In our previous blog post, we delved into the Market Wide Half Hourly Settlement (MHHS) and its impending impact on the energy industry. Today, we're peeling back another layer to unveil how this transformative project, combined with Gorilla's expertise, will revolutionize the way energy retailers operate and interact with their domestic customers.

The Current State of Domestic Energy Pricing and Forecasting

Currently, when a domestic customer seeks a new electricity and gas price, they typically visit comparison sites or individual energy supplier websites. They input their address and annual energy consumption data, receiving standardized rates that align with their region and meter type. While electric vehicle (EV) owners may encounter slight variations, the pricing landscape remains largely uniform.

Similarly, when energy suppliers forecast their domestic customers' energy usage, the focus is on the annual aggregate consumption, irrespective of when or how it occurs throughout the year. This practice stems from the lack of granular data on how and when households use electricity. This approach not only curtails the potential for energy innovation but also slows down crucial decarbonization efforts in the energy sector.

Unlocking a Paradigm Shift with MHHS

MHHS is set to bring about a paradigm shift. With Gorilla's support, energy suppliers will transition from region-based pricing to customer-centric segmentation based on consumer types. This evolution allows for the introduction of smart and dynamic time-of-use tariffs, offering more customers the opportunity to benefit from greener and cost-effective energy consumption patterns.

The Pricing Revolution

17,520 – If this number doesn't ring a bell, it's likely you haven't explored the details of pricing for B2B Bespoke sites in the GB market. It represents the quantity of Half Hours in a year. In the future, this multitude of data points will be used for the pricing of domestic customers, a stark contrast to the current reliance on a single EAC (Estimated Annual Consumption) value and generic profiles. This will require energy retailers to dramatically improve their data-processing capabilities. By using a platform like Gorilla, you are able to process millions of data points in minutes, rather than days.

42 -  This represents the number of different tariffs typically found on a supplier's website today, encompassing 14 regions, each with variations for P1, P2, and Gas. Now, consider the rapidly evolving landscape of new technologies like Electric Vehicles (EVs), Heat Pumps, Batteries, and Solar Panels. These innovations have a profound impact on customer's energy consumption patterns. Maybe there should be 98 different tariffs on every website, or perhaps even more? The challenge lies in efficiently calculating and presenting these numerous options, all while ensuring accessibility and user-friendliness. At Gorilla, we understand that data is the key to unlocking this complexity and providing tailored energy solutions.

0 - Is the number of times my energy supplier has suggested that I can reduce costs and contribute to a greener environment by switching to a more suitable tariff. We're determined to transform this status quo. By empowering energy suppliers to swiftly assess a domestic meter's consumption patterns and automatically recommend a tariff from the appropriate cluster, Gorilla ensures that customers have access to not only cost-effective but also eco-friendly energy options.

Forecasting Challenges

Forecasting the energy usage of half-hourly meters is a monumental task. For every 50,000 customers, a supplier will receive a staggering 876 million annual data points. This influx demands a major shift in how suppliers handle data, including clustering. The beauty of MHHS is that it puts the power of clustering in the hands of suppliers, without using outdated profiles.

Look at National Grid's Demand Flexibility Trial in 2022/23, which involved 1.6 million meters. To replicate this engagement at the supplier level, meters must be clustered based on consumption patterns to improve forecasting and enable peak-time consumption shifts. This can help in reducing imbalance or overall demand in periods of high price and low renewable energy generation.

Once MHHS implementation is underway, recalibration and re-clustering will be necessary. But how much work would this take and how often will you be able to execute this? Gorilla simplifies this process, allowing energy retailers to complete it regularly and focus on the more complex forecasting of their portfolio.

Moreover, Gorilla's technology analyzes the total forecast alongside available tariff structures, suggesting tariffs to balance the portfolio—taking portfolio management to the next level with minimal manual intervention. In that way, the forecasting team can inform the trading or pricing team to collaborate on reducing imbalance.

Conclusion

Energy retailers are on the cusp of a new era. Granular data will replace regional averages, enabling customer-centricity and paving the way for innovative pricing and forecasting models. With Gorilla by your side, you can embrace this transformation, unlock the power of data, and thrive in the evolving energy landscape. Your customers and the environment will thank you.

Book your 30-minute conversation with a Gorilla Data Ranger and discover how Gorilla can help you.

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