With expanding solar and wind power production, the topic of flexibility services attracts increased attention in the Swedish energy system. In this context, the potentials in using thermal storage capacities in district heating (DH) systems have been brought forward, primarily by academic scholars. Using a ‘grounded’ approach, this study investigates if professionals assigned to Swedish DH companies and electricity distribution system operators utilise, or plan to utilise, DH systems as flexibility services for the electricity grid. Original data was collected through semi-structured interviews, held with fourteen individuals affiliated to different actors in the Swedish energy system. These individuals were identified as being experts, or practically engaged, in using DH utilities as flexibility services for the electricity grid. The findings show that although technologies for coupling between DH systems and the electricity grid are already in place, initiatives for using DH systems as flexibility services for the electricity system are rare in Sweden. Coupling challenges stem from ownership and operation legislation frameworks, marginal incentives and a widespread focus on firm benefits rather than energy systems benefits. Identified initiatives for using DH systems for flexibility services are primarily run on a local scale, designed and propelled by small groups of engaged individuals.

Despite the apparent usefulness of prosumers in the DH grid, there has not been a systematic investigation into why Sweden has not seen a general uptake in prosumer integration in the district heating (DH) sector. The transition to 4th generation district heating (4GDH) and smart energy system concepts are conducive to prosumer integration. Nonetheless, the integration of heat prosumers has been slow in Sweden. Our current study investigates the drivers and barriers for prosumer integration in the Swedish DH sector and looks at if and how rules, regulations and policies may affect the enabling of prosumer integration. The research questions posed in this study are: what are the drivers and barriers for prosumer integration in the DH sector in Sweden, and, what are the rules, regulations and policies that can affect the enabling of prosumer integration in the DH sector in Sweden. A directed Content Analysis of systematically selected scientific and industry-related literature is analyzed to investigate the drivers and barriers for prosumer integration in the Swedish DH sector. The drivers for prosumer integration can be broadly categorized as DH-side drivers, prosumer side drivers and macro-trend drivers. In terms of the DH-side, costs savings, more flexibility, increasing the environmental and commercial profile of the company and increasing the effective use of energy are the main drivers. Similarly, for the prosumers, it is additional income, increased self-sufficiency and raising the environmental profile which are the main drivers. In the barriers side, not up-to-date policies and regulations about the energy use and required energy efficiency for buildings, and conflicting regulations about accounting of energy use disincentivize prosumer integration in the Swedish DH sector. There are barriers on both the DH-side and prosumers’ side hindering the integration of prosumers in the DH sector. These barriers are also enhanced by ambiguous policies, which hinder the prosumer integration in the Swedish DH sector.

Flexibility in the energy system has been studied previously but few results have been implemented in district energy (DE) pricing models. This means that pricing models are not accounting for existing information making them less efficient than they need to be. We have studied if and how business models of DE firms capture flexibility in the DE grid and suggest price model updates to harvest flexibility. A systematic literature search with content analysis of resulting scientific peer-reviewed publications and project reports has been performed. Thereby, the different business models which have been described in the literature have been categorized. Based on literature, efficient price models have been identified. Another source of information is six demonstrators aiming at generating knowledge about DE flexibility. They are part of the Flexi-sync Project (ERA-Net). Findings show that most DE grids are slow to recognize and capture flexibility that can be catalyzed through end-users, thermal inertia, heat pumps and other. Similarly, DE firms employ a marginal cost logic to determine whether flexibility should be operationalized, and often their business models and price models are not oriented towards expressing that value logic to their customers. We identify that there is a potential for DE companies to further capitalize on flexibility in the energy system. By inclusion of flexibility incentives in price models a win-win can be established by cutting operational costs for the DE provider and energy consumption of the end-user.

