How can an optimized life cycle assessment method help evaluate the use phase of energy storage systems?

Abstract

The deployment of smart technologies such as storage systems is a requirement for the integration of renewable energy sources (RES) in today's grids. The increase in the share of renewable energy, mainly wind and solar power relies on the grid operators' capacity to offset intermittency and enhance the grids' flexibility, for which the most recommended solution is the deployment of energy storage systems (ESS). However, this type of addition to the grid will have consequences on current power sources operation and lead to changes in their environmental impacts. It is no longer possible to rely on temporally aggregated data, linear impact allocation assumptions or averaged emission factors to evaluate the ESS use phase. A more robust environmental assessment tool is therefore required. In light of this limitation, we propose an optimized consequential life cycle assessment (O-C-LCA) methodology applied to the Norman grid (France) for the year 2017. We optimally simulate the operation of lithium-ion batteries as an ESS within the grid by means of an optimization algorithm. The cost of electricity production, including greenhouse gas emissions through a price on carbon, is minimized, and the various generation sources are managed. A near-real ESS operation pattern is obtained as well. Afterward, we assess the environmental impacts of electricity generation using a retrospective consequential LCA. The results highlight the importance of time-variant data in the identification of the system's temporal hotspots. The life cycle optimization analysis illustrates the generation patterns and periods that are most altered by (i) the minimization of electricity generation costs including greenhouse gas (GHG) emissions and (ii) the addition of an ESS. For this case, on average, 53% GHG emissions abatement results from the grid optimized operation and deployment of ESS, along with a total marginal operating costs reduction of 28%. Temporally-differentiated region-specific emission factors (EFs) are also recommended for enhanced assessment results. By including time-variant data and temporally-differentiated EFs, the developed method leads to an appropriate representation and a more accurate evaluation of the ESS use phase. It is therefore considered an effective tool for policy and decision makers regarding the impacts of ESS operation on the environmental profiles of power grids.