Author: ISOCARP Institute

The deliverable D7.8: Data Collection and Management Guideline Report was submitted by Future Analytics Consulting, with contributions from NTNU, LCCC, TK, MAI, MP, SB, SMO, VORU, IESRD, POW, EAP, UL, R2M, and ISOCARP in May 2021. The executive summary of the deliverable is available below and the full deliverable at the end for download:

“Task 7.4 sets out the requirement to create practical recommendations and guideline reports which detail, analyse and interpret the aggregated data collected during the M&E process, and deliver technical recommendations related to the Information and Communication Technologies (ICT), energy, community, mobility, environmental and regulatory interventions implemented in the project. Deliverable 7.5 provided initial guidelines for these processes to which future iterations of the report would be structured. The guidelines provided in D7.5 were refined in this document to develop a framework for the evaluation of project activities and interventions, and set out a way to report on the feedback and provide actionable guidelines and recommendations.

The implementation of project interventions and initiatives generates data that is captured by project partners. Through the KPI framework developed for the project, partners are able to capture specifically defined quantitative KPI-related data that would suit the requirements in the calculation of the KPI. The consistent capturing and sharing of data to the Monitoring and Evaluation Reporting Tool (MERT) enables accurate capturing and processing of quantitative KPI data which, alongside broader quantitative, qualitative and experiential data collected throughout the overall project work, is used in the analysis and derivation of insights.

Mainly, partners will be using the manual data upload process through the individual interface of each KPI in the MERT. This might cause additional workload for partners until the automated process has been enabled. A limited number of partners currently share data through the automated process using Application Programming Interface (API) connections between partner and MERT servers. The way data is shared is not only dependent on the type of data available, but also on when the data is available. Uncertainty relating to the sharing and availability of data is being worked on.

A first level of insights derived from project data is based on the analysis of the KPI monitoring data, compared to the baseline situation and the expected and targeted impact for the indicator. The comparison of these points makes it possible to assess and track the indicators’ performance over time to identify trends, track growth, and highlight significant changes, from which quantitative insights can be formulated. The insights drawn from the data are then used to formulate recommendations on M&E topics such as data monitoring, data modelling, evaluation of the expected impact, performance of the indicator, and technical points regarding the implementation of a particular indicator.

To get a better understanding of the overall impact of project activities or interventions it is important to have partners’ feedback and input that describe the quantitative data and other impacts or results achieved. Feedback will be sourced from partners through various processes, including feedback forms, interviews, learning sessions, informal discussions, and the review of relevant project documentation. The monitoring data will be used together with the additional information provided by the project partners and the intervention results documented in formal project deliverables, to derive insight and inform recommendations. As data capturing and management using online ICT systems and tools such as the +CityxChange MERT and Smart Cities Marketplace (SCM) (formerly known as the Smart Cities Information System (SCIS)) Self Reporting Tool (SRT) will continue throughout and beyond the project lifecycle, it is important to consider the best possible way of integration and interoperability between these systems. Seamless interoperability (as documented in Deliverable 1.31: Report and catalogue on the ICT data integration and interoperability) will ensure efficient use of the available systems. In support of this ideal, the MERT will be reviewed periodically to determine whether all functionalities are still fit for purpose. In addition, other tools such as the +CxC Decision Support Tool (DST) and the SRT will be reviewed alongside the MERT to determine the level of possible interoperability and ease of use for the systems.

The ongoing sharing and analysis of data, engagement with partners, and use of data management and modelling tools will result in suggestions for improvement in efficiency of execution and processes being generated. The extraction of insights and development of recommendations are therefore not only based on quantitative data, but also the coherent insight and additional validating information informed by it.

Ongoing collaboration between Work Packages 7, 8, 9 and other partners will refine a framework for the accumulation of quantitative and qualitative data and information. The framework will set out the process for the identification of project activities to be evaluated, and demonstrate the evaluation procedures (feedback forms, workshops, interviews, informal interactive group discussions, review of relevant project documentation) that can be applied in the evaluation process. The application of the framework will ensure a collaborative methodology to analyse and interpret the evaluation of project activities to enable the extraction of useful insights and recommendations to inform future decision-making in the project. This framework development is described in this report.”

