Sunday, 27 October 2019

ARTICLE 7: Peak Demand Stagger Strategy

REMINDER: This blog is a working manuscript for my next books and future projects. This article is still in 'rough draft mode' and there will be edits being made over time. Eventually, I want to include some real-world examples of how this strategy could be applied. It's also probably beneficial for many readers to also have some more info on what exactly peak demand is with regards to energy supply. If you want a crash course on energy, supply, utilities, etc., check out Schneider's Energy University for lots of free information:


Frans Johansson's research suggests that the associative barriers of experts in a given field are quite high (Read more in his book: "The Medici Effect"). This means that experts are often the least likely to understand the significance of a new idea in their field. 

Below is a white paper that presents an energy strategy that could be implemented in various unique ways around the globe. This strategy was reviewed by an Electrical Engineer who agreed the concept makes sense (If something was overlooked, please get in touch via my email and let me know where I have gone wrong). The numbers used in the calculations were pulled from the 2018 Canadian Electrical Code book, which is currently the most up-to-date version. The interesting thing to note was that although the electrical engineer confirmed the legitimacy of the strategy, they were not convinced that it was overly significant, which would corroborate Johansson's findings on the subject, although I am willing to admit that this paper extends a bit outside my own area of expertise, which was why I sought to have it reviewed by someone who is an expert in this field...



Peak Demand Stagger Strategy

Abstract

As the world ventures further into the twenty first century, the need for more efficient sources of power generation has increased in importance. The projections on increased global population, and therefore increased demand, further compound the need for efficiency. The introductions of renewable forms of energy, such as wind and solar, into The world’s energy structure create further challenges, due to issues such as intermittent supply of power. Wind power cannot be generated when there is no wind.

Although there is a great deal of research being conducted to seek alternative forms of energy storage, these solutions still have to contend with yet another issue in power generation: peak demand. This can be illustrated in the following hypothetical scenario:

Let’s say we have a city whose primary source of electricity is derived from wind power. This city features favourable geography for pumped hydro, and it has decided to utilize this form of energy storage when the wind is not blowing. The majority of the time, the city’s electrical infrastructure can handle the demand for electricity, with one exception. As soon as everyone comes home from work, the demand for electricity spikes higher than any other time during the day. On days when the wind is strong, and there is adequate reserve capacity in the pumped hydro system, the utility is able to provide uninterrupted power to the city. However, on days with less wind, or on days when the pumped hydro reserve capacity is low, the utility is forced to employ rolling blackouts. It cannot supply enough electricity to meet the demand.
This example shows just how disruptive peak demand can be for a Utility.

Throughout most of the twentieth century, many nations have implemented Daylight Savings Time (DST) in an attempt to offset energy usage during times of daylight. As the world has ventured further into the 21st century, it is important to explore and implement strategies that are more aligned with present global energy usage and peak demand. This paper seeks to introduce new strategies by applying the concepts of DST on smaller scale entities. DST is often implemented on a national or provincial level, and has a start and end date. It does not appear that it has been conclusively proven whether DST yields a net benefit or cost. (see reference at end)

Although, it should be mentioned that the scenarios and strategy presented in this paper can still operate in conjunction with DST, but it is not necessary. This means that this can easily be implemented whether DST is in operation or not.

This paper presents a theoretical model for a school board, and how it could employ a different strategy to offset peak hour demand. The hours are staggered inside of the school in the first scenario to present a situation where an organization can implement this in-house. Second, two schools are staggered within the same municipal region to achieve a similar result. Then the same strategy is applied to the school districts of two cities that are in relatively close proximity to each other to exemplify this on a larger scale.

Although, schools are used in the example, it is important to note that this strategy can be implemented in many different businesses, organizations, or even municipalities that are in the same time zone.

This strategy allows an entity, whether it is a small business or several cities, to stagger their operating hours in order to offset times of peak demand. The flexibility of this strategy cannot be overstated. The needs from one end of the world can be quite different from the needs of those at the other end of the world.

