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The decarbonisation of the building heating sector requires a shift from decentralised fossil fuel heating appliances to systems converting energy carriers with low greenhouse gas (GHG) emissions. However, for certain energy carriers, a considerable portion of GHG emissions arises upstream during production, processing and transportation, rather than during energy conversion. Accurately quantifying these indirect GHG emissions typically requires life cycle assessments, which are often resource-intensive and impractical during the early stages of energy system design. This study introduces operational GHG emissions as a pragmatic metric for the preliminary assessment of energy carrier environmental impact in building heating applications. These operational GHG emissions include both direct CO2emissions and indirect CO2, CH4and N2O emissions. Based on a comprehensive literature analysis, average estimates are proposed for the operational GHG emissions of various energy carriers within a European context, including natural gas, oil, coal and wood, as well as the average European and Belgian electricity grid, and hydrogen from various production methods. The findings underscore the significant contribution of indirect GHG emissions, as the selection of the energy carrier with the lowest environmental impact hinges on whether direct emissions alone or the broader operational GHG emissions are considered. By integrating operational GHG emissions into the early design stages of energy systems, stakeholders can make more informed decisions about which energy systems warrant further investigation, thereby facilitating more sustainable energy system development from the outset.

Residential building heating stands as a significant energy consumer with substantial environmental implications. To facilitate a sustainable transition, it is essential to assess the emissions and costs associated with current heating practices. This study investigates the economical and environmental aspects of residential building heating in the Brussels-Capital Region (BCR), Belgium. Employing a bottom-up methodology that integrates Energy Performance of Buildings (EPB) certificates with specific emissions and cost data, the analysis evaluates the emissions (including direct and indirect greenhouse gases (GHG), NOx, SO2and PM2.5) and the levelized cost of heat (LCOH) of the existing array of heating appliances in the BCR. The analysis reveals notable variations in emissions intensity and LCOH across diverse heating technologies, highlighting the intricate interplay between environmental sustainability and economic viability. Wood and electric-powered appliances demonstrate relatively low GHG emissions compared to fossil fuel appliances. Nonetheless, individual wood-fueled appliances exhibit elevated NOxand PM2.5emissions compared to the current weighted average emissions intensity of the BCR. Furthermore, sensitivity analysis underscores the substantial influence of fuel price scenario on the most cost-effective heating technology. This study provides a balanced framework for informed decision-making on residential building heating, offering benchmarks for transitioning to a more sustainable urban heating infrastructure.

Renewable Energy Communities (RECs) play an important role in driving the transition towards sustainable energy systems. In this context, energy storage systems are pivotal in mitigating fluctuations and uncertainties associated with variable renewable energy sources (VRES). Considering the variability of renewable energy generation and demand, it is imperative to conduct a comprehensive analysis under different conditions, investigating the roles of various energy storage systems in achieving optimal solutions. In this study, we propose an optimization framework for the optimal design and operation of energy systems combining both short-term and long-term energy storage technologies. The proposed framework integrates multi-objective optimization and multi-criteria evaluation to evaluate the potential of increasing the Self-Sufficient Ratio (SSR) of the system while minimizing the associated Levelized cost of exergy (LCOEx). Constraints are also defined in terms of maximal capacities of VRES production and energy storage. We provide Pareto frontiers allowing for the selection of compromises between SSR level and LCOEx. The systems include batteries, hydrogen production and storage, and thermal energy storage, achieving an SSR of 89%, around twice the SSR of a system with no energy storage. The results also reveal that hydrogen storage is required to reach SSR levels exceeding 60% and that its capacity increases with increasing VRES and storage availability. Lastly, this study delves into the synergistic interplay between local VRES and storage capacities in optimizing system performance, showing that both VRES and storage play significant roles in increasing the SSR of energy communities.

High-fidelity thermodynamic simulation software is available to perform detailed simulations of power plants. However, these models depend on many operating parameters the user must characterize to assess the power plant performances. Unfortunately, most parameters are underdetermined by experience: the validation of the model using field measurements does not allow for the complete determination of all parameters, notwithstanding the unavoidable uncertainties of the measurements themselves. These limitations can result in a drastic mismatch between simulated and actual performance and lead to biased, suboptimal decision-making. To address these limitations, we performed Uncertainty Quantification on key furnace heat transfer parameters to predict the thermodynamic performance of coal-fired power plants retrofitted to biomass (co-)firing under uncertain operating conditions. We used a high-fidelity Thermoflex® model to simulate the thermodynamic performance of the power plant, and we adopted Polynomial Chaos Expansion to perform Uncertainty Quantification in a computationally-efficient manner. Finally, we evaluated the effect of various fractions of biomass in the fuel (from 0 to 100%) on the performance, which provides additional information in the decision-making process during the retrofit of the power plant. The results illustrate that the uncertainty on the non-uniform radiant flux factor dominates the uncertainty on the power, efficiency and flue gas temperature, meaning that efforts should aim at reducing the epistemic uncertainty on the radiative heat flux in the boiler. Increasing the biomass fraction results in a decrease in the gross power and gross efficiency. The mean Furnace Exit Gas Temperature remains relatively stable, but reaches a minimum value at 60% biomass co-firing. In conclusion, Polynomial Chaos Expansion allows for a computationally-efficient probabilistic assessment of non-validated operational conditions, such as a fuel switch, in high-fidelity models for thermal power plants. Future work will focus on extending the number of uncertain parameters.

Municipal solid waste (MSW) is increasingly considered a source of energy and materials rather than an environmental and socioeconomic problem. Incineration using the grate-firing technique is one of the best available technologies for thermal treatment of non-recyclable MSW with energy recovery. The transition to a circular economy brings a new challenge to the Waste to Energy (WtE) industry. Due to advanced waste management schemes, the calorific value of the input waste is likely to decrease. Nevertheless, WtE plant designers and operators have aimed to increase the energy and material recovery efficiency of their installations, while maintaining or even decreasing operation and maintenance costs. For these reasons, there is a need for better understanding of the chemical and physical phenomena involved in the MSW incineration process. Accurate numerical modelling of MSW packed bed combustion can substantially contribute to this objective.