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11 Jan 2022
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FEA Wins Zeigo EcoHack 2020 Hackathon

Power Purchase Agreements (PPAs) are a key financial instrument for opening up access to renewable electricity for large commercial users - providing certainty for both the consumer and supplier on prices and volumes up to decades in advance. Additionally, PPAs provide hedging for customers with critical processes, such as heavy industry, as well as lock in demand for new renewable power projects at the inception stage.

However, at their core they are highly complex legal agreements that can run into the hundreds of pages and cost hundreds of thousands of pounds in fees to officiate. This makes them attractive only when millions of pounds of energy will change hands, effectively locking out smaller consumers and suppliers from access to renewable power. As the cost of electricity from wind and solar plants tumbles, PPAs are becoming more and more popular for commercial customers that do not necessarily trust the day-ahead market to get the best deals. A critical obstacle to empowering these smaller consumers in transitioning to a fully renewable supply of electricity via a PPA is reaching the volumes of demand needed to make the legal costs viable.

A variety of instruments have been created to try and address this problem, the most promising of which is the aggregated PPA. In this arrangement, a group of smaller consumers band together and agree on a fixed price and set of terms, presenting them to a supplier as if they were a single PPA. Together, their combined demand volume is equivalent to a single large customer. Whilst this is a logical and financially sound approach to overcoming the previous concerns, it opens up a Pandora’s box of fresh challenges - namely, how do we construct an aggregate PPA such that the risk profiles, risk tolerances, legal budgets, and a host of other company preferences can be combined and measured in such a way that the deal is still attractive to the supplier? Smaller consumers also require flexibility, and may not be able to commit to 5-year contracts, let alone 20-year contracts - how can the price and default risk of individual sites be fairly distributed among all parties in an aggregated PPA?

This is the goal of Zeigo, a London-based startup aiming to democratise access to clean energy for corporates committed to decarbonisation. Through data-driven recommendation systems and novel characterisation methods, Zeigo have developed a platform that matches consumers and suppliers at either end of the PPA syndication process - providing transparency and a level playing field for smaller consumers to band together into aggregate groups. To engage the energy data community and help generate novel ideas to tackle these challenges, Zeigo launched the EcoHack 2020 hackathon on the 9th of October 2020, held virtually across the day with four teams from a wide range of backgrounds. Our mission was broad - to devise solutions to break down the barriers between smaller consumers and PPAs.

Fig 1. Site-Level PPAs by Term Length and Credit Default Risk

In our winning solution we developed a brand new method for dynamically pricing power for each constituent member of an aggregated PPA, based on its credit default risk, requested annual demand, and length of contract. The price for existing members of the PPA will never change once they’re in, but dynamically pricing new entrants in this way ensures that the additional risk borne by the aggregate PPA as a whole is marginally allocated to the incoming party. This also ensures that the price and default risk seen by the supplier does not change - this is handled by calculating a dynamic exit cost for each buyer to leave the pool that is a function of the equivalent day-ahead price they would have paid had they satisfied their demand from the market.

Fig 2. 1000 Monte Carlo Default Simulations Using Zeigo's PPA Data

For the sample of PPAs provided to us by Zeigo, we created a Monte Carlo simulation of default rates for each of the sites, based on their demand volume and credit rating. From this, we took a number of quantiles and tested which would give the best indicator of individual site default risk. These were then allocated to each site proportional to their demand volume, and used to derive their dynamic and personalised price.

Furthermore, in addition to the default risk we estimated the balancing costs associated with each PPA pool, using production data from existing UK wind farms and example consumption profiles for each demand site. Doing so allowed us to quantify the volume matching cost for each consumer, enabling tailored PPA prices that internalise these externalities. The final prices reflected the capture price that the supplier could have achieved in the wholesale market, the default risk of the buyer, the volume matching cost of the buyer, and an uplift to account for additional risks and Zeigo platform costs. An example pool of resulting prices is illustrated below.

Fig 3. Dynamic Prices Allocated to Each Site, Derived From Default Risk, Balancing Exposure, Horizon, and Demand Volume.

Additionally, we presented a prototype concept for a secondary market that would allow third-party financial institutions to purchase swaps that would effectively exchange one consumer’s PPA arrangements for another’s in a different aggregate PPA, taking a cut of the difference in price between them. This not only introduces liquidity to an otherwise highly illiquid marketplace, but also gives consumers the flexibility to ‘move’ from one PPA to another without bearing any legal costs.

We will be presenting these ideas alongside Zeigo in the near future to the RE100, the largest group of UK companies committed to decarbonisation, and hope to generate some interest in a very exciting but underserved area of renewable energy innovation.

Connor Galbraith
Ayrton Bourn
FEA Non-Executive Director
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