed measurements.

Use Case

Conventional remote terminal unit (RTU) based automation approaches suffer from slow measurement update and lack of time-stamp values for precise comparison of state parameters at different locations. A time-synchronized control approach is more favorable for protection event analysis, islanding detection and grid re-synchronization practices.

Background

Microgrids are small scale decentralized electricity networks featuring more complex structure compared to large generation plants. A microgrid may consists of various types of generation units and local loads, including energy storage. Synchronous generators, induction generators and inverter based distributed energy resources (DER) are the main types of generation units in a microgrid. Load demand management is also often posited as a DER. As the penetration level of DER increases, concerns regarding the stability and interactions between units are becoming more important.

The conventional control and management of the distribution grid, where only voltage magnitudes are measured and utilized at the control center, could easily misdiagnose these new dynamics and potentially lead to severe complications in grid operations. This results in growing interest to utilize synchrophasor measurements in distribution system applications.

Use Case

High-precision synchrophasor measurements can detect early signs of equipment aging, malfunction, or incorrect operation from the electrical signature, so as to help prevent costly damage or outages.

Background

Aging and deterioration in distribution transformers or switchgear can be difficult to diagnose inexpensively online. Smaller service transformers are typically just replaced upon failure. Larger equipment such as substation transformers can be tested using dissolved gas analysis (DGA) of the transformer oil that reveals chemical evidence of degradation.

Ongoing condition monitoring of utility equipment would help both to prevent specific device failures and to establish a general improved knowledge base for planning purposes.