Two-stage multi-objective OPF for AC/DC grids with VSC-HVDC: Incorporating decisions analysis into optimization process

TL;DR

This paper introduces a novel two-stage multi-objective optimal power flow method for hybrid AC/DC grids with VSC-HVDC, integrating decision analysis techniques to automatically identify optimal operation points.

Contribution

It presents a new two-stage solution combining multi-objective particle swarm optimization with fuzzy c-means clustering and grey relation projection for decision-making in MOPF.

Findings

Effective in IEEE 14- and 300-bus systems

Automatically identifies 'best' operation points

Enhances decision-making in hybrid AC/DC grids

Abstract

A two-stage solution approach for solving the problem of multi-objective optimal power flow (MOPF) is proposed for hybrid AC/DC grids with VSC-HVDC. First, a MOPF model for hybrid AC/DC grids is built to coordinate the economy, voltage deviation and environmental benefits. Then, a two-stage solution approach, incorporating decision analysis into optimization process, is presented to solve the model. The first stage of the approach is consisted of a multi-objective particle swarm optimization algorithm with a hybrid coding scheme employed to find multiple Pareto-optimal solutions. The second stage will have the obtained solutions clustered into different groups using fuzzy c-means (FCM) clustering, and then the 'best' compromise solutions are obtained by calculating the priority memberships of the solutions belonging to the same groups via grey relation projection (GRP) method. The novelty of this approach lies primarily in incorporating the FCM-GRP based decisions analysis technique into MOPF studies, thereby assisting decision makers to automatically identify the 'best' operation points. The effectiveness of the proposed approach is verified based on the test results of the IEEE 14- and 300- bus systems.