The Advanced Distribution Management System The indispensable tool of the Smart Grid era Telvent utilities group August 2010
The Advanced Distribution Management System The indispensable tool of the Smart Grid era Introduction The Smart Grid era is the result of a shift in focus within the electricity industry a shift away from the older, familiar approach of large power stations and reliance on transmission systems to move bulk power. Our Smart Grid future is more likely to be focused on smaller distributed electricity generators, a growth in renewable resources, eliminating overloads, and reducing peak demand through demand response options. In addition to the focus on evolving management of distribution networks, the electricity consumer is being asked to change longstanding habits and manage growing appetites for energy. Regulatory organizations and utilities are trying to cope with this issue all over the world, blending advanced metering and communications technologies to bring new options. Dynamic, time of use, and other pricing alternatives are under consideration to reduce electricity network congestion and energy costs. With these changes, the need to more effectively plan, engineer, and manage the distribution network is a critical requirement. In addition, there is a rush to implement the core software to support this responsibility the advanced distribution management system (DMS). This paper will provide an overview of the advanced DMS software, including its diverse, complex portfolio of functionality, as well as its benefit to the distribution network owner and the energy consumer. What makes a DMS advanced? Distribution Management Systems (DMS) are software applications with basic capabilities. When a DMS has advanced functionality including volt/vat control, FLISR support, advanced forecasting and planning functions, and others that tightly integrates with an OMS and SCADA, it is considered to be advanced. The advanced DMS For more than 40 years, utilities have used the strength and speed of computers to model electricity networks. For the most part, that focus has been on transmission networks, and there are many mature software products on the market that provide strong functionality for bulk power transmission networks. Modeling distribution networks is a different, and in many ways, more complex problem. 1
Instead of the need to model static, meshed, and balanced transmission networks, today s advanced DMS technology must model radial, unbalanced distribution networks with rapidly-changing topologies and demand profiles. Instead of consistent and frequent telemetry from the transmission network, advanced DMS technology must be able to coordinate unsynchronized data for management of these network models. Advanced DMS must also deal with the possibility of islanding portions of the distribution network creating the potential for management of multiple and independent distribution networks. The advanced DMS must also deal with the evolving use of electricity, supporting variable, localized demand profiles created by changing consumption habits, and by new electricity-powered devices such as battery-powered vehicles and high-tech devices. Further, the advanced DMS must deal with shifting consumption patterns and customer demand for higher levels of service for their devices. Not only must service levels improve, but also the service must be high quality, including voltage levels that operate within regulatory norms. The advanced DMS is the tool that enables the power system engineer and dispatcher to effectively and efficiently engineer, plan and operate the distribution network. It analyzes unbalanced and dynamically changing distribution networks in real-time, while providing a study capability for both backward and forward review to identify options to improve network reliability while lowering electricity costs. The advanced DMS is the critical tool for management of the distribution network, and enables the acquisition of many of the benefits utilities and consumers expect from their Smart Grid investments. The foundation of the advanced DMS At the core of the advanced DMS is the ability to precisely define the network model, and to process an unbalanced load flow algorithm based on that model with telemetered data taken from the network. The network model The advanced DMS must be able to represent all aspects of the distribution network, including a variety of conductor types, transformers, switches (both manual and motorized), fuses, and other permanent and temporary devices used 2
in distribution system operations. The model must provide connectivity based on the position of switches, and be able to determine how individual demand points are connected to the energy supply. The dynamic data To enable functioning of the advanced DMS load flow algorithm, it requires data telemetered from the distribution network. That data is generally made available through supervisory control and data acquisition (SCADA) systems and their associated telemetry, through AMI networks, and from the outage management system (OMS). This manages the flow of information regarding lights-out events on the distribution network. The amount of data to be telemetered and stored is significant and changes frequently, suggesting that great care must be taken to manage the flow of data to the advanced DMS enabling it to process quickly and efficiently. The data provides a variety of information (e.g. voltage, current) and device status (e.g. open/closed) to enable the load flow algorithm to function. The advanced DMS must also be able to store copies of the data for future study and training purposes. Historical data copies can be very helpful in planning for situations that develop on the network as demand profiles and energy costs change. The unbalanced load flow algorithm The advanced DMS must have a very fast load flow algorithm that can solve unbalanced distribution networks based on data telemetered from the field. Visualization of advanced DMS results With a complex network model, significant quantities of data (both telemetered and calculated) and the wide variety of advanced DMS users (planning and design engineers, operations management, and distribution system dispatchers, etc.), providing visualization of advanced DMS results is an important consideration. An advanced DMS should be able to display network data in a geographic view (e.g. 3
