Transmission Expansion Planning Using A Noval Meta-Heauristic Method


Ova A., Dogan E., DEMİRBAŞ Ş.

INTERNATIONAL JOURNAL OF RENEWABLE ENERGY RESEARCH, cilt.12, sa.4, ss.1988-2001, 2022 (ESCI) identifier identifier

Özet

Expansion Planning (TEP) is an optimization study aimed at determining new transmission lines to be added to the transmission network in order to expansion or reinforcement of the network within the scope of different purpose functions in parallel with the increase in demand and generation. In this study, the objective function of the TEP problem is determined as minimizing the investment costs of the lines to be added to the network and the loss of load cost. This article proposes Forensic Based Investigation Optimization (FBIO) which is a new and efficient meta-heuristic method in solving of the TEP problem for the first time. In the literature, there are many studies used individual optimization methods, but comparisons of different methods are lacking. Therefore, this article presents a comprehensive comparative study of recent published 5 different methods. The proposed FBIO method is applied for 4 different scenarios on IEEE 24-bus test system which is one of the most used test system using the DC model. Obtained results are compared with the results which get using 5 different methods in literature. In addition that the reliability of the power network is a substantial issue for utilities since the stronger transmission system means the better social welfare. Hence, Transmission System Operators have to ensure the sustainable energy to consumers at any point of the grid. Accordingly, N-1 criteria of the transmission system which is extremely important for safety should be considered in the expansion planning studies. Therefore, in this study, the N-1 contingency criterion is implemented during optimization process of the TEP problem which means that the obtained results present not only a cost-effective solution, but more robust system.Python programming language is applied in modeling and solving the problem. Panda Power, an open source Python library, is used in modeling the IEEE 24-bus test system and carrying out power flows.