Power Distribution Redefined – Part 2

Power distribution is entering a new chapter in its history. A digital age which will impact our lives and business as much as electricity did at the end of the 19th century, bringing with it a wave of innovations that blur the lines between the energy and the digital space. The traditional centralized model is obsolete giving way to new economic models and opportunities. Opportunities to redefine the core basics of power distribution; efficiency, reliability, safety, security, and performance.

Recently at DreamForce I had the opportunity to join Marc Benioff, CEO of Salesforce during his keynote presentation.  In the course of the keynote the lights went out in the room – a complete blackout. Imagine if this happened to your facility. What would be the consequences? Loss of revenue? Unhappy tenants? Loss of life?


At the core of smart power distribution systems are smart devices that enable you to take preventive measures to mitigate these potential risks . These devices have become more than just responsible for controlling a single mechanism. They now measure, collect data, and provide control functions. They enable facility and maintenance personnel to deeply access the power distribution network. And they continue to become more intelligent.

In many places throughout your power network this intelligence may be embedded inside other equipment, such as the smart trip units of circuit breakers. These smart breakers can provide power and energy data, as well as information on their performance, including breaker status, contact wear, alerts, and alarms. In addition to core protection functions, many devices are also capable of autonomous and coordinated control, without any need for user intervention.

As I discussed in a previous blog post, our new Masterpact MTZ air circuit breaker (ACB) is an excellent example of a key piece of hardware that businesses have used and depended on for decades, and now has evolved to include new digital capabilities. One of these primary new digital technologies revolves around communication abilities and being able to send the data the device is gathering to a building analytic software.

Schneider Electric Building Analytics is an advanced lifecycle managed service that delivers automated fault detection, diagnosis, and real-time performance monitoring for buildings. Information is captured from building systems and sent to our cloud-based data storage. From that point, our advanced analytics engine uses artificial intelligence to process building data and continuously diagnose facility performance by identifying equipment and system faults, sequence of operation improvements, system trends, and energy usage.

Building owners and occupants are now focusing on workplace efficiency. From comfort to space, and occupant services to management dashboards, organizations are now placing more emphasis on well-being at work. When building analytics recommendations are implemented, the results are obvious – enhanced building performance, optimized energy efficiency through continual commissioning, and reduced operating costs — all with a strong return on investment and an improved building environment.


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Controls Pre-commissioning Is Like Checking your Parachute Before Jumping…A Very Wise Decision.

Wouldn’t you want to make sure your parachute rip chords are OK before jumping out of a plane?  Me too.  Safety first, right?  Well, it’s the same idea with performing a pre-commissioning controls checkout of your plant before going live the first time.  Ask yourself…Is your Distributed Control System control logic configured correctly?  The answer is likely “no  – but what can I do about it?”. How about the Programmable Logic Controllers? The Emergency Shut Down System?  The Turbomachinery Controls?  The Burner Management System? And so forth…

To quote Donald Rumsfeld–  “There are known knowns; there are things we know we know. We also know there are known unknowns; that is to say we know there are some things we do not know. But there are also unknown unknowns.” A great quote taken out of context but directly relevant – we simply do not know how good our controls are prior to commissioning.

Oil RefineryWhat if I told you that a large refinery used dynamic simulation to do pre-commissioning tests on seven separate refinery units.  They identified more than 1200 logic and control configuration issues in a completely safe and cost-effective manner prior to their plant going live. Whew! This is actually the norm and not the exception. And who do you think became the hero in that story?  The plant manager, of course…and anyone else in the company who had the foresight to employ a dynamic simulator.

Sleeping better at night

If you knew there were (on average) 150 issues on each unit that could be corrected on your controls systems prior to live commissioning wouldn’t you be more confident in the lead up to commissioning?

For a new greenfield facility or a revamp project,  the control or safety instrumented system is often seen as the critical path risk to completing the plant startup on schedule.  Low-Fidelity Tieback simulation is a good tool for basic testing, but only effectively tests single loops at a time. It certainly will provide value but today plants are highly complex and integrated and have highly non-linear responses  that limit the benefits of tie-back simulation.

What if the engineering or operating company had the foresight to use dynamic simulation in the Front End Engineering Design (FEED) stage. Those high fidelity models have already delivered significant value as discussed in the first blog in the series. They can now be readily upgraded and integrated with the controls systems to support pre-commissioning controls checkout, adding substantially more benefits.

Foresight and Planning

Even for those companies that didn’t give thought at the design phase to do model development, there is still an opportunity to reap the benefits with a little foresight and planning. The controls design and dynamic simulation can happen in parallel – so don’t believe the naysayers who say that non-linear High-Fidelity simulation cannot fit into the always compressed timelines around controls design and startup.

