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This paper presents a multi-objective optimization model for the integration of polygeneration systems into energy communities (ECs), by analyzing a case study. The concept of ECs is increasingly seen as beneficial for reducing global energy consumption and greenhouse gas emissions. Polygeneration systems have the potential to play a crucial role in this context, since they are known for producing multiple energy services from a single energy resource, besides the possibility of being fed also by renewable energy sources. However, optimizing the configuration and operation of these systems within ECs presents complex challenges due to the variety of technologies involved, their interactions, and the dynamic behavior of buildings. Therefore, the aim of this work is developing a mathematical model using a mixed integer linear programming (MILP) algorithm to optimally design and operate polygeneration systems integrated into ECs. The model is applied to a case study of an EC comprising nine buildings in a small city in the northeast of Italy. The work rests on the single- and multi-objective optimization of the polygeneration systems taking into account the sharing of electricity among the buildings (both self-produced and/or the purchased from the grid), as well as the sharing of heating and cooling between the buildings through a district heating and cooling network (DHCN). The main results from the EC case study show the possibility of reducing the total annual CO2 emissions by around 24.3% (about 1.72 kt CO2/year) while increasing the total annual costs by 1.9% (about 0.09 M€/year) or reducing the total annual costs by 31.9% (about 1.47 M€/year) while increasing the total annual CO2 emissions by 2.2% (about 0.16 kt CO2/year). The work developed within this research can be adapted to different case studies, such as in the residential–commercial buildings and industrial sectors. Therefore, the model resulting from this work constitutes an effective tool to optimally design and operate polygeneration systems integrated into ECs. [ABSTRACT FROM AUTHOR]

Biomass is widely acknowledged as a plentiful and easily accessible source of renewable energy. Unlike many other renewable sources, biomass offers a consistent and predictable power supply without significant concerns about energy and environmental impacts. When used as a fuel in polygeneration systems designed to produce multiple outputs such as electricity, heat, chemicals, and synthetic fuels, biomass greatly enhances overall system efficiency by minimizing energy losses. These systems gain further advantages when integrated in a decentralized manner with energy-intensive applications like buildings. This review article aims to shift the focus of readers from generic biomass-based systems to polygeneration systems tailored for specific applications, such as buildings. The overview will discuss various biomass resources, systematic approaches, technologies, successful case studies, potential benefits, and limitations of such systems integrated into real-life building applications. It also categorizes studies based on different conversion processes such as combustion, gasification, and anaerobic digestion, with combustion-based polygeneration systems being the most prevalent. The review also explores the use of standalone and hybrid biomass-based energy systems. Taking a multidisciplinary approach, the analysis considers energy, exergy, economic, and environmental perspectives. Parameters such as the primary energy savings (PES), exergy efficiency, simple payback (SPB) period, and CO2 emission reductions are commonly used in system analyses. The review underscores how polygeneration systems integrated into the building sector can enhance efficiency, resilience, and environmental sustainability. This synthesis aims to address current gaps, particularly in the domain of polygeneration systems connected with buildings, offering essential insights for researchers and specialists in the field. [ABSTRACT FROM AUTHOR]

This paper presents a multi-objective optimization model for the integration of polygeneration systems into energy communities (ECs), by analyzing a case study. The concept of ECs is increasingly seen as beneficial for reducing global energy consumption and greenhouse gas emissions. Polygeneration systems have the potential to play a crucial role in this context, since they are known for producing multiple energy services from a single energy resource, besides the possibility of being fed also by renewable energy sources. However, optimizing the configuration and operation of these systems within ECs presents complex challenges due to the variety of technologies involved, their interactions, and the dynamic behavior of buildings. Therefore, the aim of this work is developing a mathematical model using a mixed integer linear programming (MILP) algorithm to optimally design and operate polygeneration systems integrated into ECs. The model is applied to a case study of an EC comprising nine buildings in a small city in the northeast of Italy. The work rests on the single- and multi-objective optimization of the polygeneration systems taking into account the sharing of electricity among the buildings (both self-produced and/or the purchased from the grid), as well as the sharing of heating and cooling between the buildings through a district heating and cooling network (DHCN). The main results from the EC case study show the possibility of reducing the total annual CO2 emissions by around 24.3% (about 1.72 kt CO2/year) while increasing the total annual costs by 1.9% (about 0.09 M€/year) or reducing the total annual costs by 31.9% (about 1.47 M€/year) while increasing the total annual CO2 emissions by 2.2% (about 0.16 kt CO2/year). The work developed within this research can be adapted to different case studies, such as in the residential–commercial buildings and industrial sectors. Therefore, the model resulting from this work constitutes an effective tool to optimally design and operate polygeneration systems integrated into ECs.

