Успостављање односе између Повер Куалити Догађаји да се одреди њихова Соурце
| Локација | Industrial neighbourhood — small city, Midwest USA |
| Cause | Птица (crow) flew into medium-voltage utility switchgear — line-to-ground fault |
| Network impact | Voltage sags and momentary interruptions across several miles, affecting 200+ купаца |
| Праћење | Four I-Sense monitors distributed throughout the neighbourhood — GPS time-synchronised |
| Source determination | Time-stamp correlation of 4 monitor records confirmed a single utility-caused grid event |
| Confirmation method | Utility relay operation records matched the GPS timestamp from all four monitors |
| Customer impact | One monitored customer experienced a 13-hour process shutdown |
| Key finding | Multi-point time-synchronised monitoring can attribute PQ events to utility or customer source — resolving the most contentious question in industrial PQ disputes |
01 Context — The Source Attribution Problem
One of the most contentious and practically important questions in industrial power quality engineering is deceptively simple: when a voltage sag or interruption disrupts a customer’s process, who caused it? The answer determines who bears responsibility for the event, who funds any mitigation, and — in regulated utility environments — whether a service quality complaint has merit.
Power quality events may originate from either side of the utility meter:
- Utility-caused (grid events) — faults on transmission or distribution lines, switching operations, capacitor bank switching, voltage regulator operations. These affect all customers connected to the same feeder or substation and are the utility’s operational responsibility
- Customer-caused (internal events) — motor starts, arc furnace operations, capacitor switching within the plant, fault conditions on internal wiring. These are the customer’s responsibility and may also affect neighbouring customers connected to the same distribution bus
- Neighbouring customer-caused events — a large non-linear or intermittent load at an adjacent plant (arc furnace, large motor, resistance welder) that propagates voltage disturbances through the shared distribution network to other customers
Without appropriate monitoring — specifically, multi-point time-synchronised monitoring that captures the event simultaneously at multiple locations — it is impossible to distinguish these three cases from a single measurement point. A single monitor at the service entrance of a plant records the event but cannot determine whether it originated upstream (utility) or at a neighbouring customer’s premises.
In most jurisdictions, the utility’s obligation to provide power quality within specified limits (voltage magnitude, треперење, секундарне фреквенције) applies to disturbances that originate from the utility network. If a customer’s process disruption is caused by a neighbouring customer’s operations — a large arc furnace two feeders away, for example — the utility may have limited regulatory obligation to act, even though the affected customer’s experience is identical to a utility-caused event. Source attribution is therefore not just a technical question: it is a prerequisite for assigning responsibility and determining the correct mitigation strategy.
02 The Event — A Bird in the Switchgear
In an industrial neighbourhood in a small Midwestern city, a crow flew into medium-voltage switchgear at a utility substation. The contact between the bird and the energised equipment created a phase-to-ground fault on the distribution system. The fault current caused voltage sags and momentary loss of voltage across a significant portion of the distribution network — affecting customers over several miles and more than 200 customer accounts.
Four I-Sense monitors were distributed throughout the neighbourhood as part of the I-Grid monitoring network. Each monitor recorded the event independently, with GPS-accurate timestamps that allowed the recorded data to be precisely correlated in time.
A single phase-to-ground fault caused by a bird contact at one substation affected more than 200 customer accounts across several miles of distribution network. This illustrates the network propagation characteristic of voltage sags — unlike power interruptions, which are typically localised to the faulted feeder, voltage sags propagate across the network at the speed of light, affecting customers on adjacent feeders and even adjacent substations depending on the network impedance topology. The 200+ customers who experienced this event did not share a common feeder — they shared a common substation bus voltage that was depressed by the fault current.
03 Source Attribution — How the Monitoring Proved the Cause
Корак 1 — GPS timestamp correlation
Each I-Sense monitor recorded the voltage event independently, with a GPS-accurate timestamp. When the four records were aligned on a common time axis, all four monitors showed voltage depressions beginning at exactly the same instant — within the GPS synchronisation accuracy of approximately 1 microsecond. This simultaneous onset is the definitive signature of a grid event: an event originating within any individual customer’s premises would reach the other three monitor locations with a measurable propagation delay, not simultaneously.
Корак 2 — Waveform analysis
Analysis of the waveforms at all four monitors showed the characteristic signature of a single-line-to-ground (SLG) fault — the most common fault type on distribution systems, accounting for approximately 70–80% of all distribution faults. Note that Monitor #1 recorded line-to-line voltage while the other three recorded line-to-neutral voltage — the different measurement configurations produced different waveform shapes from the same event, which could appear inconsistent without the time-synchronisation context.
