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Energy planning through optimization techniques is not a new concept, although different new models have been proposed and used over the last 30 years. Top down versus bottom up models have been analyzed to characterize the studied context, according to the final scopes. Improvements have been added while making (i) the models bigger and (ii) more complicated to catch more details and to understand the interconnections amongst energy systems and infrastructures, technologies, resources, environmental factors and the effect of certain (energy) policy actions. The most interesting, from an engineering standpoint, are the bottom-up technology-based models, although from an economic point of view they are considered to evolve in an excessive ideal way, rather than that of a top down model. Bottom up models are able to catch all the aspects of the energy conversion: from fuels (fossil or renewable) to electricity or to thermal and/or cooling energy demand, through different technologies. Shortly, from the need of energy services to the availability of the supply aiming at the least cost of the system. In this paper an application of the Standard Markal model of an European area of half a million people is illustrated. The aim is to provide those information that are missed in bigger National models, when coming to underpin which local actions are the most performing to achieve energy and environmental local targets (also known as burden share). The role of green tags is also investigated. Electricity and heating demands over 30 years are the exogenous variables, while the choice of conversion technologies and energy carriers supply are the endogenous variables. Constrains and environmental targets, to partially achieve the 2020 European commitment, are also discussed to explain the proposed scenarios results.