Next practice – smart municipal data

The project investigates how Danish municipalities collect and apply energy data from their building portfolios and how these data are included in energy renovation projects and energy reduction activities.

The project provides an understanding of central challenges related to the collection and application of energy data and how these challenges can be solved. At the same time, the project identifies efficient processes and practices in order to inspire other municipalities.

The project shows that Danish municipalities, to some degree, already apply energy data to optimize daily operations and as input to energy renovation projects and space usage optimization.

The project demonstrates that investing in collection and application of energy data is an attractive investment. Especially when energy data is coordinated with activities related to energy renovation.

Further, the project displays that the Danish municipalities use a variety of different approaches and solutions, which can inspire other municipalities. Some solutions can be copied directly, given the right circumstances.

Having said this, the project also shows that there is room for improvement, and that many municipalities face challenges both in regards to the gathering and the application of energy data.

The technological development in the last 5 years has made it easier to collect and apply data but still, it is a task not to be underestimated.

It is necessary to allocate sufficient resources. Especially in the implementation phase, employee resources with the right technical skills and competences need to be deployed. At the same time, the organizational setup needs to be in place in order to secure the right use of data.

Outsourcing can in certain areas be a good idea, but it is important to acknowledge that outsourcing still calls for in-house resources and competences.

A strategic approach is necessary if you want to get started. You must consider which data is needed and how the data should be gathered, stored, processed, coordinated and how to make the available to people that should make use of them. It is an advantage to view gathering and application of energy data as one continuing process.

Next practices
In the project several shared improvement areas have been identified.

Data collection is the key process to manage. There are a lot of technologies and possibilities that one must relate to. The speed of technological development in this area is accelerating, so it can be very difficult to get a clear picture of the right way to go. At the same time, it’s an area with highly differentiated prizing.

Data platform / energy management system (EMS): The choice of data platform to store and process energy data is also of paramount importance. The speed of technological change is fast.

Resource allocation: In the interviews with the municipalities it has become evident that, generally, insufficient resources is being allocated to the collection and application of energy data. Due to the complex nature, it can be difficult to estimate how many resources are needed.

Outsourcing: Several specific tasks related to collection and application of energy data can be outsourced. How about all the practicalities? What should be included in the contract? Etc.

Preparation of tender and choice of provider: Several municipalities have experienced that it is a big one challenge to prepare tender for data collection, EMS system / data platform, energy labels, etc. Preparing a tender is almost a discipline. It is a task that requires both resources and the right internal skills. In addition, there are also several legal matters to be addressed.

Procurement: Several municipalities face challenges related to the procurement of data collection equipment and systems. The choice of equipment and service providers is very important task. A lot of different competences are needed to evaluate tenders.

Business cases and ROI calculations
There is considerable room for improvement related to how municipalities work with business cases and calculate return on investment. Typically a simple payback time method is being used. The net present value method is more suitable.

How to estimate optimal energy consumption levels?
The optimal energy consumption level for a given building can be very hard to estimate.Typically, municipalities compare energy consumption levels with historic consumptionlevels, but this is not always a good benchmark measure. A focused cooperation between municipalities can provide a much better practice.