INTERPRETER is a project financed in the scope of the European R&D H2020 Program entitled "Interoperable tools for an efficient management and effective planning of the electricity grid".

This project includes an ambitious validation phase, in which the solutions will be tested in 3 pilots in Belgium, Denmark and Spain, thus ensuring a high replicability across Europe.

The coordination of this 3 years project organized an online Workshop "Distributed Flexibility Markets in H2020 Projects" that was held on March 16^th, with speakers from Horizon 2020 projects PARITY and INTERPRETER together with invited guests.

Grid integration and implementation of distributed flexibility market concepts were some of the topics discussed, in the context of the solutions under development in the projects.

Among other aspects, both projects had set to deal with grid management solutions to address the significant challenges on grid balance caused by known issues such as the inelasticity of demand or the continuously increasing presence of distributed intermittent energy sources.

Demand flexibility concepts strive to become part of the solution and, as such, generate new opportunities for planning, operation and control of the network.

For more information:

Link for Event

INTERPRETER website

INTERPRETER (R&D Nester website)

The project BD4NRG - "Big Data for Next Generation Energy" is a 3-year project that started on January 2021 and will last until December 2023.

The need of increasing levels of information to operate the power systems is unveiling an enormous opportunity for energy stakeholders to leverage on Big Data and AI technologies to improve decision making.

In that respect the project BD4NRG that involves 35 partners from 12 countries will in short:

- Deliver a reference architecture to enable B2B multi-party data exchange, while providing full interoperability of leading-edge big data technologies with smart grid standards and operational frameworks;

- Deliver an open modular big data analytic toolbox (data, computing resources, models, algorithms);

- Deliver predictive and prescriptive edge AI-based big data analytics on 13 large scale pilots, deployed by different energy stakeholders (e.g. TSOs and DSOs, aggregators, local energy communities, ESCOs, etc), covering the energy value chain.

BD4NRG two days kick-off web-meeting counted with the participation of its 35 partners, from 12 countries, where, amid many others, R&D NESTER, REN, UNINOVA and ENERCOUTIM are from Portugal.

R&D Nester together with REN (Portuguese TSO) will develop proof-of-concept solutions to support two assets that are critical for the performance of the power systems:

- Condition-based maintenance of circuit breakers taking into account different operational conditions

- Generate a semi-automatic maintenance plan for overhead lines from inspection data.

The project is financed in scope of the H2020 program.

For more information:

https://cordis.europa.eu/project/id/872613

BD4NRG Project (R&D Nester website)

The project I-NERGY - Artificial Intelligence for Next Generation Energy is a 3-year project that started on January 2021 and will last until December 2023.

AI spreading in the energy sector is expected to dramatically reshape energy value chain in the next years, by improving business processes performance, while increasing environmental sustainability, strengthening social relationships and propagating high social value among citizens.

I-NERGY aims at evolving, scaling up and demonstrating innovative AI-as-a-Service (AIaaS) Energy Analytics Applications and digital twins services that will be validated along 9 pilots, which range from optimised management of grid and non-grid RES assets, improved efficiency and reliability of electricity networks operation, optimising local and virtual energy communities involvement in flexibility and green energy marketplaces.

I-NERGY involves 17 partners from 10 countries and will deliver in short:

- New AI-based energy services, fully aligned with AI4EU service requirements;

- An open modular framework for supporting AI-on-Demand in the energy sector by capitalising on state-of-the-art AI, IoT, semantics, analytics tools, which leverage on edge-level AI-based cross-sector multi-stakeholder sovereignty and regulatory preserving interoperable data handling.

For more information:

https://cordis.europa.eu/project/id/101016508

I-NERGY Project (R&D Nester website)

As the Energy Transition progresses, namely with the introduction of diverse flexibility sources, it is important to ensure that the stability, efficiency and security of supply of the system is kept. OSMOSE project ("Optimal System-Mix of Flexibility Solutions for European Electricity") is looking into those aspects.

In the context of the activities from task T1.4 - Innovative Flexibility Options in the Context of Planning, Operation and Stability, led by R&D NESTER, the partners REN (PT) and ENSiEL (IT) successfully delivered the internal deliverables associated with their sub-tasks at the beginning of the current month of April.

These reports addresses two relevant topics from WP1 (Work Package), which tackles the long-term flexibility needs of the European power system, namely through the assessment of the impact of flexibility resources in multiple dimensions:

Sub-task 1.4.2 - "Cross-border reserve exchange for improved flexibility and efficiency", led by REN (Portuguese TSO), evaluates the long-term scenarios developed within WP1, with special focus on the Continental South West region (including Portugal, Spain and France), from the operational reserve needs perspective for this interconnected system. In this work, REN resorted to own tools.

