Abstract
This paper presents a comprehensive evaluation of the effect of quasi oppositional - based learning method utilization in output tracking control through a swarm-based multivariable Proportional-Integral-Derivative (SMPID) controller, which is tuned by a novel performance index based on the step response characteristics in multi-input multi-output (MIMO) system. The role of the proposed quasi oppositional based SMPID controller is to modify the tracking strategy on AC/HVDC interconnected systems while reducing the related cost function. The proposed analysis is established considering the most highly cited, well-known tested and newly expanded swarm-based optimization algorithms (SBOAs), such as Grasshopper Optimization Algorithm (GOA), Grey Wolf Optimization (GWO), Artificial Fish Swarm Algorithm (AFSA), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO). These methods are used in the tuning process of multivariable PID (MPID) controller for output tracking control of an interconnected AC/DC system with virtual inertia emulation-based HVDC capabilities. The virtual inertia-based HVDC model, which is using a derivative technique, is attached for enhancing the system frequency dynamics with fast power injection during the contingency. The potential possibility for achieving a suitable assessment about the velocity reaction, the flexibility response, and the accuracy of the tracking process is provided by four different scenarios which are operated by step load changes as essential inputs in AC/HVDC interconnected MIMO system. Also the proposed fitness function, as deviation characteristics of the step response in MIMO transfer function in virtual inertia emulation based HVDC model, is compared with integral time absolute error (ITAE), as the standard performance index in the optimization process. The results are compared with the conventional tuned MPID (C - MPID) controller using MATLAB software. The obtained analysis emphasizes how the tuned SMPID can significantly increase the capability of tracking control on the proposed AC/HVDC interconnected model.
Highlights
The comprehensive growth and rapid development of AC systems into a multi-area interconnected scenario, including the increasing level of high power converter applications in modern power systems, is giving rise to a very multiplex and challenging issue, which will affect the overall power system and the frequency control in AC/DC systems [1]
It is useful to consider the variation of the tested multi-input multi-output (MIMO) outputs, two outputs related to MIMO features, with tie-line AC power between the areas ( PtieAC12)
In this study, an endeavor is constructed to enhance tracking control strategy on a test Algorithm (ABC) (AFSA) (AGC) interconnected system with Virtual inertia based HVDC model employing a tuned multivariable PID (MPID) controller in which the matrix of its coefficients is set based on the selected swarm-based optimization algorithms (SBOAs) that they are provided with utilizing an effective nature-inspired optimization methodology, called quasi-oppositional based learning (QO-BL) algorithm
Summary
The comprehensive growth and rapid development of AC systems into a multi-area interconnected scenario, including the increasing level of high power converter applications in modern power systems, is giving rise to a very multiplex and challenging issue, which will affect the overall power system and the frequency control in AC/DC systems [1]. This virtual inertia is emulated by using modern control of power converters by attention to the added short-term energy storage system (ESS) within the DC link of the HVDC converters [9] It can increase the possibility of having a higher amount of distributed generation systems, connected to the grid through power converters, without hindering the system stability. In many other applied systems, in addition to stabilizing, the other main aim will be signal tracking as well [28]–[30] In these cases, unlike regulator systems, all reference inputs are non–zero (r(t) = 0), and in tracking control, the closed-loop outputs will follow the reference inputs. (iii) The incorporation of swarm-based techniques with MPID control is leading to an accurate hybrid solution that can be used as an evaluated strategy for the output tracking problem of ESS-based virtual inertia emulation AC/DC systems. VIRTUAL INERTIA–BASED AC/HVDC SYSTEM This section is focused on the presentation of a definition for the concept of inertia emulation on AC/HVDC interconnected systems as a two-area model
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