maps), a schematic view, and in single-line diagrams. Further, the enduser should be able to easily manage the level of information displayed in these views. Individual utilities have developed different means to view their network information over time, and the advanced DMS must be flexible enough to support the format desired by the utility. Done correctly, the advanced DMS will be able to drive full-scale power network projections in system operations centers, both at dispatcher workstations and projected on larger screens to inform those in the control center or elsewhere. State estimation ensuring the accuracy of advanced DMS results One dictionary defines state estimation as a branch of probability and statistics concerned with deriving information about properties of random variables, stochastic processes, and systems based on observed samples. In power networks, state estimation takes observable data from the field and derives a model of what is actually happening, by processing the data to identify bad readings or to estimate missing data. The quality of data telemetered from various points on the distribution network is typically imperfect. Problems in devices or in the telecommunications networks associated with those devices suggest that prior to conducting an advanced analysis, the data must be preprocessed to eliminate bad data points, estimate non-telemetered points, and resolve any issues with time skew for unsynchronized telemetry systems. The tool that performs this quality analysis is known as state estimation, a critical feature of the advanced DMS. To trust the results of the analytical software, the inputs must be quality checked, and either adjusted or eliminated to avoid bad results. Advanced DMS analytical functionality The advanced DMS has functionality that supports several functional areas: Operations planning and analysis, loss minimization One of the primary uses for the advanced DMS is the realtime analysis that enables optimization of the distribution network. The advanced DMS continually runs real-time 4
analysis, identifying problems and suggesting approaches to better balance load, suggest switching to minimize losses, and identify other potential and real problems, as well as likely solutions. The advanced DMS enables utilities to reduce energy waste on their distribution networks through a more detailed understanding of losses and through reconfiguration and network optimization to minimize those losses. Supporting outage management activities The advanced DMS provides analytical support to ensure that outage causes are identified and resolved more quickly. Integrated with an OMS, it provides a next generation level of functionality, which that can use to improve network reliability. The advanced DMS has a strong level of functionality around fault location, identification, and service restoration (FLISR). The FLISR functionality already present at most utilities is enhanced with the advanced DMS s ability to locate faults (based on telemetry and analysis) and to provide ranked switching options to a dispatcher (e.g. prioritization based on connected load, connected customers, etc.) based on the dynamic state of the network. The advanced DMS can extend the capability of traditional self-healing network automation by allowing it to operate on the as-switched network model in any arbitrary configuration. Because the advanced DMS maintains information about the as-switched state of the network, it facilitates and automates the creation of switching orders, for planned and unplanned work that dispatchers or field operators can execute according to traditional procedures, or which can be executed automatically in the presence of field automation. This can all be accomplished while managing tagging functionality as needed, and ensuring that the state of the network is well represented at all times including the incorporation of temporary elements that may be used to support outage restoration. 5
Volt/VAR Control The volt/var control functionality contained in the advanced DMS enables utilities to ensure power quality in all parts of the distribution network. It also provides a transparent approach to demand response that utilities can exercise without any need or expectation of customer involvement. To this end, volt/var management supported by the advanced DMS enhances overall network stability and reliability. Performing analysis and control for volt/var optimization on a distribution network may require additional field telemetry and control. It may also require the identification of feeder segments where additional capital infrastructure investments may be needed to enable the creation of a more level voltage profile. The strengthening of the distribution network for maximum use of advanced DMS functionality may therefore require additional time and capital expenditures for the utility. Demand response Demand response is a key function that drives utilities to Smart Grid programs and to the implementation of advanced DMS software. The complex world of demand response suggests many options can be exercised to reduce demand in the face of increasing demand, and the potential of surging costs and network instability. The advanced DMS understands that there are multiple approaches to demand response, and the software can direct the implementation of demand response options that are created by Smart Grid programs. Some demand response actions depend on customers to react on their own. Utilities and governments routinely request for electricity consumers to change their consumption patterns when supply is short. Regulators can also create rate structures that encourage similar conduct through normal attention to energy costs. However, since these approaches do not provide sufficient reduction, additional demand response options are provided, and the advanced DMS can support the prioritized application of these options. 6
