Main results including public deliverables

D1.1 Cartography of the flexibility services provided by heating/cooling, storage and gas technology and systems to the electricity system

D1.1 summarises the main characteristics of the case studies and coupling technologies. Through mapping the main flexibility services to be found in the 7 case study countries against the case studies, possible bottlenecks and constraints to service provision and technological development are analysed and potential improvements to maximise the provision of the flexibility at the case study level are discussed.

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D1.2 Technology and case studies factsheets

D1.2 seeks to gather data from on-going and finished projects, available studies, manufacturers and case studies. These data are required for the simulation, optimization and development activities carried out in other Work Packages (WPs), as well as to evaluate expected developments of each of the identified sector coupling technologies. The main objective is to characterize the flexibility properties of coupling technologies either alone or in a specific configuration, and then to describe their ability to provide the flexibility services benchmarked in Deliverable D3.1. 

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D1.3 Technological adaptation to flexibility products and guidelines for development

D1.3 is the deliverable of Task 1.3, which is a part of WP1 “Services from synergies among multi carrier networks”. The overall goal of this report is to identify the technological and market barriers for providing flexibility services in the project case studies, and to propose potential solutions.
This report received inputs from Task 1.2 on current technology and case study characteristics and expected technological development, Task 2.1 on the project use cases, Task 3.1 on market and regulatory barriers, Task 3.2 on identified new market designs with Key Performance Indicators, Task 4.2 on tools for multi-energy system simulation and analysis, Task 3.1 and WP5 on flexibility products and procurement mechanisms, and WP6 on evaluation of integrated systems and case studies. The output of this report will inform and support Task 1.4 to draft guidelines for replicability assessment, and Task 3.5 on evaluation of business models for the case studies.
In this report, the seven project case studies were analysed, these being Mälarenergi AB, Austrian Paper Mill, Hofor, ACS, Neath Port Talbot, EMUASA, and Paris Saclay. Necessary information for each case study was collected through designing a questionnaire which was completed by relevant project partners, based on which the technological and market barriers and solutions are identified.

D1.4 Opportunities and barriers for replicating the studied flexibility products and market designs in selected countries

This deliverable (October 2020) proposes a multi-disciplinary and cross-sector analysis of the replicability and transferability of the project’s business use cases to different European countries and contexts: each use case is related to a case study, which is a Multi-Energy System (MES) operating in a determined technological, institutional, contractual, regulatory, and social framework. In order to assess if and how the studied use cases can be replicated across the consortium countries, the current situation in each of the nine States has been analysed considering different layers: technologies and MES (district heating and cooling networks, paper mills, waste-water treatment plants, gas-fired plants), energy prices, flexibility services and aggregation. Every layer was analysed for each of the nine studied European countries and then multi-layers and cross-countries comparisons were made, to identify solutions and current configurations, which, if replicated, would enhance the flexibility provision potential from MES.
The results of this work will be used in the Lessons Learnt of the project and as input to the Policy Recommendations.

D2.1 MAGNITUDE technical and commercial functional architecture

The objective of Deliverable D2.1 is to define the MAGNITUDE conceptual technical and commercial functional architectures to maximise the flexibility provision by multi-energy systems, stressing the overall organisational structures and high level simplified business use cases. These architectures and business use cases are then used in other Work Packages of the project, that define more precise use cases descriptions, tailored to their specific needs.

Specifying the technical and commercial functional architectures of the project, implies the following activities:

  • Describe the project concepts and high level conceptual architecture.
  • Identify the project business use cases.
  • Analyse the main relevant stakeholders involved in the overall process of flexibility provision by MES, considering the four energy sectors (electricity, gas, heating and cooling).
  • Describe them in terms of their roles and their interactions.
  • Using the roles and interactions, formalize generic conceptual technical and commercial functional architectures in the form of sequence diagrams which allow to describe the organisation of the stakeholders and the flexibility provision mechanisms.

