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

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 * Corresponding author. E-mail address: liyang@neepu.edu.cn (Yang Li). automatically identify the 'best' operation points. The effectiveness of the proposed approach is verified based on the test results of the IEEE 14-and 300bus systems.

Security-Constrained Multi-Objective Optimal Power Flow for a Hybrid AC/VSC-MTDC System With Lasso-Based Contingency Filtering

“…To solve this SC-MOPF model, a new mixed-coded parallel bi-criterion evolution indicator based evolutionary algorithm (BCE-IBEA), PBCE-IBEA for short, with Lassobased contingency filtering is proposed for finding the set of Pareto-optimal solutions; and then, an integrated decision making technique combining fuzzy C-means (FCM) clustering with grey relational projection (GRP) is utilized for identifying the best compromise solutions (BCSs) in [31].…”

“…As a major concern in OPF, the popular generation cost is adopted as an objective function [11,14,[30][31][32]. In addition, minimizing voltage deviation is handled as another objective, since for AC/VSC-MTDC systems, it is of the utmost importance to maintain adequate DC voltages during the actual operations [31,38]. Consequently, the objective function set F0 consists of the generation cost f1 and the voltage deviation index f2, which are…”

“…The GRP method is then utilized to assess the solutions belonging to the same cluster. For a solution l, the priority membership d is calculated by [31] To simplify the analysis, the two objectives have the same weight in this study. Note that for two solutions, the membership d with a higher value represents a better quality.…”

“…To properly evaluate the performance of our approach, comparison tests with other popular algorithms, such as the original BCE-IBEA, NSGA-II [30] and MOPSO [31], have been performed. To facilitate comparison, the common parameters of these algorithms, such as the population size, are set in the same way.…”

Social cognitive optimization with tent map for combined heat and power economic dispatch

“…Recent research demonstrates that the NP-hard problems can be approximately settled by metaheuristic or heuristic algorithms. [4][5][6] Many effective meta-heuristic or heuristic algorithms are implemented to search the optimal solution for the CHPED optimization problem. 1 The metaheuristic algorithms applied in CHPED optimization problem from the literatures include genetic algorithm (GA), 7,8 particle swarm optimization (PSO) algorithm, 9,10 ant colony optimization (ACO) algorithm, 11 bee colony optimization (BCO), 12 cuckoo search (CS) algorithm, 13 grey wolf optimization (GWO) algorithm, 14 artificial immune system (AIS) algorithm, 15 firefly algorithm (FA), 16 harmony search (HS), 17 differential evolution (DE) 18 , fish school search (FSS), 19 invasive weed optimization (IWO) algorithm, 20 group search optimization (GSO), 21 and teaching learning-based optimization (TLBO).…”