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This paper presents a review study of energy communities (ECs) in Europe, and discusses the future development of such communities in Europe – both related to energy technologies, energy carriers, regional conditions (North, Central and South of Europe), emerging regulatory development etc. From the analysis, it emerged that the future ECs in Europe will focus on utilizing local renewable energy sources (sun, wind, run of river, biogas, biomass), for covering all or part of the energy consumption for end-use customers. The ECs can be a sustainable alternative to large power plants based on fossil fuels. This is also linked to the emerging regulatory developments started when European Commission introduced such concepts in the "Clean Energy for all Europeans" package. The main goal of eNeuron H2020 project is to develop innovative tools for the optimal design and operation of ECs, integrating distributed energy resources and multiple energy carriers at different scales. Paper accepted at EEM2022 Conference

In this paper, a multi-objective Energy Management System (EMS) for polygeneration microgrids is presented. The proposed tool has been developed within the LIVING GRID project, funded by the Italian Ministry of Research (actions related to the Italian Technology Cluster on Energy), and it is characterized by a detailed representation of generation units and flexible loads, as well as electric/thermal networks and storage systems that can be present in microgrids and sustainable districts. An optimization model has been developed in which the objective function is related to the minimization of costs and emissions, and the maximization of the overall exergy efficiency of the system. The decision model is applied to a real case study represented by the Savona Campus of the University of Genoa in Italy.

The purpose of this Deliverable is to provide a comprehensive understanding of the current conditions for the uptake of renewable based community energy in selected target regions in Belgium, Germany, Italy, Latvia, the Netherlands, Norway, Poland, Portugal and Spain. Our focus on renewable community energy follows the definitions of RED II (Art. 2 (16)) where energy communities are characterised by open and active participation and control from natural persons, small or medium enterprises and local authorities, and where the primary purpose is to provide environmental, economic or social community benefits for its shareholders or members or for the local areas where it operates, rather than financial profits.

Due to their intrinsic intermittent and random nature, renewable energy sources can dramatically influence the short-term scheduling of distributed energy resources (DER) and if their uncertainties are not properly handled, the operation strategies of DER may deviate from the optimal ones. In order to overcome this issue, this paper presents a comprehensive method for modeling uncertainties of solar power generation through a scenario-generation approach and historical data for a specific area of interest. The proposed approach is particularly suitable to be used in smart grid environment for stochastic operation optimization of DER. The Roulette Wheel mechanism has been used for generating an initial set of scenarios, and a reduction process based on Fast Forward method has been then applied in order to preserve the most representative ones, while reducing the computational efforts of next potential stochastic optimization phase. A sensitivity analysis has been carried out to evaluate the effects of key parameters on the solar irradiance generated scenarios. The results could be useful as a guide to tune scenarios' generation process aimed at obtaining scenarios with specific characteristics. Moreover, case study results show that the proposed method allows generating plausible scenarios for solar power generation to be used as input for DER stochastic optimization purposes. Moreover, its high flexibility allows to estimate the behavior of stochastic operation optimization of DER in the presence of more fluctuating, but ever plausible, solar irradiance patterns.

Electricity load forecasting plays an important role in planning and a vital role in the operational management of an electric power system based on smart grids. In this work, several data-driven approaches are used to forecast the individual electricity demand for the subsequent hour of three Italian households in a nanogrid context. For each user, the tested prediction models exploit only the historic series of total electricity consumption. The results show similar performances in all models implemented. Despite a widespread delay, the predictions follow the measurement trend well, while also highlighting the particular difficulty of predicting peak values.

Recently, hybrid multi-energy systems consisting of multiple generation, conversion, and storage technologies have been receiving great attention as a promising option to meet the multi-energy demands of residential end-users, by transforming them from passive consumers to active prosumers, who both produce and consume energy. The design problem of such systems is challenging due to the large number of degrees of freedom in the design and operation phases, so the system as a whole must be optimized. Moreover, both economic and low-carbon priorities should be considered in the design problem to foster an effective implementation and deployment. The aim of this paper was to present a methodology for the optimal design of multi-energy nanogrids (MENs) operating in grid-connected and islanded modes. Based on a pre-defined MEN superstructure, a multi-objective linear problem was established to find the types and sizes of the technologies in the MEN, with the aim to reduce the total annual cost and the fossil primary energy input, while satisfying the assigned time-varying user multi-energy demand. With reference to the latter, the thermal behavior of the building was simulated by using the dynamic simulation software TRNSYS. The Pareto frontier was found by minimizing a weighted sum of the total annual cost and fossil primary energy input, and the problem was solved by using branch-and-cut. In the numerical testing, a single-family house of 200 m2 located in Italy was considered as the residential end-user. Results show the effectiveness of the model for providing good balancing solutions for end-users based on economic and energetic priorities. Moreover, it was found that the MEN operating in grid-connected mode showed economic and environmental performances much better than those found for the configuration operating in islanded mode.

