Methodology

Lead Organization: Technische Universität Graz (TUG)

Objectives: The primary focus of WP1 is on the optimization of both power and mobility systems within Positive Energy Districts (PEDs), taking into account electric vehicles (EVs) and their interaction with the power system. This includes assessing the impact of EVs on the power system through power flow analysis and, conversely, evaluating how the placement and availability of charging stations affect EVs.

Description of Work:

Task 1.1: Development of the Power System Optimization Model (M1-M14):

• Lead: TUG, with contributions from the University of Edinburgh (UE) and University of Deusto (UD).
• This task aims to develop a power system model based on the classic Optimal Power Flow (OPF) approach. The model incorporates technical inputs (such as power line reactance, power plant production capacities, storage, and EV demand time series) and economic inputs (including market prices and operation and maintenance costs). The optimization seeks to minimize costs while adhering to technological constraints like power balance, production, transmission, and dis-/charging limits. Key outputs include system costs, energy production, local marginal prices, and power line congestion. The model will be designed to represent stylized systems inspired by the case-study locations and will include shared mobility and EV behavior as input parameters.

Task 1.2: Shared Mobility Optimization (M12-M27):

• Lead: Technical University of Delft (TUD), with contributions from TUG and MyWheels.
• The objective is to develop a model that optimizes the vehicle fleet required for shared mobility services in urban neighborhoods. This includes determining the optimal fleet size and vehicle characteristics (such as seating and battery capacity) and making operational decisions regarding vehicle parking (idling or charging/discharging) from a profit maximization perspective. A surge pricing mechanism will be introduced to rebalance the fleet. This task is crucial for evaluating the business modeling aspects of V2G operations, their impact on the power grid, and their implications for carsharing system operations.

Deliverables:

• D.1.1: Functional prototype algorithms for charging station location and cost-minimized Optimal Power Flow (OPF) by Month 14.
• D.1.2: Functional prototype algorithms for fleet management and rebalancing the fleet using surge pricing by Month 27.

This Work Package aims to integrate the complexities of EV usage with power system demands, creating a sustainable, efficient, and user-friendly urban mobility and power ecosystem.

Lead Organization: HAN University of Applied Sciences / University of Aveiro

Objectives: The aim of WP2 is to delve into societal perspectives on Vehicle-to-Grid (V2G) technology, understanding the determinants, barriers, and facilitators associated with V2G adoption in daily life. It seeks to enhance knowledge on fostering inclusive and democratic decision-making in sustainability transitions, aligning societal concerns within local communities with stakeholder interests in the V2G ecosystem.

Description of Work:

• Task 2.1: Co-designing the three case studies (M1-M3):
  • Lead: University of Aveiro, with collaboration from HAN and local partners.
  • Preparation of case study fieldwork, defining a common research design, tools, and methodologies to explore citizen needs, perceptions, expectations, and concerns regarding V2G access and use. A participatory approach ensures the fieldwork is grounded in the lived realities of citizens and stakeholders, adaptable to different contexts. A clear communication plan will facilitate co-learning across case studies.
• Task 2.2: Citizen Engagement Activities in Kanaleneiland (M3-12):
  • Lead: HAN, with local Dutch partners including Energie-U, Municipality of Utrecht, and others.
  • Execution of defined citizen engagement activities, focusing on interactive sessions to gauge community perceptions and insights into V2G technology.
• Task 2.3: Citizen Engagement Activities in Aradas (M5-14):
  • Lead: University of Aveiro, with local Portuguese partners.
  • Similar to Task 2.2, tailored to the socio-cultural context of Aradas, Aveiro, Portugal.
• Task 2.4: Citizen Engagement Activities in Annelinn (M7-16):
  • Lead: University of Tartu, with local Estonian partners.
  • Execution of engagement activities as defined, with a focus on the unique demographic and infrastructural aspects of Annelinn, Tartu, Estonia.
• Task 2.5: Synthesizing and Developing Guidance on Citizens’ Perspectives (M15-20):
  • Lead: HAN, with contributions from University of Aveiro and University of Tartu.
  • Compilation of findings from the three case studies into a comprehensive report, analyzing cultural, societal, economic, governance, and geographical factors affecting V2G access and use. The task adopts a transdisciplinary approach to ensure a broad consideration of potential influences and the adaptability of findings to other contexts.

