Abstract
This paper provides a survey of big data analytics applications and associated implementation issues. The emphasis is placed on applications that are novel and have demonstrated value to the industry, as illustrated using field data and practical applications. The paper reflects on the lessons learned from initial implementations, as well as ideas that are yet to be explored. The various data science trends treated in the literature are outlined, while experiences from applying them in the electricity grid setting are emphasized to pave the way for future applications. The paper ends with opportunities and challenges, as well as implementation goals and strategies for achieving impactful outcomes.

Abstract
The modern digital era is characterized by a plethora of emerging technologies, methodologies and techniques that are employed in the manufacturing industries with intent to improve productivity, to optimize processes and to reduce operational costs. Yet, algorithms and methodological approaches for improvement of energy consumption and environmental impact are not integrated with the current operational and planning tools used by manufacturing companies. One possible reason for this is the difficulty in bridging the gap between the most advanced energy related ICT tools, developed within the scope of the industry 4.0 era, and the legacy systems that support most manufacturing operational and planning processes. Consequently, this paper proposes a conceptual architecture model for a digital energy management platform, which is comprised of an IIoT-based platform, strongly supported by energy digital twin for interoperability and integrated with AI-based energy data-driven services. This conceptual architecture model enables companies to analyse their energy consumption behaviour, which allows for the understanding of the synergies among the variables that affect the energy demand, and to integrate this energy intelligence with their legacy systems in order to achieve a more sustainable energy demand. © 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the FAIM 2021.

Abstract
This paper proposes a Local Energy Market using a P2P blockchain-powered marketplace where agents bilaterally trade energy after the consumption and production period, and not before, as usual in electricity market design. The EU and MIBEL regulatory framework for Renewable Energy Communities potentially creates space for such a market, but some improvements in the settlement procedures and agent's participation must be met. © 2020 IEEE.

Abstract
The growing digitalisation, grid complexity and the number of digitally connected devices that communicate with systems in the distribution grid are enabling the continuous development of automation and intelligence, acquisition of data from sensors, meters and devices for monitoring and managing the distribution network, to achieve an enhanced, preventive, resilient and flexible network operation philosophy. This study presents a set of use cases towards the demonstration of the benefits of implementing a platform that collects, aggregates and facilitates horizontal integration and data correlation from various sources, enabling these use cases across the distribution grid. The adequacy analysis of current distribution network architecture considered derived requirements on the characterisation of its evolution taking advantage of key digital technologies, towards the implementation of distributed control and management strategies. It is also presented a benefit analysis of implementing a centralised common data and service platform, i.e. an internet of things (IoT) platform, regarding new functionalities and applications.

Abstract
This study offers an overview of the H2020 InterConnect project, which targets the relation between smart homes and distribution grids. The project vision is to produce a digital marketplace, using an interoperable marketplace toolbox and Smart appliances REference Ontology (SAREF) compliant Internet of Things (IoT) reference architecture as the main backbone, through which all SAREF-ized services, compliant devices, platform enablers and applications can be downloaded onto IoT and smart grid digital platforms. Energy users in buildings, either residential or non-residential, manufacturers, distribution grid operators and the energy retailers will work together towards the demonstration of the smart energy management solutions in seven connected large-scale test-sites in Portugal, Belgium, Germany, the Netherlands, Italy, Greece and France. This study depicts how InterConnect project will enhance the relation and the interconnectivity between smart buildings and grids safeguarding the definition of the role of each stakeholder in energy and non-energy services.

Abstract
<p>Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The International Energy Agency (IEA) Wind Task on Wind Power Forecasting organises international collaboration, among national weather centres with an interest and/or large projects on wind forecast improvements (NOAA, DWD, UK MetOffice, ...), forecast vendors and forecast users.<br>Collaboration is open to IEA Wind member states, 12 countries are already therein.</p><p>The Task is divided in three work packages: Firstly, a collaboration on the improvement of the scientific basis for the wind predictions themselves. This includes numerical weather prediction model physics, but also widely distributed information on accessible datasets. Secondly, we will be aiming at an international pre-standard (an IEA Recommended Practice) on benchmarking and comparing wind power forecasts, including probabilistic forecasts. This WP will also organise benchmarks for NWP models. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions.</p><p>The main result is the IEA Recommended Practice for Selecting Renewable Power Forecasting Solutions. This document in three parts (Forecast solution selection process, and Designing and executing forecasting benchmarks and trials, and their Evaluation) takes its outset from the recurrent problem at forecast user companies of how to choose a forecast vendor. The first report describes how to tackle the general situation, while the second report specifically describes how to set up a forecasting trial so that the result is what the client intended. Many of the pitfalls which we have seen over the years, are avoided. <br><br>Other results include a paper on possible uses of uncertainty forecasts, an assessment of the uncertainty chain within the forecasts, and meteorological data on an information portal for wind power forecasting. This meteorological data is used for a benchmark exercise, to be announced at the conference. The poster will present the latest developments from the Task, and announce the next activities.</p>