TY - GEN

T1 - Linearized Optimization for Reactive Power Dispatch at Transmission Grid Level considering Discrete Transformer Tap-Settings

AU - Majumdar, Neelotpal

AU - Sarstedt, Marcel

AU - Leveringhaus, Thomas

AU - Hofmann, Lutz

N1 - Funding Information: ACKNOWLEDGMENT The research project "SiNED - System Services for secure electricity grids in times of advancing energy transition and digital transformation" acknowledges the support of the Lower Saxony Ministry of Science and Culture through the "Niedersächsisches Vorab" grant program (grant ZN3563) and of the Energy Research Centre of Lower Saxony.

PY - 2021

Y1 - 2021

N2 - Research indicates that an efficient operation of power systems, requires the use of optimization techniques for minimizing objectives such as grid losses, dispatch costs, reducing potential technical constraint violations etc. These are referred to as optimal power flow (OPF) techniques. Over the years different optimization techniques have been developed based on analytical methods and stochastic based approaches. Analytical methods include for example linear and quadratic optimization approaches. Metaheuristic methods like Particle Swarm optimization (PSO) and Genetic Algorithms (GA) have also been developed and researched upon. In this paper, a successively linearized optimization (sLP) method in the context of optimal reactive power dispatch (ORPF) is developed considering continuous reactive power flexibilities and discrete transformer tap-sets. The novel formulation of the transformer tap sensitivities indicate its efficiency of using discrete tap-settings and ease of implementation in the context of Linear Programming. This method is further compared to an already established PSO-based method subject to similar initial grid conditions and three different voltage constraint violation case studies. Results indicate the reliability and efficiency of the method.

AB - Research indicates that an efficient operation of power systems, requires the use of optimization techniques for minimizing objectives such as grid losses, dispatch costs, reducing potential technical constraint violations etc. These are referred to as optimal power flow (OPF) techniques. Over the years different optimization techniques have been developed based on analytical methods and stochastic based approaches. Analytical methods include for example linear and quadratic optimization approaches. Metaheuristic methods like Particle Swarm optimization (PSO) and Genetic Algorithms (GA) have also been developed and researched upon. In this paper, a successively linearized optimization (sLP) method in the context of optimal reactive power dispatch (ORPF) is developed considering continuous reactive power flexibilities and discrete transformer tap-sets. The novel formulation of the transformer tap sensitivities indicate its efficiency of using discrete tap-settings and ease of implementation in the context of Linear Programming. This method is further compared to an already established PSO-based method subject to similar initial grid conditions and three different voltage constraint violation case studies. Results indicate the reliability and efficiency of the method.

KW - Linear Programming

KW - Optimization

KW - PSO

KW - linearized transformer tap sensitivities

KW - optimal reactive power flow (ORPF)

UR - http://www.scopus.com/inward/record.url?scp=85126064631&partnerID=8YFLogxK

U2 - 10.1109/appeec50844.2021.9687678

DO - 10.1109/appeec50844.2021.9687678

M3 - Conference contribution

SN - 978-1-6654-4879-6

T3 - Asia-Pacific Power and Energy Engineering Conference, APPEEC

BT - 13th IEEE PES Asia-Pacific Power and Energy Engineering Conference 2021 (APPEEC)

ER -