Sub-task 1.4.3 - "Stability aspects", led by ENSiEL (Italian consortium of public universities), analysed the impact of high levels of renewable energy sources (RES) in the dynamic stability of South Italy power system. Additionally, assessed the contribution of these flexible resources, characterized by a power-electronics' based interface and/or low inertia (e.g. wind, solar, battery energy storage), to the dynamic stability of the system.

The two reports provide key takeaways from the analysis on the OSMOSE scenarios for 2030 and 2050 time horizons.

From the sensitivity analysis performed in T1.4.2 for the Continental South-West region (PT, ES, FR), none of the scenarios lead to any type of security of supply constraint. Nevertheless, in the scenario Current Goals 2050 the operation conditions were more demanding leading in some circumstances to reliability indexes (e.g. LOLE or EENS) greater than zero.

On the other side, in the stability analysis performed in T1.4.3 on part of the Italian power system, the simulation results support that the Sicilian power system operates within the normal frequency range when interconnection with continental Italy is maintained. In the case this interconnection is lost, the Sicilian system becomes less stable, requiring, in some scenarios, the contribution from wind farms, BESS and DSR (e.g. synthetic inertia) in order to be able to maintain the system's stability.

This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement N°773406.

For more information:

OSMOSE website

Osmose Project (R&D Nester website)

R&D NESTER participated in an online workshop organized by COST Action CA19108 - High-Temperature SuperConductivity for Accelerating the Energy Transition. 

This workshop aimed to present high temperature superconducting technologies as well as possible applications in power systems, aiming at contributing to the energy transition.

R&D NESTER performed a presentation related to the context that power systems will face in the next few years, focusing on the technical and technological challenges that the sector is facing, particularly those related to the growing penetration of renewable energy sources and associated challenges.

R&D NESTER is one of the partners involved in this COST Action, which aims to contribute to the development of high temperature superconducting technologies and includes multiple partners from industry and academia at European level.

R&D NESTER contributed to this COST Action by sharing knowledge related to the current and future context of power systems and associated challenges.

All details can be accessed at: http://www.ieee-pemc2020.org/workshop.php

All details about this COST Action can be checked at: https://www.cost.eu/actions/CA19108/

R&D Nester hosts this year 4 students who will contribute in research, studies and projects. Two of them are from ISEL - Instituto Superior de Engenharia de Lisboa and another 2 are from ISEC - Instituto Superior de Engenharia de Coimbra.

These selected students are from Electrical Engineering and Mathematics Applied to Technology and Enterprise courses.

This type of initiative allows these students to learn about the reality of the energy sector dealing with real projects and customers.

In these period of collaboration with R&D Nester, these students end up acquiring more in-depth knowledge of the many concepts of the electricity and energy sector in general that until then mostly knew in theory.

This experience seeks to reconcile the academic knowledge these students acquired in their courses, bridging the experienced in R&D Nester and the decisions that are associated to energy sector in general.

The context of R&D Nester is particularly suitable for this type of initiatives, as it provides them with work in Research, Development and Innovation areas, often close to the student's study areas and already with a connection to applications in business life.

The collaboration with these students will last between 4 to 7 months. Facing the current pandemic context by COVID-19, R&D Nester has adapted its organizational structure to the remote working mode, allowing to welcome these students remotely, managing to maintain the needed connection and information sharing.

This is intended to be an enriching and memorable experience and to boost the professional career of these 4 potential researchers and future professionals in the sector.

Trainees will work on themes such as solar photovoltaic optimal park layout, voltage control with artificial intelligence methods and machine learning techniques for wind power forecasting. 

In the scope of solar energy forecast, R&D NESTER developed a case study to test the effect of persistence algorithms in the solar forecast. The persistence was applied using Supervisory Control and Data Acquisition (SCADA) power information and tested with four different photovoltaic (PV) power plants. Four different models were developed and tested:

• A persistence application using a 2 hours refresh rate, which uses a SCADA power measure value to generate forecasts until 2 hours ahead.

• A persistence application using a 24 hours refresh rate, which uses the SCADA power measurement of the previous day to generate the forecast.

• A persistence application that performs a combination of the previous models.

• A persistence application that utilizes the persistence error (using the output of the third model and the SCADA values) to improve the forecast using the persistence's error.

In the figure bellow, it is shown the location of the PV power plants used to build the case study, as well as the formulation of the first persistence model flowchart as an example. These PV power plants have different sun tracking technologies [1], which are taken into consideration in the developed models.

In addition to these developed models, a set of quality control methodologies were used in order to guarantee the quality of the SCADA values. On the one hand, the theoretical clear sky curve [2] was used to set the sunrise and sundown. This formulation takes into account the geographic location of the site under study. On the other hand, an optimization model was built to use past historical data to fit the SCADA to the real power production. Thus, aiming to mitigate the residual noise on the SCADA data.