In this work, the results coming from the schedule optimization of a residential natural gas-fired CHP system operating according to a novel heat-driven operation strategy, based on the possibility to dump part of the thermal energy produced by the CHP system, are compared with the ones relative to the case in which the CHP system operates following a heat-driven strategy allowing load partialization. The effects of the variation of the size of the thermal energy storage system on the optimization results are also investigated. The simulation of the two different operation strategies has been realized using a numerical code written in Matlab environment, and a heuristic algorithm has been used for the economic optimization of the operation relative to both the implemented strategies. From the economic point of view, results show that the difference between the best CHP system configuration in the case with heat dumping and the one relative to the case with load partialization is minimal, with the latter presenting a slightly higher economic performance. Moreover, conditions in which heat dumping could yield higher economic performances than load partialization are also presented in this work. As concerns pollutants emissions, results show that the impact of load partialization on a local scale is much higher, with CO emissions that can be up to three times the ones relative to conventional systems for the separate generation of electricity and heat. © 2016 Elsevier Ltd

Thermal energy storage systems have increasingly attracted researchers and engineers in the last decades, not only because they permit to overcome the mismatch between thermal energy supply and demand in solar thermal systems, but also because they have the potential to improve the power grid reliability and flexibility, as they allow, for example, to store the heat or the cooling energy produced by residential electric heat pumps for a later use. In this context, this work analyses the cooling energy charging and discharging of two different cold thermal energy storage units, based on the use of a phase change material (PCM), by numerical simulation. One unit consists of an aluminum cylindrical container partially filled with a biological PCM. The other one is similar, with the only difference that it also includes an aluminum metal foam immersed in the PCM. Two different 2D axisymmetric models have been developed, both based on the effective heat capacity method in order to account for the PCM latent heat, for the numerical simulation of the two different units, and the numerical results are compared with experimental ones, obtained by means of a climatic chamber, in order to assess, in each case, the best set of the model arbitrary parameters among the considered ones. Moreover, for each simulation model, a sensitivity analysis is performed to show the effects of two arbitrary model parameters on the numerical results. Simulation results relative to the unit with only the PCM indicate that the cooling energy charging is most affected by conductive heat transfer, and in particular by the thermally resistive layer of solid PCM that forms at the lateral wall of the aluminum container, and that heat transfer by free convection plays a crucial role in the cooling energy discharging process. As concerns the unit with the PCM and the aluminum foam, numerical results show that the charging process and the discharging one are about four times and two times faster than without the foam, respectively. Furthermore, numerical results show that, with the employed aluminum foam, free convection within the PCM is negligible in both the cooling energy charging and discharging process.

Thermal energy storage systems can be determinant for an effective use of solar energy, as they allow to decouple the thermal energy production by the solar source from thermal loads, and thus allowing solar energy to be exploited also during nighttime and cloudy periods. The current study deals with the modelling and simulation of a cooling thermal energy storage unit consisting of an aluminum container partially filled with a phase change material (PCM). Two unsteady models are implemented and discussed, namely a conduction-based model and a conduction-convection-based one. The equations systems relative to both the models are solved by means of the Comsol Multiphysics finite element solver, and results are presented in terms of temporal variation of temperature in different points inside the PCM, of the volume average liquid fraction, and of the cooling energy stored and released through the aluminum container external surface during the charge and discharge, respectively. Moreover, the numerical results obtained by the implementation of the above different models are compared with experimental ones obtained with a climatic chamber. The comparison between numerical and experimental results indicate that, for the considered cooling energy storage unit, free convection plays a crucial role in the heat transfer inside the liquid PCM and cannot be neglected.

