The (Smart) Future of the Grid
The national grid has long been a focus for technological transformation. The changes have been incremental, but sometimes profound. Amongst other things, they have enabled us to understand the vital statistics of the energy economy like never before.
Over this short series of articles, we shall look at this evolution. What is the smart grid? What can it tell us about what’s next for the grid? Where should its stakeholders be looking for the next advantage?
In this first part, we will look at this definition and the process of bringing it about. We shall then go on to look at the practice of this new way of thinking, as well as look at how an organisation can best respond to these changes.
Part 1: Getting smart
We all know the grid. It is the electric power transmission network that keeps everything working. It connects production to consumption – making sure that what comes out of power stations gets to wherever it is needed.
The smart grid is this, but with the ability to detect and respond to changes in local or general supply. The degree to which it can do this determines how ‘smart’ it is. The progress in this direction breaks down into three main stages:
1. Intelligence gathering
2. Informed decision-making
3. Continuous Improvement
Let’s look at each of these and their capacity for delivering change.
We can’t make consistently good decisions based on insufficient data. This is axiomatic to the assumption there’s such a thing as good decision-making, or even ‘making a decision’ at all. Otherwise we’d just be talking about being good at guessing.
At a macro scale, the grid has been developing its sensory capacity since we invented fire. It started with us – too warm, too cold – and we’ve been gradually automating ever since. We now have a greater range of generation methods, each with their own supply profiles. Renewables have far greater variance than traditional methods such as coal or nuclear.
This is a large part of why we’ve had to improve our understanding of demand variance. In turn, this helps us see where energy is wasted and to predict where more will be needed. It allows us to plan future supply capacity accordingly. We’re not at a smart grid yet, but we’re being smart about the grid.
At a micro scale, businesses are starting to see smart building technology as key to realising their mid- to long-term energy management goals. Portable technology relies on batteries, which has brought about a revolution in monitoring and managing power consumption at very small scales. Electric vehicles will provide a source of ‘dormant’ capacity. All these factors will slowly creep into our calculations.
Micro-generation and feed-in tariffs have changed this picture further. While the usage profile of a business or building may be fairly consistent, its reliance on the grid for meeting those needs may not be. Or it might even have become a point of contribution itself, increasing the number of points of entry into the supply chain.
Balancing this equation is an order of magnitude more complex than before. Because of this, our intelligence must be gathered in ever-greater detail and go beyond the grid’s traditional limits.
This is all founded on a core maxim: knowledge is power (management). But the point of this is not knowledge for knowledge’s sake. It is a means to an end.
Information is the difference between a decision and a guess. It’s why I use a satnav instead of a Magic 8-Ball. And it’s why we’ve been busily tooling up the grid to give us better oversight.
Many of the initial decisions will be centred around quick wins. And the truth is, the grid has always been a bit smart because we’re a bit smart and we’ve been managing it. The distinction is that now we’re making it able to be smart for itself.
The simplest example of this is identifying times of excess generation and scaling it down to avoid waste. It’s a time of low-cost, high-impact tactical changes. Efficiency is often the first stage of such a process.
As we exhaust the low-hanging fruit and review the changes they’ve brought about, we’re forced to reach further for the next set of benefits. To continue from our above example, if we know there are times demand dips, one solution is to decrease production. But what if we had more tools to work with?
This opens up another option; store the excess in batteries. These batteries get their own sensors to measure capacity. After all, they are now a part of our system. So, they get measured. We double up on the batteries and load balance them, for better resilience. This gives us yet more data to analyse.
Throughout this, we’re increasing complexity. We’re also measuring the greater information flow this complexity brings. The grid is getting smarter, we’re making better decisions, and new options are opening up all the time.
By now, our smart grid is more efficient, flexible, and resilient. It also provides us with more information than ever before.
Its edge has also become fuzzier. Buildings, vehicles and even individual devices are becoming microcosms of this process. They give us more data, which will enable us to further hone our decisions about managing supply & demand. Where possible, we use the output of this greater complexity against itself to rationalise and simplify.
The information we get is not just more abundant, but also more responsive. Each time we make a change, we can measure its impact before making another. The granularity of control has increased in line with the clarity of our information map. We can now work through a cycle of gathering intelligence, making changes, gathering intelligence about those changes, and so on.
But this is still, fundamentally, us being smart on the grid’s behalf. In our next piece, we shall look at changing that with the introduction of automation.