Integrating ADMS and GIS: Powerful situational awareness benefits beyond the traditional business case

While each specific system addresses a powerful need, integration extends the reach and the value each product delivers to the utility. While integration is critical to achieve the overarching goal of grid management, the scope of the specific integrations is often defined around one specific goal or a simple list of requirements. If we use GIS and ADMS as an example, often the goal is to have a single, consistent network model which is used across the organization. While this is an important goal, it doesn’t provide the opportunity to leverage the integration beyond this initial scope. Let’s use GIS and ADMS as a case to examine how these platforms should use recent advancements like Esri’s Utility Network as the foundation for a deeper integration and how a federated architecture provides for new benefits.

Traditional GIS-ADMS Integration

GIS and ADMS are both essential, well-established electric solutions. A utility’s business is spatial in nature and the GIS provides the foundational layer of technology for asset management, regulatory compliance and operational intelligence. It is also used to deliver on numerous business-specific workflows; such as planning and updating the normal state of the network, field inspection with data collection, and analytical processes like examining usage patterns, predicting equipment outages or assessing/mitigating risk. GIS also uses the central concept of location as an integrating mechanism for the display and analytics of data from across the company.

Where GIS focuses on the normal state of the network, ADMS delivers a suite for distribution management and optimization that includes functions that automate outage restoration and optimize the performance of the distribution grid. ADMS provides critical capabilities including fault location, isolation and restoration; volt/VAr optimization; conservation voltage reduction; peak demand management; and support for integrating renewables, microgrids and electric vehicles.

Today, the most common relationship between GIS and ADMS is that GIS serves as the source for much of the network model.  Feeders are modeled in the GIS, with both conductors and devices. Structures such as poles, pads and vaults are also modeled in the GIS, giving inherent location to both. The ADMS network model represents these feeders in two ways: geographically, and schematically.  In the geographic view, devices are placed relative to landbase – whether street centerlines, curbs or lot lines. This allows for operators to determine where to route crews to conduct work in the event of trouble, for example. 

However, the ADMS also has a schematic (or geoschematic) representation, where some anchoring device, like a substation, may be placed accurately in the real world, but the feeders themselves are laid out schematically (often orthogonally) for ease of view.  While the DMS model will have other sources, such as SCADA device settings, SCADA one lines, and load curves, the GIS feeders form the backbone of the network mode.  As the GIS continues to evolve, more data traditionally stored outside the GIS also can now be sourced by the GIS for the network model – for example, the station internals are being brought into the GIS by more and more utilities. 

The GIS also serves as the integration point for making operations aware of future state changes – for example, a new device that will be constructed and commissioned next month.  This has been the most common way that the DMS interacts with the GIS – as the source for the network model.  For some utilities, the business case for ADMS and the business case for the GIS integration with ADMS (i.e. the model build) are inseparable, and in fact, the accuracy of data in the GIS is so essential to the success of an ADMS implementation, that a number of utilities are including a GIS platform refresh or a field data collection, as part of the ADMS business case.

A Modern Integration

The traditional business case has been built on the integration of a highly-detailed ADMS model with a traditional radial network configuration supported by GIS’s legacy connectivity model. While this could be made effective, the legacy connectivity model doesn’t provide real world modeling constructs needed to easily collect and maintain the details required by advanced ADMS functionality. Recognizing the limitations this legacy model presented, Esri (the world’s largest GIS vendor) has spent the last 5+ years working with the industry to produce a new semantic information model, called the Utility Network, that could deliver on the market’s needs. This new model has the depth required to match ADMS asset detail and uses a combination of new elements like structural, connectivity and containment associations, terminal configurations, assemblies, subnetwork controller, secondary grid networks, or internal substation grids to model the network in alignment with the real world. Using the UN, a utility can perform a like-to-like integration that will drive advanced ADMS. In addition, it established a new playing field for a wide range of additional benefits.

While the advanced capabilities provided by ADMS are being deployed within control centers and used to better manage the dispatch of field crews, there is also an opportunity to leverage the capabilities of the new Utility Network model and its use across the utility to better inform both stakeholders and improve situational awareness outside of operations, as well as to improve customer engagement and even create opportunities for proactive communications of risks to the grid and first responders. For example, utilities now routinely create outage maps with information provided by the OMS.  The OMS will calculate a predicted device outage, will determine which customers are impacted by that predicted device outage, and then will produce a series of maps that communicate to customers whether or not they are part of an outage, as well as an outage cause and estimated time of restoration.  Recent studies have shown that customers are more likely to feel engaged and satisfied if they are communicated with throughout their outage than they would have been if no outage had occurred.

There is an opportunity to provide similar customer engagement through communicating to customers the status of power quality, or by creating power quality maps.  Such power quality maps could also be leveraged internally to inform field crews as to where problem areas might be emerging. Information customer service representatives can see where power quality problems may be occurring so when a customer calls in the representative is already armed with the information and can proactively engage with the customer – “I see you are having some power quality issues that we are working to resolve, is this what you are calling about, or can I help you with something else?”  Similarly, power generation maps could provide information to customers that are interested to show the mix of power from traditional or renewable resources, as well as providing historical information back to inform power purchasing contracts.  Finally, as the ADMS is better attuned to and focused on proactively maintaining system stability than the OMS, which is reactive to interruptions, it also can be used to connect with first responders and community liaisons to let them know before a problem occurs that an area of the grid is at risk, enabling them to be ready to respond.

Forward looking organizations also are investigating the role ADMS plays in operations and would like to elevate ADMS into the layer of true enterprise applications. While this has significant benefits, it would require ADMS to be integrated into the enterprise fabric with connections to Work Management, Document Management, Asset Management, Purchasing etc. This type of integration is expensive and can significantly impact stability and performance. Using the UN as the foundation for integration provides a new opportunity. The GIS is often already integrated into the enterprise suite of products. Instead of integrating ADMS, this modern integration leveraging the enterprise platform capabilities of the Utility Network enables the GIS to serve as the integration point while enabling ADMS to focus on its core capabilities.

Traditionally, electric utilities will operate equipment to failure. While this is a savvy way to optimize replacement costs, an operator must closely watch operational metrics and ensure they have sufficient replacement equipment in their yards. Artificial Intelligence (AI) provides a highly effective environment for modeling and predicting failure patterns. While the application of AI in electric utilities is evolving, AI powered by ADMS is not easily realized. That said, AI is an internal part of GIS. UN based integration provides for ADMS content to be used in AI algorithms, thereby allows the benefits to be realized for limited cost and risk. 

While ADMS GIS integration is not a new idea for the electric utility community, the release of the new Utility Network information model has established an implementation pattern where additional benefits can be realized. Planning this type of project requires a fresh look at perceived benefits and would greatly benefit from the involvement of teams outside of operations such as GIS and IT architecture. This work represents an opportunity to reposition the value a utility receives from a GIS ADMS integration, improve operational efficiency, and empower users with new forms of operational intelligence for use in decision making.