Community Smart Grid - a prosumer perspective

Carbon Co-op will pilot a community smart grid in Manchester with between 100 and 200 householders, assisting them to work together to save energy, reduce bills and reduce carbon emissions through various measures centred around demand shifting - read more about the project here: http://carbon.coop/content/nobel-grid

The aim here is to look at what this might look like from an individual householder point of view and to explore the main parameters that will be necessary to measures the performance of the project.

Thus part 1 of this blog poses a number of questions related to the development of the project, eg:

  • What types of demand side responses are we looking at; saving carbon? saving money? providing grid operators with improved stability?
  • What parameters will the project need to measure in terms of power generation / availability, individual household consumption, aggregated consumption, the electricity spot price, the mix of renewables on the grid etc?
  • How can we tell whether the project is performing as we expected and what is it that we expected in the first place?

In order to review how this might work I have started by looking at our energy use at a household level. This is because it would appear that if we can make demand side responses work at a household level then it is also very likely that the aggregate approach for several houses can also be made to work (even better).
 

Benefits of a smart grid

It is perhaps important to emphasise that a (Community) Smart Grid has the potential to provide 3 broad and overlapping benefits:

  • Carbon savings – the primary focus of the review presented here.
  • Increased grid stability through the reduction in peak demand and a more predictable overall pattern of demand - a key benefit for the District Network Operator (DNO).
  • Cost savings or market value which can be “sold” to the grid operating companies and/or energy generators – the latter arises largely out of point number 2 listed above.

The following graphic has been prepared to demonstrate the economic value of battery storage; but many of the points listed in the graphic also apply to other demand side responses that might be implemented by the Community Smart Grid.

What this graphic doesn’t explain is how this might reduce carbon emissions nor exactly what would or could be measured / quantified in order to assess each of the 13 services that could be provided by demand side responses and/or battery storage.
 

Types of Demand Side Response to Investigate

Clearly there a number of ways in which the demand side response might work, including:

The Community Smart Grid might test several of these options and indeed options might be mixed together to provide (hopefully) an optimum balance between carbon saving and demonstrating a market value.

Each of these options would rely on different / various data streams; be they consumption, generation, CO2 intensity, grid voltage stability or spot prices etc. Clearly the project will need to investigate how best to gather and aggregate each of these data streams.

The electricity market in the UK means that electricity is bought and sold prior to coming down the wires to each of our households. Wikipedia describes the basic mechanism by which this market works as: The system price in the day-ahead market is, in principle, determined by matching offers from generators to bids from consumers at each node to develop a classic supply and demand equilibrium price, usually on an hourly interval (the spot price), and is calculated separately for sub-regions in which the system operator's load flow model indicates that constraints will bind transmission imports.
 

An over-view of our current household CO2 performance

I have been tracking our energy consumption for the last 15yrs and the overall result in terms of CO2 emissions looks like this:

The steep reduction in CO2 emissions that can be seen between 2014 and 2015 is as a result of our Carbon Coop Whole House Retrofit. Clearly gas use is a big (but falling) component in our overall household CO2 performance, nevertheless, the focus of the Smart Grid project is purely on the electricity side therefore it is useful to look at it like this:

NB the values plotted above have been calculated for the carbon intensity for each of the separate years as published in government / power industry sources. Thus the slight peak in CO2 emissions in 2012/13 was because the UK was consuming more coal powered electricity and not because we used more electricity.

The other observation is that the PV generated is plotted as a negative value which off-sets the electricity consumed and is plotted at the same rate of CO2 (saved) as the consumption.

The above analysis poses an important question for the smart grid project:

  • What is the correct value of carbon intensity for the electricity sourced by the members of the smart grid project?

This is question which I will return to several times in this document.

Further questions would be:

  • How do we account for the PV generated from the households (in terms of CO2 saved / off-set)?
  • Is use of PV on-site more carbon efficient than exporting the electricity?
  • How do we quantify the advantage (if any) of use on-site over exporting the PV electricity?
  • Clearly solar PV is generated during the daytime only and the amount of power available in the summer months is much greater than during the winter; what is the effect of this on carbon emissions?
  • The PV generated results in the demand for electricity being more fluctuating than without the PV; how can battery storage and other demand shifting measures be quantified in terms of environmental benefit?
     

Battery Storage for Optimisation of On-Site PV

Will it work – short answer ‘yes’ definitely (for saving money), but it is more complex to assess how much it will save in terms of carbon emissions. I will try to look at that later in the overall context of demand side measure with respect to carbon emission savings.

