This paper aims to evaluate the environmental impact along the overall life cycle of the various components of a Hydrogen Valley with multiple end-users fed by green hydrogen. As case study, a hydrogen valley including a MW-scale electrolyser powered by different percentages of energy supplied by a wind farm and/or a photovoltaic plant, and an H2 storage section is considered. The H2 produced is used to feed a fleet of fuel cell electric vehicles and a stationary fuel cell, while the residue H2 is injected in a natural gas pipeline considering a maximum safety limit of 5%vol. When the safety limit is reached, the H2 overproduction can be used to produce biomethane through a biological hydrogen methanation process. With the aim of analysing the actual contribution of these hydrogen-based ecosystems towards more sustainable energy systems, a Life Cycle Analysis of the hydrogen valley is carried out. The results show that the final use of hydrogen for fuel cell electric vehicles produces the most valuable environmental benefits. Moreover, Hydrogen Valley solutions integrated with photovoltaic plants allows to maximize the use of H2 in fuel cell electric vehicles and therefore are the most valuable choice from an environmental point of view.
This paper explores the social impact for population in the energy sector combining LCA and SIA (social impact assessment). As case study, a new 66 MW wind power plant under development in the countryside of Southern Sardinia has been considered. The innovative method, based on the analysis of the context, aims to empirically analyze some selected sustainability indicators. The proposed method starts from a detailed analysis of the wind power project, with particular reference to the plant site characteristics, technical features of the wind farm, opinions of the stakeholders, environmental and social impacts and expected economic benefits. The acquired data are validated with a Severity statistical method that identifies the KPIs. The indicators are classified into general categories of damage Human life, Safety guarantee, Social resources, Public participation and analyzed through a combined SIA-LCA method to identify indicators damage weights. This work shows the importance of putting together indicators already explored in the environmental field such as Human health, Ecosystem quality, Resource, Climate Change and as social indicators Renewable Energy with Noise, Visual Impact, Shadow Flichers, the perceptions of the local community.
The aim of this paper is to evaluate the overall life cycle environmental impact of an adiabatic compressed air energy storage (ACAES) system, which is designed to achieve the best match between the power production of a photovoltaic (PV) power plant and the power demand from the final user. The electrical energy demand of a small town, with a maximum power load of about 10 MW, is considered a case study. The ACAES system is designed with a compressor-rated power of about 10 MW and charging and discharging times of 10 and 24 h, respectively. Different sizes of the PV plant, ranging from 20 to 40 MWp, and two different solutions for the compressed air storage, an underground cavern, and a gas pipeline, are analyzed. The aim of this analysis is to compare the impacts on human health, ecosystem quality, climate change, and resource consumption of the PV power generation plant and the integrated PV-ACAES system with those of a reference scenario in which the end user demand is met entirely by the grid. The best results in terms of a reduction in environmental impact in comparison to the reference scenario are obtained for a small PV plant (20 MW) without the ACAES section, with reductions of about 85–95% depending on the category of impact. The integration of the ACAES system improves energy self-consumption but worsens the environmental impact, especially for air storage in gas pipelines. The best configuration in terms of environmental impact is based on a 30 MW PV plant integrated with an ACAES section using an underground cavern for air storage and allows for improvements in the energy self-consumption of between 38% and 61%, with a reduction in the environmental impact compared to the reference scenario of about 80–91% depending on the impact category.
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