More specifically, Chapter 2 describes the MAGNITUDE main concepts and high level conceptual architecture. Chapter 3 is devoted to the identification and characterisation of the high level (simplified) business use cases that will be investigated in the project. In Chapter 4, the concept of roles and role models is first introduced, as well as the main roles involved in the electricity, gas, heating and cooling systems, which are relevant for the MAGNITUDE project. The roles currently identified in the 7 case studies for the 4 energy sectors are then described and the main interactions between the identified roles in the current situation are provided in the form of generic sequence diagrams.  Chapter 5 describes the proposed interactions between the aggregation platform and the multi-energy systems for the provision of flexibility to the electricity systems and further extends the generic sequence diagram for the electricity system. Chapter 6 is devoted to the description of the roles and the interactions involved in the innovative market designs proposed for multi-carrier market integration and hence the enhancement of the synergies at market level. Conclusions and future perspectives are given in Chapter 7.

Finally the appendices of Chapter 9 provide the results of the detailed analysis carried out for each of the 7 real-life case studies in the current situation for the 4 energy sectors considered (electricity, gas, heat and cooling), regarding:

  • the stakeholders involved in the case study,
  • the roles they carry out,
  • the main interactions between these roles in the form of sequence diagrams. 

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D2.2 Multi-energy Data Hub Specification

The exchange of information in the energy system is an increasingly complex and resource intense process with many stages; it involves a growing number of stakeholders, thus requiring the management of a significant amount of data and an increasing number of connections between pairs of stakeholders. Indeed, the interactions among the actors involved in the rapidly changing energy sector are changing too. As an example, historically, the ancillary services had long auction periods and product durations, e.g. 1 week for Frequency Containment Reserve (FCR) or automatic Frequency Restoration Reserve (aFRR) and the aggregators have calculated everything manually. But today, in the scope of the Clean Energy Package (Directive (EU) 2019/944 and 2019/943) shorter product periods and gate closure times must be implemented and TSOs now plan to implement 1h products or even 15min products for aFRR and manual Frequency Restoration Reserve (mFRR). The trading process itself will also become automated and machine-to-machine (M2M) solutions will replace any manual bid submission in the mid-term. In future, traders and aggregators will therefore need automatic systems for trading, activation as well as accounting/reimbursement of customers.

The EU has presently no harmonized standards for this purpose, which increases implementation costs a lot and today the information flow is often slow and limited because the information is decentralised among the systems of different companies.

The MAGNITUDE project is a perfect workbench to identify the emerging needs in this domain: the analysis of the processes in the four energy sectors for the seven MAGNITUDE case studies, and the outcomes of the activities carried out in task T2.1 “Technical and commercial functional architectures”, reported in Deliverable D2.1 are the starting point to analyse the interactions among the involved stakeholders.

The present document, Deliverable D2.2, aims to provide the technical specifications of a centralised data exchange system, called data hub, as multi-carrier market facilitator. It enables and ensures interoperability between multi-energy systems (MESs) on one side and technical and commercial stakeholders of the energy sectors (electricity, gas, heat, and cool) on the other side, while shortening information exchange processes.

In Deliverable D2.1, information was provided on the interactions identified for each Case Study, which  made it possible to identify functionalities whose implementation can be useful for enabling precisely the commercial, functional, and technical framework that characterizes the context of MAGNITUDE.

Deliverable D2.2 reports the results of data collection from the seven MAGNITUDE case studies to gather further details, such as communication mechanisms, protocols, data formats, frequency of the exchanges, etc., for each interaction reported in D2.1 in the sequence diagrams representing the processes in the four energy sectors (electricity, gas, heat, and cooling) for each case study. Moreover, on the basis of the comparison of the approaches used to exchange specific type of data in the different case studies, a possible approach is proposed for each interaction in the generic sequence diagram provided in D2.1 as results of a comparative cross analysis of the roles identified in the seven case studies. User Stories are used to describe the needs of all the parties involved in all four energy sectors in the generic case.

The document illustrates the key challenges of the MAGNITUDE Multi-energy Data Hub not only to ease the exchange of data but also to create new business opportunities. Indeed, the amount and

granularity of available data makes it possible to develop new commercial services, such as demand response, energy audits, home management programmes, smart advices, etc., thus generating new revenue streams for energy market players.