The deliverable 1.3: Report and catalogue on the ICT data integration and interoperability was submitted by the University of Limerick (UL), with contributions from NTNU, LCCC, TK, IESRD, POW, FAC, TE, ABB, ATB, ABG, ESB, 4C, MPOWER, SE,
COL, and IOTA in April 2021. The executive summary of the deliverable is available below and the full deliverable at the end for download:

”This deliverable D1.3 is part of Task 1.2: ‘Data Integration and Interoperability for the ICT Ecosystem’ within WP1– ‘Integrated Planning and Design’ of the +CityxChange project.

The results presented in this report summarize the approach and achievements within the project to ensure data interoperability within a complex ICT ecosystem. The results have been developed in collaboration with partners and related ICT development tasks within the +CityxChange project. We have built on the Enterprise Architecture Framework (EAF) and ICT Ecosystem approach, detailed in Deliverable D1.2: Report on the Architecture for the ICT ecosystem. The results here specifically complement that enterprise architecture in order to ensure data integration and interoperability of ICT systems and services, including software platforms and tools, data repositories, and IoT devices. This report provides an overview of data integration challenges in the smart city domain including standards, data models, guidelines, APIs, etc.. The developed approach and lightweight data integration and interoperability framework DIIF aim to ensure agreement on open standards between service providers involved in demo projects for interoperability and support data flow between partners and demos. We document the interoperability work done between partners, the API management approach, and API catalog. To secure distributed data integration between various services in the ICT ecosystem, the potential of using IOTA and other Distributed Ledger Technologies (DLTs) as a mechanism for data transfer was examined.

This report addresses the data integration and interoperability goals of +CityxChange, through developing a lightweight +CityxChange Data Integration and Interoperability Framework. It specifically addressed two aspects (i) the Interoperability aspect under the Data Perspective, dealing with the general interoperability requirements and processes; and (ii) the DataxChange and Data Processing layers of the ecosystem, dealing with the overall data storage and exchange and its use in the data processing layer. The report concludes with a summary of lessons learnt that provide a valuable resource for replication within the +CityxChange project, application to other cities, and further research.”

The deliverable 7.10: Reporting to the SCIS System (5) was submitted by FAC, with contributions from NTNU, NTNU, LCCC, TK, MAI, MP, SB, SMO, VORU, IESRD, POW, UL, EAP, R2M, ISOCARP, TE, ABG, 4C, MPOWER, and GoCar in April 2021. The executive summary of the deliverable is available below and the full deliverable at the end for download:

”This report, Deliverable 7.10: Reporting to the SCIS (5), is part of a series of bi-annual reports and is the fourth iteration in the series, being the subsequent revision of the previous version, Deliverable 7.9: Reporting to the SCIS (4) submitted in Month 18 of the +CityxChange project. This deliverable provides an overview of the capturing and modelling of project data that is reported to the purpose-built +CityxChange Monitoring and Evaluation Reporting Tool (MERT) and the Smart Cities Marketplace (SCM) Self-Reporting Tool (SRT).

The Key Performance Indicator (KPI) framework set out in Deliverable 7.1: Approach and Methodology for Monitoring and Evaluation (D7.1) is used as the basis from which KPI performance is assessed, providing all the necessary prescriptions in the calculation of each KPI. As the project and interventions have evolved over the last two years, and data formats, frequency, and variables have become more apparent, some of the KPI calculations have had to be refined and adjusted. The refinements of these KPI calculations feed into the development and updating of the MERT, which is the main platform for the collection, processing and dissemination of KPI data for all 33 KPIs. A number of refinements and adjustments have been made to front- and back-end processes of the MERT in an effort to deliver a more efficient and functional tool. Further work on the MERT will include the adjustment of layout and design to improve the user interface and the setup of APIs to enable automated data sharing to the MERT.

