Open AccessMILP model for integrated expansion planning of multi‐carrier active energy systems
Author(s) -
Ghasemi Hosein,
Aghaei Jamshid,
Gharehpetian Gevork Babamalek,
Safdarian Amir
Publication year - 2019
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2018.6328
Subject(s) - mathematical optimization , integer programming , grid , computer science , linear programming , distributed generation , electricity , transformer , convergence (economics) , interdependence , energy carrier , engineering , renewable energy , voltage , mathematics , geometry , economic growth , political science , law , electrical engineering , economics
In growing economic energy systems, the interdependency of various energy infrastructures has led to a change in countries' policies in their expansion planning of energy networks. In this study, a mixed‐integer non‐linear programming (MINLP) model is proposed for expansion planning of the multi‐carrier systems including electricity and gas distribution networks. The optimal planning determines the best location, time, and alternative for network assets in order to minimise investment costs and reduce losses. Also, as another distinctive feature of this study, given the integration of electricity and gas distribution networks and the complexity of the problem, a new MILP model using linearisation methods is presented. In this planning model, several types of alternative plans and a set of candidates for the new placements or increase of the capacity of transformers, feeders, distributed generation, gas pipelines, and city gate stations are considered. The proposed MILP model provides the convergence of the problem to a global optimum response using the powerful commercial software. In addition, a solution based on Benders decomposition algorithm is finally proposed to reduce the solution time of the problem. Finally, the efficiency of the proposed model is evaluated by means of some simulation results.