A Distribution Transformer Monitor (DTM) is a specialized hardware device that collects and measures information relative to electricity passing into and through a distribution transformer. The DTM is typically retrofitted onto pole top and pad mount transformers. A pole top (above ground) or pad mount (below ground) transformer commonly powers anywhere from 5-8 homes in the US and is the last voltage transition in stepping down voltage before it gets to the home or business. The conventional placement of Distributed Temperature Monitoring (DTM) devices is typically observed at the terminals of transformers. However, there are instances where these devices are directly affixed to the secondary power lines.
DTM apparatus commonly comprises precision-centric sensors, either of the non-piercing or piercing variety, in addition to communication modules integrated on board for seamless data transmission. Adequate provisions for power supply are also incorporated within the DTM setup. The captured data from the DTM unit is relayed to a central data collection engine and/or the established Supervisory Control and Data Acquisition (SCADA) / Meter Data Management (MDM) system, where pertinent information pertaining to the transformer is stored and made accessible to users. Often, analytical platforms come into play to decipher the data gleaned and reported by the DTM, thereby enhancing the comprehension of the acquired information.
Overview The Distribution Transformer Monitoring (DTM) system, often referred to as an intra-grid sensor, occupies a distinctive position within the distribution grid. It is capable of providing both real-time and historical data about the transformers it monitors. Beyond individual transformer monitoring, DTMs constitute crucial information access points within the grid's architecture. When deployed in a network across the distribution grid, these devices offer multiple data points. For electric utility operators, these data points can range from basic bellwether measurements to comprehensive insights into intra-grid conditions and performance, depending on the deployment density.
The strategy for deploying DTM devices varies according to the specific needs and objectives of the utility in question. Deployments may be surgical, meaning strategically limited to key areas of the grid, or they can be comprehensive, covering larger grid sections such as line segments, specific circuit feeders, or entire substations. The decision on the placement and density of DTM deployments is influenced by the targeted data requirements and operational goals of the respective electric utility.
Remote Over-The-Air (OTA) updates/upgrades are supported by certain DTM device offerings. This OTA capability, when supported, allows the operator to perform remote configuration and/or executable code (i.e., Firmware) updates of the DTM device(s) without the need for costly truck rolls or unit replacement. By supporting OTA Firmware updates/upgrades, providers can progressively broaden and deepen the suite of data points captured by the DTM device, making it reasonably future-proof, thus escalating value and relevance to the utility operator throughout the lifespan of the DTM device(s).
Applications DTM sensors transmit timely, accurate intra-grid readings for Voltage, Energy, Current, and Temperature, thus empowering a long list of derived performance and power quality understandings for operations personnel. These fundamental data points provide direct relevance to electric utility operators. Additionally, these data points can be extrapolated to reveal enhanced grid performance and asset health information. Given the physical location of the DTM within the heart of the distribution grid, in addition to the DTM reporting frequency capability, the versatility of this intra-grid sensor is expansive.
Utilities across the U.S. are beginning to turn to transformer technologies to improve distribution reliability and efficiency, as well as customer service and operating costs.
Examples of applications derived from direct and/or indirect information presented by the DTM include: Asset management and Condition monitoring (AMCM) Preventive Grid Asset Maintenance recognition Power Theft identification Demand response assistance Voltage optimization Outage notification/Restoration enhancement Distributed Energy Resource (DER) Monitoring (i.e., bi-directional energy monitoring, voltage impacts, current impacts, etc.) Transformer under-sizing/over-loading recognition (e.g., electric vehicle charging station impacts, hydroponic marijuana grow houses, etc.) Transformer under-sizing (i.e., unnecessary added energy loss, accelerated premature failure, etc.) Abnormal transformer voltage characteristics Transformer-related temperature monitoring Transformer life expectancy estimation Phase Imbalance recognition Populate Artificial Intelligence Platforms (foresee/forecast emerging intra-grid problems that human recognition cannot identify) Facilitate Strategic Battery Storage Location Efforts (i.e., leverage DER-induced Reverse Energy monitoring to locate present and future battery placements) Identify Geographic Information System (GIS) Mapping errors
Health Concerns Given the physical deployment position of the DTM (i.e., on the distribution transformer), there are no known health concerns related to this family of intra-grid sensors. DTM devices are created with user/installer safety in mind and otherwise bear no known measurable environmental impact.
