Author Archives: Benoit Marcoux

About Benoit Marcoux

In over 35 years working in telecom and energy industries, including 20 in consulting, I have designed systems, financed them, sold them, manage multi-million implementation programs, and ran large service operations. Always a bit of a nerd, I am passionate about how digital technologies transform entire industries and I accompany my clients in this tortuous journey. I graduated as a professional engineer and went on to complete a Master degree in Applied Sciences and an MBA.

Utility-Scale Solar Report

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I finally got around to read the US Department of Energy report on utility-scale solar energy (https://emp.lbl.gov/sites/all/files/lbnl-1000917.pdf) published a couple of months ago. Here are my highlights:

  • Installation trend is compelling. Installed capacity is now 30,000 MW – about 30 times more than 5 years ago.
  • Installation costs are falling – by more than 50% since the 2007-2009 period, the lowest-priced projects being around $2/W (AC).
  • Capacity factor is now improved to 27.5%. The main factors of this variation are, in order of importance: the strength of the solar resource at the project site; whether the array is mounted at a fixed tilt or on a tracking mechanism; the inverter loading ratio; and the type of PV modules used.
  • Power purchase agreement prices have fallen. Utility scale solar PPA is now as low as $40/MWh. At these low levels – which appear to be robust, given the strong response to recent utility solicitations – PV compares favorably to just the fuel costs (i.e., ignoring fixed capital costs) of natural gas-fired generation, and can therefore potentially serve as a “fuel saver” alongside existing gas-fired generation (and can also provide a hedge against possible future increases in fuel prices).

Evolution of Energy Generation and Distribution in Canada’s Smart Power Grid – Innovation 360 Conference Panel

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On September 29, I was asked to participate on a panel titled “Evolution of Energy Generation and Distribution in Canada’s Smart Power Grid” at the Innovation 360 conference in Gatineau, Québec (http://innovation360.ca). Here is the essence of what I contributed.

By definition, in an electricity network, energy consumption plus losses equal electricity generation. This must be true at any point in time, or protection systems will shed load or trip generators.

There are 4 ways to balance load and generation:

1) Traditionally, dispatchable generators that can easily ramp up or down were tasked to follow the load. Big hydro plants and natural gas generators are particularly good at this. However, we are running of big hydro opportunities, and natural gas are sources of greenhouse gas emission, contributing to global warming.

2) Another way to balance load and generation is to interconnect with neighboring network that may not have the same load profile. Today, all of North America is interconnected in some way. However, building transmission lines is a lengthy process that typically faces major local opposition. As a result, most transmission lines run at capacity during peaks, weakening the bulk transmission system as the Northeast blackout of 2003 demonstrated.

3) In the last couple of decades, we have started to control load, like turning off air conditioning units by pager or getting large industrial like smelters to go offline for a couple of hours during a major peak. Time-of-use or market pricing are also attempts to have loads better follow available generation capacity. However, much of the conservation focus thus far has been on energy efficiency, not peak load reduction.

4) Very recently, energy storage has been getting attention. Traditionally, the only utility-scale storage technology available was pump-storage, like the Sir Adam Beck plant in Niagara, but few of those plants are possible, and they are not efficient. Going forward, batteries, either utility-scale or distributed storage, will grow, although for now utility-scale batteries are MW-class, when hundreds of MW or GW are needed.

Balancing load and generation is also becoming more and more difficult. On one hand, consumption is getting peakier, partly due to side effects of some energy saving programs, like turning down thermostats at night in the winter, and then turning them back up in early morning, just in time for the morning peak. On the other hand, wind and solar generators are replacing fossil generators, adding unpredictability to generation and taking away controllability, thus requiring even more balancing resources.

Integrating renewable into the grid is not only causing balancing problems. It also creates voltage management and protection problems. Those are solvable, but significant, engineering problems that require expensive upgrades to the electricity grid.

Ultimately, load and generation balancing, voltage management and grid protection adds costs that are ultimately born by subscribers. It therefore quickly becomes a political issue.

As a society, we have been subsidizing fossil fuels. Clearly, going forward, we will need to greatly invest in the grid if we want to limit the predicaments of global warming for our children and grand-children.

Using Analytics to Assess Station Thermal Risks Caused by Reverse Power Flow

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With sufficient Distributed Generation (DG – embedded generation in Europe) installed on the feeders of a substation, reverse power flow may occur at the station when load is low. This is especially the case when large generators (such as wind farms) are connected on express feeders dedicated to their use.

Substations have been designed, rated and operated as step-down substation with power flowing from higher system voltage to lower system voltage. Some substation transformers also have dual secondary winding transformers that do not allow for reverse power flow conditions, as unequal reverse flow in the two secondary windings would cause overheating and potential failure of the transformer.

