Status quo: The current approaches for data management in Europe
With smart metering, data on energy consumption and generation becomes available, even from small photovoltaic power plants and households. In addition, new infrastructure in the electricity networks (e.g. smart power transformers) can increase the transparency of the status quo of the networks. Besides the important discussions about privacy and security, there is a big discussion going on how we want to organize the data exchange between the smart meters, the network operators and market participants (e.g. virtual power plants, energy efficiency providers). We recommend to read this post for an overview of the current data management models in smart grids and the evaluation of these models here.
One very fundamental question in this context addresses the size (region covered or consumers connected) of the data management systems. Different concepts for data management are currently applied in Europe (a nice overview of the different data management models is provided by CEER). The Netherlands, Denmark, Belgium, Norway and others apply a centralized approach with one (regulated) entity being responsible for the data collection, verification and allocation from smart meters to eligible parties. In many cases, this regulated entity being responsible for data management is the transmission system operator (TSO) or a cooperation of different distribution grid operators (DSOs). The TSO concept is currently applied in Norway and Denmark, while Belgium (ATRIAS) and the Netherlands (EDSN) apply a centralized approach operated by different DSOs. The TSO is the network operator for the high voltage grids, while the DSO operates the low voltage grids that connect the households etc. to the transmission grids.
Why many European states assign the TSO or DSOs to develop a data management system
The discussion about the governance of data management in smart grids is quite complex, but we want to focus here on three key arguments that support the decision to delegate the responsibility for data management in smart grids to the TSO: First, the TSO already is a regulated and therefore controlled entity under the supervision of the state (i.e. the regulator), which makes it easier to supervise the operation of the data management (a sensitive issue for the government). Second, the TSO is responsible for the stability of the electricity grids, which is why the TSO requires (some of) the data from smart meters, connected generators and the network infrastructure. TSOs already have data management systems to perform their key task and can extend these systems to provide the data management for the whole energy system. Therefore, there is potential for synergies, which might result in lower costs for the development of data management systems. Third, a central approach based on the TSO has another key advantage: it is fast. The TSO already exists and has a data management system, which – of course – needs to be extended for the purpose of the whole data management, but which provides a structure to start with. To some extend, these arguments apply as well to those concepts where the DSOs cooperate to provide one data management system (like in the Netherlands or Belgium).
However, delegating the responsibility for data management to one entity also has some drawbacks. Let’s briefly discuss two of them: First, when one entity alone is responsible for data management, this results in a monopoly. But does data management qualify as a monopoly? We don’t think so (for a detailed analysis see this paper). Especially as data management does not qualify for a natural monopoly. Still, data management can become a monopoly granted by law (also known as institutional monopoly), as it is the case in many European states, like Denmark. While the solution based on an institutional monopoly might have several advantages, it is the least efficient solution from an economic perspective. We would rather expect that competition between different governance approaches and data management systems increases efficiency, reduces costs and helps to increase the level of service provided to the customers of the data management systems. Even though this is quite an optimistic view on competition, we would expect that a market-based solution (a market operating in a framework that is defined by the regulator or another public agent) is more likely to address customer needs than a monopoly.
Second, defining one single responsible party for data management might limit the scope of the management system. We do not know yet which services or applications might evolve in the near future and how the customer will react to or demand certain products. Therefore, we need the system to be open for many different innovations and developments. However, this “space for innovation” might be limited if a single party is operating a monopolistic data management system, as a monopoly does not need to convince the customer of its products, which reduces the pressure to innovate. Even if the monopoly wants to innovate, the regulatory design must support this. Likewise, regulation suffers from information asymmetry: it does not have all information about customer needs and potential products. This information asymmetry might limit the efficiency of a model that delegates the responsibility for data management to just one party.
Competition and decentralization to secure innovation
Alternatively, we can think of a system where competition defines the size of the data management systems, i.e. the level of decentralization. The idea here is that we allow different governance models for data management to compete with each other. Such approaches are known from different theories like fiscal federalism or polycentric governance. These different concepts share the idea that the state does not need to define a specific governance approach to secure the provision of a good. Rather, governance approaches can compete with each other and customers can choose which system they want to join.
The decentralized governance approach has two key features. First, it allows to develop different governance approaches for different regions. For example, in the case of Germany we know that due to the heterogeneous diffusion of renewable electricity supply (RES) and different network infrastructures that the need for flexibility provided by distributed generation and consumption will differ between regions (rural vs. cities, the north with large wind capacities vs. the south with large photovoltaic-capacities and the east with both). Driven by these technical differences the need for data exchange and management (e.g. to unlock flexibility) might differ between the different regions in Germany. Furthermore, regions might differ with respect to customer preferences etc. Therefore, it seems likely that the governance approaches for data management face heterogeneous preferences and demands. Or, to put it differently: A data management provider (a data hub if you like) faces very different needs in different regions in its target market. The question then is how to address these different needs.
Importantly, we need to differentiate between decentralization and competition, as they are not the same. Decentralization is often used to describe a governmental decision to delegate a task to a regional entity (e.g. a local jurisdiction or a local company). Competition, on the other hand, does not define the level of decentralization and the responsible entity, but allows the market actors do define the efficient size of a governance approach (at least in theory, we know that full competition is not that easy to secure). We have already stressed above that governmental decisions suffer from information asymmetry: the government does not know how to define the optimal level of decentralization as it has not enough information. Therefore, a decentralization approach based on governmental decision is not likely to result in an efficient system. Rather, we think that the government should define the basic market design for data management in smart grids (e.g. privacy policies, standards etc.) and then let the market parties that provide data management systems compete with each other.
In a system based on competition we would anticipate that the market providers develop different models and approaches to meet the customers needs. This in turn will result in a market with different governance approaches for data management. It is likely that different governance approaches will evolve for different regions but within one region as well. Some approaches will gain market shares, some will merge and thereby, over time, the market defines the level of decentralization for data management systems in smart grids. Obviously, perfect competition only exists in theory. Therefore, the public agencies, like the regulator, will have to supervise the market for data management systems and intervene when market failures occur (e.g. reduce market entry barriers, high market concentration etc.).
Still, we think that a competitive approach to define the level of decentralization for data management systems is exactly what is needed in the current development phase of smart grids: competition between different approaches to push new innovative solutions. This is why we argue in favour of a competitive governance approach for data management in smart grids. And, as a fall-back-strategy if you like, regulation can still act in case of market failure, e.g. if the market for data management in smart grids fails or leaves privacy and security issues unsolved.
What do you think? Do you prefer a regulated model? Or shall we allow competition between different data management models and different governance approaches?
This is just a short summary of our analysis described in greater detail in the following article.