Deliverables:

• D2.1: Framework and Research Approach for Fieldwork (M3)
• D2.2: Three Case Study Reports on Kanaleneiland, Aradas, and Annelinn (M16)
• D2.3: Synthesis of Case Study Comparisons (M20)

WP2 focuses on understanding and integrating the community's voice into the V2G transition, ensuring that the deployment of V2G solutions is responsive to and inclusive of diverse societal needs and perceptions.

Lead Organization: Delft University of Technology (TUD)

Objectives: WP3 is dedicated to examining the utilization patterns of electric vehicles (EVs) in both private and shared mobility contexts, focusing on Vehicle-to-Grid (V2G) capabilities. The objectives include:

• Conducting transport mode choice experiments to integrate various car usage options with V2G technology, including private EV ownership, carsharing, and renting.
• Generating quantitative insights into the trade-offs involved in utilizing V2G-enabled EVs.

Description of Work:

• Task 3.1: Stated and Revealed Preference Surveys (M7-M15):
  • Lead: TUD, with contributions from all project partners and local authorities.
  • This task involves surveying a representative sample from the three target neighborhoods to understand their mobility preferences, including V2G-capable EVs. The surveys aim to capture current mobility patterns, attitudes towards EVs, and willingness to engage in V2G activities. The data collected will inform the development of behavior parameters for simulation models.
• Task 3.2: Equity and Desirability Analysis (M16-M18):
  • Lead: TUD, with contributions from the University of Tartu (UT) and the University of Aveiro (UA).
  • Using data from the surveys, this task focuses on analyzing how V2G technology can be accessible and desirable across different societal layers. It aims to provide an average estimate of potential V2G use among various demographic groups, offering insights into the equitable distribution of V2G technology.

Deliverables:

• D3.1: Report with the results of the stated and revealed preference surveys, detailing the mobility patterns, preferences, and potential acceptance of V2G technology among different user groups (M15).
• D3.2: Analysis report on the equity and desirability of V2G technology, highlighting how different segments of society perceive and could potentially engage with V2G solutions (M18).

WP3 addresses the crucial aspect of user engagement with V2G technology, focusing on understanding the preferences, barriers, and incentives for different types of EV usage. Through detailed surveys and analyses, this work package aims to foster a deeper understanding of public attitudes towards V2G, informing the development of more inclusive and effective V2G solutions.

Lead Organization: Erasmus University Rotterdam (EUR)

Objectives: WP4 is focused on providing an in-depth analysis of how legal regulation, in conjunction with other policy instruments, can facilitate the establishment and growth of Positive Energy Districts (PEDs). This involves:

• Mapping existing legal, financial, and communication measures in selected cities and at the EU level.
• Identifying generalized institutional design variables that can be applied universally across cities.
• Offering regulatory recommendations and policy lessons for policymakers.

Description of Work:

• Task 4.1: Conceptual Framing of Regulatory and Ethical Problems/Opportunities (M1-M10):
  • Lead: EUR; contributions from all project partners.
  • Initial task to identify and analyze current and future regulatory measures affecting the effective and equitable implementation of V2G facilities in PEDs. The task utilizes desk research of literature and policy documents, focusing on broader regulatory problems/opportunities rather than specific legislative instruments. Preliminary findings will be verified through stakeholder surveys among project partners.
• Task 4.2: Analysis of Existing Regulatory and Equity Framework (M11-M19):
  • Lead: EUR; contributions from universities, municipalities, and business partners in case-study countries.
  • Examination of the legal frameworks in the three case-study cities and their impact on optimal system operations and equity concerns. The task involves legal desk research and interviews with project partners to create a conceptual framework of institutional design variables.
• Task 4.3: Development of Regulatory and Policy Recommendations (M20-M24):
  • Lead: EUR.
  • Based on findings from Task 4.2, this task will establish regulatory and policy recommendations, considering the generalized conceptual framework, specific city conditions, and normative requirements of optimal allocation and equitable distribution.

Deliverables:

• D4.1: General policy brief based on the conceptual framework (M11).
• D4.2: Regulatory and policy recommendations presented as a policy brief (M24).

WP4 addresses the critical need for comprehensive governance and regulatory frameworks that support the adoption of V2G technologies and the development of PEDs. By analyzing existing policies and offering targeted recommendations, this work package aims to remove barriers and enhance the scalability of V2G solutions across different urban contexts.