Utilities limit DG capacity downstream of a station to avoid excessive reverse-flow and to prevent overheating of substation transformers. For example, Hydro One requires that generation shall not exceed 60% of the maximum MVA rating of a single transformer plus minimum station load.

The (worst-case) engineering assumption is that maximum generation coincides with lowest load at a station. Is it the case? Some years ago, I ran a Monte-Carlo simulation between load and wind generation, based on theoretical distribution of both, but doubling the generation normally allowed. It found that generation would be excessive… less than 2% of the time (and not by much, and at a time when load is low and so are prices). Using actual smart meter data, it is now possible to actually know what is going on and better assess risks. For solar generation in hot climates, there is a negative correlation between load and generation – in other words, maximum generation does not happen in times of minimum load.

Even better: correlating with forecast weather data can assess whether reverse flow could be excessive in a few hours, and require large DGs to go off-line ahead of a problem (and this would not happen frequently). While I have not seen such an application, it is clearly in the realm of possibilities.

Deep analytics, used as a planning tool or in support of operations, enables safe integration of more distributed integration by managing thermal limit of station transformers operating in reverse flow.

Tutorial: Key Players in the Energy Markets: Rivalry in the Middle

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See also the previous post.

The players described in the previous post have vastly different characteristics. The most striking difference is the level of rivalry.

IMG_2174

Distributors operate in a defined territory, often corresponding to a city, a state or a province, where they are the sole provider – thankfully, as there would otherwise be multiple lines of poles along roads. Given this monopoly, distributors are subjected to price regulation, meaning that the price they charge for the use of their infrastructure (poles, conductors, cables, transformers, switches, etc.) is set, typically equal to their costs plus an allowed return on their investment. This is done by filing tariffs that are approved by the regulatory body following a rate hearing.

Retail is often a competitive industry, as there is no structural barrier to having multiple players. However, some distributors are also given the retail monopoly over their territory. Some may also provide retail services in competition with other retailers. In those cases, the distributor-owned retailer is also regulated and has to seek approval of its rates, but other retailers typically do not, although they may have to file their rate plans.

It is possible to have multiple transmission companies operating in the same territory, each owing one or a few transmission lines. However, because those transmission lines are not perfect substitutes (they do not necessarily have the same end-points in the network) and because transmission capacity is scarce, electricity transmitter typically have regulated rates, although they may compete for new constructions.

System operators are monopolies over a territory, and they have to maintain independence. They are, in effect, monopolies, although system operators are often government- or industry-owned. Their costs are recharged to the customer base, directly or indirectly.

Large generators are in a competitive business, competing in an open market, although distributed generators, which are much smaller, usually benefits from rates set by a regulator or a government.

Tutorial: Key Players in the Energy Markets

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I will be making a conference to investors later this year and I will also be training some people internally at my employer. The topics will touch on the electricity industry structure and I am preparing some material for it.

The industry can be quite complex in some jurisdictions. I boiled the complexity down to just this:

New Picture

Traditional large-scale generator own and maintain coal, natural gas, nuclear, hydro, wind and solar plants connected to transmission lines. Those are large plants – typically hundreds of megawatts.

Transmitters own and maintain transmission lines – the large steel towers seen going from large generators to cities. Those typically run at 120,000 volts and more, up to over 1,000,000 volts in some cases.

Distributors own and maintain the local infrastructure of poles and conduits going to customer sites. Those typically run at 1,200 to 70,000 volts, usually stepped down to 600 volts. 480 volts, 240 volts or 120 volts for connection to customers.

Most customers are connected to distributors, although some large industrial facilities (such as aluminum smelters) are directly connected to transmission lines.

While customers are connected to distributors, they purchase electricity from an independent retailer or from the retail arm of a distributor.

With customer installing distributed generation on their premises, they sell back power to the market, often through aggregators.

Retailers buy electricity from generators in an energy market – like a stock exchange, but for electricity.

By definition, the energy produced at any instant must be equal to the energy taken by customers, accounting for a small percentage of losses in transmission and distribution. (We are starting to see large-scale storage operators, which may act as both consumer and generator, depending they are charging or releasing electricity in the network.) This critical balance is maintained by the system operator that direct generators to produce more ore less to match load; in some case, the system operator will also direct distributors to shed load (customers) if generation or transmission is insufficient to meet the demand.

The next post will deal with energy and money flows in the market.

Covered Conductors Vs. Single-Phase Reclosers

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A utility client told me that they were trying out covered conductors on a feeder in a forested area. This was the first time that this large utility tried covered conductors. The objective is to reduce the impact of tree contacts and falling branches that blow fuses and therefore result in permanent outages for customers. In this context, the great length of feeders and the high system voltage (25 kV) make coordinating reclosers and fuses difficult.