The needs that emerged from the analysis of the outcomes of Task 2.1, and the general expectations a user has from a data hub are reported in the form of Use Cases specifications. From these, the MAGNITUDE Multi-energy Data Hub requirements are elicited, prioritised, and formally reported in the document.  The requirements are differentiated in functional requirements, which specify what the system should do, and non‐functional requirements, which specify how the system should perform a certain function.

Finally, based on the requirements elicited, the MAGNITUDE multi-energy Data Hub high level architecture is conceived and graphically represented using the Architecture View model approach, which provides a complete, basic, and simplified description of the software architecture by using multiple views to describe the system from the perspective of different stakeholders such as end-users, developers, project managers, and testers. Some of the views used to represent the architecture show the software requirements. 

D2.3 Interoperability adaptation layer

The MAGNITUDE project proposes a centralised data exchange system as multi-carrier market facilitator, capable of shortening information exchange processes between multi-energy systems flexibility service providers on one side and commercial and technical stakeholders on the other side, by providing the necessary level of interoperability and, as much as possible, underlying standardised data exchange.

This document, to be intended as the accompanying report of the software Deliverable D2.3 Interoperability adaptation layer, provides the description of the final version of the MAGNITUDE Interoperability Framework architecture and each software components. The interoperability framework is based on FIWARE, an open-source initiative defining a universal Next Generation Service Interface (NGSI) standard for context data management which facilitates the development of smart solutions for different domains such as smart cities, smart industry, smart agrifood, and smart energy. FIWARE NGSI Agents allow to simplify the management and the integration of devices by collecting data from devices through heterogeneous protocols and translating them into the standard platform language. FIWARE allows to publish, consume, and subscribe to data coming from multiple sources.

The FIWARE framework also owns a data store where data in the short to medium term are persisted. Data in the long term are stored in the MAGNITUDE Data Hub that is based on the open-source Comprehensive Knowledge Archive Network (CKAN) data management system for powering data hubs and data portals.

Moreover, in this document, the Open Automated Demand Response (openADR) protocol is proposed to standardise MES interactions with the Aggregator (to enable and facilitate the access of the multienergy system (MES) to the market services) and with their customers (to put in place specific demand side management). In this view, the needed customisation of the openADR data model, as envisioned by the same standard, is described; the protocol stack software implementation has been updated accordingly. Lastly, a novel NGSI Agent is proposed in MAGNITUDE to enable the integration of openADR within the FIWARE ecosystem.

D3.1 Benchmark of markets and regulations for electricity, gas and heat and overview of flexibility services to the electricity grid

The objectives of D3.1 are to provide:

  • An overview of the most relevant services towards the electricity system, which allow to increase the share of Renewable Energy Sources (RES), avoid curtailment of variable RES and enhance security of supply. These services should also allow to increase the synergies and trading between electricity, gas and heat/cooling networks: this capability will be studied in other Tasks and Work Packages of the project.
  • For the most relevant services identified, a comparative analysis of the associated electricity markets and/or service provision mechanisms, including the following aspects: market mechanisms and regulations, products exchanged, remuneration and/or tariffs systems, main stakeholders involved and the key relationships.
  • A comparative analysis of market segments for the gas and heat sectors, which will be affected by the service provision. To the extent possible, this analysis will also cover the market mechanisms and regulations, the products exchanged, the remuneration and/or tariffs systems, the main stakeholders involved and the key relationships.
  • The identification of market and regulatory barriers that might affect the provision of the services.

The analysis is carried out for the case study countries, namely Austria, Denmark, France, Italy, Spain, Sweden, and the United Kingdom. However, for this latter, only Great Britain is considered and not Northern Ireland.

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D3.2 Evaluation of future market designs for multi-energy systems

The objective of this deliverable is to identify, elaborate and evaluate future market schemes for multi-energy systems. Currently, electricity, gas and heat are traded in separated markets with very different trading principles (e.g., trade types, pricing methods) and different temporal specifications (i.e., temporal resolution, clearing horizon, gate closure times). As an example, the majority of gas is traded on a long term yearly basis, whereas more and more electricity is traded on a more short term hourly basis typically a day in advance or even closer to real time. Organised heat markets are currently non-existent and, in most situations, a fixed heat price applies.

