Achieving High Performance With Advanced Approaches to Distribution Management Accenture

Achieving high performance with advanced approaches to distribution management

For example, operators would sort out printed trouble tickets from the call center and group them based on areas. They would then hand the packet to a field supervisor who would go to the field, find the problem and fix it. Planned switching was often done by filling out a paper when a request came in to isolate a certain part of the network. Finally, the switching arranger would use a paper map to identify which switches to operate and in what order to perform the switching steps.

Due to technology advancements and increasing complexity of distribution networks, as well as greater customer demands for better reliability and information, many utilities have implemented outage management systems (OMS). These systems maintain

Until recently, these processes have served utilities well because the traditional characteristics of the distribution systems held true. Power flowed in one direction, energy supplies from large generators followed whatever the demand was, infrastructure had a large capacity margin and system operators knew their systems well.

Transformational changes in the electric utility industry and the advent of smart grid technologies have changed that.

Today’s utilities are experiencing the largest-ever changes in the industry. In the distribution utility of the future, power will flow in two directions, energy supplies will come from new technologies and various-sized suppliers connected anywhere on the network, customers will need to adjust their

the as-operated model of the network and can automatically group trouble tickets based on the model. This results in more accurate prediction of outage device and extent so outages can be restored quicker and better information can be provided to customers.

Some outage management systems have also developed switching applications to automate the process of planned switching. This allows switching requests to be completed electronically. The arranger can electronically prepare and validate switch orders and use the same operating model as that of an outage management system. Records of switching steps, their instruction and execution, and the required authorizations and clearances are kept in a database for future access and reporting.

2 | Achieving high performance with advanced approaches to distribution management

IntroductionIn the past, managing the distribution network was a hands-on activity consisting mainly of restoring unplanned outages after they occur and performing planned switching for construction and maintenance. Many utilities performed these functions using manual, paper-based methods.

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demand to respond to supply constraints, and ageing infrastructure will be pushed to higher loading levels and lower margins. The workforce is also ageing, and employees who entered the work force in the 1960s and 1970s will be taking their tremendous knowledge of the system with them as they begin to retire in droves. Fortunately, new technologies and innovative approaches are meeting the challenges of our time and creating an exciting transformation that will likely to continue for years to come.

For distribution management, this means the enhancement of capabilities far beyond just handling planned and unplanned outages. It means operating the system more actively and with the use of smart devices, sensors and advanced analysis applications. This evolution includes the expansion of

automation to all distribution substations and further onto the feeders with automated reclosers, switches, regulators, capacitors, and other smart devices and sensors. This paper describes the key concepts of the advanced distribution management system (DMS) and provides a roadmap for its implementation and future development.

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A DMS provides functionality to:

• Maintain the as-operated model of the network: Reflecting device operations, temporary network changes (jumper lines, line cuts and phase changes), and safety and information tags on the network model to create an accurate operating model for use in applications and visualization.

• Monitor and control the distribution network: Monitoring the electrical state of the network, processing limit violations and other alarms, preparing for and responding to contingencies, and issuing controls as needed to ensure reliable and secure operation of the distribution grid.

• Manage outage restoration process during normal operations and storms: Receiving notification of outages, reviewing and responding to outages, managing the restoration

process, estimating restoration times, and ensuring completion of required information.

• Dispatch the right crew to the right job: Monitoring the status and location of crews in the field, dispatching assignments to appropriate crews, communicating the required information to the crews and managing the crew activity.

• Locate and isolate faults and restore service: Receiving and processing fault information from fault devices and location applications to locate the fault and develop switching schemes to isolate it and restore service to un-faulted areas.

• Manage planned switching: Receiving and processing switching requests, creating and validating switching schemes, identifying and notifying affected customers, issuing and managing authorizations and clearances, and executing switch orders.

DMS functionality

• Communicate timely and accurate information to stakeholders: Capturing and calculating accurate information in a timely manner to communicate to internal and external stakeholders, such as customers, management, service representatives and media.