Covered conductors have a thin insulation covering – not rated for the full phase voltage, but sufficient to reduce the risks of flashovers and fire when a tree branch falls between phases, when a tree makes momentary contact with a conductor, or when an animal jumps to it. Covered conductors also allow utilities to use tighter spacing between conductors.

While covered conductors help with tree contacts, they also have a number of operational disadvantages:

  • High impedance faults with a downed conductor are more likely, leading to public safety issues, especially since the conductor may not show arcing and may not look as if it is energized.
  • Covered conductors are more susceptible to burndowns caused by fault arcing. Covering prevents the arc from motoring with magnetic forces along the wire, concentrating heat damage. Repair time and cost increase significantly.
  • Covered wires have a larger diameter and are heavier, increasing loading, especially with freezing ice and high wind, which can likeliness of mechanical damages (including broken poles and cross arms), leading again to high repair time and costs.
  • Covered conductors have somewhat lower ampacity at high temperature (worsened by the black color that absorb more heat from the sun), with more limited short-circuit capability. High temperature also degrades the insulation. This results in more design and planning constraints that may increase construction costs.
  • Water can accumulate between insulation and wire at the low point between of a span, causing premature corrosion and weaken the conductor and can lead to failure.
  • Covered conductors must be installed differently than bare ones. For instance, using conducting insulator tie can lead to partial discharges and radio interference.
  • Finally, cost is an obvious issue – replacing conductors on existing lines is extremely expensive, possibly as much as $100k per km.

These issues got me thinking on how I could provide a better alternative. Replacing fuses with single-phase reclosers appears to be an interesting (if unlikely) alternative to covered conductors. Cutout-mounted single-phase reclosers can easily be installed in existing cutouts to protect lateral circuits. Those circuits are then protected against tree contacts without the disadvantage of covered conductors. Coordination with upstream mainline reclosers is eased by making the single-phase recloser faster than the mainline recloser. Cost is clearly lower than re-conductoring.

Full disclosure: I am employed by S&C, and S&C makes a cutout-mounted recloser.

Pseudo-Realtime Voltage Regulation to Increase DG Penetration

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Close-loop voltage control in distribution networks traditionally relied on Potential Transformers (PT) on feeders communicating with a control algorithm sending setting signals to voltage regulators and capacitor banks. More recently, Faraday devices have been used instead of PTs, being less expensive to purchase and to install.

What about smart meters with voltage measurement capability? Some smart meters measure voltage at the service point, which accounts for voltage drop in secondary feeders and transformers. There are also far more meters than PTs or Faraday sensors, providing greater coverage. But there is a problem: smart meter networks have long internal latency – it may take minutes for voltage signals to get back to a control center. This renders smart meters unusable in a traditional real-time control loop.

However, analytics could make use of delayed smart meter data, combined it with other data such as weather and historical data, to provide pseudo real-time feedback.

This could prove particularly effective with high level of Distributed Generation (DG) penetration that is affected by weather, such as solar and wind. Where a traditional voltage control system relying on real-time feedback could be overwhelmed or mislead by the variability of renewable generation, a control system relying on deep analytics of smart meter and weather data could be more effective in maintaining distribution grid stability.

Using Analytics to Assess Islanding Risks of Distributed Generators

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One of the most critical situations with Distributed Generators (DG – embedded generators in Europe) is that a interrupter on a distribution feeder may trip to isolate a circuit section and the DGs might continue supplying the load on that section, creating an “island”. When load closely match generation in the island, it may be sustained for some time, posing safety hazards – this is known to have caused death.

Distributed generators have various passive or active anti-islanding mechanisms that open a breaker at the point of connection when an islanding condition is detected. However, islanding detection techniques used in small DGs (such as residential photovoltaic generators) are far from perfect – without expensive circuitry, they may not always immediately detect an island when generation and load are closely matched. Therefore, some utilities require that load on any feeder section (i.e., between interrupters) be always greater than generation, ensuring that an island cannot sustain itself. This means that the total distributed generation capacity on a feeder section must be significantly less than the minimum aggregated load on that section. The problem is compounded by the fact the engineers assessing DG connection requests usually do not know actual load and generation per line section – estimations need to be made.

In the end, allowable distributed generation on a line section can be a pretty small number – in Ontario, Hydro One requires that total generation must not exceed 7% of the annual line section peak load – meaning that few customers are allowed to have generators.

