Abstract-Energy communities and peer-to-peer energy exchanges are expected to play an important role in the energy transition. In this context, the blockchain approach can be employed to foster this decentralized energy market. Our goal is to determine the design that should allow a Distribution System Operator (DSO) to accept peer-to-peer energy exchanges based on a distributed ledger supported by the blockchain technology. To this end, we will evaluate several designs based on criteria such as acceptance of the wholesale/retail market, the resilience of the consensus to approve a block, the accuracy, traceability, privacy and security of the proposed schemes.

Renewable Energy Communities consist in an emerging decentralized market mechanism which allows local energy exchanges between end-users, bypassing the traditional wholesale/retail market structure. In that configuration, local consumers and prosumers gather in communities and can either cooperate or compete towards a common objective, such as the minimization of the electricity costs and/or the minimization of greenhouse gas emissions for instance. This paper proposes data analytics modules which aim at helping the community members to schedule the usage of their resources (generation and consumption) in order to minimize their electricity bill. A day-ahead local wind power forecasting algorithm, which relies on state-of-the-art Machine Learning techniques currently used in worldwide forecasting contests, is in that way proposed. We develop furthermore an original method to improve the performance of neural network forecasting models in presence of abnormal wind power data. A technique for computing representative profiles of the community members electricity consumption is also presented. The proposed techniques are tested and deployed operationally on a pilot Renewable Energy Community established on an Medium Voltage network in Belgium, involving 2.25MW of wind and 18 Small and Medium Enterprises who had the possibility to freely access the results of the developed data modules by connecting to a dedicated web platform. We first show that our method for dealing with abnormal wind power data improves the forecasting accuracy by 10% in terms of Root Mean Square Error. The impact of the developed data modules on the consumption behaviour of the community members is then quantified, by analyzing the evolution of their monthly self-consumption and self-sufficiency during the pilot. No significant changes in the members behaviour, in relation with the information provided by the models, were observed in the recorded data. The pilot was however perturbed by the COVID-19 crisis which had a significant impact on the economic activity of the involved companies. We conclude by providing recommendations for the future set up of similar communities.

a b s t r a c tWe propose a pragmatic procedure to facilitate the connection process of Distributed Generation (DG) with reference to the European regulatory framework where Distribution System Operators (DSOs) are, except in specific cases, not allowed to own their generation. The procedure is termed Global Capacity ANnouncement (GCAN) and is intended to compute the estimates of maximum generation connection amount at appropriate substations in a distribution system, to help generation connection decisions. The pragmatism of the proposed procedure stems from its reliance on the tools that are routinely used in distribution systems planning and operation, and their use such that the possibilities of network sterilization are avoided. The tools involved include: long-term load forecasting, longterm planning of network extension/reinforcement, network reconfiguration, and power flow. Network sterilizing substations are identified through repeated power flow computations. The proposed procedure is supported by results using an artificially created 5-bus test system, the IEEE 33-bus test system, and a part of real-life distribution system of ORES (a Belgian DSO serving a large portion of the Walloon region in Belgium).

The main goal of the E-Cloud, as with every microgrid, is to maximize the consumption of energy produced locally. To reach this goal, based on consumption profiles of customers willing to participate in the E-cloud and given some local restrictions (e.g. wind turbines cannot be put everywhere), an optimal mix of green generation sources (in kW) and local storage (in kWh) needs to be computed. Then according to this computation, the required generating units and storage device are installed. A repartition mechanism grants the customer a share of the generated electricity and storage capacity. These shares are either computed offline, or dynamically adapted on line. The project will test two models: either the DSO or a producer owns and operates the storage device. Two flows of information (real-time for operation of the storage facility and ex-post for its settlement) are needed to correctly manage the E-Cloud and to ensure correct information exchange with the wholesale market. These information flows are completed thanks to a forecast that provides members of the E-Cloud the full capability to anticipate and obtain the maximum benefits of the local generation. The expected benefits for the customer are a reduction of their electricity bill by a minimum of 10%. Societal benefits should also arise: 1) easing the technical integration of renewables' generation embedded in the distribution network, and 2) avoids extra investment on the DSO network. The E-Cloud may also ensure new revenue for the DSO thanks to new services provided to the E-Cloud community.

The blockchain technology allows interested parties to access a common register, the update, and integrity of which are collectively managed in a decentralized manner by a network of actors. It is the consensus protocol that ensures a common and unambiguous update of transactions by creating blocks of transactions for which integrity, veracity, and consistency are guaranteed through geographically distributed nodes. Bitcoin, the first popular blockchain concept, introduced the Proof of Work consensus based on work validation, and has been extended to thousands of participants. Despite its success and its large use in other crypto-currencies, Proof of Work's disadvantages are a high latency, a low transaction rate, and a high energy expenditure, making it a less-than-perfect choice for many applications. In addition the validation of transactions is not carried out with a definite temporality. For Bitcoin, it takes on average 10 minutes to create a block. However, for certain use cases such as auctions or the exchange of energy, there is a need for this temporality. The purpose of this article is to propose a new type of consensus that is faster, less energy-consuming and that can be synchronized with a time reference. The core of the reflection is the use of the Condorcet voting mechanism to determine the miner.