For energy modellers, first idea is using externalities (extra costs in the objective function) but what's the point for the LCA modellers? Evolutive environmental profiles?
Hi there,
Yes, you can do that. We have developed a model that optimize multiple objectives at the same time (we use multi-objective evolutionary algorithm). I am not expert about different indicators. But I want to say that using the model you can optimize multiple objectives simultaneously.
Energy parameters should be linked with CO2 and acidfication figures along the whole life cycle of fuels. They can be normalized and aggregated to a single score using distance to ttarget approaches as well.
The standardization of indicators LCA is more than complex, unworkable. Perhaps creating specific scenarios can be given more importance to some than to others and weigh, but the reality is that it is not logical. There is a working group in Belgium which has an integration procedure.
Years ago some eco-eficiency indicators, based on principles developed by the World Business Council for Sustainable Development (WBCSD), were proposed. The 3 main indicators are:
1) energy intensity (total energy consumption – MJ per production unit). From this you could estimate the CO2 emissions based on the energy mix of a country.
2) waste intensity (total waste – kg per production unit)
3) water intensity (water consumption – m3 per production unit)
It might appear simplistic but using these indicators in an (energy) optimization model can help a lot as it is relatively easy to implement.
Indicators can be these you say but also the LCA indicators. The problem is how to combine them and weigh them.
My point is how to evolve the environmental profile (the LCA approach) in time at the same time (in an iterative process) in an integrated framework based on MARKAL/TIMES, an energy systems optimisation model generator (I think in TIMES but it would be interesting also other bottom-up optimisation-type models). These type of models develop a techno-economic optimisation using an extensive objective function (wich is minimised via different algorithms, using LP or NLP).
My question is more related to this: how to solve the soft-link between LCA and the energy optimisation models. The new approaches to the "dynamic" LCAs are simulation-based and they don´t really optimise anything. The issue of monetising the damages (extrnalities) to include them as extra costs was deeply studied n the European NEEDS Project a few years ago so my question is more focused on the idea of evolving the environmental indicators within an energy optimisation model, not as an ad-hoc input (with a lot of assumptions behind).
What do you think about his?
What about using exergy consumption, for example see this application
http://www.sciencedirect.com/science/article/pii/S0360544203001117
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