This early identification and resolution of controls issues in pre-commissioning has a dramatic impact in terms of shortening the commissioning time in the plant and ensures that a plant will be on-line sooner. Here’s an example where a power company saved an estimated $ 1 million dollars by performing  a Controls Pre-commissioning Checkout.  Intermountain Power Service Corporation purchased a simulator upgrade as part of a DCS upgrade project to help prepare operations for the new user interface and control logic changes.  After implementing a controls checkout using Schneider Electric’s SimSci DYNSIM product, the plant identified and fixed critical errors prior to going online.  Read the complete success story to learn more about their challenges and the results.

Lifecycle Management

In the first blog of this series I highlighted the potential returns on investing in modeling early on in the project lifecycle. The same model has now become an asset and added extra value prior to plant commissioning by being utilized for controls pre-commissioning. The journey isn’t over yet. Please read the next blog in the series to learn about the additional benefits that can be realized by taking the controls checkout system and using it to train your operations staff. Operations staff directly impact safety, profitability and plant availability. Highly competent and skilled operators will maximize all three.

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Asset Performance Monitoring Saves $1 Million in Potential Transformer Losses

The recent growth of non-traditional Internet-connected devices is often referred to as the “Internet of Things” (IoT) revolution. In the realm of power distribution, IoT plays an important role by enabling owners of power distribution equipment (e.g., transformers, transfer switches and breakers) to migrate from a reactive and preventive maintenance model, to a condition-based maintenance business model. Information concerning practical deployments of power distribution-related IoT implementations have come to light. Schneider Electric’s Asset Performance Monitoring-as-a-Service (APM-aaS), a predictive analytics software solution, was recently deployed at several pilot locations.

The purpose of Asset Performance Monitoring is to provide insight as to the health of electrical distribution assets. The steps executed in the process include the following:

  • Gathering of behavioral data through sensors
  • Consolidation of collected data via a dashboard
  • Monitoring and analysis of that data by power experts.
  • Transformation of data to action

Asset Performance Monitoring IOT Schneider Electric

At these pilot locations, medium/low voltage switchgear, circuit breakers, dry transformers and high voltage oil filled transformers were targeted for monitoring. In addition, wireless temperature and partial discharge technologies were integrated into the platform, and medium and low voltage circuit breakers algorithms were refined.

Sensors were placed inside of the targeted assets in order to gather performance data to help analyze the operating performance of each asset. By leveraging the recent advancements in cloud technologies, data was transferred from the customer’s location to the Schneider Electric data center.

During this process, data was analyzed at three levels. At the first level, analysis was performed through asset specific algorithms, combined with rules and thresholds specific to asset application and utilization. The second level consisted of remote analysts located at a centralized service bureau who were responsible for day-to- day operations and for the initial anomaly discovery process. The third level engaged a network of experts, either product line or system experts, who further validated the findings, and developed a detailed report along with recommended next steps. The findings were submitted to the pilot customers, with a detailed action plan to address all findings.

At one pilot site, the team applied a wireless temperature technology on two dry-type transformers supporting a double-ended substation, which featured a Main-Tie-Main configuration. One side was supplied by a 4-year old transformer and the adjacent transformer, which was part of the original installation, had been in service for approximately 30 years.

Two weeks after monitoring began, it was observed that the heat signature of the two transformers were quite different. The newer transformer, displayed a very tight temperature profile, with “B” phase being the higher temperature of the three phases. The older transformer displayed a heat signature that was quite different. The temperature disparity between the phases was greater. Analysts observed that “C” phase was running hotter than A and B. Typically, on a dry-type transformer, if load is balanced, “B” phase temperature should be hotter than “A” & “B” due to its physical location.

After some investigation with the customer, it was deemed that load was not the cause of the higher than expected temperature of the “C” phase, and no other contributing factors could explain the higher temperature of “C” phase. As analysts researched the history of the transformer, it was discovered that an identically configured transformer, 4 years’ prior, had been replaced because of a catastrophic failure caused by a coil short circuit. The lost revenue, clean up, and replacement costs were estimated to be in the vicinity of $ 1 Million.

It was deemed by the expert analyst that the heat trend within the older transformer was a possible warning that the insulation inside was beginning to deteriorate. Faulty insulation can lead to short circuit issues. The report produced by the Asset Performance Monitoring team, which was based on the data gathered, was enough to convince the customer’s management team to upgrade to a new transformer, thereby avoiding a repeat scenario of catastrophic transformer loss.

This is one of several examples of how true predictive maintenance, based on an IoT configured solution, can help avoid disruption to business continuity and the associated financial losses. For more information on Schneider Electric asset management offerings, visit http://www.schneider-electric.com/b2b/en/services/field-services/.