The following graph presents an analysis of our household energy use and PV generation (over our 12 month period) in terms of electricity imported, exported, used on site (the battery component thereof is a theoretical or calculated performance) etc:

Looking at this over a typical 24 hour period in March the (theoretical) balance looks like this:

Based on these 2 graphs it is clear that a battery system attached to a house with a PV array can improve the matching demand with the available supply of solar electricity across a whole year and that this is achieved largely by helping to carry electricity from the solar from the daytime period over into the evening / night-time. The theoretical benefit of the battery system modelled above would be to increase the annual proportion of our electricity which we get from the PV from ~32% currently (without a battery) to ~71% with the addition of a 5kWh battery.
 

OpenEnergyMonitor - A more detailed look at electricity consumption

As I stated above up to now I have been estimating our household CO2 emissions based on the carbon intensity of the gas and electricity we have used on an annual basis. However, the actual carbon intensity is something that varies all the time depending on the mix of power sources on the grid.

In order to work out the real time (instantaneous) carbon emissions from our electricity we need to measure:

  • Real time electricity usage and on-site electricity generation where applicable (from solar PV); and
  • The real time carbon intensity of the various power sources on the electricity grid

The OpenEnergyMonitor team (mainly Trystan Lea in this instance) are well on their way to being able to provide the necessary information using the EmonPi energy monitor and various tools on the EmonCMS dashboard.

Thus looking at the last 24hrs (15th December 2015) our electricity consumption and PV generation looked like this:

At the same time the output from the national grid looked like this:

Thus in simple terms it might be assumed that our carbon emissions could be calculated from:
[electricity consumption] x [carbon intensity measured at same time].

This is certainly one way of looking at the question, but when we start to look at what this might imply for demand side measures implicit in the Community Smart Grid project things start to get complicated, with questions such as coming the fore:

  • If we shift our electricity use away from the times when there is a lot of coal and gas fired electricity on the grid will that really reduce our CO2 emissions? Or
  • Will the gas / coal fuelled electricity just be moved from that time to the time of day when we choose to use the electricity? ie
  • Will there be any spare wind and other renewable sources available at other times of day for us to use when we want / need it?
  • Do 100% renewable tariffs have any bearing on these questions?

Thus, we already have a fairly long list of questions even before we get onto aggregating the electricity use of 100 of so households. These questions can in some ways be summed up as the difference between electricity supply and consumption and between the micro and macro scale.
 

Electricity from my Electricity Supplier

The UK electricity market includes a number of different suppliers, some of which offer products which claim various green or low carbon credentials.

In my particular case I opted for Cooperative Energy approximately 2yrs ago on the basis that they were offering 60% renewable energy and that theirs was one of the few dual fuel deals available at the time which had a “low carbon” option. Since then they seem to have changed their energy mix but now offer a “user chooser” feature whereby you can tailor the electricity they supply based on specific sources of electricity.

The options I have gone for are shown in this graphic:

Thus, it would appear that based on these options that Cooperative Energy are supplying me with electricity which is 81% renewable (averaged over 12 months).
As with all such energy supplier options it is important to note that the electricity that comes down the wires to your house is the same as everybody else’s electricity on your (local or regional?) electricity grid.

Green tariffs mean that the supplier agrees to purchase the kWh from renewable sources which is equivalent to the power you have purchase from them. They are not saying when they purchased them; ie they could purchase all of these kWh in the last 30 days or based on spot prices for electricity and as such the matching with your consumption cannot and is not likely to occur.

The best way to look at such contracts (in my opinion) is that they are a mechanism whereby consumers of energy can encourage more renewables to be installed onto the grid, but the exact amount that they manage to achieve in overall terms is difficult to quantify.
 

Conclusions to Part 1 – what have we learnt?

The main conclusions I would take from this initial review of the Community Smart Grid idea are:

  • It is a really good idea that has the potential to reduce the need for fossil fuel back-up of renewable energy on the grid.
  • The technology is becoming available to enable communities to take charge of the energy they use and how they use it.
  • Measuring the performance of a community smart grid is complex but is also an essential part of the smart grid itself.
  • Information will need to be made available to consumers, prosumers and other members of the community smart grid team in an appropriate and understandable manner.

In Part 2 (to be written in 2016) of the blog we will investigate the metrics and other tools that will be needed in implementing the community smart grid.

 

Comments

Jonathan's picture

Looking forward to part 2!

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