Design of Load Frequency Control for a Microgrid Using D-partition Method

Verónica, Airam; Kumar, Naresh; González-Longatt, Francisco

doi:10.1515/ijeeps-2019-0175

Cited by 17 publications

(12 citation statements)

References 15 publications

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“…The result was remarkable however, the controller operates only when the load is reduced. (Veronica et al, 2020) presented a work on load frequency control (LFC) scheme for the distributed generation (DG) system of the microgrid using the D-partition method (DPM). Simulation results demonstrate the robustness of the DPM, which is superior in damping frequency oscillations of microgrid in small load only.…”

Section: Related Workmentioning

confidence: 99%

An Improved Hybrid Micro-Grid Load Frequency Control Scheme for an Autonomous System

Abdulwahab¹,

Faskari²,

Belgore³

et al. 2021

FUOYEJET

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This paper presents an improved hybrid micro-grid load frequency control scheme for an autonomous system. The micro-grid system comprises of renewable and non-renewable energy-based Power Generating Units (PGU) which consist of Solar Photovoltaic, WT Generator, Solar Thermal Power Generator, Diesel Engine Generator, Fuel Cell (FC) with Aqua Electrolizer (AE). However, power produce from renewable sources in microgrid are intermittent in supply, hence make it difficult to maintain power balance between generated power and demand. Therefore, Battery energy storage system, ultra-capacitor and flywheel energy storage systems make up the energy storage units. These separate units are selected and combined to form two different scenarios in this study. This approach mitigates frequency fluctuations during disturbances (sudden load changes) by ensuring balance between the generated power and demand. For each scenario, Moth flame optimization algorithm optimized Proportional-Integral controllers were utilized to control the micro-grid (to minimize fluctuations from the output power of the non-dispatchable sources and from sudden load change). The results of the developed scheme were compared with that of Quasi-Oppositional Harmony Search Algorithm for overshoot and settling time of the frequency deviation. From the results obtained, the proposed scheme outperformed that of the quasi-oppositional harmony search algorithm optimized controller by an average percentage improvement of 35.95% and 28.76% in the case of overshoot and settling time when the system step input was suddenly increased. All modelling analysis were carried out in MATLAB R2019b environment. Keywords—Frequency Deviation, Micro-grid, Moth flame optimization algorithm, Quasi-Oppositional Harmony Search Algorithm.

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Section: Related Workmentioning

confidence: 99%

An Improved Hybrid Micro-Grid Load Frequency Control Scheme for an Autonomous System

Abdulwahab¹,

Faskari²,

Belgore³

et al. 2021

FUOYEJET

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“…The filter aids to suppress the undesired high-frequency noise of the control signal [33][34][35][36]. Furthermore, some researchers have suggested implementing the Fuzzy logic controller (FLC) along with conventional controllers to improve the overall system performance [37][38][39][40][41]. The input variables of the fuzzy control system are generally defined by combinations of membership functions known as fuzzy groups and the parameters can be tuned more smoothly to produce the desired performance required by the system [42,43].…”

Section: Introductionmentioning

confidence: 99%

“…Authors in [52] proposed a fuzzy self-tuning PID controller for LFC based on the Tribe-DE optimization algorithm in parametric uncertainties in addition to the presence of external perturbations. Although the previous fuzzy-based LFC structures had demonstrated a good system response, they could not be considered fully optimized controllers because the input and output scaling factors were the only optimized parameters while the boundaries of the membership functions were selected by the designer experience [37][38][39][40][41][42][43][44][45][46][47][48][49][50].…”

Section: Introductionmentioning

confidence: 99%

Optimal Fuzzy PIDF Load Frequency Controller for Hybrid Microgrid System Using Marine Predator Algorithm

et al. 2021

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This paper presents a fully optimized fuzzy proportional-integral-derivative with filter (FPIDF) load frequency controller (LFC) for enhancing the performance of a hybrid microgrid system. The Marine Predator Algorithm (MPA), a recent optimization algorithm, is used to optimize the gains as well as the input scaling factors and membership functions of the proposed fuzzy PIDF controller. The controller performance is tested on a two-area hybrid microgrid system containing various renewable energy sources and energy storage devices. The effectiveness of the MPA based FPIDF controller is compared with conventional PIDF and FPIDF controllers based on other heuristic techniques presented in literatures. Moreover, different scenarios are implemented in this study to verify the robustness and sensitivity of the proposed controller to different step load perturbations, system parameters variations, wind speed fluctuation and solar irradiance variation. The dynamic response of the system is compared using different controllers in terms of settling time, maximum overshoot and undershoot values. The results are presented in the form of time domain simulations conducted via MATLAB/SIMULINK. INDEX TERMSFuzzy control, load frequency control, marine predator algorithm, microgrid system, PIDF controller, renewable energy, storage systems. NOMENCLATURE A Rotor swept area ACE Area control error B1, B2 Frequency bias coefficients BES Battery energy storage CE Change of error Predator step size control ratio Power coefficient COR Competition over resources E Error FF Fitness function FLC Fuzzy logic controller FPIDF Fuzzy proportional-integral-derivative with filter G Solar radiation ( ) Controller transfer function Solar irradiance under standard test conditions 1 , 2 Input scaling gains 12

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“…Particularly, one of the challenges that are facing the NPS is the reduction of the total system inertia [1], [2]. The total system inertia has been decreased due to the increase of the wind power plants installed in the NPS, closure of thermal power plants, closure of Swedish nuclear power plants and more than 50% increase of the capacity of the interconnector between the NPS and other power systems [3], [4]. It has been estimated that the total kinetic energy of the NPS will be below 120-145 GW•s around 1-19% of the time, this value will be depending on the clime year [5], [6].…”

Section: Introductionmentioning

confidence: 99%

“…Consequently, an efficient procedure to deal with the low inertia and improve the system frequency is the fast-active power injection/absorption (FAPIA) controller. It is a frequency sensitive controller that imitate the inertia response of the synchronous generators by using a proportional (K-f) and derivative (K-df/dt) control actions [4]. The extremely fast response within 1 second and the very short time-delay related to measurement are two advantages that highlight the FAPI controller performance.…”

Section: Introductionmentioning

confidence: 99%

Optimal Settings of Fast Active Power Controller: Nordic Case

Acosta

González-Longatt

Denysiuk

et al. 2020

2020 IEEE 7th International Conference on Energy Smart Systems (ESS)

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The Nordic power system is continuously changing, and it has been experiencing a growing replacing of conventional power plants with renewable power plants, this together with other factors are causing reduction of the total inertia of the Nordic power system. The application of technologies that emulates the dynamic response of the synchronous generators has been a feasible solution. This paper focuses on finding the bests control adjustment of the fast-active power injection/absorption (FAPIA) model by using an optimization algorithm. The FAPIA model has two frequency sensible control actions: a proportional control (K-f) and a derivative control (K-df/dt). The optimization problem is defined using the gains of the proportional and derivative control together with the volume of FAPIA model contribution as decision variables. Two objective functions are determined based on two system frequency response indicators: minimum frequency, the and steady-state frequency. A simplified version of the Nordic power system is implemented for system frequency response studies.

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Design of Load Frequency Control for a Microgrid Using D-partition Method

Cited by 17 publications

References 15 publications

An Improved Hybrid Micro-Grid Load Frequency Control Scheme for an Autonomous System

An Improved Hybrid Micro-Grid Load Frequency Control Scheme for an Autonomous System

Optimal Fuzzy PIDF Load Frequency Controller for Hybrid Microgrid System Using Marine Predator Algorithm

Optimal Settings of Fast Active Power Controller: Nordic Case

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