Each one of the developed persistence models parameters were optimized using past historical data of real power production and SCADA data. In a first step, the total normalized root mean squared error (NRMSE) for the full year of 2019 was calculated. The error resulting from the numerical weather prediction (NWP) models are used as the baseline in which the persistence models are applied. These results are detailled in the Table below:

The results show that using the persistence models with the NWP models can provide a benefit in terms of global error. Each one of the developed persistence models are able to reduce the NRMSE when compared to the NWP. Nevertheless, the latter two models are providing better results giving the fact that they are combining other models and, in the last one, using past error as refeed to self-correct the model.

The effect to each one of the developed persistence models can be easily seen when depicting the NRMSE values over a 2 hours time horizon. The contribution of each model can be clearly seen in the Figure bellow:

References:

[1] C. S. Solanki, "Solar Photovoltaics Fundamentals Technologies and Applications", New Delhi, PHI 2009.

[2] L.T. Wong, W.K. Chow, Solar radiation model, Applied Energy, Issue 3, July 2001, Volume 69, Pages 191-224.

- Network management sub-layer: implements networking of a broadband carrier communication network, network maintenance, and route management; and aggregates and distributes application layer packets.

- MAC sub-layer: competes for physical channels based on the two channel access mechanisms, carrier sense multiple access with collision avoidance (CSMA/CA) and time division multiple access (TDMA), to provide reliable data transmission.

- Physical layer: encodes and modulates MAC sub-layer packets to broadband carrier signals and sends them to power lines or receives broadband carrier signals from power lines, demodulates them, and then sends them to the MAC sub-layer.

IPCTN 2019 - R&D Nesterin the list of the 100 companies in Portugal that invested most in R&D activities (category equivalent to SMEs).

Recently the National General Directorate of Statistics of Education and Science (DGEEC) published the Final results of IPCTN survey for 2019, regarding R&D expenditure in Portugal by companies.

According to this publication, the investment in 2019 placed R&D NESTER in the list of the 100 companies that invested most in R&D activities in Portugal, in the category equivalent to SMEs.

For R&D Nester, this achievement is a sign of commitment towards its shareholders and country, in developing new and innovative solutions in the energy sector.

Currently, R&D NESTER is working in several R&D Projects, covering topics such as Renewable Integration, Flexibility, Cooperation TSO-DSO, Big Data, among others. The complete portfolio of finished and under development projects can be found here.

Regarding national results, in the year under review, total R&D expenditure in Portugal reached 2,992 million euros (1.40% of GDP), which represents an increase of about 8% compared to 2018.

In the ranking of thematic areas with the highest growth in R&D investment in 2019, compared to the previous year, the highlights were "Transport, Mobility and Logistics", with a variation of 32.3%, and "Energy", with an increase of 18.8%.

However, it is in the areas of "Information and communications technologies" and "Health" that most was invested in R&D, 23% and 19% of total expenditure, respectively.

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¹ The IPCTN is the official source of statistical information on R&D activities in Portugal. It is a survey of mandatory response, carried out in accordance with the criteria laid down at international level by Eurostat and OECD, with reference to the Frascati Manual.

R&D Nester partakes in the project FleXunity - "Power Flexible Communities Scaling-up project powered by Blockchain and AI", submitted to the European Commission's H2020 program and approved.

This project aims to develop commercially the concept of the energy community through the logical aggregation of consumers and distributed energy resources using AI and Blockchain.

FleXunity focuses on minimizing the cost of energy and optimizing the use of distributed renewables from the utility or community portfolio. Our energy community approach will promote active participation of end-users monetizing their flexibility and energy sharing, supported by secure transaction mechanisms with technologies such as blockchain. Below are some key figures associated with the project:

The key project outcomes will be achieved by testing and demonstrating the proposed services in two distinct pilots, in Iberia and in the UK, with very different market conditions:

On March 2021 was released the first issue of FleXunity's newsletter, where you can find the latest developments and details.

Also 2 brochures have also been published as part of this project. The last one was released recently in May.

FleXunity Website

FleXunity Project (R&D Nester website)

The World Energy Issues Monitor provides a snapshot of what keeps CEOs, Ministers and experts awake at night in over 100 countries. The Monitor helps to define the world energy agenda and its evolution over time. It provides a high-level perception of what constitute issues of critical uncertainty, in contrast to those that require immediate action or act as developing signals for the future.

This 12^th iteration of the World Energy Issues Monitor is based on insights of more than 2,500 energy leaders in 108 countries to provide 60 national assessments across six world regions. This year's report also asks energy leaders to highlight the priority issues for 2021 and how prepared their country is to handle different risks.

This year's survey reveals diversity in regional perceptions of preparedness to pandemic crisis, adding to the list of new energy shocks - cyber threats, extreme weather events (flooding, drought, ice and forest fires). Successful recovery planning will require resilience to be built-in to avoid new energy shocks.