Business case justification Utility spending on asset management and grid monitoring technology is to hit almost $50 billion by 2023, according to a new study from Navigant Research. Given the pioneering stage of the DTM technology, significant business case information is limited in availability for public review. Arguments against DTM deployment commonly assert that the secondary transformer value of $1000.00 to $2000.00 US (average) does not justify applying a retrofit DTM to monitor the transformer assets’ performance. However, the DTM value is based upon a combination of features/benefits that include not only the transformer condition monitoring importance, but also a series of data visibility and reconciliation features from within the heart of the distribution grid that is otherwise unavailable to the electric operator (see Applications).
In essence, while the Advanced Metering Infrastructure (AMI) or smart meter providers supply a series of data points to utilities, the DTM offers another dimension of real-time and historical data access for the grid operator and is capable of detecting information that AMI assets cannot capture and/or report with the necessary frequency to the operator. Each utility must evaluate, among other things, their unique grid management needs, their levels of unidentifiable losses that can be remediated/mitigated by DTM deployment, their Demand Response savings potential through Volt/VAR and conservation voltage reduction (CVR) related practices supported by DTM devices, and their need for real-time and/or historic data from within the heart of the distribution grid when formulating their business case justification. Investment decisions relating to DTM deployments involve a collection of monetary benefits that include savings for the utility through decreased operations costs, reduced power outages, lessened power outage durations, reduced peak demand costs, and recoverable power theft losses; and indirect financial benefits associated with improved power delivery and quality to rate payers, reduced truck rolls which lessen service costs in addition to yielding decreased environmental impacts, improvement of the utility's Key Performance Indicators (e.g., SAIDI, SAIFI, CAIDI, etc.), and improved stakeholder/shareholder value through enhanced bottom line fiscal performance by the utility.
To date, smart grid providers have presented electric utility operators with management and control tools for substations, and have introduced Advanced Metering Infrastructure (AMI, or smart meters) to improve data access at the beginning and endpoints within the distribution grid. However, the expansive and most vulnerable segment of the grid remains the section between substations and endpoint meters—comprising over 6 million line miles (US grid), and 40+ million distribution transformers (US grid) -- which is now collectively coined the "heart of the grid".
Presently, the “heart of the grid” area is somewhat devoid of a sufficient density of versatile, cost-effective sensors, thereby leaving operators with limited visibility into this critical area. To further evolve from a traditional reactionary management and problem resolution state within the “heart of the grid” space, to a more proactive posture that is congruent with the purpose and value of a ‘smart grid’, the emergence of the DTM is timely. While efforts have been made to leverage substation and endpoint meter data, along with supporting algorithms to speculate and postulate occurrences and needs within the “heart of the grid”, it is evident that grid operators require precision-accurate, timely information from within this expansive segment of the grid in order to proactively and efficiently manage its performance. The need to effectively combine all three critical points of measure (i.e., substations, endpoint meters, and DTM data from within the “heart of the grid”) may be collectively required to advance a comprehensive smart grid experience.
Why Distribution Transformer Monitors are fundamental for creating Grid Modernization—Achieving valuable results that Advanced Meter Infrastructure cannot reliably address:
Advanced Metering Infrastructure (AMI), Automated Meter Reading (AMR), and/or Manual Meter reads accurately and reliably represent endpoint data only. If any power is tapped before the endpoint meter (i.e., pre-meter tapping), accurate detection of this power diversion is difficult or nearly impossible without the use of a reconciliation point upstream—preferably at the distribution transformer. By accurately capturing unique data at the distribution transformer, DTM devices provide necessary reconciliation points between the substation and endpoint meters, thus enabling utility operators to effectively detect power diversion occurring in front of the endpoint meter. Without a reliable reconciliation point at the distribution transformer, the utility operator's power theft detection system remains porous, inefficient, and unreliable. If AMI alone was a complete solution for diversion detection/identification, then AMI-installed utilities would seldom experience more than 1-3% loss from otherwise unavoidable technical losses. According to the United States Energy Information Administration (US EIA) most power distribution utilities report annual energy losses of nearly 5% or more. DTM devices and associated Data Analytics have the functionality to allow the utility operators to quickly identify intra-grid anomalies. AMI is a component in the diversion detection and solution process, but without a reliable reconciliation point at the distribution transformer, the detection system remains porous and inefficient. Many utilities, even those with AMI, actually suffer from the necessary availability of timely, granular, accurate intra-grid information that is necessary for improved energy loss detection, and enhanced Grid Modernization. Energy measurements at the distribution transformer allow for ongoing validation of the AMI meters to ensure accurate meter performance, and to reveal improper metering issues within the distribution grid.