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Big data lessons: How to apply analytics to improve utility distribution operations

Editor’s note: This is part two of a two-part series. To read part one on key lessons and best practices, just click here.

Applying analytics to deliver results: focusing on distribution

After identifying the right questions, how do utilities access, collect and use big data to develop answers? The key is to derive insights that can improve business processes across the utility, all the way from billing and customer care to demand side management and distribution planning. The second part of this two-part series provides guidance on five key areas to focus on when deploying analytics. Because utilities operations are so diverse, I’ve focused on challenges within distribution operations and planning as a representative example of where analytics can make a difference.

1. Ensure electricity is delivered more reliably

Weather is still the biggest wildcard for utility planning, and it’s getting wilder. Various studies have concluded that storm-related power outages alone cost the US economy up to $50 billion per year. 

Outages are inevitable. However, when they do happen, it’s important to react fast. Advanced analytics, drawn from grid planning applications, can help utilities quickly identify service break points---perhaps several at once---on the distribution system. Utilities can see which part of the system demands its attention first and decide where it should send crews first for the greatest impact. Analytics also help systems operators route service crews to assess the damage, restore service and inform customers regarding service restoration. 

Grid analytics helps utilities identify and fix outages in hours rather than days. They also help keep the customer informed throughout the process with notifications and information essential to utility business success. 

2. Fix the distribution system before it breaks

Restoring outages quickly helps. What is even better is to proactively anticipate and plan well enough so that outages that can be prevented do not occur. Power outages, especially those caused by poor planning, system overloading conditions or improper and inadequate system maintenance, are the surest way to damage the reputation of any utility. With changes in customer behavior and expectations, social media and lightning-fast communications, word gets out swiftly when a part of the distribution system is down. Utility regulators are increasingly tightening reliability standards and linking them to performance-based incentives and penalties.

With distribution analytics, utilities can gain operational visibility into the entire distribution network across different geographies. Analytics drawn from real time and near term data can quickly identify impending problems and send notifications so system operators can take immediate remedial actions. Interactive maps can reveal the hot spots within the grid and point out areas where system planners and operators should focus their attention. 

Analytics driven from feeder and transformer operational data can point out if a particular transformer or feeder gets frequently overloaded. Anticipating problems through predictive analytics and planning can help utilities evaluate system upgrades and improvements before customers get left in the dark.  

3. Integrate distributed energy resources

In the past, generation typically operated upstream on the grid with respect to distribution. Now utilities find themselves managing generation within the distribution network as more consumers and businesses install solar panels. Consumers are now becoming “prosumers” as  solar and energy storage economics are becoming far more favorable. Economics aside, consumers like the idea of generating clean energy near their homes. Microgrids and nanogrids are being developed at various communities as self-contained energy ecosystems. These trends will only continue and get more intertwined

This is all good news for the environment and for consumers who want to have a say in their energy generation sources. However, distributed energy resources often operate intermittently, and this poses new challenges in managing the distribution networks. Advanced software applications and analytics are required to manage the impact of these distributed energy resources on distribution networks and utility operations. .

These advanced software applications can suitably model the behavior of the entire distribution network including distributed energy resources (DERs). These applications can analyze weather patterns, generation profiles and forecast the generation that will be available from the DERs on the distribution network. Analytics will highlight areas that need voltage support, perhaps the end of a feeder where back-up power is needed or where demand warrants additional utility supply.

Through sophisticated management of distributed energy resources and their impact on existing distribution grid infrastructures, utilities can better embrace the coming change and better position themselves for grid modernization efforts while improving customer satisfaction and meeting regulatory pressures. 

4. Improve efficiency by reducing energy loss

Utility regulators are demanding that utilities eke out all possible efficiencies to keep rates in check. The Environmental Protection Agency under Clean Air Act section 111(d) is pushing for efficiency and the use of more renewables to limit carbon emissions. And, let’s face it; efficiency is good for the bottom line too. For North America, a 1-2% savings in utility operating expense can represent hundreds of millions of dollars in annual savings. Line loss represents a common reality on the electric utility grid. On an average around 6% of electricity generated in the US is lost in transit on the T&D networks before it ever gets to consumers. 

With the right distribution analytical solution such as Volt-VAR optimization, utilities can help reduce these line losses significantly and achieve optimal management of voltages and VAR flows across the distribution feeders. Also, by reducing losses, utilities can free up capacity to serve additional load. 

5. Better manage peak demand 

Utilities are continuously looking for new ways to mitigate the risks from rising peak demand and the proliferation of intermittent renewable energy resources. More and more utilities are offering demand response programs that engage customers to reduce energy use at critical times in order to reduce overall load on the distribution network. It is now possible to coordinate demand response activities between neighboring utilities with compensation provided from a single system. 

Utilities can benefit in multiple ways by integrating demand response management systems (DRMS) and DERs into overall distribution planning and management systems by utilizing advanced distribution analytics from the integrated system. 

Distribution analytics can help utilities analyze the distribution network with various physical and equipment limitations where the cost of electricity fluctuates throughout the day. Based on the derived recommendations from these analytics, utilities can call targeted and location aware demand response and thus notify customers to reduce power usage during periods of high electricity demand. Utilities can do this while taking into account feeder capacity and the network condition throughout the entire distribution territory. This enables utilities to pinpoint and reduce demand when and where it is needed.  Integration of the demand response and distribution management systems can also enable the measurement and verification of actual demand reductions that occurred through the demand response events with respect to the distribution grid topology. 

Taking best practices for data analytics across the utility distribution operations 

In order to take advantage of the increasing volumes of big data available to distribution planning and operations, utilities must be able to analyze this data in order to overcome these new challenges and to develop better operational business processes. Business processes must not only traverse the myriad of traditional utility silos but go beyond the four walls of utilities and touch customers in order to improve utility operations on both the grid and demand side of the business. Customer engagement is a key part of this equation

It’s not always clear when the sun will shine, the wind will blow or a storm would hit, but predictive distribution grid analytics can help utilities identify and address these intermittent conditions and better manage operational risk. In my view utilities must start incorporating analysis of big data into distribution planning as well as broader operations to achieve a wide range of operational improvements while boosting the bottom line.

Editor’s note: This is part two of a two-part series. To read part one on key lessons and best practices, just click here.

Milani is Nexant's senior vice president of software and chief technology officer. He directs the strategy, development and delivery of Nexant’s customer-centric software platforms that help utilities align strategic planning, grid operations and demand side management to improve customer engagement, boost operational efficiency, reduce risk and deliver improved business results. Milani is an industry-recognized thought-leader and expert on cloud computing and SOA with more than 20 years of experience in product design, development and distributed systems architecture spanning the evolution of distributed systems.


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Thank Martin for the Post!

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