Day-ahead multi-objective reactive power optimization

Date

2025-2-11

Author

Elma, İsmail

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Transmission system operators (TSOs) need to control voltages along the grid to have an economic and reliable system operation. The coordination between the voltage setpoints of power plants, transformer tap positions and switching of shunt elements may be defined as an optimum reactive dispatch problem. This thesis aims to develop an efficient algorithm for the optimum reactive power dispatch problem. The main objective of this problem is the minimization of transmission losses. Due to operational costs of switching equipment of shunt elements and transformer tap changers, TSOs also expect the number of switching of these devices to be minimized. In this study, the minimization of switching of shunt elements and transformer tap changes are included in the objective function. Hence, the problem is formulated as a multi-period and multi-objective optimization problem. The optimum reactive power dispatch problem is a nonlinear and non-convex optimization problem due to the nonlinear power balance constraints. In addition, since the switch statuses of shunt elements and transformer tap positions are integer variables, the problem becomes a mixed integer nonlinear optimization problem (MINLP). Execution time for MINLP problems for large systems become impractical. Moreover, there is no guarantee for convergence. The main difficulty is the integer variables. Hence, in the first stage of the algorithm, the switch statuses of the shunt elements will be determined. Although the transformer tap variables are integer variables, these variables can be linearized without any practical loss of information. In the second stage of the algorithm the problem becomes a nonlinear optimization problem which can be solved using nonlinear interior point algorithm. The developed algorithm has been tested on IEEE 118 bus test network and convergence performance and execution time of the algorithm is considered as applicable for day ahead reactive power optimization.

Subject Keywords

Day-ahead planning, Multi-period optimization, Multi-objective optimization, Optimal power flow, Reactive power control

URI

https://hdl.handle.net/11511/113768

Collections

Graduate School of Natural and Applied Sciences, Thesis