Pursuing environmental and economic objectives in the design of distributed generation and district heating plants

Distributed generation (DG) appears to be the state of the art solution to efficiently meet growing energy demand, thanks to recent cost reductions for small scale power generation units and to energy market liberalization and also in view of insufficient capacity and reliability of existing transmission grid or of high costs and environmental impacts of grid expansion. In particular, the potentials of efficient small scale power production are related to the opportunities of cogeneration: meeting significant heat requirements by activities located close to such plants could thus yield advantages in terms of economic and energy performances. This is especially true for urban areas, where the effects of cogeneration could be optimised through the combination of DG and district heating. Reduction in overall fossil fuel consumption and associated global emissions – especially in terms of greenhouse gases (GHG) – are most important benefits associated with district heating. However, in public decision making concerns often arise as regards local air emissions, which are frequently neglected in preliminary feasibility studies. Models adopted in early design stages, in fact, mainly aim at cost optimisation and emissions are usually calculated afterwards, often focusing on GHG only. More articulated approaches, typical of regional and national energy planning, are seldom used for local small scale projects. In the present study, a multi-criteria model is developed to support the synthesis of optimal cogeneration and district heating systems in terms of economic, local and global environmental performances. The approach is applied to a project of natural gas engine based cogeneration and district heating in North-Eastern Italy. Optimal sizing and foreseen operation of the system, including several cogeneration units and serving, among others, a large hospital, will be presented and compared with the results of economic optimisation models, thus assessing the effect of pursuing compromise solutions aiming at more satisfactory environmental performances.