Sunflower optimization based fractional order fuzzy PID controller for frequency regulation of solar-wind integrated power system with hydrogen aqua equalizer-fuel cell unit

Nayak, Pratap Chandra; Nayak, Barada Prasanna; Prusty, Ramesh Chandra; Panda, Sidhartha

doi:10.1080/15567036.2021.1953636

Cited by 23 publications

(9 citation statements)

References 28 publications

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“…In [23], a fractional-order version of PID is designed, and one FLS is used to optimize all gains. In [24], the frequency control in MG is studied, and a FLSbased PID is schemed. In [25], the efficiency of FLS-PID is examined on a power system, and the accuracy improvement by FLSs is shown.…”

Section: Literature Reviewmentioning

confidence: 99%

A New Type-3 Fuzzy PID for Energy Management in Microgrids

Fan

Mohammadzadeh

Kausar

et al. 2022

Advances in Mathematical Physics

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More recently, type-3 (T3) fuzzy logic systems (FLSs) with better learning ability and uncertainty modeling have been presented. On other hand, the proportional-integral-derivative (PID) is commonly employed in most industrial control systems, because of its simplicity and efficiency. The measurement errors, nonlinearities, and uncertainties degrade the performance of conventional PIDs. In this study, for the first time, a new T3-FLS-based PID scheme with deep learning approach is introduced. In addition to rules, the parameters of fuzzy sets are also tuned such that a fast regulation efficiency is obtained. Unlike the most conventional approaches, the suggested tuning approach is done in an online scheme. Also, a nonsingleton fuzzification is suggested to reduce the effect of sensor errors. The proposed scheme is examined on a case-study microgrid (MG), and its good frequency stabilization performance is demonstrated in various hard conditions such as variable load, unknown dynamics, and variation in renewable energy (RE) sources.

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Section: Literature Reviewmentioning

confidence: 99%

A New Type-3 Fuzzy PID for Energy Management in Microgrids

Fan

Mohammadzadeh

Kausar

et al. 2022

Advances in Mathematical Physics

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“…The state-space equations defining the considered microgrid system are expressed as (11)(12)(13)(14)(15)(16)(17)(18)(19):…”

Section: State-space Equation Of Microgridmentioning

confidence: 99%

“…For the steady operation of an AGC of thermal power system comprising cycle gas turbine, PI/PID controller are adjusted successfully by fractal search algorithm in Reference 17. The perception of economic efficiency of AGC and its problem in power systems using Sunflower optimization (SFO) based fractional order controller 18 and Grasshopper optimization (GO) based multi‐stage PID 19 controller is well addressed, respectively. The response of FACTS devices and additionally different types of secondary controllers are used for solving the AGC problem in Reference 20.…”

Section: Introductionmentioning

confidence: 99%

Hybrid dragonfly algorithm and pattern search optimized adaptive fuzzy PID controller for frequency regulation of multi microgrid system using Henkel matrix based reduced‐order model

Mishra

Nayak

Prusty

et al. 2022

Int J Numerical Modelling

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This paper proposes frequency regulation of multi microgrid systems. The system under study consists of wind energy, solar energy and energy storage system operating in dissimilar combinations to establish equilibrium among the production and consumer demand. In this proposed work, stability analysis of the concerned model is studied using the Henkel matrix approach of the reduced‐order model. Again, an attempt is made to apply the adaptive fuzzy proportional integral and derivative (AFPID) controller for frequency control of the system. The optimal gains of the controllers are tuned by reducing the integral time absolute error using a hybrid dragonfly algorithm supported by the pattern search (hDAPS) algorithm. The efficacy of the proposed adaptive fuzzy controller is examined with fuzzy PID and PID for different cases of the concern system. The efficacy of the hDAPS algorithm is justified over the genetic algorithm, dragonfly algorithm and particle swarm optimization. The robustness study also reveals that the systems are offering reduced overshoot and undershoot under different scenarios of load and source environment. To demonstrate expediency of the proposed controller sensitivity analysis was carried out under different loading conditions. In addition, to show the efficiency of the hDAPS tuned AFPID controller, the outcomes were associated with other artificial intelligence methods reported in the literature.

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“…For frequency regulation of hybrid power systems with electric vehicles, the authors in [14] developed the fractional-order adaptive fuzzy PID controller with modified salp swarm algorithm optimization. The fractional order fuzzy PID controller for frequency regulation of a solar-wind integrated power system with a hydrogen aqua equalizer-fuel cell unit was presented by the authors in [15]. In [16], the authors suggested developing a fuzzy logic controller for load frequency management in an isolated hybrid power system.…”

Section: Introductionmentioning

confidence: 99%

Optimal Sizing and Power System Control of Hybrid Solar PV-Biogas Generator with Energy Storage System Power Plant

et al. 2023

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In this paper, the electrical parameters of a hybrid power system made of hybrid renewable energy sources (HRES) generation are primarily discussed. The main components of HRES with energy storage (ES) systems are the resources coordinated with multiple photovoltaic (PV) cell units, a biogas generator, and multiple ES systems, including superconducting magnetic energy storage (SMES) and pumped hydro energy storage (PHES). The performance characteristics of the HRES are determined by the constant power generation from various sources, as well as the shifting load perturbations. Constant power generation from a variety of sources, as well as shifting load perturbations, dictate the HRES’s performance characteristics. As a result of the fluctuating load demand, there will be steady generation but also fluctuating frequency and power. A suitable control strategy is therefore needed to overcome the frequency and power deviations under the aforementioned load demand and generation conditions. An integration in the environment of fractional order (FO) calculus for proportion-al-integral-derivative (PID) controllers and fuzzy controllers, referred to as FO-Fuzzy-PID controllers, tuned with the opposition-based whale optimization algorithm (OWOA), and compared with QOHSA, TBLOA, and PSO has been proposed to control the frequency deviation and power deviations in each power generation unites. The results of the frequency deviation obtained by using FO-fuzzy-PID controllers with OWOA tuned are 1.05%, 2.01%, and 2.73% lower than when QOHSA, TBLOA, and PSO have been used to tune, respectively. Through this analysis, the algorithm’s efficiency is determined. Sensitivity studies are also carried out to demonstrate the robustness of the technique under consideration in relation to changes in the sizes of the HRES and ES system parameters.

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Sunflower optimization based fractional order fuzzy PID controller for frequency regulation of solar-wind integrated power system with hydrogen aqua equalizer-fuel cell unit

Cited by 23 publications

References 28 publications

A New Type-3 Fuzzy PID for Energy Management in Microgrids

A New Type-3 Fuzzy PID for Energy Management in Microgrids

Hybrid dragonfly algorithm and pattern search optimized adaptive fuzzy PID controller for frequency regulation of multi microgrid system using Henkel matrix based reduced‐order model

Optimal Sizing and Power System Control of Hybrid Solar PV-Biogas Generator with Energy Storage System Power Plant

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