A Probabilistically Constrained Approach for the Energy Procurement Problem†
AbstractThe definition of the electric energy procurement plan represents a fundamental problem that any consumer has to deal with. Bilateral contracts, electricity market and self-production are the main supply sources that should be properly combined to satisfy the energy demand over a given time horizon at the minimum cost. The problem is made more complex by the presence of uncertainty, mainly related to the energy requirements and electricity market prices. Ignoring the uncertain nature of these elements can lead to the definition of procurement plans which are infeasible or overly expensive in a real setting. In this paper, we deal with the procurement problem under uncertainty by adopting the paradigm of joint chance constraints to define reliable plans that are feasible with a high probability level. Moreover, the proposed model includes in the objective function a risk measure to control undesirable effects caused by the random variations of the electricity market prices. The proposed model is applied to a real test case. The results show the benefit deriving from the stochastic optimization approach and the effect of considering different levels of risk aversion. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Beraldi, P.; Violi, A.; Bruni, M.E.; Carrozzino, G. A Probabilistically Constrained Approach for the Energy Procurement Problem. Energies 2017, 10, 2179.
Beraldi P, Violi A, Bruni ME, Carrozzino G. A Probabilistically Constrained Approach for the Energy Procurement Problem. Energies. 2017; 10(12):2179.Chicago/Turabian Style
Beraldi, Patrizia; Violi, Antonio; Bruni, Maria E.; Carrozzino, Gianluca. 2017. "A Probabilistically Constrained Approach for the Energy Procurement Problem." Energies 10, no. 12: 2179.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.