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This work presents the modeling and thermodynamic analysis of two novel small-scale polygeneration systems that are capable of simultaneously converting residual biomass to methanol (MeOH), electricity, heat and a CO2-rich stream for agricultural greenhouses. The first system is based on a downdraft gasifier, while the second relies on a dual fluidized bed (DFB) gasifier. Both configurations leverage the H2, O2, and electricity generation capabilities of reversible solid oxide cells (RSOCs). The Aspen Plus process simulator is used to model the thermodynamic performance of the proposed polygeneration systems, which operate at total efficiencies ranging from 83.9 to 85.0%. From a biofuel and electrical efficiency perspective, the system based on a DFB gasifier is superior, providing the added benefit of enabling carbon capture and storage, as a N2-free stream with a molar purity exceeding 90% CO2 is generated, which could be readily liquefied or sequestered. [ABSTRACT FROM AUTHOR]

One of the biggest concerns of the present century is energy security and climate change. Further, studies suggest that there would be a huge lack of fossil fuels in near future. Moreover, in terms of cleaner production, the most popular and practiced way of power generation is renewable energy sources which are intermittent in nature, require large land area, and also dependent on geographic positions and climatic conditions. Besides, nuclear energy is also having some limitations including government policies and public apprehensions. To overcome these hurdles, these two carbon-free technologies can be integrated and form a nuclear-renewable hybrid energy system (N-R-HES). Literature related to the proposed systems is extremely rare and the systems are not yet well-developed. Keeping that into concern, this paper discusses the operation, status, prospects, and benefits of N-R-HES. Various possible integration techniques along with their operation are discussed in detail. Moreover, six aspects of interconnections are identified: electrical, thermal, chemical, mechanical, hydrogen, and information. The paper also discusses the reactor licensing, permitting procedures along the different benefits of N-R-HES. Additionally, research limitations and needs are identified for further exploration of the topic throughout the paper.

Agricultural greenhouses are still heavily dependent on fossil fuel-based products despite the abundant residual biomass at their disposal. This paper presents two novel decentralized systems that can convert biomass simultaneously into synthetic natural gas (SNG), electricity, useful heat, and a CO 2 -rich stream. To do so, the electricity and H 2 /O 2 production features of reversible solid oxide cells (RSOCs) are exploited. A steam dual fluidized bed (DFB) gasifier is used in the first proposed system, while the second one adopts a simpler oxygen/steam-blown downdraft gasification approach. Thermodynamic simulations using Aspen Plus software reveal that the total polygeneration process efficiency could reach 86.6%, with a CO 2 generation capacity exceeding 275g per kilogram of biomass input. If not used inside the greenhouse atmosphere to enhance crop growth, this high-purity CO 2 stream could be sequestered/liquefied to render the process carbon negative. The flexibility of the polygeneration systems is investigated through parametric analysis, where maximum SNG efficiencies that are on par with large-scale plants are obtained. The possibility of storing surplus electricity from intermittent sources as chemical energy in SNG is also highlighted. • Natural gas, electricity, heat, and high-purity CO 2 are produced at 86 % efficiency. • Thermodynamic modelling highlights the flexibility of the small-scale systems. • Maximum synthetic natural gas yield at 63 % is similar to large-scale systems. • Carbon capture and storage at a maximum recovery rate of 52 % is possible. [ABSTRACT FROM AUTHOR]

This submission contains the complete balanced process matrix of an off-grid community system primarily powered by a micro-hydroelectric powerplant. The system is meant to provide the needs of the community for electricity, potable water and ice. The system also considers the provision of a diesel engine generator set as a back-up to provide electricity. The data serves as inputs to simulate the performance of the system under different drought scenarios. The data provided here is in support of the co-submitted article of Aviso et al. [1].

The optimization of polygeneration systems considering hourly periods throughout one year is a computationally demanding task, and, therefore, methods for the selection of representative days are employed to reproduce reasonably the entire year. However, the suitability of a method strongly depends on the variability of the time series involved in the system. This work compares the methods Averaging, k -Medoids and OPT for the selection of representative days by carrying out the optimization of grid-connected and standalone polygeneration systems for a building in two different locations. The suitability of the representative days obtained with each method were assessed regarding the optimization of the polygeneration systems. Sizing errors under 5% were achieved by using 14 representative days, and the computational time, with respect to the entire year data, was reduced from hours to a few seconds. The results demonstrated that the Averaging method is suitable when there is low variability in the time series data; but, when the time series presents high stochastic variability (e.g., consideration of wind energy), the OPT method presented better performance. Also, a new method has been developed for the selection of representative days by combining the k -Medoids and OPT methods, although its implementation requires additional computational effort. • Comparison of representative days' selection methods for optimization. • Pros and cons of averaging, k -Medoids and OPT methods are evaluated. • Guidelines for applying adequate representative days' selection method are provided. • A new method, combination of k -Medoids and OPT methods, is proposed. [ABSTRACT FROM AUTHOR]

