In the last decade, feed-in-tariffs (FiTs) have emerged as a mechanism that enable prosumers to export excess power,  produced from distributed energy resources (DERs), back to the electricity grid in return for incentives. One consequence of this has been that the traditional top-to-bottom power flow approach became, to some extent, a bottom-to-top one, resulting in reverse power flow in the electricity network.

There was a simple way to deal with this. A limit was imposed for the maximum amount of electricity that could be fed onto the grid. For instance, in Queensland since June 2011, this limit has been 5 kW per solar photovoltaic (PV) system, per premise, which seems to have worked temporarily.

But the FIT has not pleased everyone. While the rate was initially higher, at 40-50 c/kWh, the policy was highly successful in creating a good solar PV base. When the FIT rate dropped to around 3 c/kWh, as happened  in Western Australia, the contentment amongst solar PV owners plummeted.

In an effort to improve contentment as well as solar PV uptake, a new excess power sharing model has been suggested, a local energy market (LEM). This marketplace uses peer-to-peer (P2P) energy trading between prosumers and consumers to sell and buy energy by executing bilateral transactions – supported by blockchain technology, artificial intelligence and machine learning algorithms. LEM’s aid the creation of lucrative decentralised markets. 

As LEMs can be set up without any consideration to the current state of the electricity grid, it is possible for the market to encourage behaviour that the grid cannot sustain. For example Peter, who owns a 10 kW solar PV system and 14 kWh battery system, could decide to sell a large amount of electricity to Adam in the P2P market. Several other prosumers in the electricity network could do the same as Peter to make substantial profits out of the LEM. However, multiple P2P transactions could trigger excessive local penetration, resulting in the electricity system burning out. Which would cost the distribution utility tens of thousands of dollars to repair, leading to an unsuccessful approach. Therefore, the LEM operation – without considering the impacts it has on the electricity  network – can cause maloperation of electricity grid assets, such as voltage limit violations, overheating, congestion complexity and so on (see Figure 1), creating more problems than it solves.

There are three possible solutions to this. Firstly, the distribution utility can use a curtailment or turn off approach to impose its constraints on every transaction made in the LEM network. So, if Peter tries to sell 7.3 kW, and it is not safe for the electricity grid, this approach prevents the electrical transaction from occurring. As 7.3 kW of electricity was not delivered, the financial transaction would have to be adjusted accordingly on the blockchain platform. 

The second approach is more sophisticated and operates at the software level where a fixed limit is set on the amount of kW which is allowed to be traded. As Peter pushes the button for the sale of 7.3 kW, the software ‘greys out’ the button until the grid-friendly amount (of say 5 kW) is selected. 

Of course, the grid-friendly amount, rather than being a fixed limit, could be a time and place dependent quantity. Thus, the third approach is slightly different and dynamic to the second. This approach sets the limit dynamically – every fifteen minutes for instance –  to guarantee maximum local penetration of solar PV via P2P. This is called dynamic hosting capacity, or dynamic operating envelope (DOE). This method allows Peter to inject more or less than 5 kW at any one time depending on the electricity network conditions. Due to this method's  temporal flexibility, it is now the favoured way for many distribution utilities around the world.

The fixed limit consideration could be suitable when existing prosumers of an electricity grid take part in P2P trading. This is due to the fact that the authorised distribution utility has already analysed the electricity network conditions, before approving them to install solar PVs and batteries. However, a DOE-facilitated LEM is expected to become the system of choice in the long term. This is because a prosumer like Peter can earn an increased amount of financial gain through maximum local penetration, of more than 5 kW at different times, via P2P trading. The electricity grid sustainability can also be maintained by verifying the network constraints frequently. Further, a traditional consumer, like Adam, can be permitted to install a solar PV and battery of his choice. Rather than buying energy from Peter, Adam can become a prosumer himself, as the electrical grid is able to automatically optimise with the addition of solar PV energy. 

Whichever option we choose, approaches like these are bringing home the reality that the LEM is with us, and will transform our grids as we speak. 

To learn more about how fixed or dynamic network limits can be applied, in the context of a LEM, please reach out to Powerledger here.

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Dr Imran Azim is working as a Product Specialist at Powerledger