This report proposes possible multi-carrier market schemes which can better reflect the interaction and interdependencies between the different energy carriers, which eventually can lead to higher overall social welfare. The report specifically focuses on the design of day-ahead (DA) multi-carrier energy markets as this is seen as the first step.

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D3.3 Specification of the multi-energy market simulator

The contribution of this deliverable is twofold. In the first part, we investigate the design of multiple integrated multi-carrier gas, electricity and heat market models and their mathematical formulations.

The market designs include new market order types and constraints allowing market participants to describe their technical constraints and cost structures in a context of integrated multi-carrier markets. An order is a means for market participants to communicate their willingness to produce or consume energy at a certain price to the market operator. Three order types are defined, namely elementary orders, conversion orders, and time-shifting orders. A constraint is a statement that makes the acceptance of an order conditional to the acceptance of orders of different carriers, or of orders of different time periods in a predefined manner. We define four types of constraints namely: pro-rata, cumulative, implication, and exclusive constraints. An integrated multicarrier market as such can be cleared in a centralised or decentralised fashion.

Consequently, in the second part of the deliverable, we study the design of the integrated multi-carrier market that clears in a decentralised fashion, considering different settings regarding agents that are involved, the information that has to exchange at each step of the iterative process. Subsequently, we reflect on potential implications implementing such market design(s) can have on organisational structure of European energy markets.

D3.4 Multi-energy market simulator

The multi-energy market simulation software tool was implemented in Deliverable D3.4. Several market designs were introduced and extensively discussed in the MAGNITUDE Deliverable D3.3. The mathematical formulation of the selected market designs available in Deliverable D3.3 have then been implemented as a software to obtain a fully functional market simulator.

Developments of the market simulator have focused on the implementation of key market designs and specifically on the implementation of the computational engine required to clear market design MD-5.1 “Integrated multi-carrier market design with centralised clearing (Integrated – Centralised)”. The reason is that a clearing tool for MD-5.1 provides the key building block to clear all the other market designs proposed in Deliverable D3.3.

The multi-energy market simulation tool can be used to simulate different alternative multi-carrier market designs for a certain (future) scenario and context (e.g. geographic area) and compare them with a benchmark design, i.e. a market design where the markets related to different carriers (electricity, gas, and heat) are de-coupled. This analysis can be done by calculating Key Performance Indicators (KPIs) based on the simulation outcome of each simulated market design and comparing them. The envisioned KPIs have been introduced in the MAGNITUDE Deliverable D3.2.

D3.5 Business model evaluation

Business model evaluation of the different case studies for the simulated markets” is the final deliverable of WP3 and presents the outcome of Task 3.5 of the Magnitude project. The deliverable assesses the business models for the different case studies (multi-energy systems) of the Magnitude project. The deliverable gives a description of potential business models of the flexibility services provided by the multi-energy systems (MES) and an assessment of the economic viability of the identified business models for each of the cased studies based on a cost-benefit analysis. This assessment was done through a differential analysis of scenarios without and with flexibility services provision, including or excluding improvement strategies (such as the investment in additional storage capacity). The services considered include ancillary services (FCR, mFRR, aFRR, RR), energy market participation (DA, ID) and redispatch mechanisms. In addition, the aggregator business model is presented for the different case studies. The deliverable provided valuable insights on the aspects which have an impact on the feasibility of the business model, such as the remuneration structure of the services considered, the direct and indirect costs related to flexibility provision, the cost allocation approach among the aggregator’s assets, the revenue sharing model between the MES and the aggregator, etc

D4.1 Methodology for multi energy system simulation

This deliverable is dedicated to outline a methodology for the modelling, simulation and optimization of multi-energy systems. In general, this is a very complex step as these types of systems cover spatial, temporal and functional dimensions at different levels. They also strongly require representing the tight interrelationship linking together different energy carriers’ systems. This very complex goal is pursued in this deliverable providing an overview of the state of art of the different techniques currently emerging in the literature and of the steps proposed for WP4 activities organized into a workflow.

