Markets and Business for DC4Cities

In order to unfold an impact on the share of renewable energy used in data centres („RenPercent“), the technical solution of DC4Cities needs to be distributed and applied in real-world data centres. To this end, at the same time the European market was analyzed with respect to good starting conditions and new business models were created.

The Markets

A specific DC4Cities market is positioned in areas where a conglomeration of suitable data centres meet favourable conditions like ambitious smart cities in a climate that offers an abundance of solar or wind energy.

The map shows where these three conditions meet:

  • Striving data centre markets are represented by screens
  • Highly developed and promising smart cities are represented by stars and
  • An abundance of solar or wind energy by suns and clouds respectively.


However, the map does not identify a clear pole position to market DC4Cities. Therefore in a second iteration, 6 cities in Europe were closely scrutinized to answer the question, if any of them is a good candidate as reference market for DC4Cities. Apart from Barcelona, as a partner in the DC4Cities consortium these were the „Big 5“ in data centre industry because, except for Madrid, they are also among the most advanced smart cities in Europe: Amsterdam, Frankfurt, Paris, London, and Madrid.

Amsterdam: most promising starting point with a diverse data centre market, good weather conditions and an ambitious smart city concept that drives investment into renewable energy infrastructure

Frankfurt: about equal conditions for marketing DC4Cities; a well developed smart city with the goals to become 100% dependable on renewable energy sources by 2050 and a very high share of data centre energy consumption at the total city energy consumption. The only drawback is the focus on colocation data centres, to which DC4Citis, as of now (end of 2015) DC4Cities does not offer specific business models.

Barcelona: also a good local market to explore DC4Cities market penetration; very advanced smart city; however the goals to increase the share or renewables are not quite as high as in Frankfurt and Amsterdam; there are also less data centers in Barcelona.

London, Paris, and Madrid: Marketing DC4Cities in these cities will be less successful: in Paris and London, infrastructure of intermittent renewables is less developed so that the share of renewables cannot be increased substantially; and in Madrid the economic crisis has diminished the local data centre industry in great parts, so that there will not be enough DC4Cities customers in near future.


  • Highly developed data centre industry
  • High share of data centre industry at local power demand
  • Ambitious goals of the smart city to increase the share of renewables or reduce CO2 consumption
  • High level of infrastructure of local intermittent renewable energy sources (solar, wind)
  • Favourable national or supranational legislation/taxation e.g. EU ETS CO2 certificates
  • Good climate and weather conditions to exploit renewable energy infrastructure


  • Tight SLAs with data centre customers that do not allow for a lot of scope to shift workload
  • High level of interactive workload in data centres vs. batch oriented workload
  • Business model that does not grant the data centre much control over the workload, e.g. colocation
  • Cultural factors in data centres or city administrations cementing current business flows and ways of doing things
  • Lack of financial incentives to increase the utilization of sun and wind based electricity

Business for DC4Cities

The impact of DC4Cities depends on its penetration in real markets. One of the project tasks is related to the identification of business models that offer the highest potential for DC4Cities to be economically viable for all involved parties.

In order to define these business models, the DC4Cities partners used an iterative approach that started from the definition of the key market drivers and dimension (WP2 of the project) and from the description of the environments in which trials are performed (WP6).

The first step of this methodology consisted in the provision of a common ground for the participants, for which an overview of the intermediate market analysis results and scenarios was given. The second step was the introduction of the Business Model Generation methodology, the Value Proposition (VP) and Business Model Canvas (BMC). Right after we went through a workshop that consisted of several brainstorming sessions in which a number of value proposition and business model ideas were elaborated. After the workshop the valid canvases and their components were analysed in detail in order to be polished and to elaborate more structured reports. The final step in the consolidation of the business model canvases was to evaluate if they are viable.

In DC4Cities we identified 15 different value propositions. Based on them, 8 business models were created and poured into 8 different business model “packages”. The most relevant one is the Capacity Planner, which describes the core functionality of DC4Cities, and it is the basis for the other models that actually represent different ways of presenting the core offer. As example, the business model canvas for the Capacity Planner is shown below:

Capacity planner canvas