Data has been submitted to the MERT for 14 KPIs, with a total of 19 KPIs reporting measurements as of Month 30, subject to pending refinements of the calculation methods. As it stands, no KPI data has yet been reported to the MERT in the categories that align with the SCM SRT data capturing requirements and can therefore not be reported to the SCM. Other KPIs that potentially can report to the SCM do not have actual monitoring data as yet. Once it is clear what data is available and how it will be used in the calculation of a KPI, the KPI/data owners and WP7 will collaborate to determine whether it aligns with the SRT requirements and how it will be calculated in the MERT and SCM.

Although the COVID-19 pandemic has restricted physical engagement with stakeholders and curtailed the implementation of interventions, engagement has intensified using various online platforms, with every effort being made to collaborate with project partners where needed. WP7 will continue to liaise with partners to address the reporting of KPI data to the MERT and the SCM. This document is a continuation of the previous Deliverable D7.9 and repeats the main content from there. Changes are described in the Introduction.”

The deliverable 5.3: Campus Microgrid Model Prototype was submitted by NTNU, ABB, POW & TE with contributions from NTNU and TK in April 2021. The executive summary of the deliverable is available below and the full deliverable at the end for download:

+CityxChange (Positive City Exchange) is a research and innovation smart city project, where cities experiment to integrate smart positive energy solutions. Through the use of digital services (e.g., smart automation), the quality of life for and together with the citizens shall be improved, more energy produced than consumed (e.g., Positive Energy Blocks), and experiences with cities across Europe exchanged to learn faster together. In this regard, Positive Energy Blocks are a cornerstone on integrating renewables, introducing smart coordination of energy assets (e.g., energy storage, solar PV and EVs) among buildings, and promote a consumer-centric energy transition in smart cities.

As part of the +CityxChange project, this report details the work carried out to optimise, automatize, smart control, and exploit the energy flexibility potentials of buildings within a microgrid. Through enabling smart operations and real-time control of the buildings’ energy management systems, the objective is to contribute to the realisation of local energy markets and Positive Energy Block (PEB). A well-functioning PEB will require smart automatization and ensure that on-site local energy production is efficiently used by activating flexibility assets or mechanisms (e.g., demand response, storage, load shedding or shifting, etc.) to balance renewable production (e.g., solar PV) or potentially react to signals (e.g., prices) of an ‘intra-PEB’ market between the participating buildings and the wider microgrid. This report, deliverable D5.3 of the +CityxChange project, details the work related to implementing smart flexibility in buildings in the context of a microgrid by applying it to a real-life case (NTNU campus microgrid). Increasing the energy flexibility in the microgrid brings more synergy between production and consumption, and therefore, contributes to move NTNU towards a PEB. The development of this demonstrator and related work activities were as follows:

1. Estimating flexibility potentials from two energy assets in buildings. We provide a framework along with its theoretical foundation on how to estimate the flexibility potentials and the benefits of smart control to: reduce energy demand, make energy supply-demand operations more efficient, and enable the possibility to react to external signals (e.g., electricity prices from a common energy market). Some of these frameworks will also be used to detect flexibility in D5.6 and D5.11.

2. Requirements and methods to enable smart control of assets. We were deploying this demonstrator in a real-life setting needed coordination among multiple software platforms. Here we combined new software (model created by NTNU in the programming language Python), the deployment of ABB OPTIMAX (Virtual Machine), and the buildings’ existing ICT management system.

3. Demonstrating smart control of energy assets into the NTNU campus microgrid. By developing an automated optimisation model connected to live data sources and regional energy market along with forecasting features (i.e. a rolling horizon approach for scheduling), we demonstrate the operations of two buildings in the NTNU campus, more specifically, smart control one heat panel in a ventilation system and one heat tank in a waterborne system.

4. Replicability and scalability to other energy assets, applications and services. Based on the campus’s Electrical Vehicles, an analysis of their flexibility value and smart charging potentials is outlined.

5. Based on the campus microgrid analysis, this report provides a predictive assessment of how the inter-PEB market can work in Trondheim between multiple PEBs. This presents various scenarios and results in the design of the common energy market.

6. As part of the solutions and demonstrator potentials done in this deliverable, a summary of methods to deploy this on follower cities or interested stakeholders is summarised (the optimisation models as software are made available as open source).