The apparent usefulness of prosumers in the district energy (DE) grid, with the transition to 4th generation district heating (4GDH) and smart energy system is beginning to be realized. Similarly, there is a burgeoning interest in the exploitation of flexibility in the DE grid. But, whether the business models for prosumers also capture the flexibility provided by the prosumers is doubtful. Our current study ponders on: what are the business models for prosumers in the heating sector? do they capture flexibility? And, if so, how do they capture flexibility? A directed Content Analysis of systematically selected scientific literature is analyzed to investigate the business models for prosumer integration in the DE sector, and how they capture flexibility. Fifteen scientific articles were chosen through a systematic selection process. The selected literature was analyzed under the following categories: research objectives or research questions, methodology used, key actors considered, key technologies, pricing logic of heat, control of the prosumer system, computation of benefits and flexibility consideration. The findings from the selected articles show that when looking at how prosumers can supply peak heat, most studies consider the marginal cost of heat supply as an important parameter in the price logic. Similarly, the benefits are computed in a system-wide manner as the difference between the marginal cost of heat either through production from DE system or through production from the prosumer. In calculating the marginal cost of heat investment costs are not considered, which is not conducive for positive decision-making by the potential prosumer looking to invest in heat pumps or excess-heat exploiting technologies. © 2021 The Authors

The IRIS project has defined goals and targets in the project proposal, and the monitoring and evaluation work package (WP) 9 will analyse to what extent the project reaches these goals and objectives. The monitoring and evaluation will also provide information concerning the performance of the different solutions demonstrated in the Lighthouse (LH) cities in IRIS which is important for the replication of the solutions both in the LH cities and in other cities. This is of importance for the replicability of the solutions, both in the LH cities (Utrecht, Nice and Gothenburg) and in other cities. The project consists of several demonstration projects which are divided by 5 transition tracks (TTs): TT1; Smart renewables and closed- loop energy positive districts, TT2; Smart Energy Management and Storage for Grid Flexibility, TT3; Smart e-Mobility Sector, TT4; City Innovation Platform (CIP) Use Cases, TT5; Citizen engagement and co-creation.

D9.5 is the result of 2 years of work with several iterative processes involving the LH cities and their partners with the ultimate goal to:

Define a set of Key Performance Indicators (KPIs) which evaluate the effectiveness and impact of the cities proposed measures.Setup monitoring plans for each IS to define how each parameter is being measured to ensure that the KPIs can be calculated.Define how the baseline and the targets are defined and measured.This work started as described in D9.2 (Report on monitoring and evaluation schemes for integrated solutions) [1] with:The definition of the initial list of KPIs and how to calculate them, based on Smart Cities Information System (SCIS) [2], the CITYKeys Project [3] and the IRIS project itself .The assignment of KPIs to relevant measures within the project.An evaluation plan to measure performance on project level, including aggregation of KPIs.

The process has continued with D9.3 (Report on data model and management plan for integrated solutions) [4] and D9.4 (Report on unified framework for harmonized data gathering, analysis and reporting) [5], which define the basis of the methodologies used to come to the results written in this report.

Feedback from several workshops on this topic has led to a guideline that supports the partners responsible for implementation of the demonstrators in setting up their projects such that:KPIs that are being measured are well understood.KPIs give a meaningful result.The right data is being measured to calculate the required KPIs during the implementation of the measures.

An important part of this process is to have a close look at the KPIs that are projected for each demonstrator, the calculation method of the KPIs, and the expected results. By means of KPI interpretation forms. By doing so:

• KPIs are defined and calculated such that only one way of interpretation is possible. This way results from different projects and cities are homogenized.

• It is well understood what result the measurement of a KPI leads to.The method and results of this process are described in this report, which is a revised KPI list where KPIs are added, removed or adapted.

In addition to this, the KPI interpretation forms created the basis for the formulation of detailed monitoring plans for all measures within the project. Together with template forms for reporting these plans and a common data structure, which were provided to the affiliated partners, these plans are obtained and described for all measures per Transition Track and per Lighthouse city in this report.

Another essential part of measuring the performance of the IRIS project is the establishment of the baseline measurements and review if targets are met. Tables with KPI data requirements, consisting of the associated parameters, data sources, baseline and (possible) targets for all measures are incorporated.

