We introduce the Python-based open-source library Energym, a building model library to test and benchmark building controllers. The incorporated building models are presented with a brief explanation of their function, location and technical equipment. Furthermore, the library structure is described, highlighting the necessary features to provide the benchmarking and control capabilities, i.e., standardized evaluation scenarios, key performance indicators (KPIs) and forecasts of uncertain variables. We go on to characterize the evaluation scenarios for each of the models and give formal definitions of the KPIs. We describe the calibration methodologies used for constructing the models and illustrate their usage through examples.

The electricity sector foresees a significant change in the way energy is generated and distributed in the coming years. With the increasing penetration of renewable energy sources, smart algorithms can determine the difference about how and when energy is produced or consumed by residential districts. However, managing and implementing energy demand response, in particular energy flexibility activations, in real case studies still presents issues to be solved. This study, within the framework of the European project “SABINA H2020”, addresses the development of a multi-level optimization algorithm that has been tested in a semi-virtual real-time configuration. Results from a two-day test show the potential of building’s flexibility and highlight its complexity. Results show how the first level algorithm goal to reduce the energy injected to the grid is accomplished as well as the energy consumption shift from nighttime to daytime hours. As conclusion, the study demonstrates the feasibility of such kind of configurations and puts the basis for real test site implementation.

HVAC systems are becoming increasingly important around the world due to the increasing need for climatization in recent years. While district heating systems have been used for a long time, district cooling systems tend to be something that is only reserved for large buildings, making decentralized cooling flourish, shaping the idea of considering it as the first choice when it comes to cooling devices, disregarding the efficiency of larger systems. This article compares two technologies for district energy solutions. One option features single-stage absorption chillers using solar thermal technologies (Fresnel collectors) for heat, while the other uses high-efficiency compression chillers with photovoltaic technologies. Parametric studies were used to determine system sizes and considerations were taken to perform such as comparison. This paper concludes that compression chillers are the better option for cooling systems with variable demand while absorption chillers are a good choice for systems with constant demand, like data centers, especially when there is a high-temperature heat source available.

This project works towards developing a simulation tool using TRNSYS (TRaNsient SYstems Simulation Program) software. Through the implementation of different technologies with a compartmentation method in the software (the use of macros), different combinations of these technologies are to be developed and combined in more complex structures (to be called decks). In this paper an example of these combinations will be shown and evaluated.