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Alternative Energy: Be smart to survive

Bill Meehan
Bill Meehan
Director of Utility Solutions, ESRI
[email protected]

What would happen if everyone stopped using petroleum to power their automobiles and switched to electric vehicles? Demand for raw electric energy would soar. The most likely alternative to petrol is some form of electric power that would surely put significant strain on electric generation, transmission and distribution systems. While that's not likely to happen overnight, it may happen quicker than we think, given the world's depleting oil supply and climate change.

As carbon cap-and-trade systems are implemented, the percentage of distributed green generation sources will also grow considerably. Already wind and solar energy systems are proliferating. These intermittent sources of power challenge the grid. Smaller, more geographically dispersed generators will place additional burdens on the electric subtransmission and distribution systems. Today, impending changes aside, electric utilities face fundamental business challenges. The existing electric infrastructure is old. A significant portion of utility workers will soon retire. Access to capital is difficult. Customers are intolerant of power interruptions and demand modern interaction with their utility. These factors, additional facility security, and the need to keep costs under control will force utilities to operate differently and more intelligently.


What exactly is a smart grid?
Smart grid is a concept. It is about an electric delivery system that responds to the needs of, and directly communicates with, consumers. Smart grid is about four things: managing loads effectively; providing significantly more automation during post-outage restoration; enabling interaction between energy providers and consumers; and understanding the health of the electric system before something bad happens.

What are the parts of the Smart Grid?
The key to smart grid is the installation of smart meters to link consumer behaviour with electric energy consumption. Smart grid will require energy storage systems to level usage peaks and enable utilities to access the most efficient and environmentally sound generation options. Smart grid will require a distribution management system (DMS) for analysis and control. A DMS will enable utilities to make decisions based on information from the sensor network and smart meters about loading, predictive equipment failures, outages, and restoration. A sophisticated data management system will store historic and current realtime data about the system from meters and sensors.

Smart grid will communicate the state of the system from the sensor network to both the utility and the customers. The electric distribution system will grow from a single network to an integrated dual network system. One network will represent the power system and the other an advanced communication network. Utilities need a means of collecting data from the sensors and smart meters to make decision about self-healing the grid, load shifting and billing. Self-healing means that the electric distribution system will configure itself to limit the extent of customer outages without human intervention.

Smart grid will need real-time analytic engines able to analyse the network, determine the current state and condition of the system, predict what may happen, and develop a plan. These engines will need data from the utility and from outside parties such as weather services. The combination of smart meters, data management, communication network, and applications specific to metering is advanced metering infrastructure (AMI).

A critical facet of smart grid is the underlying electric and communications network. An enterprise geographic information system (GIS) provides the tools, applications, workflows, and integration to support smart grid.


An enterprise GIS exhibits four strong patterns of behaviour: data management of assets such as sensors, poles, conduit, smart meters, trucks, and people; situational awareness for visualising the business spatially in cases such as a small house with high electric consumption; data collection from the field to integrate with corporate data bases; analysis and planning to determine the optimal placement of fault indicators or locate places in the system most susceptible to lighting strokes.


GIS is widely recognised for its strong role in managing traditional electric transmission and distribution, and telecommunications networks. GIS provides the most comprehensive inventory of the electrical distribution network components and their spatial locations. With smart grid's sophisticated communication network superimposed on the electric network, data management with GIS becomes utterly critical.


Utilities use GIS to visualise the electric and communications systems and the relationships that exist between them. It goes well beyond the traditional "stare and compare" method commonly used by utilities to a notion of seeing relationships. GIS provides a means to monitor and express the health of the system in an obvious way with commands such as, "show me all the sensors that have failed to report results in the last hour." GIS can show the realtime view of the grid and note where things are changing. In effect, GIS (as compared with a SCADA system) shows the complete state of the grid, represented by a realistic model in a way that people understand.


GIS helps manage data about the condition of utility assets. After parts of the system go into service, utilities must maintain the system through the collection and maintenance of asset condition data. Some condition data can come from automated systems and others from inspection systems. Utilities are rapidly adopting GIS-based mobile devices for inspection and maintenance. Enterprise GIS, with its desktop, server, and mobile components, allows utilities to gather condition data.


The power of GIS helps utilities understand the relationship of its assets to each other and to the surrounding environment. Since the smart grid is composed of two networks-electric and communications-utilities must understand the physical and spatial relationships among all network components. These relationships will form the basis for some of the advanced decision making the smart grid makes. Smart grid must have a solid understanding of the connectivity of both networks. GIS provides the tools and workflows for network modeling and advanced tracing.

GIS is used to determine optimal locations for smart grid components. During the rollout of smart grid, utilities will need significant analysis to determine the right location for sensors, communication marshalling cabinets, and a host of other devices such as fiber optics in conduit and on poles. GIS provides the proper means to perform these design services, since the optimal locations depend so heavily on the existing infrastructure.

GIS can provide a spatial context to the analytics and metrics of smart grid. With GIS, utilities can track the metrics over time and provide a convenient means of visualising trends. Since smart grid is supposed to be smart, it must be able to provide advanced grid performance analytics, track trends in equipment performance and customer behaviour and record key performance metrics.


The data quality in a utility's GIS must be outstanding. Utilities are now able to build a GIS on an accurate land base. Since GIS has been used by utilities for more than 20 years, it predates GPS. Utilities that continue to base facility location on antiquated grid systems will not be able to successfully use GIS until they make the land base and the facility information spatially correct.

For utilities that have not yet built a comprehensive GIS for infrastructure, the goal should be an accurate, GPScompliant land base. Lack of a digital model of the electrical system-whether urban, overhead, underground, networked, radial, or some combinationwill limit the overall effectiveness of the smart grid. Some utilities have built a GIS piecemeal, with some parts of the service territory converted to digital form and others still in CAD or even paper form. Many have only converted primary data and not secondary networks. Others have converted rural overhead areas, but have not converted urban networked areas. The piecemeal approach is not effective if GIS is to be the heart of the smart grid. Installing smart meters in areas where the utility has not modeled the electrical network will inhibit much of the usefulness of the equipment.

In this case, the use of the smart meter will probably be limited to billing. The lack of good customer address information will inhibit the utilities' use of GIS for smart grid. Even in countries where virtually every premise has a physical address, utilities struggle to keep data current.


In concert with smart grid technologies such as advanced sensors, smart meters, energy storage devices, and renewable energy systems, GIS will contribute to the transformation of the grid from a largely passive and blind system to an interactive, intelligent, and energy efficient system. For the smart grid initiatives to be successful, utilities must make sure their GIS is enterprise ready, integrated with all their back office systems, and kept meticulously up-to-date.