The perfect match of data and heat planning

The role of heating in
achieving a reduction target of 55% of greenhouse gas emissions by 2030 is increasing.
The recast Energy Efficiency Directive, as part of the legislative set
presented by the European Commission on 14 July, foresees the requirement of a
heat planning for cities over 50,000 inhabitants. It will be key for cities to
have an easy access to data to draft relevant heat plans.

Cities are often a
step ahead: some did not wait to take measures to harness heat data. Information
on available resources and heat demand in a defined area is a strong support to
the design of locally best-fitted solutions (individual heating systems,
district heating…). In the Netherlands, the open data approach has been
favoured for long. Energy utility companies must publish the effective
consumption data of small clusters of buildings, which proves very helpful for
cities to do urban planning at district level. In addition, oil and gas
companies are required to share data from their exploratory studies, which
gives cities access to data to estimate the geothermal energy potential of an
area. More recently, in Poland, an obligation for households to declare the
heating system they use entered into force on 1^st of January 2021.

Why
are data so important?

Data provide a better understanding of the reality and are a true support to make sustainable and cost-efficient decisions. For instance, the Metropolitan City of Milano wanted to investigate the possibilities to refurbish the building stock envelop and to promote renewable heating and cooling through district heating[1]. Politecnico di Milano, who carried out the research study on the topic, focused on the following dataset:

• Heat:
  Heat demand, heating sources (existing and potential)
• Residential
  sector: Residential sector heating demand density, density of residential
  building, residential building total energy demand
• Heating
  systems: Heat potential for district heating, potential district heating
  sources, best technologies for heating in areas of non-district heating suitability
• Environment:
  Environmental impact indicators.

The secret of good
projections

The data collection showed two main findings[2]:

• More energy efficient buildings will drive the network
  costs higher, reducing district heating potential. But it also showed that
  low-temperature district heating could compensate for the drop in its
  cost-effectiveness.
• Building renovation should be performed with criteria,
  and not evenly.

Collecting these
data helped Milan identify the most interesting areas, from
both a heat density and an economic point of view, and then investigate the
potential synergies with available heat sources. Of course, additional
parameters can help finetune the modelling, such as building ages, materials,
surface and height, or heating systems. The optimum solution to a good
projection often lies between direct collection and data modelling.

Data collection for
renewable heating and cooling uptake

 Data are thus an essential component of heat planning. In the United Kingdom, local governments can receive grants from the Heat Network Delivery Unit to perform feasibility studies and the related early stages of infrastructure development. This includes heat mapping, energy masterplans, techno-economic feasibility, and detailed project development[3]. All this information also contributes to reassuring investors, providing them with valuable information on viability of projects and long-term perspectives. As highlighted in a report by IRENA[4], one of the main barriers to renewable heating and cooling uptake is the inadequate data and statistics on types and amounts of energy required to meet heating and cooling needs. Collecting data is also a way to favour the penetration of renewable energies in heating systems. Given their long lifetime, they require long-term planning for urban development: the more accurate the data, the easier to plan the decarbonisation.
Human resources and training are key

So, what does it
mean concretely? Data collection is a crucial support for cities to plan
energy district networks and to do heat mapping and zoning. It helps develop
possible decarbonisation scenarios and discuss them with stakeholders and
citizens. However, it requires human resources and training for data and heat
planning to be the perfect match. All EU Member States should take inspiration
from the Netherlands, Poland, and the United-Kingdom to remove barriers to
access data for cites and to support them technically and financially.

[1] Deep Demonstration: Milan. Energy Workshop of 4th February 2021.

[2] Spirito, G.; Dénarié, A.; Fattori, F.; Motta, M.; Macchi, S.; Persson, U. Potential Diffusion of Renewables-Based DH Assessment through Clustering and Mapping: A Case Study in Milano. Energies 2021, 14, 2627.

[3] IRENA, IEA and REN21 (2020), ‘Renewable Energy Policies in a Time of Transition: Heating and Cooling’. IRENA, OECD/IEA and REN21

[4] IRENA, IEA and REN21 (2020), ‘Renewable Energy Policies in a Time of Transition: Heating and Cooling’. IRENA, OECD/IEA and REN21

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