Also, it is important to keep in mind that this strategy will have downsides as well, such as the challenge of clock synchronization of financial markets if two cities decide to implement this strategy within the same time zone. Any business, organization, or government will need to perform a cost-benefit analysis to determine the appropriate scope of the strategy implementation.

SCENARIO 1A
In this scenario, the Peak Demand Stagger Strategy will be applied to a school. The data used is based on a randomly selected high school in the Edmonton area.

1912 students * 0.7 = 1342 students (assume 70% of students are in class at any given time)
If we assume average class to have 30 students, then we get 44.73 classes – round to 45 classes.
Average class size is approx. 84 square meters.
According to code book (P.107) assume 50W/m^2
45 classes  x  84 m^2   x 50W/m^2 = 189,000.0W

Let’s assume all classes run from 9am – 3pm for a total of 6 hours.
It would look like the following:

9am – 3pm 189,000W * 6 hours = 1,134,000kWh
Time

Total Energy
9:00am – 10:00am
189,000kWh
189,000kWh
10:00am – 11:00am
189,000kWh
189,000kWh
11:00am – 12:00pm
189,000kWh
189,000kWh
12:00pm- 1:00pm
189,000kWh
189,000kWh
1:00pm – 2:00pm
189,000kWh
189,000kWh
2:00pm – 3:00pm
189,000kWh
189,000kWh
Total

1,134,000kWh
NOTE: the energy displayed is isolated to that which is used inside the classroom, in order to present the scenario in a simplified way. There would still be a baseline amount of electricyt being used by the school.

SCENARIO 1B

If we stagger the classes to have half of them running from 6am-12pm and the other half to run from 12pm - 6pm, then we have the following breakdown:

Time

Total Energy
6:00am – 7:00am
92,400kWh
92,400kWh
7:00am – 8:00am
92,400kWh
92,400kWh
8:00am – 9:00am
92,400kWh
92,400kWh
9:00am – 10:00am
92,400kWh
92,400kWh
10:00am – 11:00am
92,400kWh
92,400kWh
11:00am – 12:00pm
92,400kWh
92,400kWh
12:00pm- 1:00pm
96,600kWh
96,600kWh
1:00pm – 2:00pm
96,600kWh
96,600kWh
2:00pm – 3:00pm
96,600kWh
96,600kWh
3:00pm – 4:00pm
96,600kWh
96,600kWh
4:00pm – 5:00pm
96,600kWh
96,600kWh
5:00pm – 6:00pm
96,600kWh
96,600kWh
Total

1,134,000kWh

6am – 12pm 22 classes * 84 m^2  x 50W/m^2 = 92,400kWh  
12pm - 6pm 23 classes * 84 m^2  x 50W/m^2 = 96,600kWh

In both scenarios, the amount of energy used is the same (1,134,000W), but in scenario 1A, the staggering of start times and break times allows for a much lower peak demand half of the time the classes are operating.


SCENARIO 2A

In this scenario, the same principal will be applied to two separate schools within the same municipality. For simplicity, the same data will be used from the previous scenario.
This assumes both schools operate at the exact same times of day. Note: there would still be a base energy used above and beyond the class room times, but these have been eliminated for ease of understanding.

Time
School A (energy used)
School B (energy used)
Total Energy
9:00am – 10:00am
189,000kWh
189,000kWh
378,000kWh
10:00am – 11:00am
189,000kWh
189,000kWh
378,000kWh
11:00am – 12:00pm
189,000kWh
189,000kWh
378,000kWh
12:00pm- 1:00pm
189,000kWh
189,000kWh
378,000kWh
1:00pm – 2:00pm
189,000kWh
189,000kWh
378,000kWh
2:00pm – 3:00pm
189,000kWh
189,000kWh
378,000kWh
Total