In this paper, the energy and exergy performance of several polygeneration arrangements driven by low and medium temperature geothermal resource is investigated. The aim is to assess and compare different coupling schemes, identifying suitable thermally driven technologies for each type of arrangement. The polygeneration system is intended to produce power, cooling and heat for direct uses by considering variations of series and parallel coupling schemes along with different alternatives of ORC and absorption cooling machines. The study was conducted considering a temperature range of low-to-medium geothermal resource from 80 °C to 150 °C. Mathematical models are developed based on first and second law of thermodynamics and solved by means of an equation solver. The results show a threshold temperature that makes a shift between feasible polygeneration arrangements and the type of thermally driven technologies adopted, resulting in two different polygeneration arrangements with highest energetic and exergetic performance. The first arrangement correspond to a temperature range that lies between 80 °C and 110 °C, and the second one between 110 °C and 150 °C. The polygeneration arrangement with highest exergetic performance for the first range of temperatures was the hybrid parallel-series cascade arrangement (HPS2) having exergy efficiencies between 42.82% and 50.11%, while the one corresponding to the second temperature range was the series cascade arrangement (SC1) presenting exergy efficiencies from 51.44% to 52.9%. This effect is a consequence of the available temperature of the geothermal resource and the intrinsic energy performance of the different technologies considered. In regard to thermally driven technologies, arrangements where ORC and TDC subsystems are placed at the first thermal level, are the ones with the highest energetic and exergetic performance. Arrangements that have those components at the last level, present lowest performances. [ABSTRACT FROM AUTHOR]

In the present context of energy transition towards a carbon neutral society, residential sector plays an important role to combat climate change since it represents about 40% of the global final energy consumption and 30% of direct CO 2 emissions in the European Union. Polygeneration systems, facilitating the integration of renewable energies, are a feasible alternative enabling efficient use of natural resources with low environmental impact. This work analyzes the economic viability, in terms of net present value (NPV), and environmental benefit (CO 2 eq emissions) of an energy supplier company playing the role on an aggregator for both demand and supply. As an owner of a polygeneration system, optimally designed through a MILP approach, it delivers various energy services (electricity, space heating, domestic hot water and cold) to several customers (50 dwellings). The analysis is performed, considering three different business models, in two different locations, Zaragoza (Spain) and Marseille (France), with different energy demands, energy mixes and energy regulations. The optimal configuration obtained, consisting of cogeneration module, PV, reversible heat pump, boiler and thermal energy storage has shown to be very resilient and cost-effective in the scenarios analyzed. Results indicate that the proposed scheme represents an added value for both the supplier company (aggregator), with a positive NPV , and the final customers (owing savings greater than 30%), with significant reduction of CO 2 eq emissions. [Display omitted] • Feasibility and economic viability of an aggregator providing Energy-as-a-Service. • Small district (tens of customers). • All residential demands offered (heat, DHW, cooling, electricity). • Optimized solutions for three cases (varying contracts and prices) and two locations (Zaragoza, Spain and Marseille, France). • Non constant prices considered as well as revenues and taxes. [ABSTRACT FROM AUTHOR]

The steel industry is the main generator of CO 2 among the different industrial sectors. That is why efforts are being made to reduce or avoid CO 2 emissions by process optimisation or by Carbon Capture and Storage (CCS) processes. In the steel production by blast furnace technology, three main off-gases are generated, namely the Blast Furnace Gas (BFG), the Coke-Oven Gas (COG) and the Basic Oxygen Furnace Gas (BOFG). Many processes and technologies can be identified for their use, depending on the volume and composition of the steelwork off-gases. In the present work, a review and an analysis of several alternatives proposed during last years to use these off-gases are carried out, with a particular focus on thermochemical processes. Three main alternatives are considered: the thermal use of the gases, the recovery of valuable compounds for selling and the synthesis of a high-added value product. The possible implementation of these alternatives may conduct to improvements in energy efficiency of the steel making process with subsequent reduction of CO 2 emissions. [ABSTRACT FROM AUTHOR]