Корак 3 — Utility record confirmation
The hypothesis that all four recordings represented a single utility-caused event was definitively confirmed when utility company records revealed a relay operation on a parallel feeder with exactly the same timestamp as the power quality events recorded by all four monitors. The relay operated to clear the crow-induced fault — a routine protective operation — but its timestamp provided irrefutable confirmation of both the cause and the time of the event.
The event was unambiguously utility-caused. The crow-induced fault at the substation switchgear propagated voltage sags to all customers connected to the affected distribution network. No customer action caused or contributed to the event. This determination was only possible because of the multi-point GPS-synchronised monitoring network — a single monitor at any one customer’s service entrance would have recorded the sag but could not have distinguished it from a neighbouring customer’s load-switching event.
04 Customer Impact and Mitigation
One of the four monitored customers experienced a 13-hour process shutdown as a result of this event. The shutdown duration is disproportionate to the electrical event duration — the voltage disturbance itself lasted only a few cycles. The 13-hour shutdown reflects the restart time and complexity of the customer’s industrial process, not the duration of the power quality event. This is a common pattern in process industries: a millisecond electrical event causes an hours-long production disruption.
The original study notes that analysis of the waveforms from all four monitor locations shows that commercially available voltage sag mitigation equipment would have protected customer equipment from this event at all four monitored locations. The voltage sag characteristics — depth and duration — were within the operating envelope of dynamic voltage restorers (ДВР) and uninterruptible power supply (УПС) systems designed for process protection. A 13-hour production loss from a 3-cycle sag that a $50,000 sag corrector would have prevented entirely illustrates the economics of voltage sag mitigation in process-critical environments.
Implications for monitoring network design
The study draws an important conclusion about monitoring network density. Because grid events — caused by utility network faults — propagate across the network and are experienced simultaneously by all customers in a geographical region, it is not necessary to monitor every customer to assess the power quality environment of a region. A monitoring network covering a small percentage of customers, if properly designed and time-synchronised, provides statistically representative data for the entire region.
This principle has significant implications for utility PQ monitoring program design: sparse, well-placed, time-synchronised monitors can characterise network-wide PQ behaviour far more efficiently than dense, uncoordinated single-point measurements at individual customer service entrances.
05 Power Quality Perspective
This case study is the clearest possible demonstration of why source attribution requires network monitoring — not just customer-side measurement. From a utility engineering perspective, the case study validates a principle that is fundamental to distribution PQ management: grid events are network phenomena, not individual customer phenomena. A crow in a switchgear at one substation produces voltage sags at 200+ customer locations simultaneously. No individual customer measurement, however sophisticated, can identify this as a single grid event rather than 200 separate events.
The GPS synchronisation technology used in the I-Grid system is the key enabler. Without time synchronisation accurate to the microsecond level, the four monitor records could not be reliably correlated — a 60 Hz power system cycle is approximately 16,700 microseconds, and distinguishing simultaneous onset (grid event) from near-simultaneous onset (propagating internal event) requires much better than cycle-level time resolution.
У 30 years of utility power quality work, the source attribution question — “is this our fault or theirs?” — is the most frequently contentious issue between utilities and industrial customers. The customer experiences a process disruption and a production loss. They call the utility. The utility checks its relay records. If no relay operated on the customer’s feeder, the utility concludes the event was internal. The customer disagrees. Without multi-point time-synchronised monitoring, neither side can prove their case definitively. This case study demonstrates that the technology to resolve the question definitively has existed since at least 2003. The gap has been deployment and coordination — not technology. A utility with a well-designed PQ monitoring network can resolve source attribution disputes in minutes. Without one, disputes can last years.
Референце
- Divan D, Brumsickle W, Eto J. A New Approach to Power Quality and Electricity Reliability Monitoring — Case Study Illustrations of the Capabilities of the I-Grid™ Систем. Ернест Орландо Лавренце Беркелеи Натионал Лаборатори, LBNL-52048, Април 2003.
- ИЕЕЕ Стд 1159-2019. IEEE Recommended Practice for Monitoring Electric Power Quality. ИЕЕЕ, Њујорк, НИ, 2019.
- ИЕЦ 61000-4-30:2015+AMD1:2021. Electromagnetic compatibility — Part 4-30: Методе мерења квалитета електричне енергије. ИЕЦ, Geneva.
Divan D, Brumsickle W, Eto J. A New Approach to Power Quality and Electricity Reliability Monitoring — Case Study Illustrations of the Capabilities of the I-Grid™ Систем. Lawrence Berkeley National Laboratory, LBNL-52048, Април 2003.
This case study is presented in summary and commentary form for educational purposes. Original material is attributed to the authors and Lawrence Berkeley National Laboratory. The PQ Perspective section (Одељак 5) and SVG diagram are original IPQDF editorial content by Denis Ruest, M.Sc. (Applied), P.Eng. (ret.). IPQDF does not claim authorship of the original research.