• Exchange data seamlessly with the enterprise: Sending and receiving data and transactions to other systems dynamically and seamlessly to support the integrated and smooth operation of enterprise systems and applications.

These and other evolving functionality provided by the DMS improve operational efficiency in the distribution management workflow while also supporting better energy efficiency and system reliability of the distribution system.

A distribution management system, or DMS, is the primary system used by distribution control center operators to operate the distribution network reliably, efficiently and securely.


The data required include:

• Infrastructuredata(equipmentinstance, type, location, rating).

•Metadata(elementnaming,typedata, limit data, analysis param-eters).

•Networktopology(connectivity,phasing, normal device states).

• Customerdata(name,address,phone, meter, type).

• Customertonetworklink(viaservicedrop or transformer).

• Engineeringdata(impedances,con-nections, settings, sensing node).

The network data for the model are typically maintained in a GIS, which grew from a mapping background (automated mapping/facilities management or AM/FM) and was initially engaged to produce paper maps used by various departments

and must be considered in the design of the DMS data interface. Fortunately, the engineering data can be mapped to data types, such as line types and device types, which do not change frequently.

Advanced DMS applications may also require additional data. For example, a short-circuit-based fault location application will require the short-circuit capacity at every source, i.e., connection point of the distribution model to the high-voltage transmission or sub-transmission.

There are also other data considerations, depending on the designed level of DMS functionality in a project. These considerations include modeling of distribution substations, modeling of secondary networks, approach to building and maintaining schematic representations, and the processing ofplannedconstructiondata.Each

within a utility. As the technology progressed, GIS captured and processed geospatial information about the network, such as connectivity. An interface from GIS to the DMS is used to build and update the as-built network model (normal connectivity) in the DMS. GIS is the master of the as-built network model, while the DMS is the master of the as-operated network model (current connectivity). The periodic process to update the DMS data from GIS is often called the incremental update process and is run frequently, as often as daily or weekly.

In addition to basic network data and customer data, the DMS network model also requires engineering data, such as impedances of lines and transformers, as well as connections and settings of transformers, regulators, line drop compensators and capacitors. These data sets may exist in planning, engineering, asset or other databases

DMS data modelAt the heart of the DMS is the detailed and accurate distribution network model that operators can use to make decisions and operate the system. However, the DMS is highly dependent on data from a geographic information system (GIS), customer information system (CIS) and other data sources to build and maintain this model of the network.

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of these considerations requires a detailed analysis of business processes to implement a holistic process across multiple systems.

As many utility executives and managers would attest, data quality is by far the most critical success factor in a DMS implementation project. Data issues can occur in data attributes, network connectivity, phasing, equipment and line types, and other areas. For example, some utilities capture whether distribution lines are three-phase or single-phase but do not capture what phase those single-phase lines are. Data inaccuracies or incomplete data have a significant impact on smart grid applications.

Typically, the extent of these data issues is not fully known prior to the DMS implementation, since older systems and applications only required a basic subset of data to function. Many utilities perform a data correction and validation project as part of or prior to the DMS implementation project. It is important to perform a detailed data analysis considering planned capabilities to evaluate the extent of the data improvement that may be required to achieve the targeted benefits of DMS implementation.


A single solution for supervisory control and data acquisition (SCADA) systems/DMS/OMS presents the most effective architecture, as it eliminates the need to maintain and synchronize multiple operating models and provides a single user interface for the distribution operator to perform all the work. The challenge with this solution is to ensure that optimal functionality and features are provided for in the solution. Also, a single solution represents a large change in the business processes of a utility and requires a strong governance and change-management process to ensure a successful transition of the business to the new system.

Another configuration that has been considered is one solution for SCADA/DMS along with an existing or upgraded OMS solution. While this reduces the amount of change that a utility will have to implement in one time, there are other challenges.