2,268,000kWh


SCENARIO 2B

School A runs from 6am – 12pm
School B runs from 12pm – 6pm
Time
School A (energy used)
School B (energy used)
Total Energy
6:00am – 7:00am
189,000kWh
-----------
189,000kWh
7:00am – 8:00am
189,000kWh
-----------
189,000kWh
8:00am – 9:00am
189,000kWh
-----------
189,000kWh
9:00am – 10:00am
189,000kWh
-----------
189,000kWh
10:00am – 11:00am
189,000kWh
-----------
189,000kWh
11:00am – 12:00pm
189,000kWh
-----------
189,000kWh
12:00pm- 1:00pm
-----------
189,000kWh
189,000kWh
1:00pm – 2:00pm
-----------
189,000kWh
189,000kWh
2:00pm – 3:00pm
-----------
189,000kWh
189,000kWh
3:00pm – 4:00pm
-----------
189,000kWh
189,000kWh
4:00pm – 5:00pm
-----------
189,000kWh
189,000kWh
5:00pm – 6:00pm
-----------
189,000kWh
189,000kWh
Total


2,268,000kWh

In both scenarios, the amount of energy used is the same (2,268,000 kWh), but in scenario two, the staggering of start times and break times allows for a much lower peak demand half of the time the classes are operating.


SCENARIO 3

In this scenario, the principal is applied to all of the schools in City A and City B. Both cities are in the same time zone. For the sake of simplicity, it will be assumed that both City A and City B both have 100 schools within their municipal district.

In this scenario, the start time for each municipality is staggered in the same way as before. It’s important to keep in mind that there are added advantages that may not be apparent at first glance. For instance, if the start time in one municipality is staggered in such a way that the start time of the school falls outside of rush hour traffic, then this would also reduce traffic congestion, and reduce pollution from the many vehicles that would otherwise be idling during times of gridlock.

Without time stagger:
Time
City A (energy used
For 100 schools)
City B (energy used
For 100 schools)
Total Energy
9:00am – 10:00am
18,900,000kWh
18,900,000kWh
37,800,000kWh
10:00am – 11:00am
18,900,000kWh
18,900,000kWh
37,800,000kWh
11:00am – 12:00pm
18,900,000kWh
18,900,000kWh
37,800,000kWh
12:00pm- 1:00pm
18,900,000kWh
18,900,000kWh
37,800,000kWh
1:00pm – 2:00pm
18,900,000kWh
18,900,000kWh
37,800,000kWh
2:00pm – 3:00pm
18,900,000kWh
18,900,000kWh
37,800,000kWh
Total


226,800,000kWh


With Time Stagger:
Time
City A (energy used
For 100 schools)
City B (energy used
For 100 schools)
Total Energy
6:00am – 7:00am
18,900,000kWh

18,900,000kWh
7:00am – 8:00am
18,900,000kWh
--------------
18,900,000kWh
8:00am – 9:00am
18,900,000kWh
--------------
18,900,000kWh
9:00am – 10:00am
18,900,000kWh
--------------
18,900,000kWh
10:00am – 11:00am
18,900,000kWh
--------------
18,900,000kWh
11:00am – 12:00pm
18,900,000kWh
--------------
18,900,000kWh
12:00pm- 1:00pm
--------------
18,900,000kWh
18,900,000kWh
1:00pm – 2:00pm
--------------
18,900,000kWh
18,900,000kWh
2:00pm – 3:00pm
--------------
18,900,000kWh
18,900,000kWh
3:00pm – 4:00pm
--------------
18,900,000kWh
18,900,000kWh
4:00pm – 5:00pm
--------------
18,900,000kWh
18,900,000kWh
5:00pm – 6:00pm
--------------
18,900,000kWh
18,900,000kWh
Total


226,800,000kWh

The main goal of this strategy is to reduce overall hour-by-hour demand. There is no net difference in the amount of energy consumed whether the times are staggered or not. This allows for a lower overall peak demand, thereby reducing the risk that a utility is not able to keep up with energy demand. This could also increase savings experienced by large enterprises who are often charged in accordance with peak energy demand, and lower the overall output that an electric infrastructure is expected to produce.

Here is another Viable Underdogs video to try and add more visual context to the strategy:


#YouBuying?
#ViableUnderdogs

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References:

Aries, M. & Newsham, G. R. (2008). The effect of daylight saving time on lighting energy use: a literature review. Energy Policy, 36, June 6, pp. 1858-1866. doi: 10.1016/j.enpol.2007.05.021

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