A Multistage Solution Approach for Dynamic Reactive Power Optimization Based on Interval Uncertainty

Xiaodong Shen,Yang Liu,Yan Liu

doi:10.1155/2018/3854812

Abstract

In order to solve the uncertainty and randomness of the output of the renewable energy resources and the load fluctuations in the reactive power optimization, this paper presents a novel approach focusing on dealing with the issues aforementioned in dynamic reactive power optimization (DRPO). The DRPO with large amounts of renewable resources can be presented by two determinate large-scale mixed integer nonlinear nonconvex programming problems using the theory of direct interval matching and the selection of the extreme value intervals. However, it has been admitted that the large-scale mixed integer nonlinear nonconvex programming is quite difficult to solve. Therefore, in order to simplify the solution, the heuristic search and variable correction approaches are employed to relax the nonconvex power flow equations to obtain a mixed integer quadratic programming model which can be solved using software packages such as CPLEX and GUROBI. The ultimate solution and the performance of the presented approach are compared to the traditional methods based on the evaluations using IEEE 14-, 118-, and 300-bus systems. The experimental results show the effectiveness of the presented approach, which potentially can be a significant tool in DRPO research.

Highlights

Reactive power optimization’s importance in enabling the operation safety in the power system has been proved
In order to solve the uncertainty and randomness of the output of the renewable energy resources and the load fluctuations in the reactive power optimization, this paper presents a novel approach focusing on dealing with the issues aforementioned in dynamic reactive power optimization (DRPO)
From the mathematical point of view, the reactive power optimization can be formulated as the mixed-integer/nonlinear programming model, which is mainly categorized into the static reactive power optimization (SRPO) [1,2,3] and the dynamic reactive power optimization (DRPO) considering multiperiod coupling [4,5,6,7,8,9]

Summary

Introduction

Reactive power optimization’s importance in enabling the operation safety in the power system has been proved. The reasons mainly include the following: (1) DRPO contains the continuous and discrete variables as a typical mixed integer nonlinear nonconvex problem so that its global optimal solution cannot be obtained due to the nonconvex power flow equations [5,6,7,8,9]; (2) DRPO specially considers the intertemporal constraints for the operating times of adjusting discrete reactive power compensation devices. This point makes the solution become computational intensive and time consuming [6,7,8,9,10]. The rest of this paper is organized as follows: in Section 2, a dynamic reactive power optimization model based on interval uncertainty is presented; Section 3 presents the solution of the model; Section 4 presents the solution of the MISOCP based relaxation formulation; Section 5 discusses the experimental results; Section 6 concludes the paper

A Dynamic Reactive Power Optimization Model Based on Interval Uncertainty

Optimization Model Conversion Based on Interval Uncertainty

The Multistage Mathematical Model of Dynamic Reactive Power Optimization

Experimental Result

Conclusion