D4.2 Tools for multi energy system simulation and analysis

The goal of Task 4.2 (Tools for multi-energy system simulation and analysis) is to simulate and analyse the integrated multi-energy systems and to quantify system specific operation boundaries for flexibility service provision to the electric system. The seven case studies in the MAGNITUDE project including ACS Milan, EMUASA, HOFOR, MälarEnergi AB, Austrian paper mill, Neath Port Talbot (NPT), Paris-Saclay were analysed. Depending on the system configuration, technologies and flexibility services in each case study, appropriate modelling methodologies were adopted for the analysis of operational characteristics of the multi energy systems. The models were validated and calibrated based on historical operation data from the case studies.

D4.3 Optimization of flexibility provision from multi carrier system

Deliverable D4.3 documents the work carried out in task T4.3. This task consisted in developing suitable tools to optimize the operation of Multi-Energy Systems (MES) maximizing the provision of flexibility to the electricity system. The challenge dealt with in this task was the development of optimisation algorithms and methods for each of the seven project case studies. The algorithms and methods were designed to simulate and assess MES in the base-case configuration and under new technological configurations (defined in WP1), market services associated to each case study (from WP2), boundary conditions and scenarios (from WP6) and maximizing the identified key performance indicators (KPIs) (WP6). The outcomes from the developed tools were configured in order to satisfy the requirements posed by the Aggregation Platform (developed in WP5).

For each case study distinct optimization methods and algorithms were developed to:

  • perform optimization towards grey or black-box models, based on the simulation models previously developed and documented in Deliverable D4.2, highlighting generation, loads and storage devices/systems;
  • study the enhanced configurations identified for each MES and constituted by the addition of improvement devices or management strategies. The assessment of the enhanced configurations, against (a sub-set of) the identified KPIs, allowed to verify their effectiveness to increase the MES’ performance;
  • optimize the MES behaviour while facing the identified electricity market services. The outputs of this optimization permitted to evaluate the benefits, arising to the MES-operator and possibly to the (national/regional) electricity system operator, by the quantification of the remuneration/cost-reduction and the amount of flexibility really made available;
  • assess the overall performance of MES while participating to the market services sharing the available flexibility and the potentials and barriers encountered.

The analysis performed allowed to highlight the need to (optimally) manage the rebound effects on heating, cooling, gas and also electricity systems arisen from the introduction of improved configurations at the technological or management level and of electricity market participation.

The main outcome provided by task T4.3 is the temporal and technical description of flexibility, expressed as market service bids, under specific technological, financial and regulatory scenarios, and compliant to the integration requirements posed by the aggregation.

 

D5.1 Specifications of Multi-Energy Aggregation platform for provision of flexibities

This deliverable (July 2020) provides an overview of the general functional requirements of an aggregation platform that utilizes flexibility services from multi-energy systems and the detailed specification of this multi-energy aggregation platform to be applied in the case study simulations performed in the MAGNITUDE project. Furthermore, the MAGNITUDE simulation approach is explained in detail in D5.1.

D5.2 Tools for optimized market allocation of flexibilities

Deliverable D5.2 (July 2020) explains the market price forecasting algorithms developed and tested in the project. Forecasting algorithms have been developed for all 7 case study countries and for day ahead markets of electricity and gas as well as for flexibility markets like intraday, mFRR, aFRR and FCR. The second part of the deliverable focusses on the tool for optimized bidding under consideration of the given uncertainties in the practical application.

D5.3 Tools for multi energy carrier aggregation

Three tools for technical aggregation of flexibilities are detailed in Deliverable D5.3 (August 2020).

A flexibility-forecasting tool for the aggregation of a large number of “unmanaged” units was developed based on a data driven approach.

The optimization problem of a bidding strategy for a flexibility aggregation pool was solved by means of a stochastic model; this tool can propose the optimal volume of backup in a given pool of flexibilities.

A practical method for the flexibility assessment of “unmanaged” energy storage was developed and coded, and was finally tested on a real-life dataset.

