Energy demand prediction for the implementation of an energy tariff emulator to trigger demand response in buildings

Buildings are key actors of the electrical gird. As such they have an important role to play in grid stabilization, especially in a context where renewable energies are mandated to become an increasingly important part of the energy mix. Demand response provides a mechanism to reduce or displace electrical demand to better match electrical production. Buildings can be a pool of flexibility for the grid to operate more efficiently. One of the ways to obtain flexibility from building managers and building users is the introduction of variable energy prices which evolve depending on the expected load and energy generation. In the proposed scenario, the wholesale energy price of electricity, a load prediction, and the elasticity of consumers are used by an energy tariff emulator to predict prices to trigger end user flexibility. In this paper, a cluster analysis to classify users is performed and an aggregated energy prediction is realised using Random Forest machine learning algorithm.This paper is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 768614. This paper reflects only the author´s views and neither the Agency nor the Commission are responsible for any use that may be made of the information contained therein

Analysis of building energy upgrade technologies for implementing the dual energy efficiency and demand response scheme for non-residential buildings

The continuous growth of renewable energy and the transition to a more de-centralised electricity generation adds significant complexity to balance power supply and demand in the grid. These imbalances are partially compensated by demand response programs, which represent a new business opportunity in the building sector, especially for ESCOs. Including demand response to their traditional energy efficiency-based business model adds an additional revenue stream that could potentially shorten payback periods of energy renovation projects. This paper introduces this new dual-services business model, and evaluates the potential suitability of HVAC, generation and storage technologies to ensure proposed energy efficiency and flexibility goals.This paper is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 745594. This paper reflects only the author´s views and neither the Agency nor the Commission are responsible for any use that may be made of the information contained therei

Smart Building: The Tecnalia KUBIK Use Case

Buildings have long been equipped with sensors and actuators to automate their control. Smart buildings are those whose facilities and systems (air condition ing, heating, lighting, access control systems, etc.) allow integrated and automated building management and control to increase energy efficiency, security, and usabil ity. With the democratization of the Internet of Things (IoT), the number of sensors and actuators is constantly increasing, giving ways to new applications. The reduc tion of sensors and actuators cost is driving a digital shift in the building sector.EUROPEAN COMMISSION H2020, 780351, ENAC

two software tools for facilitating the choice of ground source heat pumps by stakeholders and designers

For promoting the diffusion of GSHP and making the technology more accessible to the general public, in the H2020 research project "CHeap and Efficient APplication of reliable Ground Source Heat exchangers and PumpS" (acronym Cheap-GSHPs) a tool for sizing these systems has been developed, as well as a Decision Support System (DSS) able to assist the user in the preliminary design of the most suitable configuration. For all these tools a common platform has been carried out considering climatic conditions, energy demand of buildings, ground thermal properties, heat pump solutions repository, as well as renewable energy database to use in synergy with the GSHPs. Since the aims of the tools are different, there are different approaches. The design tool is mainly addressed to designers. The calculation may be done in two ways: with a simplified method based on the ASHRAE approach and with a detailed calculation based on the numerical tool CaRM (Capacity-Resistance method). The DSS final aim is to support decision-making, by providing the stakeholders at all the level with a series of scenario. The Cheap-GSHPs project has developed a DSS tool aimed at accelerating the decision-making process of designers and building owners as well as increasing market share of the Cheap-GSHPs technologies. Hence the DSS generates different possible solutions based on a defined general problem, identifying the optimal solution. Both tools are presented in the paper, showing the potentialities provided by both software

Two software tools for facilitating the choice of ground source heat pumps by stakeholders and designers

For promoting the diffusion of GSHP and making the technology more accessible to the general public, in the H2020 research project “CHeap and Efficient APplication of reliable Ground Source Heat exchangers and PumpS” (acronym Cheap-GSHPs) a tool for sizing these systems has been developed, as well as a Decision Support System (DSS) able to assist the user in the preliminary design of the most suitable configuration. For all these tools a common platform has been carried out considering climatic conditions, energy demand of buildings, ground thermal properties, heat pump solutions repository, as well as renewable energy database to use in synergy with the GSHPs. Since the aims of the tools are different, there are different approaches. The design tool is mainly addressed to designers. The calculation may be done in two ways: with a simplified method based on the ASHRAE approach and with a detailed calculation based on the numerical tool CaRM (Capacity-Resistance method). The DSS final aim is to support decision-making, by providing the stakeholders at all the level with a series of scenario. The Cheap-GSHPs project has developed a DSS tool aimed at accelerating the decision-making process of designers and building owners as well as increasing market share of the Cheap-GSHPs technologies. Hence the DSS generates different possible solutions based on a defined general problem, identifying the optimal solution. Both tools are presented in the paper, showing the potentialities provided by both software