• Energy Research
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• 13. Climate action close
• 11. Sustainability close
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Abstract To achieve the EU climate and energy objectives, a transition towards a future sustainable energy system is needed. The integration of the huge potential for industrial waste heat recovery into smart energy system represents a main opportunity to accomplish these goals. To successfully implement this strategy, all the several stakeholders' conflicting objectives should be considered. In this paper an evolutionary multi-objective optimization model is developed to perform a sustainability evaluation of an energy system involving an industrial facility as the waste heat source and the neighbourhood as district heating network end users. An Italian case study of heat recovery from a steel casting facility shows how the model allows to properly select the district heating network set of users to fully exploit the available waste energy. Design directions such as the thermal energy storage capacity can be also provided. Moreover, the model enables the analysis of the trade-off between the stakeholders’ different perspectives, allowing to identify possible win-win solutions for both the industrial sector and the citizenship.

Upwelling processes bring nutrient-rich waters from the deep ocean to the surface. Areas of upwelling are often associated with high productivity, offering great economic value in terms of fisheries. The sensitivity of spring/summer-time coastal upwelling systems to climate change has recently received a lot of attention. Several studies have suggested that their intensity may increase in the future while other authors have shown decreasing intensity in their equatorward portions. Yet, recent observations do not show robust evidence of this intensification. The Senegalo-Mauritanian upwelling system (SMUS) located at the southern edge of the north Atlantic system (12°N–20°N) and most active in winter/spring has been largely excluded from these studies. Here, the seasonal cycle of the SMUS and its response to climate change is investigated in the database of the Coupled Models Inter comparison Project Phase 5 (CMIP5). Upwelling magnitude and surface signature are characterized by several sea surface temperature and wind stress indices. We highlight the ability of the climate models to reproduce the system, as well as their biases. The simulations suggest that the intensity of the SMUS winter/spring upwelling will moderately decrease in the future, primarily because of a reduction of the wind forcing linked to a northward shift of Azores anticyclone and a more regional modulation of the low pressures found over Northwest Africa. The implications of such an upwelling reduction on the ecosystems and local communities exploiting them remains very uncertain.

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Abstract This paper investigates the optimal choice of building energy efficiency (BEE) standard in the context of centralised urban district heating system in northern China. By employing a techno-economic analysis approach, we demonstrate that the current BEE standard implemented in the Chinese cities should be tightened further in order to achieve a socially optimal level. Without considering the externality costs associated with carbon dioxide (CO2) emissions, current BEE standards need to be upgraded to the equivalent level of French RT2005 standard coupled with a properly designed district coal-fired Combined Heat and Power (CHP). In contrast, the equivalent efficiency standard of Swedish building code is preferably to be implemented in the case of explicit carbon emission restriction as long as the marginal cost of carbon emission (carbon price) is sufficiently high. The fuel-switching policy (from coal to natural gas) in the urban district heating system would result in significant increase in overall costs if the BEE upgrade is not taken into account simultaneously. It is also found that BEE improvements in northern Chinese cities are more cost-effective than investing in low-carbon technologies such as wind power or Carbon Capture and storage in the EU and US with regard to CO2 emissions mitigation.

Microgrids are increasingly being used as a platform to integrate distributed generation such as renewable energy sources and (RESs) conventional sources in both grid-connected and isolated power systems. Due to the inherent intermittent nature of RESs, energy storage systems (ESSs) that can absorb fluctuations have become inevitable. Nevertheless, large capacities of ESSs increase the initial cost while small capacities lead to instabilities and increase in the cost of conventional fuels. Therefore, finding the optimal size of the ESS for a given application is essential for the reliable, efficient and economical operation of a microgrid. Once the battery size is decided, maintaining its energy at appropriate levels is essential to ensure stable and safe operation of the microgrid. This paper presents a novel expert fuzzy system - grey wolf optimization (FL-GWO) based intelligent meta-heuristic method for battery sizing and energy management. The proposed energy management operation is carried out by a Grey Wolf Optimiser (GWO) that is helped to set the membership functions and rules of the fuzzy logic expert system. The unit commitment (UC) issue, which is essential for the proper operation of the isolated microgrid, has been additionally considered in this paper. To verify the performance of the proposed method, results are compared with the rules-based method and traditional GWO algorithm. It has been proven from the results that the FL-GWO has a significant convergence property and capability to minimize the Levelized Cost Of Electricity (LCOE) by 14.13% and 24.15% compared with conventional GWO algorithm and rules-based method, respectively. The weather conditions for different climates is used to verify the performance of the intelligent energy management method under different operating scenarios. The results show that the intelligent online multi-objective energy management strategy is capable of managing a smooth power flow with the same optimal configuration in the isolated microgrid, minimising the fossil fuel utilisation and reducing the CO2 emission level.

Abstract This article focuses on the results obtained by the enforcement of a original greenhouse gas emissions policy, issued in recent years in several municipalities in Northern Italy. The Municipality of Reggio Emilia was one of the firsts in Italy to develop and adopt a voluntary building energy-consumption certification method called Ecoabita, aiming to promote energy efficiency in buildings over its jurisdiction. Several reasons make this project innovative: first, the certification method has been processed through and verified by a quality international agency, secondly the procedure is assisting financial-incentive policies both on mandatory (European Directive 2002/91/CE) and voluntary basis (Municipality Protocol Ecoabita), finally it allows to obtain eligible credits for avoided emissions that can be negotiated on the CO2 exchange market. With specific reference to Reggio Emilia case, acknowledged the amount of actions, that are normally scheduled in the municipality throughout a year, it has been evaluated the benefit, in terms of environmental improvement, descended from the protocol, also projecting their trend in future years up to 2020 as well, demonstrating the scheduled interventions are fundamental in sought of the achievement of the Kyoto and Copenhagen commitments. The entire procedure has been developed in accordance to the parameters given by UNFCCC for these kinds of analyses and has been recently confirmed to be one of the most accurate international accounting procedure by a survey developed by the scientific committee of the European Project LIFE-LAKS.

Abstract This paper presents a non-stoichiometric equilibrium model for the simulation of biomass downdraft gasifiers. The chemical equilibrium is determined by minimizing the Gibbs free energy. Five elements characterize the biomass and 15 chemical species are considered in the syngas. The model calculates the lower heating value of the syngas and the relative abundances of gasification products. An advantage of this model is that it can easily calculate not only the concentrations of the main gasification products, but also the concentrations of minor product, especially the pollutant chemical species containing Nitrogen and Sulfur. To analyse the model behaviour, a sensitivity analysis on process parameters is presented. The model is validated by comparing its results with the results of simulation carried out with a stoichiometric model and with experimental data found in literature. Finally, the model is applied to the study of the gasification of forest waste.