Monthly Archives: September 2015

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

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 ( 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

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.