• Energy Research

Abstract In the context of European efforts to reduce energy consumption and CO2 emissions in the building sector, the second recast of the Energy Performance of Buildings Directive promotes the acceleration of the energy renovation of European building stock. To do this, a cost optimization is necessary to find the best combination of energy efficiency measures which minimize the global cost during the entire life-cycle of the building, as suggested in the first recast of the same Directive. Since a great number of combinations must be analyzed, an automated procedure is necessary to reduce the calculation time. In this work, an iterative input-output process is set, thanks to the coupling of a dynamic energy simulation software (TRNSYS) and a generic optimization software (GenOpt). The cost optimization is applied to a new social housing construction – a multi-family building located in Northern Italy. The methodology that was adopted allows the simultaneous optimization of both the building energy demand (building envelope) and the building energy supply (technical systems and renewable sources). Results are compared with those obtained using a more widespread sequential approach whose purpose is firstly the optimization of one of these two factors, and subsequently the optimization of the other one. This study has demonstrated that an integrated approach allows a larger number of possible combinations of energy efficiency measures to be explored with respect to the sequential approach.

In the current context of joint efforts towards the decarbonisation of buildings, integrating occupants’ comfort and health with latest technological advancements for energy efficiency is at the center of the latest development of research, policies and professional practice. Radiant systems are encountering great success since the low-thickness systems can also be used in renovation projects for both heating and cooling, while guaranteeing optimal comfort. However, dehumidification is often required for optimal radiant cooling operation with no condensation risks, and the great potential of mechanical ventilation systems to optimally address the needs for dehumidification, air renewal, health and energy efficiency appears to be far from its full exploitation in the post-COVID-19 era. The present paper aims at providing a quantification of the energy and financial impacts of the implementation of a controlled mechanical ventilation system (CMV) coupled to a radiant system in a typical residential case study building in Italy. The results show that the sole CMV may decrease primary energy demand and energy costs by more than 30% and contribute to an increase in the smart readiness of the building by 8%, but further incentive policies must be developed to cover the still high investment and maintenance cost.

Abstract In order to meet European targets for decarbonisation in 2050, the amount of building energy needs that must be covered through RES is going to increase. Considering the increasing needs for space cooling, mainly due to climate change, technical solutions involving renewable sources of energy for cooling purposes are of great interest. Solar absorption chillers represent a valid answer, but their use in the residential sector is at early stage. This work explores the ability of a solar cooling system to meet the summer energy demand of a multi-family building located in the Mediterranean area. An energy model was developed in TRNSYS® and a simulation-based optimization framework was used to optimize the system design, maximize its energy benefits and relate energy performance to investment and operational costs. The resulting optimal design has reduced the initial non-renewable primary energy demand by 48%, increasing the renewable energy ratio up to 83%. Results demonstrate the ability of the proposed approach to support valuable design choices in this field and reveal the potential of solar cooling to reach the NZEB target in view of future climate change and the future developments of energy requirements for buildings.

Abstract Nowadays, the design of energy efficient and comfortable building results as the solution to a complex optimization that involves a great number of interdependent variables. In such a complex system that is characterized by many requirements, sometimes conflicting, the use of an integrated design approach can speed up the design process, allow evaluating and comparing a great number of design options and lead to optimized performance at multiple levels. We present the conception of a replicable methodology, including the integrated tools and metrics, for supporting the integrated design of the building envelope, aiming at minimizing the building total energy demand (resulting from the sum of heating, cooling and lighting energy needs) in a thermal and visual comfort context. The methodology relies on a simulation-based optimization process. For each of the two thousand of design solutions that are analyzed within the design space of the problem, the thermal and visual comfort conditions are evaluated at the same time. A “filter” approach is used for combining the different objectives. The methodology is applied to the design of a school classroom as a reference case study. Results are compared for four different building orientations and two different climatic conditions. The differences in design between the optimized building configurations in the different location and orientation emerge from the study, however resulting in similar energy performance (total primary energy demands in the range 78.6–82.8 kWh/m2y for Turin and 57.7–60.1 for Palermo). In all cases, energy-optimal solutions result as nearly optimal also from the comfort point of view, which demonstrate the validity of the implemented total energy approach. Beyond the numerical results, we provide an effective integrated methodology that is able to support designers in defining a unique energy and comfort optimized solution to be implemented in the real design analyzing the design space and determining the optimal set of passive solutions to minimize the total energy needs of a building in a context of good comfort conditions, going beyond the Pareto optimality concept and without dealing through complex multi-objective optimization processes.

In the context of increasing energy demands and the integration of renewable energy sources, this review focuses on recent advancements in energy storage control strategies from 2016 to the present, evaluating both experimental and simulation studies at component, system, building, and district scales. Out of 426 papers screened, 147 were assessed for eligibility, with 56 included in the final review. As a first outcome, this work proposes a novel classification and taxonomy update for advanced storage control systems, aiming to bridge the gap between theoretical research and practical implementation. Furthermore, the study emphasizes experimental case studies, moving beyond numerical analyses to provide practical insights. It investigates how the literature on energy storage is enhancing building flexibility and resilience, highlighting the application of advanced algorithms and artificial intelligence methods and their impact on energy and financial savings. By exploring the correlation between control algorithms and the resulting benefits, this review provides a comprehensive analysis of the current state and future perspectives of energy storage control in smart grids and buildings.