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The iHost software module for the state estimation method is being tested with offline data, obtained from the Distribution Network Management System. Several additional Smart Navigator 2.0 devices have been installed on 33kV overhead lines on Shrewsbury, Meaford and Lydney primary networks.
The iHost software module for the state estimation method is being tested with offline data, obtained from the Distribution Network Management System. Severa…
Objective(s)
Create policies for equipment installation and location;
Carry out assessments of the accuracy and consistency of determining power flow directions within WPD’s distribution network;
Provide recommendations on the number and location of devices needed for full visibility of power flowdirection;
Quantify the savings gained by using the Smart Navigator to detect and communicate auto-recloser operations (rather than using visual inspections of AR equipment);
Quantify the savings made to Customers Minutes Lost (CMLs) through the use of OHL directional FPIs;
Provide the control room with visibility of overhead line real-time post-fault ratings.
Problem(s)
Historically, it has been difficult to capture data in overhead networks, due to the construction of the system and the availability of equipment throughout the network to gather data. As Western Power Distribution (WPD) transitions from a DNO to a DSO, there is an increasing requirement for localised network monitoring to enable and enhance system operation functions. Moreover, improved monitoring could unlock latent capacity, hence leading to more efficient and economical utilisation of the assets.
The connection of Distributed Generation (DG), across all Distribution voltage levels has the potential to backfeed into faults. Currently in multi-branched radial or closed-ring networks it is very difficult to pinpoint the specific location of faults, while OHL fault locations tend to be currently identified via manual visual inspections.
Auto-recloser operations are also recorded manually via visual inspections. This is time-intensive for field staff that could be better deployed on other tasks. Moreover, due to operating temperature uncertainties and limited visibility, the control room currently only makes limited use of probabilistic post-fault OHL ratings, thus potentially underutilising the available circuits.
Method
As the utilisation and requirements of the distribution network increase so too does the need for localised network monitoring. Historically, it has been difficult to capture data for the overhead network due to the construction of the system and the availability of equipment throughout the network to gather data. This project will trial a device that is capable of self-powering operation to provide real-time voltage, current and power flow information.
This information will be used to more accurately assess network operation, such as latent generation output and directional fault detection to more quickly identify the location of faults. Five business needs have been identified, all referenced within WPD’s Distribution System Operability Framework, which will be addressed by the following trials:
Method 1: Directional Power Flow Monitoring;
Method 2: Directional Power Flow State Estimation (using directional monitors to infer power flow direction through non-directional sensors);
Method 3: Detection of Auto-Recloser Operations (to assist with maintenance efficiency and short interruption quantification);
Method 4: Directional fault detection (especially in 33kV networks with high levels of DG); and
Method 5: Conductor Temperature Monitoring (feeding into the post-fault rating of overhead lines).
By using innovative data analytic techniques, this project tackles a key network and operational issue which forms a part of an overarching industry need – the increased requirement for data to support energy market operations. This project will take industry data from the Data Transfer Service (DTS) data set and apply leading edge cognitive analytics to provide WPD improved visibility of EVs and DER to support forecasting of the proliferation of PV/EV across networks and other DER connections to support network planning including the options of active/flexible network management.
The project will help define the requirements for the delivery of an enhanced dataset proof of concept model allowing us to leverage the analytics tools and techniques to support WPD to identify unregistered LCT, understand how best to validate suspected installations and to estimate the likely uptake of technologies in different areas for planning purposes. The project will overlay and analyse data on a number of representative network topologies across WPD’s Electricity Service Areas (ESAs). It is likely that all the ESAs will be required in order to ensure a sufficient number of known locations to help train and validate the model. This is particularly true for heat pumps where there are relatively few records. The number of customers assessed for LCT identification will reflect the volumes required to generate a sufficiently large candidate set to validate the model and to identify regional differences in model effectiveness. Many of the project costs are not scale dependent.
The project will be delivered in over the course of three years, in three phases, as summarised below.
Technology Readiness Level at Start TRL 5 Technology Readiness Level at Completion TRL 8
Phase 1: Design and Build (December 2018 – March 2020)
In this phase, the functionality of the OHL Power Pointer solution will be defined for each of the five Methods
(directional power flow monitoring, directional power flow estimation, auto-recloser operation detection, directional fault passage indication (FPI) and post-fault rating of overhead lines). The software will be designed and implemented. Network locations will be identified and equipment installation locations selected. In addition, the trials of the various methods will be designed.
Phase 2: Install and Trial (August 2019 - February 2021)
In this phase, the Smart Navigator 2.0 equipment (for directional power flow monitoring, auto-recloser detection, directional fault passage indication and post-fault rating determination) will be installed and trialled.
Initially, 50 sets of devices will be installed to cover the trials of the various Methods. These devices will communicate to Nortech’s iHost system for rapid prototyping of the software and support with the solution design. As part of the main trials, an additional 50 sets of devices will be installed, communicating to WPD’s iHost system and the 50 sets installed as part of the initial trials will be transitioned across to WPD’s iHost system.
Phase 3: Analysis and Reporting (December 2018 – November 2021)
In this phase, the results from the trials will be analysed and a report on the learning resulting from each of the Methods will be produced. Results and key learning outputs will be disseminated and policies will be written to
facilitate the wider adoption of the OHL Power Pointer solution WPD’s business should WPD proceed with Business as Usual (BaU) roll-out.
The knowledge gained through this project will relate to:
Creation of functional specifications to guarantee the suitability of the device for different applications and overhead line types;
Determination of a systematic methodology for identifying where enhanced network monitoring is required;
Identification of strategic installation locations for delivery of maximum operational benefit;
Evaluation of the performance and optimisation of the Directional Flow State Estimation method;
Quantification of the savings gained by using the Smart Navigator 2.0 to detect and communicate auto recloser operations, rather than using visual inspections of AR equipment, and quantification of the savings made to CMLs through the directional fault detection method;
Assessment of the practicability of the real-time post-fault rating method, details of how the enhanced ratings could be used by WPD and other GB DNOs and identification of future enhancements.