Project

Ebalance-plus (www.ebalanceplus.eu)

Goal: The Ebalance-plus project aims to increase and predict the available energy flexibility of distribution grids and increase grid resilience.

This is done by developing and deploying an energy-balancing platform that integrates technologies from various electricity domains, enhances grid observability and predictability and at the same time supports electric operators and energy end-users with tailored user interfaces.

The European Union supports the project within the Horizon 2020 framework programme. https://www.ebalanceplus.eu/

Date: 1 February 2020 - 1 July 2023

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Project log

Pasquale Vizza
added a research item
The recent forecasts regarding the penetration of electric vehicles (EVs) in the transport market and their impact on national electricity distribution grids has presented new challenges in the fields of both of application and research. In this context, vehicle-to-grid (V2G) technology presents itself as an extremely valid solution in terms of application of the "demand side flexibility" paradigm. In this context, the aim of the paper is to analyze from a technical and economical point of view the use of EVs as new flexibility resources to provide network flexibility services in an Italian framework. Within this scope, a methodology for evaluating the flexibility service that a single EV or an EV fleet can offer, and therefore for estimating the EV storage system charge and discharge profile and determining its economic benefit, is proposed. Some numerical results and observations are reported to highlight possible incentive mechanisms for motivating EV end-users to offer flexibility services.
Krzysztof Piotrowski
added 2 research items
Currently, ensuring the correct functioning of the electrical grid is an important issue in terms of maintaining the normative voltage parameters and local line overloads. The unpredictability of Renewable Energy Sources (RES), the occurrence of the phenomenon of peak demand, as well as exceeding the voltage level above the nominal values in a smart grid makes it justifiable to conduct further research in this field. The article presents the results of simulation tests and experimental laboratory tests of an electricity management system in order to reduce excessively high grid load or reduce excessively high grid voltage values resulting from increased production of prosumer RES. The research is based on the Elastic Energy Management (EEM) algorithm for smart appliances (SA) using IoT (Internet of Things) technology. The data for the algorithm was obtained from a message broker that implements the Message Queue Telemetry Transport (MQTT) protocol. The complexity of selecting power settings for SA in the EEM algorithm required the use of a solution that is applied to the NP difficult problem class. For this purpose, the Greedy Randomized Adaptive Search Procedure (GRASP) was used in the EEM algorithm. The presented results of the simulation and experiment confirmed the possibility of regulating the network voltage by the Elastic Energy Management algorithm in the event of voltage fluctuations related to excessive load or local generation.
The growing penetration of Renewable Energy Sources (RES) due to the transition to future smart grid requires a huge number of power converters that participate in the power flow. Each of these devices needs the use of a complex control and communication system, thus a platform for testing real-life scenarios is necessary. Several test techniques have been so far proposed that are subject to a trade-off between cost, test coverage, and test fidelity. This paper presents an approach for testing microgrids, by developing an emulator, with emphasis on the micro-inverter unit and the possibility of flexible configuration for different grid topologies. In contrast to other approaches, our testbed is characterized by small volume and significantly scaled-down voltages for safety purposes. The examination is concentrated specifically on the inverter behavior. The test scenarios include behaviors in case of load changes, transition between grid-tied and islanded mode, connection and removal of subsequent inverters, and prioritization of inverters.
Pasquale Vizza
added a research item
The integration of renewable energy sources is one of the principal issues of the electric power system. The ebalance-plus project to achieve this goal will implement and test a management energy platform and new business models. Such solutions will be tested in four demo sites located in Spain, Denmark, France, and Italy. The Italian demo site is considered in this paper. After the first part, in which the configuration of the Italian demo site is described, the technological solutions implemented to provide energy flexibility are listed.
Krzysztof Piotrowski
added a research item
Ensuring flexibility and security in power systems requires the use of appropriate management measures on the demand side. The article presents the results of work related to energy management in households in which renewable energy sources (RES)can be installed. The main part of the article is about the developed elastic energy management algorithm (EEM), consisting of two algorithms, EEM1 and EEM2. The EEM1 algorithm is activated in time periods with a higher energy price. Its purpose is to reduce the power consumed by the appliances to the level defined by the consumer. In contrast, the EEM2 algorithm is run by the Distribution System Operator (DSO) when peak demand occurs. Its purpose is to reduce the power of appliances in a specified time period to the level defined by the DSO. The optimization tasks in both algorithms are based on the Greedy Randomized Adaptive Search Procedure (GRASP) metaheuristic algorithm. The EEM1 and EEM2 algorithms also provide energy consumer comfort. For this purpose, both algorithms take into account the smart appliance parameters proposed in the article: sections of the working devices, power reduction levels, priorities and enablingof time shifting devices. The EEM algorithm in its operation also takes into account the information about the production of power, e.g., generated by the photovoltaic systems. On this basis, it makes decisions on the control of smart appliances. The EEM algorithm also enables inverter control to limit the power transferred from the photovoltaic system to the energy system. Such action is taken on the basis of the DSO request containing the information on the power limits. Such a structure of EEM enables the balancing of energy demand and supply. The possibility of peak demand phenomenon will be reduced. The simulation and experiment results presented in the paper confirmed the rationality and effectiveness of the EEM algorithm.
Mara J. van Welie
added a project goal
The Ebalance-plus project aims to increase and predict the available energy flexibility of distribution grids and increase grid resilience.
This is done by developing and deploying an energy-balancing platform that integrates technologies from various electricity domains, enhances grid observability and predictability and at the same time supports electric operators and energy end-users with tailored user interfaces.
The European Union supports the project within the Horizon 2020 framework programme. https://www.ebalanceplus.eu/