Integration of energy supply and energy demand response curves in the Process and Network Synthesis

Abstract

The ongoing climate change, the depletion of resources and the visible environmental changes led in the last decades to a revolution in our thinking about resources. Several technologies have been and continue to be developed in order to avoid depletion of fossil fuels by shifting the use from non-renewable to renewable resources. One of the most important related fields of study is the energy sector: the need to pass from a fossil-fuels based energy production to the so called Green Energy has brought many opportunities of development and growth but also raised many issues to solve. On a local scale, the main issues of this ongoing process are to meet the needs of the consumer by an optimized use of the local available resources and the economical sustainability of green energy production. In the RegiOpt software the principles of Process Network Synthesis (PNS) are used to advice the stakeholders in the planning of a profitable and sustainable regional energy supply system. The software compares the possible energy supply technologies and gives as output one or more optimal sets of technologies that optimize the use of resources with regard to the economical potential and the sustainability of the single processes. While the economical and the environmental aspects are considered in the RegiOpt, the further development of the software requires the consideration of time-dependency of energy supply and energy demand on annual basis. The capacity of covering energy demand over time is a central issue of energy production industry, under this point of view the current study focused on the time-dependency of supply and demand. Yearly response curves of strong time-dependent supply technologies have been found and have been combined with the yearly demand response curves, in order to evaluate the gap between the proposed energy system and the regional demand. The resulting curve has then been divided into a reasonable number of intervals representing periods of higher and lower difference between production and consumption. To fit the results in the RegiOpt software, we proceeded to an approximation of every period by its mean: the mean value of the curve in every period fairly represents the curve itself. Under this conditions the RegiOpt can be run multi periodically optimizing the technologies network for all periods.