Gestão de Recursos em Edifícios para Flexibilização da Potência Contratada



BeNeFiCE is a project, proposed by GECAD/ISEP that aims to address a relevant societal problem by improving the integration of renewable energy resources, consumption flexibility, storage system, electric vehicles (EVs), and flexible contracted power in collective residential buildings. The actual problem formulations for optimal energy resource management neither fully consider the contracted power flexibility nor exploring the advantages to look for a collective building with only one electrical customer. Therefore, The current project shall propose advances with new models and algorithms, including computational intelligence, which considers uncertainty while approaching different time scheduling horizons. Overall, BeNeFiCE should capture the interdependencies between energy resources and ultimately achieve optimal operation with higher integration of renewables in residential buildings, thus leading to more economic benefits for end-users.

Start Date: 1st June 2018
Duration: 38 months


  • Improving the integration of renewable energy resources in building context;
  • Explore the consumption flexibility, storage system, EVs, and flexible contracted power in collective residential buildings;
  • Propose new models and algorithms, including computational intelligence, which consider uncertainty while approaching different time scheduling horizons;
  • Evaluation of eventual economic benefits for tenants.


Work Packages (WP)

WP1: This WP aims to provide a smooth organization and coordination of BeNeFiCE tasks, ensuring the administrative and technical coordination of all them, in order to reach high quality of results to achieve a major impact. The progress will be monitored and tracked to manage the risk and guarantee that the required deliverables are reported and delivered properly.

WP2: The requirements and business models activity includes the preparatory tasks required for the scientific-technical development of the project, mainly concerning the models and methods that will be developed in WP1, WP2, and WP3. In this WP, the motivations and the project framework are explored to assure the contributions above the state of the art, guaranteeing the scientific validity. Different case studies will be analyzed based on existing solutions concerning energy management systems in buildings. Each use case will be analysed taking into account its specific functional requirements, which need to be explicitly identified. Use cases will describe the different application contexts and relevant business requirements and relevant actors, which will be the basis to the specification of the solution requirements, technical specifications, and architecture definition of the solution to be developed.

WP3: This WP includes an electrical consumer characterization framework supported by knowledge discovery in database. It is intended to identify typical load profiles (TLP) of residential consumers and to develop a rule set for the automatic classification of new consumers. To achieve a data-mining-based methodology several steps are required including data pre-processing (indeed, the quality of final decisions is directly related to the quality of data, which justifies the need for an initial data pre-processing step), clustering algorithms application, evaluation of the quality partition and also a classification model based on the resulting clusters in order to characterize new consumers.

WP4: WP4 proposes to support decisions and select which techniques are suited to aggregators needs for a certain moment. The selection of a forecasting method depends on many factors, such as the context of the forecast, the relevance and availability of historical data, the degree of accuracy desirable, the time period to be forecast and the time available for making the analysis. The focus of this activity is to present an overview of this field, by simulating different forecasting approaches, taking into consideration the type of the input data and, basically, exploring how to match method to problem. Scheduling problems associated to the storage systems and EVs charging will be considered.

WP5: In this task, the project team will research, study, and develop energy resources management models in order to provide efficient use of energy resources in residential buildings. Adequate energy resources management will be developed taking into consideration the generation and consumption (uncertainty task), storage systems and EV scheduling problem for different time horizons. This activity will provide the intelligent layer for the BeNeFiCE functioning assuring the resources optimization. The main goal will be the maximization of the building energy sources and costs minimization, while keeping the comfort levels and context awareness.

WP6: In this WP, a simulation and study analysis to test and validate the models and methods resulting from BeNeFiCE project is conducted. This activity includes scenarios and case studies definition. In this task, realistic case studies and scenarios will be defined to cover a wide set of situations that allow a suitable test and validation of the proposed models and methods. Whenever possible, realistic case studies will use real databases and additional scenarios based on assumptions will fill the gaps not covered by real data sources. The realistic scenarios and case studies will be used to assess the quality of the decision support provided to aggregator by the building energy management system, resulting from WP5.

WP7: This WP handles the communication and dissemination strategy to maximize the impact of the BeNeFiCE project results. It contains a dissemination and exploitation plan to create and exploit routes to maximize usage of the expected results and application concepts by business customers.