Never Leave Me, Walk Close Beside Me

Today's post is named after one of my favourite songs of all time's opening lyrics. "Dry and Dusty" by Fever Ray.

"Never leave me, walk close beside me.

Your hand, my hand, fits so easy.

No tomorrow, let us stop here,

We did some great things, oh, didn't we?"

I love it's quiet intensity and focus. I love it's focus. I love its focus. I love its focus.

This photo is from a fan video of Dry and Dusty. Have a look at this amazing fan video if you want to. It's absolutely amazing.

I love this video so so much and that's mainly because it's got pylons. Lots and lots of pylons here.

Just a tiny tiny bit on Edge Management

I have been looking at the Schneider Electric web page and looking at what their offering is on Edge Management Solutions - link here. As always as a software engineer this is to try and better understand what can be built.

Today's Plan - A cross comparison between Schneider Electric's section on Edge Management in their Smart Grid for businesses page, and the beginning of the last article I was reading - "Distributed intelligence for a DER-based grid."

A comparison

Electricity is evolving. Electricity is evolving. Electricity is evolving.

The way in which consumers use energy is evolving. The way in which consumers use electricity is evolving.

Because of this we need greater visibility and control at the grid edge. 

We need greater visibility and control at the grid edge. 

Greater visibility and control. Visibility and control. Greater visibility and control. This is due to the, and I quote, "evolving sophistication of how consumers are using electricity". This currently is lacking in the systems that we have today.

Remember that using distributed intelligence can decrease time gaps between decision-making and action, and therefore can lead to:

• A more resilient grid (YAY! Yay! Yayyyyy! We love resilient grids on this blog).
• (Yayyyy thank you!).
• Better insights into grid operations (Schneider electric have a section on operations too in this page and NOW I WANT TO READ THIS TOO and MAYBE EVEN DRAW THIS INTO MY COMPARISON TODAY IF I HAVE TIME).
• AND OR IF NOT THEN AT LEAST, AT LEAST AT SOME POINT.
• Improved customer engagement - this is very very good and very important for operating the smart grid, as we need to have consumer data on DERs and usage to properly manage load.
• Increased safety
• Good distributed intelligence can help to protect workers who are fixing the grid, spot faults before they happen, prevent faults, and so on - and so much more.

However it is important that the data produced is of very high quality and is very true to the reality of the grid and what is going on.

We want data that produces actionable results, it says here.

What I Love

It's been the energy for me. It's always always been the energy. It's always been the electricity. I can go absolutely wild with excitement over a pylon. I can and regularly do go pylon spotting and I have favourite pylons literally all over the world. I will go ecstatic over a wind farm - I can and I do every day. 

I love pylons. I love wind farms. I love wind energy. I love offshore wind farms. I love offshore wind energy.

I have accidentally read through the rest of the article

My plan had been to draw a comparison between the DI article and the Schneider Electric website, however I spent my weekend reading through the rest of the article. I also looked at the Schneider electric website too several times.

I don't know where to go from here. 

Summarising the rest of the article

Since I have been through the rest of the article then what does it say?

"The distributed intelligence value proposition"

Distributed Intelligence allows us to discover how our grid is "actually responding to loads at the edge of the grid versus relying on assumptions made by engineering models."  This is good as there are wider challenges "facing distribution grid operators" - these are caused by the "rapid growth of DERs" and the "complexity of the ensuing power flows." Moreover, with this growth there is also a great increase in the amount of data that are becoming available, in line with the increased frequency of, for example, smart meter reads.

This leads to "'a need for visibility and control at the grid edge because of the evolving sophistication of how consumers are using electricity." Unfortunately, although this increase in use of DERs has changed our power flows and has changed what is going on at the grid edge, the "systems that existing today" are still "lacking" in the ability to provide us with the visibility and control that we need over power flows at the grid edge.

