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A Quasi Opposition Lion Optimization Algorithm for Deregulated AGC Considering Hybrid Energy Storage System

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Abstract

This paper presents the integration of renewable energy resources into the Automatic Generation Control (AGC) of two area power system under deregulation. Area-1 includes the combination of thermal system, gas power system, aggregate Electric Vehicle (EV), and Dish-Stirling Solar Thermal system (DSTS) whereas area-2 contains thermal system, gas power system, aggregate electric vehicle, and Wind Turbine System (WTS). To achieve the realistic approach, nonlinearities such as Generation Rate Constraint (GRC), Governor Dead Band (GDB), and Boiler Dynamics (BD) are explored in proposed test system. AGC's main aim is to keep the balance between load and generation and to achieve this balance secondary frequency regulation mechanism play an important role. Therefore, a tilt proportional integral derivative controller has been used to achieve desired dynamic response of the system. A new Quasi Opposition Lion Optimization Algorithm (QOLOA) has been suggested for studied system to get the optimum values of controller and system parameters. Integral Square Error (ISE) is considered as an objective function for the optimization of the anticipated AGC mechanism. Furthermore, Hybrid Energy Storage (HES) is used to damp the oscillation of the considered AGC system. Hence, for this investigation, it consists of the hybridization of the Redox Flow Battery (RFB) and Superconducting Magnetic Energy Storage (SMES) system. Additionally, the sensitivity analysis is also performed to evaluate the robustness of the proposed QOLOA based control scheme. The suggested control mechanism is compared with previously published work on the same platform to show the effectiveness and its superiority of presented work.

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Abbreviations

AGC:

Automatic generation control

DSTS:

Dish-stirling solar thermal

WTS:

Wind turbine system

EV:

Electric vehicle

GRC:

Generation rate constraint

GDB:

Governor dead band

BD:

Boiler dynamics

QOLOA:

Quasi opposition lion optimization algorithm

HES:

Hybrid energy storage

SLP:

Step load perturbation

RLP:

Random load perturbation

ES:

Energy storage

BES:

Battery energy storage

FES:

Flywheel energy storage

CES:

Capacitive energy storage

SMES:

Superconducting magnetic energy, storage

RBF:

Redox flow battery

UC:

Ultra capacitor

GENCO:

Generation company

DISCO:

Distribution company

TRANSCO:

Transmission company

PID:

Proportional integral derivative

2DOF:

Two degree of freedom

DPM:

DISCO participation matrix

FO:

Fraction order

IO:

Integral order

Kp :

Proportional constant

Ki :

Integral constant

Kd :

Derivative constant

N:

Derivative filter

n:

Tilt constant

ub:

Upper limit

lb:

Lower limit

ISE:

Integral squared error

IAE:

Integral absolute error

ITSE:

Integral time-weighted squared error

ITAE:

Integral time-weighted absolute error

FOD:

Figure of demerit

PSO:

Particle swarm optimization

WOA:

Whale optimization algorithm

TLBO:

Teaching learning-based optimization

GWO:

Grey wolf optimization

SOC:

State of charging

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Authors and Affiliations

  1. Department of Electrical Engineering, NIT Patna, Patna, India

    Ashiwani Kumar & Ravi Shankar

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  1. Ashiwani Kumar
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  2. Ravi Shankar
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Correspondence to Ashiwani Kumar.

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Appendix

Appendix

1.1 Thermal Power System

Thermal power plant: Tg = 0.08 s; Kr = 0.5; Tr = 10 s;Tt = D 0.3 s; Ng1 = 0.8; Ng2 = 0.2/π; GRC: 10%/minute. Boiler dynamics: K1 = 0.85; K2 = 0.095; K3 = 0.92; CB = 200; TD = 0 s; TF = 10 s; KIB = 0.030; TIB = 26 s; TRB = 69 s.

\(\Delta P_{T}\) = Turbine output of thermal generator.

\(\Delta P_{{TH}}\) = Thermal generator output.

1.2 Gas Power System

X = Speed governor lead time constant = 0.6 s, Y = Speed governor lag time constant = 1 s, valve position constant = a = 1, b = 0.05 and c = 1, Fuel.

Power System = 0.23 s, TCR = combustion reaction time delay = 0.01 s, TCD = Compressor discharge volume time constant = 0.2 s.

1.3 Power System

Power system constant = KP = 120 Hz/pu,

Tie line constant = T12 = 0.0866, Ratio of power capacity of area-1 to area-2 = \(\alpha _{{12}}\) = -1, System Loading = 50%, Bi = 0.425, Hi = 5 s, Time constant of power system = Tpi = 20 s, Rth = 2.4 Hz/pu MW.

1.4 Electric Vehicle

1/Rev = 0.4167, KEV = 1, Ngv = 10,000.

1.5 Renewable Sources

Gain of wind system = KWTS = 1,

Time constant of wind system = TWTS = 1.5 s,

Gain of solar system = KDSTS = 1,

Time constant of solar TDSTS = 5 s.

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Kumar, A., Shankar, R. A Quasi Opposition Lion Optimization Algorithm for Deregulated AGC Considering Hybrid Energy Storage System. J. Electr. Eng. Technol. 16, 2995–3015 (2021). https://doi.org/10.1007/s42835-021-00835-0

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