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This work presents an optimization strategy and the cost-optimal design of an off-grid building served by an energy system involving solar technologies, thermal and electrochemical storages. Independently from the multi-objective method (e.g., utility function) and algorithm used (e.g., genetic algorithms), the optimization of this kind of systems is typically characterized by a high-dimensional variables space, computational effort and results uncertainty (e.g., local minimum solutions). Instead of focusing on advanced optimization tools to handle the design problem, the dimension of the full problem has been reduced, only considering the design variables with a high "effect" on the objective functions. An off-grid accommodation building is presented as test case: the original six-variable design problem consisting of about 300,000 possible configurations is reduced to a two-variable problem, after the analysis of 870 Monte Carlo simulations. The new problem includes only 220 possible design alternatives with a clear benefit for the multi-objective optimization algorithm. The energy-economy Pareto frontiers obtained by the original and the reduced problems overlap, showing the validity of the proposed methodology. The No-RES (no renewable energy sources) primary energy consumption can be reduced up to almost 0 kWh/(m2yr) and the net present value (NPV) after 20 years can reach 70 k€ depending on the number of photovoltaic panels and electrochemical storage size. The reduction of the problem also allows for a plain analysis of the results and the drawing of handy decision charts to help the investor/designer in finding the best design according to the specific investment availability and target performances. The configurations on the Pareto frontier are characterized by a notable electrical overproduction and a ratio between the two main design variables that goes from 4 to 8 h. A sensitivity analysis to the unitary price of the electrochemical storage reveals the robustness of the sizing criterion. [ABSTRACT FROM AUTHOR]

Micro-district heating networks based on cogeneration plants and renewable energy technologies are considered efficient, viable and environmentally-friendly solutions to realizing smart multi-energy microgrids. Nonetheless, the energy production from renewable sources is intermittent and stochastic, and cogeneration units are characterized by fixed power-to-heat ratios, which are incompatible with fluctuating thermal and electric demands. These drawbacks can be partially overcome by smart operational controls that are capable of maximizing the energy system performance. Moreover, electrically driven heat pumps may add flexibility to the system, by shifting thermal loads into electric loads. In this paper, a novel configuration for smart multi-energy microgrids, which combines centralized and distributed energy units is proposed. A centralized cogeneration system, consisting of an internal combustion engine is connected to a micro-district heating network. Distributed electric heat pumps assist the thermal production at the building level, giving operational flexibility to the system and supporting the integration of renewable energy technologies, i.e., wind turbines, photovoltaic panels, and solar thermal collectors. The proposed configuration was tested in a hypothetical case study, namely, a University Campus located in Trieste, Italy. The system operation is based on a cost-optimal control strategy and the effect of the size of the cogeneration unit and heat pumps was investigated. A comparison with a conventional configuration, without distributed heat pumps, was also performed. The results show that the proposed configuration outperformed the conventional one, leading to a total-cost saving of around 8%, a carbon emission reduction of 11%, and a primary energy saving of 8%. [ABSTRACT FROM AUTHOR]

Renewable Energy Communities (RECs) are increasingly recognised as potential tools for promoting the adoption of Renewable Energy Sources (RES). However, their success depends on the energy flexibility of participants – that is, their willingness to adjust habits to better align with energy production and loads. This study aims to provide insights into whether participation in a REC can enhance users' flexibility compared to individual prosumers. Our analysis is grounded in an experiment conducted with 192 young adults, using a web-based serious game developed specifically for this study. The results of a logit regression analysis suggest that the sense of belonging to a REC increases flexibility when combined with peer pressure. Control variables such as environmental or ethical concern are also found to influence energy flexibility. These findings provide useful suggestions for policymakers and energy managers in promoting renewable energy sources and sustainable energy practices. [ABSTRACT FROM AUTHOR]

The scientific literature lacks methodologies for assessing HRES investments because of complex interactions among HRES components, conflicting objectives, and uncertainty in the energy demand. This work fills this gap by presenting a methodology to assess long-term investments in HRES for off-grid buildings. To strengthen the reliability of the assessment, the methodology exploits an HRES optimal synthesis, sizing and operation simulating the system and embodying the interactions among HRES components for both electrical and heat generation, the building loads evaluation, and the verification of the effect of uncertainties in the energy demand. These aspects have already been investigated, but, to our best knowledge, have never been considered in a concurrent and integrated way. The resulting designs are optimised through an NSGA-II algorithm that minimises the system CO 2 emissions and differential cost with respect to a solution that does not use renewable energy sources. The soundness of the solutions is evaluated through a scenario analysis and a sensitivity analysis using the Morris method. The applicability of the proposal was verified through a case study in an off-grid facility, showing possible savings up to 47 k€ and 320 t CO 2. The methodology is thus strongly consistent with the building decarbonisation addresses set by the policymakers. • The methodology optimises HRES synthesis, sizing and control in off-grid building. • The methodology is applied to a case study of a farm hostel in Italy. • The Pareto frontier is created considering environmental and economic aspects. • Five optimal solutions are analysed, distinct for total costs and caused emissions. • Scenario and sensitivity analyses corroborate the robustness of the solutions. [ABSTRACT FROM AUTHOR]