This paper analyzes theoretical dynamic performance of centralized polygeneration technologies using district networks as distribution system. Three Spanish cities have been studied using as input variables Typical Meteorological Years (TMY), representative local constructions and normative internal loads for residential and tertiary buildings. Energy simulation has been carried out with the software TRNSYS. Different dynamic models that connect renewable and conventional technologies have been developed to represent the thermal and electrical performance of a polygeneration plant. The thermal model is based on the combined operation of solar thermal collectors and biomass boilers using cogeneration systems as a backup when both renewable technologies cannot supply the thermal district loads. The electrical model is based on the independent operation of photovoltaic panels and wind turbines in combination with Polymeric Electrolyte Membrane (PEM) fuel cells. Global systems work at their limit operation to compare the final results of the three cities. Different configurations have been studied to evaluate the annual thermal and electrical coverage reached by the plant. Once optimized the area of the solar field the energy fraction covered by the renewable systems increases logarithmically with the power of the biomass boilers. The simultaneous operation of photovoltaic panels and wind turbines to feed PEM cells maximize the electrical coverage achieved by the district. Results of both simulation models show that for all weather conditions studied, the optimal solution is a combined operation of the renewable technologies used. [ABSTRACT FROM AUTHOR]

This paper is framed within the context of intra-day optimal control of polygeneration systems and storage connected to microgrids. In particular, the paper proposes an optimal control strategy that accounts for both electrical and thermal processes taking place in multi-building energy networks. To this end, the proposed optimal control strategy, based on the use of a Model Predictive Control, has been developed with the aim of providing optimal resource set-points for the coming 24 h. The proposed approach takes into account: day-ahead and spot prices of electricity, resource prices in terms of fuel cost and shut-down, start-up costs as well as the presence of electrical and thermal storage. The ability of this thermo-electric optimal control strategy is then demonstrated through simulations considering three case studies, namely: (a)fixed electricity price, (b)electricity spot-price and (c)different seasonal cases. The paper also studies the shaving of peaks through the use of optimally sized units in a system with the proposed method. [ABSTRACT FROM AUTHOR]

• Cost-effective and sustainable energy systems retrofit for buildings. • 2nd life Li-Ion batteries in polygeneration systems for buildings. • To cut off the natural gas consumption at affordable cost. The building sector represents around one-third of the energy related to the EU CO 2 eq emissions, which makes it a crucial sector for achieving the EU's energy and environmental goals. Thus, the EU has established a legislative framework to foster, among others, the modernisation of the existing building stock through a better energy system integration. In this sense, bearing in mind the needs of energy system retrofit of the public buildings in Spain, this paper carried out a thorough analysis of different trade-off solutions obtained from the multiobjective optimization of a polygeneration system for the TR5 building of the Polytechnic University of Catalunya. The results highlight the selection of PV panels, cogeneration modules and 2 nd life Li-Ion batteries, among others, to achieve cost-effective and sustainable energy systems. By covering the available area, 2000 m 2 , the PV panels attend about 23% of the electricity required for the building. On the other hand, considering the current geopolitical tensions, it presents a potential configuration that allows to cut off the natural gas consumption reducing about 6% the current cost. The study was carried out by using a Mixed Integer Linear Programming model maximizing the Net Present Value of the project considering the environmental impact. [ABSTRACT FROM AUTHOR]

The residential sector plays an important role to combat climate change. It requires alternatives to reduce its energy consumption and greenhouse gases emissions. Thus, polygeneration systems are a suitable alternative enabling efficient use of natural resources with low environmental impact. On the other hand, microgrids are considered a key component for improving power reliability and quality, besides they offer resilient and viable solution for integrating renewable energy sources at a large scale. Accordingly, this paper proposes an approach for the design of polygeneration systems for residential buildings considering them not only as a microgrid but as a smart energy system. A Mixed Integer Linear Programming (MILP) model was developed for the optimization of polygeneration systems considering different constraints which allow the energy system to work as a microgrid. Different thermal and electrical technologies where evaluated under different conditions, finding affordable and sustainable configurations and interesting synergies between technologies. Results show the importance to consider both thermal and electrical demands and technologies simultaneously for the design of energy systems. It is highlighted the displacement of batteries by thermal energy storage to achieve more cost-effective solutions in contrast to the current tendency to uphold battery systems as the key for future energy systems. • Approach for the design of polygeneration systems for residential buildings. • Integration of thermal and electrical energy storage in polygeneration systems. • Energy communities as microgrids. [ABSTRACT FROM AUTHOR]

Highlights: [•] We explore nuclear-renewable hybrid energy systems. [•] They will increase grid flexibility, reduce greenhouse gas emissions, and optimize capital use. [•] Six aspects of interaction are identified and discussed. [•] System-level aspects are also discussed. [•] Gaps and research needs are identified to promote further exploration of the topic. [Copyright &y& Elsevier]

This submission contains the complete balanced process matrix of an off-grid community system primarily powered by a micro-hydroelectric powerplant. The system is meant to provide the needs of the community for electricity, potable water and ice. The system also considers the provision of a diesel engine generator set as a back-up to provide electricity. The data serves as inputs to simulate the performance of the system under different drought scenarios. The data provided here is in support of the co-submitted article of Aviso et al. [1]., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships which have, or could be perceived to have, influenced the work reported in this article., (© 2020 The Authors.)