Open AccessA Stochastic Programming Model for the Optimal Allocation of Photovoltaic Distributed Generation in Electrical Distribution Systems Considering Load Variations and Generation Uncertainty
Author(s) -
Ali Reza Kheirkhah,
Alejandra Tabares,
Seyed Farhad Zandrazavi,
John F. Franco,
Jônatas Boás Leite
Publication year - 2020
Publication title -
anais do simpósio brasileiro de sistemas elétricos 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.48011/sbse.v1i1.2247
Subject(s) - distributed generation , photovoltaic system , sizing , mathematical optimization , computer science , reliability engineering , ac power , electric power system , minification , reduction (mathematics) , electricity generation , power (physics) , renewable energy , voltage , engineering , electrical engineering , mathematics , art , physics , geometry , quantum mechanics , visual arts
Nowadays, the penetration of distributed generation (DG) units in power systems is increasing because of their benefits on the power systems. Place, type and size of distributed generators play an important role in power loss reduction, power quality improvement, security enhancement, and cost reduction. Therefore, optimal placement and sizing of DG units in electric power systems are one of the most important problems that should be evaluated carefully. DG allocation is a constrained optimization problem with different important objectives such as power loss minimization, voltage profile improvement, reliability enhancement, investment and operation cost reduction, etc. In this paper, regarding higher distribution active losses compared to transmission and generation losses and investment limitation, DG allocation problem is solved for photovoltaic units, aiming minimization of energy and investment costs considering generation uncertainty and load variation. Due to high uncertainties of solar energy resource, the problem is evaluated under different scenarios of solar radiation under a stochastic programming approach. Tests were carried out using the 33-node distribution system and the obtained results demonstrate the advantage of optimal DG allocation as well as the efficiency of the adopted mathematical to find the optimal solution.