The energy transition — a hip buzzword or a real life development revolutionizing the way we generate, transport, sell, buy, and consume energy? Probably a bit of both. But, undeniably, we are already experiencing changes and developments in the energy environment and in all probabilities, this is only the beginning. For Capgemini Consulting, topics like sustainable and decentralized generation, flexibility in use and pricing of energy and transparency of information around energy generation, transport and use are becoming more and more common in assignments at Utility clients.

Dynamic Pricing is believed to be one of the drivers of this transition because it gives energy consumers the ability to control and steer energy consumption based on a real time energy price, connected to real time energy usage. This change in energy consumption behavior is expected to be driven by cost, although, due to low volatility in energy prices, the projected savings are limited. So, the question is whether consumers can be motivated to become active energy users when the cost advantage is low, combined with the fact that energy always has been a habitual and noninterest product.

What we should also take into account, in this development, is the societal perspective. With increasing levels of renewable energy generation and electric vehicle usage, electricity grids experience more short-interval load changes. Without proper response from related parties, this could lead to a higher risk on outages. If consumers start reacting on changing prices, dynamic pricing can become part of the flexibility arsenal of grid operators to balance the load on the grid. When grid operators are capable and willing to put a price tag on this source of flexibility, it would make the case for dynamic pricing more compelling.

Dynamic Pricing is the pricing scheme model for calculating energy costs based on real time prices from hourly APX intraday quotes and real time usage measured via smart meters.

So, different players in the energy market are looking into this. Grid operators are looking for demand side flexibility to better control the balance of the grid and retailers are searching for the Holy Grail to change the model of delivery from being commodity based to services based. The instrument of Dynamic Pricing will play a central role on both the sides. This broad relevancy was the reason for the Energy & Utility team of Capgemini Netherlands to compose a research topic, in cooperation with Erasmus University Rotterdam, on Dynamic Pricing models. Erasmus has assigned this topic to Navid Sadat-Razavi, a graduation student while the Energy & Utility team of Capgemini Consulting, Netherlands has hosted and guided this assignment. Our goal is to deepen our knowledge in this field and use it to assist our clients during the challenges of energy transition.

The main aim of our research was to examine customer patterns of residential households in a dynamic price setting. With the development of new technologies such as smart meters, utility providers have the opportunity to inherently change the way they are communicating with their customers.

One way in which the utility providers aim to improve the interaction with their customers is by introducing dynamically changing electricity prices, based on real electricity market prices. Given that different people can have a diverse set of values and preferences, it is assumed that their reaction to changing electricity prices will be quite diverse. Therefore, we want to evaluate how household characteristics and dynamic electricity prices influence household electricity consumption in dynamic price settings. We believe that clarifying the relationship of these two components with electricity consumption behavior can deliver valuable insights for future energy services.

We have constructed the following research questions:

  1. How do dynamic prices influence a household’s capability to change electricity usage behavior?
  2. How do household-level attributes influence a household’s use of electrical energy throughout the day?

Who will properly react to the introduction of changing electricity prices and during what time? Which parameters will be influenced by this potential change in behavior?

The research is based on a real Dynamic Pricing proposition and data from a proof of concept started by the Dutch sustainable and innovative energy supplier, Qurrent in cooperation with Vereniging Eigen Huis (home owners association). From the beginning of this year, 300 customers from Qurrent have enrolled in this experiment. The real pricing, usage, and attribute data from this experiment is being used in this research. For this, the contribution of the customers is greatly acknowledged.

  1. How do dynamic prices influence a household’s capability to change electricity usage behavior?

Our research proves that dynamic pricing leads to a shift of energy consumption by changing behavioral patterns as a response to dynamic electricity prices. This shift in energy consumption is the strongest between 8am and 5pm. This took us by surprise because we expected an insignificant relationship between the usage behavior during the day and electricity prices due to the absence of individuals in many households. However, our results were opposite. The participating households were especially capable of changing their electricity usage behavior during this time. One possible explanation is that individuals staying at home during the day, might feel a higher sense of control over their electricity usage and the overall impact of their behavior, and have, therefore, properly reacted to price signals during this time.

We have observed that households have changed their behavioral patterns in response to dynamic prices. It is possible to claim that the increased level of communicated information in the form of hourly prices, that reflect real-world electricity market situations, has enabled the households to do so. Perhaps, the additional information has increased energy usage awareness and a sense of higher individual impact.

As a result, future energy services should provide a more fine-grained information about energy use, ideally on an individual level rather than a household level, in order to unlock higher customer responsiveness. This applies to the general provision of information, as well as dynamic electricity prices (e.g. personalized prices). A possible consequence would be that customers will change their patterns also during other times of the day, i.e. after 5pm. Additionally, dynamic price variations could be increased for households to deem electricity prices as relevant.

Essentially, all of these recommendations for energy services are addressing the need for utility providers to communicate a more comprehensive and complete picture of the energy sector and energy usage to residential households. This would encourage households to move towards a more rational decision making process. However, if all residential households receive dynamic electricity prices and everyone starts to change its consumption behavior based on these prices, the price variations on the APX electricity market will become flatter, as demand during low-price times will increase and demand during high-price times will decrease. Consequently, this would reverse the effect of dynamic electricity prices based on electricity market prices at least during the time of 8am to 5pm, and households are likely to go back to previous habitual patterns. Therefore, future energy services should also focus on nonmonetary incentives and an increased level of information provided to households. Additionally, future Demand Response Programs should explore the options to use personalized or artificially varying electricity prices to engage their customers in a dialogue.

  1. How do household-level attributes influence a household’s use of electrical energy throughout the day?

In our research, we found proof that the effect of household attributes on electricity usage is less positive in a group exposed to dynamic price settings than in the control group exposed to traditional price settings.  More specifically, the variables building age and building size have a weaker positive relationship with usage of electricity in the dynamic price setting than in the traditional price setting. This supports our argument that a more fine-grained delivery of electricity information decreases the strength of the relationship between household attributes and electricity usage, as we can regard the dynamic electricity price as an enhanced way of communicating the electricity market situation to residential households.

Based on these findings, we can also support the assumption that the investigated household attributes reflect lifestyle patterns of households. With the relationship of the household attributes on usage of electricity decreasing, it is possible that these lifestyle patterns have changed or have become less relevant predictors of electricity usage. This would mean that the households of our group exposed to dynamic price setting have started to engage in more rational electricity usage behavior, based on prices, rather than habits. Our findings have shown that the price sensitivity of households exposed to technology-enabled dynamic price settings is higher as compared to household exposed to the traditional price settings, which applies to most households today.

In addition, we have found that the significance of these household attributes varies during different hours of the day. Hence, future efforts to determine household price sensitivity should focus on evaluating price sensitivity on an hourly basis, based on different set of variables.

So, is Dynamic Pricing one of the golden keys?

We are convinced it is; households who participated in our research showed a significant shift in energy usage over time and became more price sensitive and less habitual consumers of energy. But will it be enough to drive the energy transition? No, it can be one of the keys, but the energy transition will need a set of keys which work over different market participants in an interconnected way. This will lead to solutions which will affect systems, processes, and people of all who are involved in the energy & utility market. Being ready for this will be the biggest challenge ever faced by the energy market. And, this challenge will lead to survivors, winners as well as losers. On which side of the equation you end up, will depend on your ability and willingness to act now and steer your business towards a digital and sustainable future.