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Dream Big: Decarbonization key to utilities’ future

Utilities are undergoing a fundamental transformation as they wrestle with the challenges of climate change. The earth is warming and that can cause large, potentially hazardous changes in the climate and weather and have a widespread impact on human and natural systems. Utilities’ infrastructure, scattered across wide areas and often outside, is particularly exposed to the impacts of climate change, with coastal grid and generation infrastructure at risk from severe weather and rising sea levels. Because the electricity and heat generation sector is the largest emitter of global greenhouse gases (43 percent), it is of critical importance that utilities commit to significantly reducing emissions over the coming years and formulate a plan of how best to do this.


Worldwide legislation is compelling all industries to make more environmentally friendly decisions. In April 2016, 175 countries signed the United Nations’ Paris Agreement, which aims to limit warming to “well below 2°C above pre-industrial levels” and seeks to limit the temperature increase to 1.5°C. Additional targets include the long-term global goal of a 100 percent carbon-neutral world. Moreover, many countries have their own, often even more stringent, climate regulations.

Not only is electricity generation the single largest contributor to greenhouse gas emissions, its emissions are fairly concentrated in clearly identified sites (compared to other sectors such as transportation or agriculture). This makes it an easy target for governments looking for a place to start with emissions reduction.

Undeniably, these goals put pressure on utilities to address global warming, but as utilities already know, there is more at stake for them than compliance. For example, changes to the environment have an unknown impact on fossil fuel reserves, unpredictable weather can cause fluctuations in demand, an increase in hurricanes and coastal storms can lead to more power outages, and unpredictable weather can create health and safety risks.

Stranded assets risk is another example. Decarbonization goals out to midcentury will influence utilities investments today. Indeed, a new fossil-fired power station today would be expected to have a useful life of about 25 to 40 years. With the Paris Agreement comes long-term pathway planning to ratchet up emission reduction ambitions, in the long term, enforcement of strong greenhouse gas limitations could leave utilities with fleets of redundant, high-emitting fossil fuel power stations they can no longer operate. A power plant that looks like a good investment today may not be such a lucrative asset in a few decades when its operations are limited or stopped by a high carbon price, carbon tax, or stringent regulation. Regulators will consider climate goals when making decisions on which assets utilities should invest in, especially if depreciation extends beyond the horizon for full decarbonization. Power plants and other electric infrastructure have long operating lives, so the decisions made today will impact the fuel mix and carbon emissions for decades to come.

Let’s take a look at three major areas for improvement: energy efficiency, demand-side management, and renewable energy.

Scenario modeling by the International Energy Agency predicts 40 percent of the emission reductions needed to meet global goals will come from energy efficiency. This makes energy efficiency one of the key areas on which utilities can focus. It is also the cleanest, most economical energy resource — if energy isn’t being used, it doesn’t need to be transmitted, generated, or distributed. It is the so-called negawatt.

Utilities can reap big benefits from improving efficiency, including lower costs for energy generation, transmission, and distribution, more reliable systems (because of less stress on equipment), and reduced dependence on scarce resources. A good place to begin with is in increasing the efficiency of energy-consuming processes and products in both supply and demand.

Demand-side management programs seek to influence consumer behavior. Technology advancements such as smart meters and other intelligent devices allow utilities to collect data that gives consumers visibility into their energy use. This allows them to make informed decisions on how they consume energy and the information can encourage them to make more efficient choices such as reducing the amount of energy they use or consuming at off-peak times. Utilities can also encourage the use of energy-efficient appliances (e.g. heat pumps), electric devices (e.g. LEDs), and building designs (e.g. passive or bioclimatic architecture).

Demand response programs and aggregators are improving flexibility by managing electricity use, which allows utilities to better adapt the demand for power rather than adjusting the supply. This has the added benefit of potentially lowering the cost of electricity in wholesale markets. The objective is to better align energy use with its availability.

Renewable energy, particularly solar and wind energy, is the fastest growing source of electricity, especially distributed generation. It is expected to overtake coal as the largest source of electricity by the early-2030s and accounts for more than half of all growth over the period from now until 2040. In addition, the cost of renewable generators continues to drop, fueling renewables’ growth, and its integration into traditional grid networks is ongoing. Although the continued shift to renewables can be challenging, utilities moving toward the smart grid will find the benefits outweigh the negatives.

The same can be said about all the upcoming environmentally motivated changes. Yes, they’re required and necessary, but rather than looking at a carbon-neutral world as a barrier to operations, utilities should focus on the many opportunities the changes will bring.


To learn more about the future of the utility industry, download our free ebook, Powering an Always-on World. And be sure to check out the other blogposts in this series:

  1. Dream Big: The future of reliability for utilities
  2. Dream Big: Utilities efficiency in the future
  3. Dream Big: A Safer Future with Digitized Utilities

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