An optimal reactive power pre-dispatch approach for minimizing active power losses

Renewable energy sources (RES) depend on location and weather conditions, which can negatively impact the transmission system operator’s active power losses. This paper proposes a method that operates between the day-ahead market clearing and real-time operation. It enables transmission system operators (TSOs) to procure supplemental reactive power from generator companies (GenCos) in order to minimize active power losses. To achieve this, a multi-objective, bi-level optimization model is proposed. The leader’s goal is to find a fair reactive power price that leads to the best trade-off between the two conflicting objectives of maximizing the savings for the TSO and the extra reactive power income for GenCos. The follower problem considers an optimal power flow model and minimizes the costs for the TSO by selecting the appropriate control action. The method was evaluated using the Nordic 44 test case. Results indicate a potential price range starting from <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m1"> <mml:mrow> <mml:mn mathvariant="bold">0</mml:mn> <mml:mtext> $</mml:mtext> <mml:mo>/</mml:mo> <mml:mtext>MVarh</mml:mtext> </mml:mrow> </mml:math> , which is the preferable price for the TSO, up to <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m2"> <mml:mrow> <mml:mn mathvariant="bold-italic">1.08</mml:mn> <mml:mtext> $</mml:mtext> <mml:mo>/</mml:mo> <mml:mtext>MVarh</mml:mtext> </mml:mrow> </mml:math> , representing the best possible price for the GenCos. Using the Tchebycheff scalarization method, the reactive power price of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m3"> <mml:mrow> <mml:mn mathvariant="bold-italic">0.28</mml:mn> <mml:mtext> $</mml:mtext> <mml:mo>/</mml:mo> <mml:mtext>MVarh</mml:mtext> </mml:mrow> </mml:math> is found to be the best trade-off for both parties. However, these prices depend on multiple factors related to the case study. Overall, the method can improve the interaction between GenCos and the TSO by proposing a fair remuneration for GenCos, which is still profitable for the TSO.