Appraising the Optimal Power Flow and Generation Capacity in Existing Power Grid Topology with Increase in Energy Demand

Gideon Ude Nnachi, Yskandar Hamam and Coneth Graham Richards
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Gideon Ude Nnachi: Department of Electrical Engineering, Faculty of Engineering and the Built Environment, Tshwane University of Technology Private, Bag X680, Pretoria 0001, South Africa
Yskandar Hamam: Department of Electrical Engineering, Faculty of Engineering and the Built Environment, Tshwane University of Technology Private, Bag X680, Pretoria 0001, South Africa
Coneth Graham Richards: Department of Electrical Engineering, Faculty of Engineering and the Built Environment, Tshwane University of Technology Private, Bag X680, Pretoria 0001, South Africa

Energies, 2022, vol. 15, issue 7, 1-23

Abstract: Several socioeconomic factors such as industrialization, population growth, evolution of modern technologies, urbanization and other social activities do heavily influence the increase in energy demand. A thorough understanding of the effects of energy demand to power grid is highly essential for effective planning and operation of a power system network in terms of the available generation and transmission line capacities. This paper presents an optimal power flow (OPF) with the aim to determine the exact nodes through which the network capacities can be increased. The problem is formulated as a Direct Current (DC) OPF model, which is a linearized version of an Alternating Current (AC) OPF model. The DC-OPF model was solved as a single period OPF problem. The model was tested in several case studies using the topology of the IEEE test systems, and the computation speeds of the different cases were compared. The results suggested dual variables of the problem’s constraints as an extra tool for the network designer to see where to increase the network capacities.

Keywords: alternating current model; cost of constraint relaxation; deep reinforcement learning; direct current model; energy demand; linear programming; maximum generation capacity; maximum power flow; optimal generation capacity; optimal power flow (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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