Controller Parameters Optimization for Multi-Terminal DC Power System Using Ant Colony Optimization

Abstract

Voltage source converter based multi -terminal DC grids (VSC -MTDC) are widely used for integration of renewable resources. Control of these grids requires vector control method, which includes inner and outer current controllers, tuning of these controllers is very important. Conventionally used tuning methods consider approximated linear model to tune the proportional -integral (PI) parameters of voltage source converter (VSC) which fails to produce optimum disturbance rejection results. In this research an Ant Colony Optimization (ACO) technique is used to get the optimum parameters of inner and outer power control layers for multi -terminal DC system. ACO is applied simultaneously on inner and outer control layers and results are compared with classical tuning method and well established meta -herustic technique, Particle Swarm Optimization (PSO) using MATLAB software. Dynamic models of VSC -MTDC are developed in PSCAD/EMTDC to exalt the qualities of the presented tuning method. In this paper, a four terminal VSC -MTDC has been used under different sequence of events of disturbances e.g. load change on AC side, active power reference change for inverter and rectifier mode and disconnection of one terminal to evaluate the robustness of ACO algorithm with respect to classical method. The proposed tuning method gives superior results under different disturbance compared to conventional method.

A Coordinated Optimization Model for Solar Photovoltaic Integrated DC Distribution Networks

“…The dynamic response of the proposed controller scheme performed well when subjected to varying irradiances. Furthermore, research on the predictive control and optimal controller parameters to improve response of converters to disturbances in DC distribution networks is presented in [27], [28].…”

Coordinated optimization model for solar PV systems integrated into DC distribution networks

“…Economic benefits of integrating the use of DC DERs into distribution systems [5][6][7][8][9][10][11] Optimal siting and design of grid-connected PV systems [12][13][14][15][16][22][23][24][25][26] PV output research [17][18][19][20][21] Techno-economic feasibility of an AC/DC hybrid distribution network [27][28][29][30][31][32][33] Optimal control of DC-DC, and AC-DC converters supporting DC distribution [8,[34][35][36][37][38][39] DC distribution-Analysis and optimization [40][41][42][43][44][45][46][47] To the best of the authors' knowledge, there are no existing works that present a coordinated optimization tool for the control of voltage controllers in DC distributed networks incorporating solar PV systems, such that solar power is maximized, and substation power is minimized.…”

“…The dynamic response of the proposed controller scheme performed well when subjected to varying irradiances. Furthermore, research on the predictive control and optimal controller parameters to improve response of converters to disturbances in DC distribution networks is presented in [38,39].…”

Hybrid Optimized PI Controller Design for Grid Tied PV Based Electric Vehicle

“…The issues faced by conventional PI controllers are solved and the performance is enhanced by using metaheuristic algorithms, which are simple, robust and easy to implement [18][19][20][21]. Some of the metaheuristic algorithms that are adopted to tune the PI parameters more accurately are Grey Wolf Optimization (GWO) [22], Whale Optimization Algorithm (WOA) [23], Ant Colony Optimization (ACO) [24], Coot Bird Metaheuristic Optimizer (CBMO) [25], etc. For increasing the optimization efficiency in a wider range the hybrid algorithms are introduced by combining different algorithms.…”