This work aims to present the results of an energetic and economic analysis of a biomass fueled CCHP system operating according to different design configurations. The investigated system consists of a biomass-fueled cogeneration unit, an absorption chiller, a thermal energy storage system and a cold one, providing electricity, heat and cooling to an Italian cluster of buildings. For each simulated configuration, the feasible investment cost of the CHP unit is evaluated considering the economic savings obtained with respect to separate generation of electricity, heat and cooling. The best configuration from the economic point of view is indicated, and the incidence of the variation of the absorption chiller and storage systems sizes on the feasible investment cost of the CHP unit is evaluated and discussed as well. Results indicate that the most influencing parameter is represented by the absorption chiller power. © 2017 The Authors.

In this work, an operation strategy for a biomass-fired combined cooling, heating and power system, composed of a cogeneration unit, an absorption chiller, and a thermal energy storage system, is formulated in order to satisfy time-varying energy demands of an Italian cluster of residential multi-apartment buildings. This operation strategy is adopted for performing the economical optimization of the design of two of the devices composing the combined cooling, heating and power system, namely the absorption chiller and the storage system. A sensitivity analysis is carried out in order to evaluate the impact of the incentive for the electricity generation on the optimized results, and also to evaluate, separately, the effects of the variation of the absorption chiller size, and the effects of the variation of the thermal energy storage system size on the system performance. In addition, the inclusion into the system of a cold thermal energy storage system is analyzed, as well, assuming different possible values for the cold storage system cost. The results of the sensitivity analysis indicate that the most influencing factors from the economical point of view are represented by the incentive for the electricity generation and the absorption chiller power. Results also show that the combined use of a thermal energy storage and of a cold thermal energy storage during the hot season could represent a viable solution from the economical point of view. © 2017 Elsevier Ltd

In this work the economic optimization of a micro-CHP system producing electricity and heat during the cold season, for a multi-apartment housing situated in Italy, is addressed. The system is composed of a prime mover, fed by natural gas, a thermal energy storage system and an auxiliary boiler. Two heat-led operational strategies have been implemented in order to evaluate the operation scheduling that maximizes the revenues for the energy cogeneration with respect to the separate generation. The first strategy limits the prime mover production to the user heat request and the heat required to fill the thermal energy storage, while the second novel one permits to have thermal energy produced in excess by the prime mover, or rather it allows to have heat dumping. The analysis of the micro-CHP system has been realized using two different solvers, namely, a home-made numerical code written in Matlab environment, that has been used in order to perform the economic optimization of the micro-CHP system operation, and the commercial software TRNSYS 17, used to carry out the dynamic simulation of the micro-CHP system. The main result of the present study is represented by the demonstration of the practical feasibility of the operation resulting from the economic optimization of the micro-CHP system, for both the analyzed operation strategies.

In this work the characterization of pollutants emission of two different commercial prime movers producing electricity and heat during the cold season for a multi-apartment housing situated in Italy is addressed. In particular, an internal combustion engine and a microturbine, both fed by natural gas, have been analyzed separately. For each prime mover, the emission of CO2, CO and NOx resulting from two different optimized operation modes are reported and discussed. The results show that the micro-CHP system with the internal combustion engine as prime mover involves a marked augmentation of dangerous CO and NOX emissions on a local scale. © 2015 IEEE.

In this work the scheduling optimization of micro-CHP systems producing electricity and heat for a single-family house situated in Italy is addressed. Three different commercial prime movers have been analyzed separately, and for each of them the operation scheduling that maximizes the revenues for the energy cogeneration with respect to the separate generation has been evaluated by means of an optimization algorithm. © (2014) Trans Tech Publications, Switzerland.

In this study the optimal operation of micro-CHP systems producing electricity and heat for a single-family house situated in Italy is addressed considering the effects of heat dissipation relative to thermal storage systems. Three different prime movers have been analyzed separately, and for each of them the operation scheduling that maximizes the revenues for the energy cogeneration with respect to the separate generation has been evaluated by means of an optimization algorithm. © 2014 IEEE.

In the present work the unsteady numerical simulation of a solar domestic hot water (DHW) system composed of two flat plate collectors, a water tank for heat storage, and a coil heat exchanger is addressed. The simulations have been performed using two different solvers, namely a home-made code written in Matlab, and TRNSYS 17. In the first part of the paper, the analytical models used in the Matlab code, and the TRNSYS case are reported in detail. Successively, the results of the simulations realized by means of the two solvers are presented and compared. © 2014 The Authors. Published by Elsevier Ltd.