Solution | BIPED

Positive Energy Districts (PEDs) are a key building block in the future energy paradigm for carbon-neutral cities and communities. With the rise of modern technology, PED development is set to evolve towards a more agile arrangement in which decisions are first tested and fine-tuned in virtual environments before they are deployed on the ground.

A key enabler of this virtual prototyping is the Local Digital Twin (LDT) technology. Traditionally, LDTs create digital representations of a functional territory by combining low- and high-velocity data with dynamic models of energy, traffic, buildings and natural environment.

However, focusing narrowly on these domains means that digital twins of PEDs will lack representation of other elements that make up the urban fabric. LDTs that omit social, economic and cultural properties will only provide a partial representation of an area they are design to model.

This shortcoming in LDT-PED modeling, which can be caused by limited data availability and siloed systems design, can lead to suboptimal decisions, impacting negatively ambitious efforts of sustainable development in cities and communities.

BIPED's ambition is to unlock a spectrum of data-driven decision making, covering both short-term city operations and long-term policy planning, to guide AI-supported optimisation of PED development.

How to boost PED's replication potential for the benefit of Cities Mission?

How can soft data support the advancement of digital twin development?

How can LDTs be extended to refine a district's profile representation?

objective 1

Extending LDT capabilities to better represent PED's multi-dimensional profile

Current LDT implementations lack sophistication necessary to characterise PEDs in all their complexity, as they typically address a limited number of urban systems, such as mobility, transport and energy consumption. BIPED will go beyond these domains to provide a deeper understanding of PEDs in general and Brabrand in particular. By integrating social, cultural and political properties of a city, BIPED will guide PED development toward a more holistic model that more accurately represents urban dynamics.

objective 2

Enriching PED development by integrating 'soft' datasets

Properties that define a district's profile can often be measured quantitatively due to their discrete nature, using air or traffic sensors, for example. However, properties that are less quantitatively tangible, such as people's perceptions or urban environment, are harder to capture but, once tapped, can show whether and where citizens feel happy or sad. This kind of emotional mapping has huge, though as yet unexplored, potential for urban planning. BIPED will pioneer the development of novel methodologies for gathering such “soft data” and its adequate representation in LDTs.

objective 3

Boosting PED's replication potential for the benefit of climate neutral cities

Although PEDs have common characteristics, they tend to be very specific to the local context. It is not easy to replicate the solution from one district to another, even in the same city, which limits the scalability potential. BIPED will use international standards, and in particular MIMs (Minimal Interoperability Mechanisms), to facilitate cross-district and cross-border integration of datasets, models and services. This will ensure that the necessary technical requirements are met to develop replication strategies on a country level as well as more widely across the Cities Mission.

Knowledge baselining and co-creation

1.1 Emissions baseline and KPIs

Aarhus has pledged to reach net-zero GHG emissions by 2030, meaning that the balance between direct reduction and offsetting of residual emissions is zero. This goal of net-zero GHG emissions by 2030 is in line with the definition of climate neutrality applied by the Cities Mission. Currently, the city emits 400,000 tonnes of carbon. 200,000 tonnes will be eliminated using natural carbon sinks and carbon capture on large industrial plants. The remaining 200,000 tonnes will be targeted by the creation of digital twin of PED which will stimulate pathways to change in key areas such as

Mobility and transportation: Reduce 11-20% of emissions by switching to greener transport options
Energy generation: Deliver 100% renewable energy in all sectors
Consumption: Extend CO2 tax creating further incentives for the city's buyers to make sustainable choices

The cities Climate Plan will help inform the baselining of target KPIs for the duration of the project and beyond: 2030, 2050.

1.2 PED framework design and co-creation

This step involves co-creating a robust methodological framework to determine which technologies, know-how and resources are needed for an optimal PED design. Relevant economic, social, technical, legal and ethical aspects will be considered. Data collection will happen in a series of co-design workshops where participants will work together on user requirements for a planned digital twin solution.

PED design and validation

2.1 Critical data assessment

The goal is establish a robust framework for integrating high- and low-velocity data, including 'soft' data, in a digital twin environment, based on the current state of the art and international best practices. To this end, the assessment will be guided by an extensive expertise within the consortium on matters related to energy transition and data-driven innovation. Aarhus is a mentor city in the 100 Intelligent Cities Challenge. Together with DTU and Center Denmark, the trio is leading the establishment of data spaces across Denmark, in cooperation with public authorities and the private sector. On a European level, DTU, OASC and AIT are key players in the establishment of a European Energy Data Space through OMEGA-X, a GAIA-X lighthouse, and in the Green Deal Data Space GREAT.

2.2 Agile development
The approach follows agile software development methods to build a digital twin of PED in Brabrand. This will involve multiple frequent deliveries of software updates to develop a sound solution that meets user requirements and project objectives. Four platform development platform and integration cycles with accompanying deliverables are scheduled over a three-year period.

2.3 Implementation and validation
The monitoring will analyse digital twin’s impact on PED development, focusing in particular on how local communities have been affected and what the different socioeconomic impacts might be in the future. Based on that, a roadmap for green transition will be developed using the PESTLE framework to account for political, economic, social, technical, legal and environmental factors that have a bearing on climate-neutrality objectives.

Sustainability and growth

3.1 Knowledge transfer and replicability

The ultimate purpose is to share BIPED's experience of deploying PED in Aarhus so that other cities can fast-track climate neutrality, one district at a time. The process will be documented in a handbook where all the knowledge and building blocks will be presented to facilitate transferability and replicability of the BIPED solution. Open-source tools, MIMs and standardisation will be the main components of scalability.

Objectives

The BIPED project demonstrates how to overcome these barriers in a simple yet highly efficient manner that works everywhere by answering three key questions to push PEDs to the next level: wide deployment.

Research design

BIPED follows a three-stage methodology to design its scalable and multi-functional solution for positive energy districts.

Technology

BIPED will build a world-class LDT for the district of Brabrand in Aarhus. Based on the ambitious EU roadmap for Federated LDTs (Digital Europe Programme), MIMS developed in the context of Living-in.EU (MIMs Plus) and the global y.MIM format, the first iteration of BIPED's solution will be created, comprising a detailed semantic 3D model of the physical environment, along with additional geospatial data and soft datasets.

The geometrical and visual representation of the digital twin will feature a terrain model, orthophotos, 3D vegetation models, street furniture models, and building models as specified by the OGC CityGML standard with at least Level of Detail (LOD) 2 geometrical and semantical differentiation. Higher LODs with additional information of facade and roof structures will be created as needed.

Open standards such as CityGML, GeoJSON, GML, GlTF, and open interfaces such as OGC WMS, WFS, WCS, OGC API Features will be incorporated to a) enable live data exchange with existing spatial data infrastructures and b) ensure portability with IT infrastructures of other European cities.

Subsequent iterations will link spatial data with domain specific data and tie in live information from sensors. Depending on local needs and modelling requirements, further integration with traffic networks, IoT sensors, mobility and energy systems may be undertaken to provide an optimal solution for decision making.

On the data management layer, multiple technologies will be implemented to support data storage, processing, filtering and analysis, with each module ensuring the highest level of interconnectivity.