Optimal design of fuzzy-AGC based on PSO &amp; RCGA to improve dynamic stability of interconnected multi area power systems

Falehi, Ali Darvish

doi:10.1007/s11633-017-1064-0

Cited by 17 publications

(10 citation statements)

References 28 publications

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“…The iteration of HQL is updated according to (10) and (11). Assuming that the probability of the action occurring in the initial state is the same, the action a k is executed, and the state is transferred to s k+1 .…”

Section: A: Hql Algorithmmentioning

confidence: 99%

“…In practice, proportional-integral (PI) controller is widely used in the total power references tracking of AGC in microgrids. Moreover, bacterial foraging optimization (BFO) [9], particle swarm optimization (PSO) [10], genetic algorithm (GA) [11], and conventional gradient descent algorithm were applied to simultaneously optimize all the control parameters of microgrids. In previous studies of the authors, the reinforcement learning (RL) has been applied to the traditional AGC [12]- [14] of the interconnected power grid to solve the random disturbance caused by massive integration of distributed energy.…”

Section: Introductionmentioning

confidence: 99%

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A Virtual Generation Ecosystem Control Strategy for Automatic Generation Control of Interconnected Microgrids

Jian-chu

et al. 2020

IEEE Access

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The continuous access of new energy and distributed energy, as well as the random disturbance of load power, affect the security and stability of microgrids. A virtual generation ecosystem control (VGEC) strategy is proposed in this paper, which adopts the idea of time tunnel and the principle of a new winloss criterion to achieve a fast automatic generation control power dispatch, optimal coordinated control of microgrids. A two-layer dynamic power dispatch structure is introduced in the proposed strategy, which combines hierarchical Q-learning with consensus theory to improve the adaptability of the consistency algorithm in complex random environments. Both the IEEE standard two-area load frequency control model and the interconnected microgrids model are used in simulation for comparison and verification. The results show that, by using the VGEC strategy, the control performance of microgrids can be improved, while can reduce power generation cost, and obtain faster convergence speed and stronger robustness compared with other algorithms. INDEX TERMS Automatic generation control, virtual generation ecosystem control, time tunnel idea, interconnected microgrids.

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Section: A: Hql Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Virtual Generation Ecosystem Control Strategy for Automatic Generation Control of Interconnected Microgrids

Jian-chu

et al. 2020

IEEE Access

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“…The state space equations of the understudy power system have been presented as follows :

\overset{x}{true} = italicAx + italicBu + G

x^{T} = ([],,,,,,,,,,,,,,,,,, normalΔ f_{1}, normalΔ P_{R 1}, normalΔ P_{G 1}, normalΔ P_{italicref 1}, normalΔ x_{1}, normalΔ f_{2}, normalΔ P_{R 2}, normalΔ P_{G 2}, normalΔ P_{italicref 2}, normalΔ x_{2}, normalΔ f_{3}, normalΔ P_{R 3}, normalΔ P_{G 3}, normalΔ P_{italicref 3}, normalΔ x_{3}, normalΔ P_{12}, normalΔ P_{23}, normalΔ P_{31})

u^{T} = ([],,, normalΔ P_{D 1}, normalΔ P_{D 2}, normalΔ P_{D 3})

…”

Section: Linearization and Modeling Of Interconnected Power System Wimentioning

confidence: 99%

“…PSO, one of the global heuristic‐based random‐walk algorithms, is patterned from the social and group life of swarms like fish schooling and bird flocking . Particles are stochastically created over the feasible design domain.…”

Section: Description Of Multi‐objective Optimization Algorithmsmentioning

confidence: 99%

Optimal Fractional Order BELBIC to Ameliorate Small Signal Stability of Interconnected Hybrid Power System

Falehi

2019

Env Prog and Sustain Energy

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The small signal stability of power systems integrated with fallback large‐scale distributed energy resources is of utmost importance during the perturbation conditions. Among the various renewable resources in power systems: photovoltaic, fuel cell, wind turbine, diesel engine, aqua electrolyser, battery, ultra‐capacitor, and flywheel is becoming more favored in last decades. AGC, a main control system of frequency modulation, must correctly alleviate the low frequency oscillations caused by the perturbation and variable output power of renewable resources. In this regard, FOBELBIC is here introduced to enhance the damping capability of AGC. Since both the frequency and tie‐line power oscillations must be concomitantly alleviated, the small signal stability problem has been multi‐objectively formulated. Due to the exploration capability of MOALO, it has been chosen to extract the optimal parameters of FOBELBIC. Furthermore, MOPSO, MOBA, and NSGA‐II have been studied to demonstrate the capability of MOALO. To verify and validate the damping performance of suggested controller, it has been evaluated in three‐area reconstructed power system under the load perturbations as well as wind speed and sun radiation variations, and at the same time compared with BELBIC and PID controllers. Finally, the simulation results have evidently confirmed the damping the performance of MOALO‐based FOBELBIC to enhance the small signal stability of hybrid power system. © 2019 American Institute of Chemical Engineers Environ Prog, 38:e13146, 2019

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“…The authors of [18] employed a differential evolution approach to improve AGC while taking nonlinearity into account as a governor deadband. In order to improve the performance of a single-area AGC in [19] uses a more appropriate technique based on increasing the controller's transfer function using Laurent series to boost the controller performance of two-area AGC systems, the Firefly Algorithm outperformed various optimization strategies [20]. The gravity search technique was designed in [21,22] to increase the reaction to a deviation in frequency between multi-area power systems.…”

Section: Introductionmentioning

confidence: 99%

Optimal Design of Automatic Generation Control Based on Simulated Annealing in Interconnected Two-Area Power System Using Hybrid PID—Fuzzy Control

Magzoub

Alquthami

2022

Energies

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Electricity demand continues to rise on a daily basis. The most difficult task is ensuring that customers have access to reliable, high-quality electricity regardless of the weather. Automatic generation control (AGC) accomplishes this by keeping the target output power and frequency constant despite load fluctuations. This paper presents a hybrid PID-fuzzy controller for optimal automatic generation control in a two-area interconnected power system. A comparative analysis of the proposed controller was performed with the PID controller. The parameters of the both controllers were developed by simulated annealing (SA) techniques in order to obtain the best dynamic performance. MATLAB Simulink software was used to simulate the models. The results of the simulation for the two-area power system based on simulated annealing using the hybrid PID–fuzzy controller showed superior performance in comparison to a conventional PID controller.

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Optimal design of fuzzy-AGC based on PSO & RCGA to improve dynamic stability of interconnected multi area power systems

Cited by 17 publications

References 28 publications

A Virtual Generation Ecosystem Control Strategy for Automatic Generation Control of Interconnected Microgrids

A Virtual Generation Ecosystem Control Strategy for Automatic Generation Control of Interconnected Microgrids

Optimal Fractional Order BELBIC to Ameliorate Small Signal Stability of Interconnected Hybrid Power System

Optimal Design of Automatic Generation Control Based on Simulated Annealing in Interconnected Two-Area Power System Using Hybrid PID—Fuzzy Control

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