The key factors in determining the performance are:

• Size of the distribution network

• Numberofcustomersserved

• Numberandlocationofusers

• NumberofSCADApointsandscancycle requirements

• Communication bandwidth to remote offices

• Peak number of calls, advanced meter infrastructure (AMI) notifications and outages

• Number,typeandperformancerequirements of system interfaces

These factors must be evaluated both in normal conditions and in high activity conditions, such as storms and large contingencies.

One main issue is to ensure that the operating models for OMS and DMS are updated from GIS at the same time so that the current state of the system is consistent between the two models. The DMS-OMS interface required will need to be well-designed to ensure this consistency. User interface is also another major consideration in the split model, as operators will have to interact with two systems to perform their work.

A major architectural consideration for distribution management systems is performance. A DMS is a real-time system similar to an energy manage-mentsystem(EMS)andhassimilarexpectations in many areas such as display call-up time. However, at the same time, it has to handle orders of larger magnitude, such as network elements, events and users, as well as business transactions and workflows.

DMS architectureThe core components of distribution management are SCADA, operating model, user interface, outage management and advanced DMS applications. While the ideal architecture consists of one solution that enables all components, various utilities and vendors are architecting distribution management solutions differently based on their current investments and business drivers.

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In addition, a DMS is a mission-critical system requiring high availability and disaster recovery. These requirements must consider the different components of the system, such as application servers, database servers, messaging middleware and networking, to ensure no single point of failure exists in the architecture. A smooth transition to a disaster-recovery back-up site and back is also an integral part of a highly available DMS.

Security must be an integral part of the DMS architecture. Although distribution systems are not currently part of some national critical infrastructure protection (CIP) requirements, levels of automation and control at the distribution level are increasing. Therefore, utilities are placing equal importance on distribution system security. DMS architecture

must include a scalable and adaptable framework for governance and control of all sensitive data to meet the data protection objectives (e.g., identity and access management, intrusion detection and prevention, security information and event monitoring, plus network and meter security).

Finally, the DMS architecture must support multiple environments in addition to the production environment. These include a quality assurance system (QAS), training system, testing system, and other environments as required by the needs of the business. Managing multiple environments require a structured approach to managing software releases, as well as database and configuration management.

A well-designed DMS architecture will take into account the mission-critical and real-time nature of the DMS and its integration to other enterprise systems, as it brings together information technology (IT) and operational technology (OT) aspects of the smart grid distribution system operation.


It uses and exchanges data and trans-actions with numerous other enterprise systems, including:

• Geographic information system (GIS) to build and update the network model and landbase maps.

• Customer information system (CIS) to update the customer data as well as trouble tickets.

• Interactive voice response (IVR) for automated trouble-call entry and restoration verification, as well as notification calls for planned outages.

• Advanced metering infrastructure (AMI)/Meter data management (MDM) to process outage and restoration notifications from meters, as well as load profile and voltage information.

Today, many of these interfaces have been implemented as custom or point-to-point interfaces. With the increase in the level and complexity of the required system integration for advanced distribution management, a structured and standards-based approach is crucial to the viability and maintainability of the overall system. The IT standard for this approach is the enterprise applicationintegration(EAI),whichis an open, standards-based platform designed to ease integration of various systems and applications into a cohesive enterprise architecture using service-oriented architecture (SOA)andenterpriseservicebus(ESB).EAIisanintegrationframeworkforenabling cross-application business processes while minimizing the need for custom interfaces.

• Mobile data system (MDS) to automatically communicate assignments to the field crews and receive assignment status and completion updates.

• SCADA/EMS to receive device sta-tus, measurements and calculations at network boundary between transmission and distribution.

• Work management system (WMS) to create and update work orders for outages and planned switching.

There are many other existing and new systems, such as automatic vehicle location (AVL) and condition-based maintenance(CBM)amongthem.

DMS system integrationDistribution management touches many business processes, such as customer service, power quality, service connects and disconnects, construction and maintenance.