D5.4 Multi-energy aggregation platform for provision of flexibilities

This deliverable (August 2020) describes the integration of the developed tools into the Multi-Energy-Aggregation platform and its interaction with other tools developed in MAGNITUDE by means of a practical example for the Austrian market. This document proves the functions of all developed tools and algorithms and provides a guideline for the simulation work performed in Work Package 6 Case Studies.

D6.1 KPIs and assessment procedure

Seven real-life case studies of multi-energy systems (MES) of different sizes and technological features located in seven European countries are used to provide the data foundation for the assessment and for the modelling activities taking place in different Work Packages (WP) in the project.
This deliverable aims at identifying the key performance indicators that can be used to evaluate and assess the performance of the combined system modules for the evaluation of the entire systems under study and monitor the MAGNITUDE improvements.

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D6.2 Evaluation report

Deliverable D6.2 evaluates 7 real-life case studies of the MAGNITUDE project through a set of Key Performance Indicators (KPIs) defined in Deliverable D6.1. These KPIs allow to assess the performance of several configurations of the case studies in terms of flexibility provision, energy efficiency, environmental efficiency, and economic efficiency. For some of the cases, the participation in flexibility markets through a Multi-Energy Aggregation Platform is considered to increase the ability of these sites to participate in markets under the current regulation. The results show case studies’ ability to provide flexibility at a moderate cost with the energy, environmental and economic efficiency differ depending on the type of systems considered.

Additionally, this deliverable presents the results from the simulation of two innovative day-ahead multi-carrier market designs developed in Deliverable D3.3: a decoupled multi-carrier market design with decentralised clearing (sequential market), and an integrated multi-carrier market with centralised clearing (coupled market). The performance of these two markets is compared through a set of KPIs defined in Deliverable D3.2. In the simulations coupled multi-carrier markets were better at dealing with forecast errors and shortages and can more easily integrate renewable electricity sources than the sequential markets. These benefits come at the price of higher computational times for calculating market-clearing outcomes of coupled multi-carrier markets compared to sequential markets.

D7.2 Communication materials and tools

D7.2 describes the communication materials and tools developed and used during the project implementation to disseminate its activities and results, namely:

  • MAGNITUDE brand image
  • Project public web site
  • Social media
  • Project press release
  • Newsletters
  • Poster and leaflet
  • Project public presentation

These communication materials and tools have been shaped to target the European public and private stakeholder communities including utilities, distribution and transmission system operators, energy suppliers, service providers, regulators, policy makers and standardisation groups.

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D7.3 MAGNITUDE lessons learnt

Deliverable D7.3 is dedicated to the capitalization of the main outcomes and lessons learnt from the MAGNITUDE project and its seven real-life case studies, as well as identified or potential barriers and recommendations.

The following aspects are covered in the deliverable:

  • provision of flexibility by multi-energy systems (MES),
  • aggregation of MES for flexibility trading,
  • market and regulatory perspectives,
  • replicability of the investigated use cases,
  • assessment of the business models of the MES operator and the aggregator,
  • stakeholders’ roles and interactions, multi-energy data hub and interoperability layer.

Finally, the remaining challenges and future work are also described in a dedicated chapter as well as recommendations for further research and development activities, and for future demonstration projects.

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D7.4 policy recommendations

The objective of Deliverable D7.4 is to deliver policy recommendations in a pan-European perspective and to provide inputs to the ongoing policy discussions in the energy field.

The MAGNITUDE policy recommendations address market mechanisms, regulation, and standardization. They build on the “Lessons Learnt” deliverable D7.3.  and on an in-depth analysis of the project results to translate them into tangible recommendations for EU-level, based on a holistic approach, thereby enabling wider renewable energy integration thanks to new services from cross energy carrier systems. To download the full document, please click here.

D7.5 MAGNITUDE exploitation plan

Deliverable D7.5 describes the plans of the participants to exploit the project results and to move the technology forward. The report covers both, the activities of dissemination and exploitation of the outcomes and learnings carried out during the project lifetime, and the partners’ strategies for the commercial exploitation, non-commercial exploitation (e.g. further research, development, etc.) and dissemination of the results after the end of the project.

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