In general, the available options fit into three categories, which are listed in order of customer impact (lowest to highest): 1. Conservation voltage management (CVR) also known as Distribution System Demand Response (DSDR) This functionality utilizes volt/var management functionality to reduce demand through reduced voltage on the distribution network. The voltage reduction (usually between 3 percent and 7 percent) results in reduction in the power delivered by a similar amount, all without customer awareness. Further, voltage management can be accomplished on a feeder or feeder segment basis to resolve a local overload (perhaps as a result of electric vehicles or other infrequent demand anomalies) instead of on a systemwide basis. This surgical use of demand response and its lack of impact on customers is often the critical reason to implement an advanced DMS. 2. Direct load control Most utilities have implemented some form of direct load demand response, generally through radio-controlled devices located on water heaters, air conditioners and pool pumps. Using this form of demand response, utilities can turn off these devices for a short period of time (perhaps 15 to 20 minutes) to reduce demand on the distribution network. The direct load programs already in place rotate the turn-offs around the service territory to reduce customer impact. Since there is some amount of customer impact, while minimal, utilities must generally ask customers to opt-in to such a program, and often trade a rate advantage or discount to customers who choose the program. Direct load control will continue to increase in complexity with the evolution of home area network (HAN) technology and the continued roll-out of AMI systems. The advanced DMS is designed for integration with these end-of-network systems, supporting direct load control by identifying appropriate feeders segments and timing in a prioritized manner. 7
3. Load interruption/islanding When other demand response options fail, utilities disconnect some demand to maintain the ability to serve the rest. Again, most utilities have opt-in programs for such interruption, including interruptible rates that are supported by regulators and governments. However, depending on the nature of the overload and danger to the health of the distribution network, utilities may have to exercise interruption options with little or no advance notice even to customers who have not elected this option. Once again, the advanced DMS makes recommendations and prioritizes options for utility dispatchers to enable decision making in situations where it is unavoidable. Distributed generation The Smart Grid was initially intended to support the addition of environmentally-renewable energy resources to the distribution network, including wind, solar, biomass, and others. However, managing a distribution network with hundreds or thousands of potential energy sources requires an advanced DMS. The advanced DMS can help maintain the balance needed to reliably operate a diverse supply environment in the face of dynamic changes in demand and in the topology of the distribution network. As distributed generation becomes more prominent, distribution networks may tend to become small islands of energy that can operate while connected to the rest of the distribution network. They may also operate independently as a micro-grid in a disconnected manner. The advanced DMS can manage the network through these operating approaches, optimizing it for losses, reliability, or cost of operation, while maintaining a secure distribution network. Distribution network planning and demand forecasting Since utilities must take a forward look in planning their distribution networks, the advanced DMS must provide functionality to enable planning and budgeting for maintenance of reliability and quality of service. Advanced planning functionality must start with demand forecasts for the time frames required. The advanced DMS includes demand forecasting (short, medium, and long-term) contributing to the planning process. 8
Dispatcher training simulator In addition to the diverse real-time and off-line analytical functionality contained in the advanced DMS, it is also possible to take a snapshot of the distribution network including the network model and associated telemetry. This snapshot can then be used to train distribution system dispatchers. The advanced DMS can also support the storage of past forecasted models. To be effective, the dispatcher training simulator must also have the ability to move through time (typical demand and supply changes), with events that can be programmed by an instructor. In this manner, the simulator enables training cases based on experience or in advance of anticipated events. Summary The advanced DMS is an indispensable tool of the Smart Grid era. Starting with the foundation of a fast, unbalanced load flow engine and the ability to validate data via state estimation, the advanced DMS provides complete functionality to help utilities optimize their distribution networks. The software also provides dispatchers, engineers, and others who operate and manage the network with easy network visualization. The advanced DMS includes significant functionality to manage outages and perform FLISR operations. It also has the tools to support volt/var optimization, which enables voltage-based demand response functionality (DSDR), the form of demand response that has the least impact on customers. The software supports distributed generation, enabling the utility to grow and accommodate the renewable generation expected of the Smart Grid era, while optimizing the network for reliable service. Lastly, the advanced DMS supports short, medium and longer term planning, and also enables the capture of cases to support the training of dispatchers who operate the distribution network. Advanced DMS the indispensable tool of the Smart Grid era. Telvent (NASDAQ: TLVT) is a global IT solutions and business information services provider that improves the efficiency, safety and security of the world s premier organizations. The company serves markets critical to the sustainability of the planet, including the energy, transportation, agriculture, and environmental sectors. (www.telvent.com) The concept of the virtual power plant Virtual power plants (VPP) come from a utility s ability to dispatch (set appropriate output levels) an amount of power that exists in the form of distributed generation and demand response, instead of as a physical power plant. Using a variety of demand response approaches (e.g. direct load control, volt/avr management, etc.) and distributed energy resources (e.g. energy storage, renewable generation, etc.), a utility can create a profile of a virtual power plant, and use it in its energy dispatch algorithms when balancing demand and supply. This also requires critical analytics and controls, such as those provided by the advanced DMS using SCADA, DMS, and other tools as needed to create the VPP and the forward operational plan a utility would expect in a power plant environment. The advanced DMS is the tool that enables the VPP concept. 9