GoO Trading in Previse Coral

Demand for Guarantees of Origin (GoOs) has grown substantially in recent years: from 37 TWh in 2006 to 621 TWh in 2019. The main driver behind this development is the corporate sector, where the evidence of climate-positive factors (such as the origin of electricity consumed) is increasingly expected from stakeholders.

Increasing market volumes and rising prices have fuelled interest from utilities, specialised traders and trading venues – and they have also led to highly differentiated product characteristics and process parameters.

GoO Trading companies face two main challenges:

• Capturing and managing all required and relevant data and information
• Sourcing prices for an adequate valuation of GoO positions

Due to the evolving nature of this market over recent years, these complexities have led to many companies currently lacking proper system support – GoO Trading is typically managed with a combination of spreadsheets, e-mail and manual tasks.

Also, as the GoO market is at this point still rather illiquid and also not transparent, sourcing reliable market prices for position valuations is a difficult task. Most available prices get published by brokers and are typically simplified representations based on a very small part of the traded market – e.g., they disregard characteristics like Eco Labels and other elements which affect valuation.

The proper capturing and processing of GoO trades requires many specific data points. Besides basic production information such as technology (Wind, Solar, Hydro …), country or region of origin and period, additional data such as the following may need to be captured:

• Logistic information (registries, registry accounts and agreed transfer period)
• Group of generation units or specific generation unit
• Subsidy regime
• Eco Labels

In addition to these attributes, further constraints and optionality may apply to certain GoOs or specific GoO transactions. Associated Eco Labels may mandate, for example, that the generation unit be commissioned no more than one year ago.

The unique data model of Previse Coral has been designed to manage all the specific optionalities, constraints and other complexities of GoO trades in a structured manner. Its high flexibility fully supports all currently known requirements arising from electricity marketing and consumer demands.

As a state-of-the-art software solution Previse Coral avoids typical spreadsheet risks by ensuring segregation of duties, standardized workflows and full auditability.

Trade capture and related document creation is intuitive and fast, with the common trade repository providing full transparency (and prompt trade matching) for both trade parties.

With up-to-date trade lists and GoO positions, Previse Coral has all the data necessary for efficient certificate transfers readily available. Settlement and invoicing run fully automated as part of the common trade repository.

The main purpose of any trading software lies in enabling the organisation to focus on value-adding tasks to drive profitability, and to avoid unnecessary costs and risks.

For an optimal positioning in this evolving market, it is essential to have the right IT infrastructure in place – enabling operational control and process automation as well as providing tools to understand trends and service-specific demand.

Previse Coral provides energy companies a decisive competitive edge. As modern energy trading software, both solutions are designed specifically to cover new market sectors such as renewables.

Key features include:

• Data completeness and transparency as well as immediate visibility and availability
• Operational risk reduction through efficient processes with a high degree of automation

Forecasted & Actual Production. In Previse Coral, GoO trades can be linked to the underlying electricity generation. Automated upload of forecasted and actual power production then updates also the related GoO positions, providing GoO full position transparency.

Market Prices. Standard APIs capture market prices from different sources via Ecosystem Apps. Such Apps enable an analysis of available prices – e.g., calculate averages between price sources or add premiums for specific Eco Labels to the forward prices. This leads to a more accurate view of the market value of a GoO portfolio.

Reporting. The valuation engine of Previse Coral utilises embedded Microsoft Power BI as the presentation layer for performant reporting with easy configurability. For position valuation, different price curves can be assigned based on generation technology for accurate Mark-to-Market and Profit/Loss calculations.

Cash Flow Forecasting. For every trade captured or amended, a settlement schedule based on the precise agreed payment terms is calculated, enabling a precise prediction of cash flows.

Transfer Automation. As the registries build APIs to allow electronic communication, Apps can be built to allow automatic integration to the different registries for a further reduction of manual labour and operational risks.

Optimization. In the flexible data model of Previse Coral, GoO constraints are broken down into logical data objects. Ecosystem Apps can utilise these for algorithms to optimize the allocation of available GoOs and maximise value creation.