Applying analytics on smart meter data can better assess how much distributed generation can safely be connected to a line section. For instance, minimum load may never be correlated with maximum generation – e.g., in hot climates, minimum load occurs at night, when there is no solar generation. Analytics can look into past load and generation records to determine how much generation can be connected without getting into potential islanding condition. Safe generation levels may be many times more than the previous conservative worst-case-that-never-happens engineering guidelines allowed.

Better DG Connection Assessment by Validating Phase Mapping and Tap Settings with Utilities Analytics

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Distributed generators (DG – embedded generators in Europe) can cause voltage excursions outside the allowable range and can exacerbate phase imbalance, increasing losses (especially on North American networks). Utilities set engineering rules to try to mitigate those effects, for example by limiting how much generation can be connected per feeder section.

Unfortunately, meter-to-transformer-to-phase (MTP) mapping (MPT in Europe) is notoriously inaccurate, meaning that engineers do not know the distribution of single-phase DGs on a feeder – with DGs often clustered on single-phase laterals, DG dispersal across phases may be far from even. Similarly, distribution transformer tap positions are generally unknown, but often set high because under-voltages was the traditional problem – with DGs, over-voltage can become the issue. This forces engineers to take an overly cautious approach when assessing DG connections or face the risk of network problem later.

In the past, validating MTP mapping and distribution tap settings required extensive fieldwork to track each triplex to a transformer, to track the transformer to a phase, and to visually check tap setting with a bucket truck. Now, analytic applications can correlate voltage levels over time to identify to what transformers and phase each meter belongs, and identify transformers where tap setting is too high or too low. The analytical engine can also correlate service point street address and longitude/latitude coordinates with those of the transformer. The correlations are statistical, but, with enough historical data, the accuracy is equal to or better than a visual survey, at a much-reduced cost.

With reliable phase and tap information, engineers can now assess DG connections requests with greater confidence that voltage stability of the grid will be maintained.

Reducing Reliance on Individuals in Field Regions

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In a previous post, I said that consolidation reduces costs. But it does more: consolidation eases implementation of systems to reduce dependency on the particular knowledge and experience of key individuals. This is particularly clear in 2 areas:

  • Work Scheduling and Dispatching. Advanced schedulers, such as ClickSoftware, may automatically dispatch field crews based on skillset, equipment and availability, without relying on dispatchers’ particular knowledge and experience, especially for unplanned (emergency) work. In reducing human interventions, dispatchers become supervisors of the overall process, focusing on difficult situations that the system cannot process effectively by itself. In addition to more efficient truck rolls, the number of dispatchers and schedulers (now consolidated) can be reduced.
  • Customer Relationships Management (CRM). Large utilities may have sophisticated Customer Information Systems (CIS) for millions of residential and small commercial and industrials accounts, but there is often no system to manage the hundreds of large commercial, industrial and institutional (CI&I) customers. Therefore, these remain the privy of local resources owning the customer contacts. The lack of rigour in regard to customer contact is probably a contributor to low CI&I customer satisfaction often observed. It would not make sense to implement a large system for a few customers, but a light CRM, such as Salesforce.com, can be cost effective and have a relatively fast implementation time

Full disclosure: My father worked for 25 years as a utility dispatcher. He is long dead now, but I am sure that he would be amazed to see the tools that dispatchers at modern utilities may have now.

Reducing Overhead by Consolidating Field Regions

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Large utilities have many multiple regions in their territory, with each region having multiple field depots. This structure leads to a great amount of duplication and overlap of responsibilities as key business functions such as work planning, work scheduling, project management and customer relationships are duplicated across regions. This also causes deviations and lack of uniformity in the way the work is executed in regions and depots.

There is a clear trend in the industry to consolidate regions and depots, flattening the organisation. Talking to utility managers having gone through consolidation of field regions, I concluded that one can expect a 20% reduction in overhead in a 2:1 consolidation – and this can be compounded many times, i.e. a 4:1 consolidation leads to almost 40% overhead reduction.

Why was this not done earlier? Implementation of Enterprise Resource Management (ERP) systems, which forces standardization of process, is one key driver. Furthermore, an ERP can effect consolidation without requiring centralization of roles – consolidation without centralization has less organizational resistance from middle management than pure centralization.

Let’s Build a Smarter Planet: Energy and Utilities

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I presented on the future of electric utilities at the “Les entretiens Jacques-Cartier” on October 3, 2011. The presentation itself is in English.

Here is the presentation, with notes:

Let’s Build a Smarter Planet Energy and Utilities – EJCDownload

Les véhicules électriques: une revolution? (Electric Vehicles : a revolution?)

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Here is a presentation I did at the Projet Ecosphère conference on October 25, 2010. It outline problems and solution for the introduction of electric vehicles on our roads. This one is in French.

EcosphereBMarcouxIBM20101025v05Download