An important part of the monitoring strategy of the IRIS project is the KPI tool, which is described in detail in report D9.4 [5]. This tool is established to collect all relevant monitoring data from the IRIS project in order to calculate and visualize the performance of the project. The tool partly obtains it’s data by means of the City Information Platforms (CIP). The monitoring details combined with the updated KPIs, result in an inventory containing an overview of all data sources with as main objective:

• To make sure that all data sources are known and will be measured by the responsible partners.

• To know what kind of data needs to be collected by the KPI tool.

• To know when monitoring in each demonstrator starts and data can be expected.

• To have a clear overview for all responsible partners what to deliver.

Besides setting up the collection of the indicators data, D9.5 also continues the work on aggregation of KPIs. For each city a revised list is made that indicates which KPIs will be aggregated to Transition Track-, City- and IRIS-level.

In the conclusion the challenges that where met during the process of setting up the monitoring framework are described. Because of delays within the IRIS project, not all monitoring plans have been obtained yet. Therefore, a future update of this report will be submitted as soon as this information is available. Further on a perspective is described for future work to start gathering the data and visualize results of the IRIS project.

The target group for this report is mainly people who:

-  Are interested in how to apply a unified monitoring and evaluation scheme into a large Smart City project with many different partners and stakeholders. For example, people working on comparable (Smart City) projects, or the follower cities within the IRIS project.

-  Are interested in how the performance of several different Smart city projects can be evaluated.

-  Are interested in the implementation of KPIs from projects such as SCIS and CITYkeys.

-  Want to learn from project partners from within the IRIS project who work on similar projectsabout their monitoring. For example, partners from different cities affiliated with the same transition track or transition track leaders.

- Want to find out what kind of data can be expected from the IRIS project. For example, external researchers interested in the results of Smart City projects, but also partners working on WP4 (CIP) and WP9 (monitoring and evaluation).Want to learn what the current state is of the monitoring and evaluation of the IRIS project.

The IRIS project has defined goals and targets in the project proposal and the monitoring and evaluation work package (WP) 9 will analyse to what extent the project reaches these goals and objectives. The monitoring and evaluation will also provide information concerning the performance of the different solutions demonstrated in the LH cities in IRIS which is important for the replication of the solutions both in the LH cities and in other cities.

The deliverable particularly addresses the IRIS Lighthouse Cities partners responsible for specific solutions and the leaders from the five Transition Tracks. The main objective of D9.2 is to present an all- embracing evaluation plan and monitoring program. A set of Key Performance Indicators (KPIs) has been selected to evaluate the effectiveness and impact of the cities proposed integrated solutions. Deliverable D9.2 sets out the requirements and objectives for the monitoring and evaluation to be carried out in the lighthouse cities and their integrated solutions and is a significant step towards the establishment of the unified monitoring infrastructure of the IRIS project.

The selection of the KPI set was carried out in collaboration with key representatives from the lighthouse cities and involved their partners responsible for specific solutions and the leaders from the five Transition Tracks. The final selection of KPIs fulfil the ambitions of the Grant Agreement and set targets, as well as specific input from partners wishing to assess more accurately the success level of each solution or methodology tested by the demonstrators.

The definition of Key Performance Indicators has been harmonized with other European projects working on energy smartification of European cities. The main initiatives that have been consulted for the definition of the key performance indicators (KPIs) are SCIS and CITYkeys, although some new indicators originate from the work conducted within the IRIS project. The use of SCIS and CITYkeys KPIs in IRIS will facilitate incorporation of all performance data into the SCIS throughout the project.

The work done in D9.2 will be used in D9.3 that is due in month 14 (M14). D9.3 will create the data model and the management plan for the integrated solutions and forms the basis for the establishment of a unified framework for harmonized data gathering, analysis and reporting which will be concluded in deliverable D9.4 which is due M18. Deliverable D9.2 will also provide input for WPs 3, 5-7 and 8.