# Autonomous Cyber-Physical Systems Enabling Smart Positive Energy Districts
## 3 Emerging Technologies Enabling Positive Energy Districts
### Digital Twins
DTs enable the optimization and automation of energy management in PEDs, reaching the goals of ZEB requirements. DT ecosystems are associated with three main entities, namely (i) a physical object, (ii) its virtual duplication, and (iii) the connection of the physical object and its virtual duplication. Such DTs reduce lifecycle management for storing, managing, and processing big data regarding the urban environment. Digital PED twins can also be classified into three distinct levels, namely (i) an improved version of the BIM model, (ii) platforms of semantic data flows, and (iii) analysis and feedback of big data [20]. Practical application cases for DTs in PEDs include the following:  
1. _Energy Flow Optimization:_ Simulation and optimization of the energy flows within a district with a DT, through modeling of energy generation, energy consumption, and energy storage. 2. _Demand Response and Load Shifting:_ DT forecasts energy demand and supply and thus enables dynamic demand response programs to reduce peak loads, avoid fossil fuel-based grid reliance, and improve grid stability. 3. _Renewable Energy Integration:_ DT evaluates where and how to deploy renewable energy most effectively, considering local climate and urban structure; hence, optimal operation of distributed energy resources is obtained for maximum energy production and minimum losses. 4. _Integration with Smart Grids and Utilization:_ DT acts as a virtual control center that balances energy inflows/outflows and interacts with utility signals for bi-directional energy trading and integration into larger energy networks. 5. _Battery and Thermal Storage Management:_ DT predicts energy needs and storage behavior to schedule charging/discharging. 6. _Carbon Emissions Tracking and Mitigation:_ DT quantifies carbon footprint from building operations, transport, and energy use by supporting strategies to meet EU, national, and local-level carbon neutrality targets. Figure 1: Key components in a digital PED twin [20]. * _Urban Planning and Retrofitting:_ DT simulates the effects of insulation, window upgrades, passive solar design, and HVAC improvements for providing cost-effective design choices. * _Citizen Engagement and Behavior Modeling:_ DT models human behavior, such as thermostat settings, and provides feedback via apps or dashboards to promote energy-saving behaviors and increases public engagement in sustainability goals. * _Predictive Maintenance of Infrastructure:_ DT detects anomalies in system performance and predicts maintenance needs for preventing downtime, increasing energy efficiency, and reducing operational. The DigiTwins4 PEDs project (2023-2026) is a PED which focuses on living labs in Stuttgart (Germany), Vienna (Austria), Rotterdam (the Netherlands), and Wroclaw (Poland) and integrates urban digital twins into processes of public participation. The project aims to apply the urban DT framework to simulate, model, and visualize the PED and to empower the local community to engage in PED co-creation together with city representatives. The living labs operate as mediators among stakeholders for the evaluation of the potential of using urban digital twins as a collaborative tool for PED co-creation [39]. Similarly, the DT4 PEDs project utilizes digital twins in new construction and retrofitting across Austria, Sweden, and Turkey. It uses living labs for energy information flows, stakeholder dialogue, and quality assurance throughout the PED development process [40]. A digital twin combined with the IoT and AI was used in Rome for simulation of and optimization of energy interventions in a PED with 16 buildings, including 216 apartments. The results showed improvements in renewable energy integration and progress toward near-zero energy building standards [25].