PLC – HMI Automation Based Cascaded Fuzzy PID for Efficient Energy Management and Storage in Real Time Performance of a Hydro Electric Pumped Storage Power Plant

Priyadharson, A. Selwin Mich; Ganesan, R.; Surarapu, Prabhu Kumar

doi:10.1016/j.protcy.2015.10.022

Cited by 8 publications

(2 citation statements)

References 7 publications

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“…Real-time experimentation was performed to study the effect of external disturbances and parameter variations. The technique of ADRC-P (Zuo et al , 2016), PID-P (Priyadharson et al , 2015) and the proposed controller was applied in the same process. The process was settled at 0% levels initially and then a set-point of 40% level is given to it and the effect of controller efforts was recorded.…”

Section: Resultsmentioning

confidence: 99%

Active disturbance rejection-based industrial cascade control plant with cloud monitoring

Bhaskarwar¹,

Aole²,

Chile³

2021

JEDT

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Purpose The purpose of this paper is to provide benefits for companies or organizations, which deal with fewer input-outputs and wanted to control their industrial processes remotely with a robust control strategy. Design/methodology/approach In this paper, an active disturbance rejection control (ADRC) strategy is used for the two tank level process plant and it is remotely monitored with the industrial internet of things technology. The disturbances in a primary and secondary loop of the cascade process, which are affecting the overall settling time (ts) of the process, are eliminated by using the proposed, ADRC-ADRC structure in the cascade loop. The stability of the proposed controller is presented with Hurwitz’s stability criteria for selecting gains of observers. The results of the proposed controller are compared with the existing active disturbance rejection control-proportional (ADRC-P) and proportional-integral derivative-proportional (PID-P)-based controller by experimental validation. Findings It is observed that the settling time (ts) in the case of the proposed controller is improved by 60% and 55% in comparison to PID-P and ADRC-P, respectively. The level process is interfaced with an industrial controller and real-time data acquired in matrix laboratory (MATLAB), which acted as a remote monitoring platform for the cascade process. Originality/value The proposed controller is designed to provide robustness against disturbance and parameter uncertainty. This paper provides an alternate way for researchers who are using MATLAB and ThingSpeak cloud server as a tool for the implementation.

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Section: Resultsmentioning

confidence: 99%

Active disturbance rejection-based industrial cascade control plant with cloud monitoring

Bhaskarwar¹,

Aole²,

Chile³

2021

JEDT

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“…Others have investigated applications of fuzzy logic to regulate small hydroelectric systems [13,14]. Unlike the level-based controllers, the newly proposed method improves control of hydroelectric turbines by employing controllers that regulate according to the mass flow rates of rivers.…”

Section: Turbine Control Algorithmsmentioning

confidence: 99%

A Computed River Flow-Based Turbine Controller on a Programmable Logic Controller for Run-Off River Hydroelectric Systems

Jidin

Othman

2017

Energies

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Abstract:The main feature of a run-off river hydroelectric system is a small size intake pond that overspills when river flow is more than turbines' intake. As river flow fluctuates, a large proportion of the potential energy is wasted due to the spillages which can occur when turbines are operated manually. Manual operation is often adopted due to unreliability of water level-based controllers at many remote and unmanned run-off river hydropower plants. In order to overcome these issues, this paper proposes a novel method by developing a controller that derives turbine output set points from computed mass flow rate of rivers that feed the hydroelectric system. The computed flow is derived by summation of pond volume difference with numerical integration of both turbine discharge flows and spillages. This approach of estimating river flow allows the use of existing sensors rather than requiring the installation of new ones. All computations, including the numerical integration, have been realized as ladder logics on a programmable logic controller. The implemented controller manages the dynamic changes in the flow rate of the river better than the old point-level based controller, with the aid of a newly installed water level sensor. The computed mass flow rate of the river also allows the controller to straightforwardly determine the number of turbines to be in service with considerations of turbine efficiencies and auxiliary power conservation.

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Development on Intellective Collecting Apparatus of Slope Monitoring Data with Human Machine Interaction

Shen

Tan

Wang³

2018

Wireless Pers Commun

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PLC – HMI Automation Based Cascaded Fuzzy PID for Efficient Energy Management and Storage in Real Time Performance of a Hydro Electric Pumped Storage Power Plant

Cited by 8 publications

References 7 publications

Active disturbance rejection-based industrial cascade control plant with cloud monitoring

Active disturbance rejection-based industrial cascade control plant with cloud monitoring

A Computed River Flow-Based Turbine Controller on a Programmable Logic Controller for Run-Off River Hydroelectric Systems

Development on Intellective Collecting Apparatus of Slope Monitoring Data with Human Machine Interaction

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