A stochastic mixed-integer convex programming model for long-term distribution system expansion planning considering greenhouse gas emission mitigation

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Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Date
2019-06-01
Major/Subject
Mcode
Degree programme
Language
en
Pages
10
86-95
Series
International Journal of Electrical Power and Energy Systems, Volume 108
Abstract
This paper proposes a multistage convex distribution system planning model to find the best reinforcement plan over a specified horizon. This strategy determines planning actions such as reinforcement of existing substations, conductor replacement of overloaded feeders, and siting and sizing of renewable and dispatchable distributed generation units. Besides, the proposed approach aims at mitigating the greenhouse gas emissions of electric power distribution systems via a monetary form. Inherently, this problem is a non-convex optimization model that can be an obstacle to finding the optimal global solution. To remedy this issue, convex envelopes are used to recast the original problem into a mixed integer conic programming (MICP) model. The MICP model guarantees convergence to optimal global solution by using existing commercial solvers. Moreover, to address the prediction errors in wind output power and electricity demands, a two-stage stochastic MICP model is developed. To validate the proposed model, detail analysis is carried out over various case studies of a 34-node distribution system under different conditions, while to show its potential and effectiveness a 135-node system with two substations is used. Numerical results confirm the effectiveness of the proposed planning scheme in obtaining an economic investment plan at the presence of several planning alternatives and to promote an environmentally committed electric power distribution network.
Description
Keywords
Conic programming, Distributed energy, Multistage distribution system expansion planning, Renewable energy sources, Stochastic programming
Other note
Citation
Home-Ortiz, J M, Melgar-Dominguez, O D, Pourakbari-Kasmaei, M & Mantovani, J R S 2019, ' A stochastic mixed-integer convex programming model for long-term distribution system expansion planning considering greenhouse gas emission mitigation ', International Journal of Electrical Power and Energy Systems, vol. 108, pp. 86-95 . https://doi.org/10.1016/j.ijepes.2018.12.042