Lead Organization: University of Deusto (UD)

Objectives: WP5 focuses on adapting an existing multi-agent simulation platform to the project's requirements, integrating knowledge generated from WP1-4, and simulating various V2G scenarios. The main objectives are:

• To adapt the multi-agent simulation platform for the project's V2G modeling needs.
• To integrate the insights from WP1-4 regarding power systems optimization, citizen perceptions, EV usage, and governance regulations into the simulation platform.
• To perform simulation studies assessing V2G pilot implementations, evaluating their impacts on the power grid and mobility systems.

Description of Work:

• Task 5.1: Development of the Multiagent-Based Model (M06-M24):
  • Lead: UD, with contributions from TUD, TUG, and other partners.
  • This task involves adapting a multi-agent system to simulate the interaction between EVs, charging infrastructure, and the power grid. The simulation environment will incorporate the electrical power system model from WP1 and the business models/regulations defined in WP4. The model aims to facilitate two-way communication between agents (representing EV users) and the power system, exchanging information such as control signals, power availability, and demand at each node.
• Task 5.2: Integration of the Knowledge Generated in the Project (M12-M30):
  • Lead: UD, with contributions from all project partners.
  • This task focuses on integrating the comprehensive project knowledge into the simulation model. It includes adjusting the trip generation and transport choice models based on WP3's findings, incorporating WP2 insights on EV and V2G usage, and deploying an open multi-modal route planner to simulate driving and charging behaviors. The task will develop tests to ensure the model's parameters and overall functioning are accurate and reliable.
• Task 5.3: Case Study Simulations (M24-M36):
  • Lead: UD, focusing on executing simulations for the project's case studies.
  • The simulations will use data from WP2-3, public datasets, and previous behavior models to create a detailed profile of typical days in the pilot neighborhoods. The model will simulate travel patterns, vehicle usage, charging needs, and interactions with the power grid to assess the impacts of V2G implementation in different scenarios.

Deliverables:

• D5.1: Multi-agent Based Platform and Technical Documentation, including model assumptions, environments, and agent behaviors (M24).
• D5.2: Results of the Simulations, featuring an open document for reproducibility and an open dataset with the numerical results of the simulations (M36).

WP5 is pivotal for applying the project's interdisciplinary research findings to realistic urban scenarios, offering critical insights into the feasibility, efficiency, and societal impacts of V2G solutions in urban districts.

Lead Organization: University of Tartu (UT)

Objectives: Work Package 6 focuses on assessing the socio-spatial applicability and impacts of Vehicle-to-Grid (V2G) solutions in urban neighborhoods, aiming to:

• Understand the potential for a socially just design and implementation of V2G systems in socioeconomically disadvantaged neighborhoods.
• Synthesize social justice aspects of V2G implementation based on findings across all Work Packages (WPs).

Description of Work:

• Task 6.1: Travel Behavior and User Preferences Data Collection (M13-M18):
  • Lead: UT, with contributions from HAN and UA.
  • Collection of input data from national travel surveys, registers, and geospatial databases, complemented by qualitative data on user preferences from WP2 and quantitative data from WP3's stated choice experiments. This task aims to create detailed user profiles for the case study areas, capturing travel behavior patterns, vehicle ownership, and openness to novel technologies.
• Task 6.2: Inclusivity and Accessibility Analysis (M17-M30):
  • Lead: UT, with participation from TUD, HAN, UA, Tartu, EUR, ICA, EESTI, and local authorities.
  • This task analyzes the potential for a socially just and inclusive design and implementation of V2G systems. It involves overlaying user profiles with V2G-enabled vehicle ownership and spatial distribution models to identify equitable solutions that can be replicated in similar socio-spatial contexts. The findings will be upscaled to broader spatial contexts to assess generalizability.
• Task 6.3: Case Study Synthesis (M29-M36):
  • Lead: TUD, with contributions from UD, UT, HAN, TUG, EUR, and UA.
  • Synthesis of the social justice aspects of V2G systems based on case study analysis and inputs from all previous WPs. This task will consolidate the knowledge produced into concrete guidelines for increasing the sustainable and equitable uptake of V2G technology.

Deliverables:

• D6.1: Report on inclusivity and accessibility analysis results, including user profiles (M30).
• D6.2: Synthesis report of social justice issues in V2G access and guidelines for promoting V2G in typically excluded neighborhoods (M36).

Work Package 6 is essential for ensuring that the benefits of V2G technologies are equitably distributed across different social groups, especially in socioeconomically disadvantaged neighborhoods. Through detailed analysis and synthesis of social justice aspects, WP6 aims to provide a foundation for the development of inclusive V2G solutions that address the needs of vulnerable communities.