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A DMS utilizes these data sets via enterprise application integration with AMI and MDM systems.

For outage management, the ability to ping meter status and confirm single customer outages represents a large savings in avoiding unnecessary truck rolls related to outages on the customer side of the meter. In addition, timely and accurate outage notification helps operators respond to outages quicker and more appropriately. Also, restoration notification and the ability to ping meters (to confirm restoration) can help identify nested outages after restoration of a larger outage, especially during storms. This capability enables better customer reliability and reduces outage costs, since crews can respond to nested outages while in the field and, perhaps, nearby.

to validate network and engineering data accuracy, and volt/var control applications can be validated to avoid voltage problems for customers. Ultimately, smart meter voltage readings (that can be communicated in a timely manner) can be used directly in distribution state estimation, as additional measurements leading to even more accurate estimation of the distribution network state.

Correlating smart meter data and other network measurements can also be used for a variety of other system operation benefits. Some utilities are using this data to predict cable and equipment failure or flag phasing issues. As technology advances, there will be new areas for leveraging smart meter data in system operations.

DMS advanced applications also can use data from smart meters to improve meter performance. For example, smart meter load profiles can be used to estimate load distribution on a distribution feeder more accurately than use of other methods, such as size of the connected transformer, thus enabling the DMS to calculate power flows, voltages and losses more accurately. In fact, incorrectly sized transformers can be identified using smart meter load profile data to prevent transformer failures due to overload.

In addition to metering demand, smart meters also can record voltage levels at the meter and report them either as raw data or through alarms activated when low-voltage or high-voltage limits are exceeded. As a result, power flow-calculated voltages can be checked

DMS integration with AMI/MDMIn the past, smart grid was often equated with smart me-ters. This was understandable, since most of the early smart grid projects consisted of implementation of smart meters. While smart meters are a fundamental part of smart grid infrastructure, the data they capture and communicate has been used mostly for improved billing purposes. However, there are many areas where smart meter data can enhance system operation. The basic operational data available from smart meters include outage and restoration status, load profile data and consumer voltage.


The latest trend in feeder automation in recent years has been the installation of auto-restoration schemes using multiple devices that can communicate with each other (peer-to-peer communication). These teams of devices can work together to isolate a fault and restore service to un-faulted areas based on local or distributed intelligence. Utilities have installed these auto-restoration schemes on their worst performing feeders to gain the most benefit in terms of reliability improvements. However, as these schemes become more intelligent, they require more data and maintenance. For example, they need to know the logical model of the devices participating in the team. In addition, if the configuration of the feeders changes, devices may need to be reprogrammed. Also, in certain cases of severe imbalance or high loading, the restoration scheme may actually cause additional outages.

There is, however, a trade-off between the holistic view of centralized automation and localized response of distributed automation—response time. Local automation can typically respond in cycles, whereas control-center-based automation can take many seconds. Many factors such as communication speed and calculation performance affect the response time of centralized automation applications. In summary, distributed automation provides fast, localized response and can be implemented where most needed, while centralized automation can consider systemwide impacts and avoid cascading issues. Utilities will need to have elements of both. A well-designed approach to the integration and coordination of distributed automation with a DMS can enable a balance of both automation approaches and provide the benefits of both systems.

This might occur, for example, if a section is switched onto a feeder that is already near capacity.

The advances in central modeling and analysis of the network and investments that utilities are making in tele-communication infrastructure have enabled new forms of “centralized” automation. For instance, centralized fault location, isolation and restoration applications can run in a DMS with the benefit of systemwide power flow analysis and can avoid loading problems by performing multistep restoration. In addition, the DMS volt/var optimization application can optimize the system as a whole and avoid conflicting operations of capacitors and regulators at various locations on the distribution system. A third example is the automated switching reconfiguration application that can reconfigure the distribution system in cases of contingencies to provide better load balancing.

