Secure, reliable and affordable energy supplies are fundamental to economic stability and development. However, the current trend of rising energy demand and CO2 emissions collides to the pollution reductions that are required to prevent dangerous climate change.
The industrial sector currently accounts for more than one third of the global energy consumptions and the quota is assumed to increase in the next future. However, the reduction of CO2 emissions is an achievable target, but it requires the development of a wide range of energy efficiency measures and low-carbon technologies. Almost the half of the final energy savings from energy efficiency improvements expected by 2035 comes from the manufacturing sector.
The thesis presents the optimization of industrial energy supply systems, designed to provide heat and electricity to a set of users. The evaluation is performed with reference to an energy system made of nine factories belonging to the Ponte Rosso Industrial Area of San Vito al Tagliamento (Italy), but it can be applied, with appropriate modifications, to other real case studies.
According to industrial stakeholders, the objective is the minimization of the total annual cost for owning, operating and maintaining the energy supply system, which is represented through a mixed integer linear programming model, specifically developed to determine the best configuration and operation of the whole structure.
Although the minimum cost is the objective of the research, environmental issues, like pollutant emissions and availability of energy resources, need to be considered too. That is reason because various low impact alternatives and renewable energies technologies are included in the problem and their benefits are evaluated: distributed generation, combine heat and power modules, photovoltaic collectors and solar district heating system