"A Growing Ecosystem"

The more partners that this kind of software works with, the more kinds of options become available to them - the more doors open up for them. The more DERs that are integrated into the grid - the more "'real-time monitoring is needed to maintain the reliability and quality of supply." For example, now, "a meter or group of meters can communicate with one another and take action" and "stop customers with solar photovoltaic generation from pushing excess power to the grid." This is interesting - so it stops the grid from overloading. Overloading means imbalance - imbalance means power outage. 

I wonder what this means for customers though - do they get annoyed if they can't export as much power as they would've liked to, and therefore get paid for it? And from a software engineering point of view - how do we build this software? How do we build this tech? As always, I am wondering...

"Valuing the Use Case"

This section of the article cites examples of utility companies using this kind of DI software and finding additional unexpected benefits. For example, through using smart software to find exactly where the fault is in a grid failure, expensive replacements of certain hardware machines can be prevented, with instead just fixing the relevant fault. 

This can save money, not only on time taken to find and fix and repair the fault but on any compensation to the customer that the grid operator might have had to pay out in terms of power outages.

The last two parts

I have gotten this far too the end of the article, and the whole thing has been challenging, and I feel like I have gotten most of the important points down. And so in the last two paragraphs which are jumping out at me a little bit less, are there any other parts that seems really relevant to me? Thanks...

On the below note, where I talk about this article favouring DI over back-office analyses, then this part of the article does touch on how the two can be combined together. I am not sure if I would be so quick to skip the human step that is involved in these processes... even when there is good software involved. Once again however this article touches on the common, reoccurring theme within renewable energy technology of hardware versus software. It seems to be implying once again, that, with no new hardware, the software has the ability to do so much and change so much even just as far as driving innovation within the renewable energy transition goes. This reinforces the point made by the first ever article I read on this topic - that digital software solutions will now drive innovation faster in energy tech than hardware can.

Smart meter technology has the grounds to break barriers and break down boundaries and to drive and to create new innovations within tech. I suppose the only question is - who is going to build this? And how? And whose job is it to come up with this? As the article that I have linked to above concludes by saying - we are going to need people who are both experts in renewable energy and software engineering. And that could be me.

That could be me.

This article seems to be taking it one step further

A lot of the articles that I have read previously - for example, this Medium one, which I have spent quite a bit of time reading - seem to have talked about the need for aggregating and analysing data all together. This current DI article seems to have taken it a step further - it doesn't just want data to be aggregated and analysed by someone in the "back office". It was devices and sensors and chargers to be smart. Chargers and meters. 

Schneider Electric

I went through the three main sections under "Explore Our Smart Grid Software" on this page, so what does it say then?

Under Asset Management...

... it says that their grid asset performance software "helps utilities to

• understand asset health, and
• understand asset risks

This allows utilities to 

• prioritise maintenance actions.

This allows for:

• more timely and informed decision-making

And this causes us to:

• Maximise Crew Resources
• Avoid Outage
• Save costs.

It also talks about "integrating workflows that have traditionally been siloed", as is the common theme that has come up throughout my research.

Under Edge Management...

It talks about two kinds of solutions

• Demand management solutions
• Grid metering solutions

These solutions can allow/help utilities to better:

• Design and operate their low-voltage grids (oh, oh my god, how I love these...)

And to enhance:

• Their meter operations
• Their data collection
• And their data quality.

And this will allow them to:

• Gain system insights
• Maximise DERs capacity hosting, and
• Increase customer engagement.

This in turn will allow them to:

• Support usage optimisation.
• Support demand management.

And as usual, here I am. I am asking... as a Software Engineer... as Software Engineers. As someone who loves to code... as the people who love to code: how can we build this thing? 

How can we fix this thing? How can we make it better? How can we save the planet? Is what we do enough? Will what we do ever be enough if people don't learn to use resources more sparingly?

So what is the common theme among the two resources?

Well... most definitely avoiding outages...

Prioritising maintenance actions - oh well but then that was most definitely a common them with the Medium article as well...