DMS integration with feeder automationMost utilities have implemented some form of feeder (distributed) automation. The most basic form of feeder automation has been the installation of reclosers and sectionalizers to help with restoration of momentary outages and isolate sustained outages. These devices have local controls that are set by distribution engineers and changed as needed when normal configuration or loading of the feeder significantly changes. Similarly, capacitors with local controllers can automatically operate based on their var, voltage or time-control settings to reduce losses and improve voltage profile.

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For example, planning applications sometimes run on a simplified model of the network, whereas operational applications need to run a full-detail model. Also, the loading used for planning applications was typically that of peak load and normal configuration, but operational applications must run on current loading conditions and the corresponding as-operated connectivity. These differences require operational applications to have much greater scalability and performance over their planning counterparts.

The basic applications that are being implemented today are:

• Distribution power flow: Per-phase network analysis to calculate currents and voltages throughout the network and identify any limit violations.

• Distribution state estimation: Utilization of large numbers of measurements and advanced analysis

• Volt/var optimization: Automated and integrated control of capacitors and regulators to reduce losses (var control) and peak demand (conservation voltage reduction).

As previously mentioned, the quality of the infrastructure and engineering data comprising the network model is critical in the proper function of DMS advanced applications. To operate the grid smartly, we must first accurately model the grid.

In addition to these applications, there are many new areas of R&D being developed that present new and exciting promises for further improvements in the operation of the distribution network.

to develop the best estimate of the state of the distribution network.

• Fault location: Prediction of possible fault locations using short-circuit analysis and fault measurements, such as fault magnitude, type and phase.

• Simulation: What-if scenario simulation for switching analysis and verification.

• Restoration switching: Identification and analysis of switching scenarios for fault isolation and service restoration.

• Switching reconfiguration: Identification and analysis of switching scenarios for overload relief and load balancing.

• Fault location, isolation, and service restoration (FLISR): Automatic detection and locating of faults followed by automatic switching of automated devices for isolation of the fault and restoration of service to un-faulted areas.

DMS advanced applicationsAdvanced network analysis and optimization applications are the engines behind many DMS benefits, including improved system efficiency and reliability. Such applications continuously analyze the state of the network to determine ways to improve its operation. Previously, distribution applications such as load flow and short circuit analysis applications were typically the domain of distribution planning engineers. To adapt these applications to the operations domain required some key operational considerations.


Some new advanced applications and capabilities that will be required include:

• Integrationofdistributedgeneration(DG) and other distributed energy resources(DER),suchasrenewablegeneration and battery storage.

• Coordinateddemandresponse (DR) to address localized capacity constraints during contingencies.

• Integrationwithassetmanagementsystems (AMS) and condition-based maintenance(CBM)programstoimprove asset utilization and system reliability.

•Distributionshort-termload forecasting (STLF) to anticipate and prepare for loading contingencies impacting system switching.

•Dynamicratingtoadjustequipmentlimits, based on ambient conditions and improve capacity utilization.

These and other areas of R&D will continue to grow for decades to come. A main challenge for utilities is to build their enterprise architecture with the long term in mind—to adapt their technologies and business processes and utilize future advances.

DMS research and developmentAs smart grid evolves, utility operations will need innovative applications to support new operating models. For example, as utility customers install renewable generation (such as solar and wind on their homes), the premise of one-way power flow in the distribution network changes. Control centers must be able to model and manage customer generation, as well as other distributed generation connected to the distribution network to safely and securely operate thesystem.Newtypesofgenerationandenergystoragealongside demand response programs can be used to respond to contingencies such as peak loading or substation loss.

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A main challenge for utilities is to build their enterprise architecture with the long term in mind—to adapt their technologies and business processes and utilize future advances.


Implementing an advanced DMS represents significant potential benefits for a utility, including:

• Improvedreliabilityandpowerquality.

• Reducedenergylossesandpeakdemand.

• Increasedassetutilizationandhealth.

