A New Dynamic and Stochastic Distributed Generation Investment Planning Model with Recourse

• Type: Article in International Conference Proceedings Book
• Date: 2016

Authors

Fitiwi, DZ (Author) Other; Santos, SF (Author) Other; Bizuayehu, AW (Author) Other; Shafie khah, M (Author) Other; Catalao, JPS (Author) FEUP

Conference proceedings International

Title: 2016 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING (PESGM)

IEEE-Power-and-Energy-Society General Meeting (PESGM)

Boston, MA, JUL 17-21, 2016

Indexing

ISI Web of Knowledge - 0 Citations

Scopus - 1 Citation

Other information

Authenticus ID: P-00M-VRF

DOI: 10.1109/pesgm.2016.7741093

Abstract (EN): This paper presents a new dynamic and stochastic decision supporting model for distributed generation investment planning (DGIP). The model is formulated as a mixed integer linear programming (MILP) optimization problem that simultaneously minimizes emission, operation and maintenance, as well as reliability costs. One of the salient features of the model is that it is based on a two-period planning horizon: a short-term planning period that requires robust decisions to be made and a medium to long-term one involving exploratory or flexible investment decisions. Each period has multiple decision stages. The operational variability introduced by intermittent generation sources and electricity demand are accounted for via probabilistic methods. To ensure computational tractability, the associated operational states are reduced via a clustering technique. Moreover, uncertainties related to emission price, demand growth and the unpredictability of intermittent generation sources are taken into account stochastically. A real-life distribution network system is used as a case study, and the results of our analyses generally show the efficacy of the proposed model.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 5