Abstract
This work aims to tune multiple controllers at the same time for a HVDC system by using a self-generated (SG) simulation-based optimization technique. Online optimization is a powerful tool to improve performance of the system. Proportion integral (PI) controllers of Multi-infeed HVDC systems are optimized by the evaluation of objective functions in time simulation design (TSD). Model based simulation setup is applied for rapid selection of optimal PI control parameters, designed in PSCAD software. A multiple objective function (OF), i.e. Integral absolute error (IAE), integral square error (ISE), integral time absolute error (ITAE), integral time square error (ITSE), and integral square time error (ISTE), is assembled for testing the compatibility of OFs with nonlinear self-generated simplex algorithm (SS-SA). Improved control parameters are achieved after multiple iterations. All OFs generate optimum responses and their results are compared with each other by their minimized numerical values. Disturbance rejection criteria are also proposed to assess the designed controller performance along with robustness of system. Results are displayed in form of graphs and tables in this paper.
Highlights
The AC/DC system stability is a significant performance evaluator of HVDC systems (Anbarasi and Muralidharan, 2016)
Multiple Proportion integral (PI) controllers of the HVDC system are considered and it was concluded that the system can be robust by tuning their control parameters
It is observed that integral time absolute error (ITAE) is the best option with SA tuner because it gives the best overall responses than other objective function (OF) in minimum runs of 87
Summary
The AC/DC system stability is a significant performance evaluator of HVDC systems (Anbarasi and Muralidharan, 2016). The simplex algorithm is one of the convergence algorithms to obtain optimized control values, in order to produce the smallest fitness value of an objective function through a soft computing optimization technique This technique is used in this work to get the optimal values of multiple PI (Aazim et al, 2017) controller parameters (Saravanakumar et al, 2015). The first step is to set the initial control parameters of the HVDC bipolar system and to generate a current error, which is sent to the objective function to integrate the whole error effect and obtain the fitness value This process evaluates the best objective function through multiple runs of simulation for selecting optimal control parameters by using a simplex algorithm (Gole et al, 2003; Zhao et al, 2007). Our main focus is to stabilize the current that in turn improves the system
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