• Reducedmaintenanceandrepaircosts.

• Fasteroutagedetectionand restoration.

Eachofthesebenefitsandotherscanbe incorporated into a business case with specific and measurable savings. However, the mix and priority of these benefits changes from one utility to another. Some utilities are tackling reliability improvement challenges with FLISR applications while others plan to defer additional generation capacity requirements using the volt/var optimization application. The business case for each utility will also have to consider the infrastructure improvements that may be necessary to achieve the targeted benefit of a specificapplication.Nomatterthebusiness case specifics, it is certain that implementation of a modern DMS is fundamental in any utility’s plan to build a smarter grid and realize benefits.

DMS business benefitsMany utilities today are making major investments in the implementation of advanced DMS as the foundation for the new way they will operate their distribution system going forward. This shows that the industry has now concluded on the necessity and the numerous business benefits of implementing DMS.

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However, the roadmap must include:

• Enterprise architecture: Advanced distribution management requires implementation and coordination of various devices, communication technologies, systems and applications from various vendors. A well-thought out and standards-based enterprise architecture is a key part of the roadmap. This architecture will ensure consistency and seamless integration between various components and projects within the overall program.

• Data quality: Starting with good GIS data is essential to the success of advanced distribution management. This includes connectivity, phasing, wire sizes and lengths, and other attributes to support analytics and advanced applications. Current data quality must be reviewed and new data collection and validation projects instituted as needed at the beginning of the program.

A long-term and comprehensive approach to distribution management—including enterprise architecture, data management, change management and security—protects utilities against silo solution implementation, costly integration and maintenance issues and obsolete investments. While there are many challenges, the core technology and leading practices for a successful DMS implementation already exist, and utilities can use them to build the smart grid foundation needed to achieve high performance today and in the future.

• Data management: The data required to support advanced distribution management comes from many sources and have different characteristics/applicability. An enterprisewide smart grid data management approach is fundamental to ensure data consistency, a “single version of the truth” and continued high data quality.

• Program management: Distribution management projects are complex and involve risks in technology, scope and implementation. A rigorous program management approach is essential to achieving targeted business objectives.

• Change management: Implementation of such a system impacts customers as well as many organizational groups and represents a large change in the organization. Change management must be an integral part of distribution automation projects.

DMS implementation considerationsAlthough the industry vision for the distribution management of the future is converging, there is no single solution as the next step for all utilities. The distribution management roadmap must be developed for each utility based on its current conditions and its business realities, goals and drivers.


Contact usTo find how Accenture can help you achieve high performance with distribution management and accelerate the attainment of your smart grid objectives, please contact:

North AmericaHormoz [email protected]

Asia [email protected]

Europe, Middle East, Africa and Latin AmericaMaikel van [email protected]

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About AccentureAccenture is a global management consulting, technology services and outsourcing company, with more than 215,000 people serving clients in more than 120 countries. Combining unparalleled experience, comprehensive capabilities across all industries and business functions, and extensive research on the world’s most successful companies, Accenture collaborates with clients to help them become high-performance businesses and governments. The company generated net revenues of US$21.6 billion for the fiscal year ended Aug. 31, 2010. Its home page is www.accenture.com.

About the Accenture Utilities groupThe Accenture Utilities group has more than 30 years of experience working with electric, gas and water utilities worldwide. We work with 93 percent of the utilities on the 2010 Global Fortune 500 list, providing the deep industry knowledge, people and assets utilities need to develop the strategies and adopt solutions to improve performance in the dynamic energy market.

With 100 smart grid projects in more than 20 countries, one of Accenture’s key focus areas is in helping our utilities clients with the transformation to a smarter grid. From generation to in-home energy management, from strategic blueprints to operational data analytics, and from the boardroom to the operations center, Accenture offers the skills and experience that can help utilities frame their vision of a smarter grid and then achieve its many benefits.

Achieving High Performance With Advanced Approaches to Distribution Management Accenture

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