Renewable energy source<b>-</b>based multiarea AGC system with integration of EV utilizing cascade controller considering time delay

Saha, Arindita; Saikia, Lalit Chandra

doi:10.1002/etep.2646

Cited by 51 publications

(53 citation statements)

References 23 publications

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“…Raju et al reported the issue of LFC of MAPS with distributed generation resources, using a hybrid Ant-Lion Optimizer (ALO) pattern search optimization technique [38]. The LFC of a power system with electric vehicles was discussed by A. Saha in [39]. Here, electric vehicle system was integrated and the effect of cascade controller was studied.…”

Section: Lfc In a Maps With Conventional Sourcesmentioning

confidence: 99%

“…LFC in conventional power system with single area Contemporary technologies for energy storage; behavior of the load; impact of data latency on LFC; algorithms for optimal tuning of LFC [23][24][25][26] LFC in conventional power system with two area Multi-source two area power system with PI controller; reliability concerns; whale optimization algorithm; multi-source power system with PV and wind turbine; electric vehicle with LFC challenges; multiple sources and the related challenges; intelligent controller for AGC [27][28][29][30][31][32][33] LFC in conventional power system with multiple area controllers for LFC of MAPS; flower pollination algorithm; wind driven optimization algorithm for LFC; GRC with nonlinearity; stochastic fractional search algorithm for LFC; hybrid ALO pattern search optimization; effect of cascade controller on electric vehicles; security concern related to LFC [34][35][36][37][38][39][40] LFC in power system with renewable sources social spider optimizer technique; LFC for multi micro grid power system; improvisation of swarm optimization technique; grasshopper optimization technique; intelligent optimization techniques with renewable sources [41][42][43][44][45][46][47][48][49] Advancements in controllers for LFC of power system…”

Section: Domain Key Problems Addressed Referencesmentioning

confidence: 99%

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Load Frequency Control Using Hybrid Intelligent Optimization Technique for Multi-Source Power Systems

et al. 2021

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The automatic load frequency control for multi-area power systems has been a challenging task for power system engineers. The complexity of this task further increases with the incorporation of multiple sources of power generation. For multi-source power system, this paper presents a new heuristic-based hybrid optimization technique to achieve the objective of automatic load frequency control. In particular, the proposed optimization technique regulates the frequency deviation and the tie-line power in multi-source power system. The proposed optimization technique uses the main features of three different optimization techniques, namely, the Firefly Algorithm (FA), the Particle Swarm Optimization (PSO), and the Gravitational Search Algorithm (GSA). The proposed algorithm was used to tune the parameters of a Proportional Integral Derivative (PID) controller to achieve the automatic load frequency control of the multi-source power system. The integral time absolute error was used as the objective function. Moreover, the controller was also tuned to ensure that the tie-line power and the frequency of the multi-source power system were within the acceptable limits. A two-area power system was designed using MATLAB-Simulink tool, consisting of three types of power sources, viz., thermal power plant, hydro power plant, and gas-turbine power plant. The overall efficacy of the proposed algorithm was tested for two different case studies. In the first case study, both the areas were subjected to a load increment of 0.01 p.u. In the second case, the two areas were subjected to different load increments of 0.03 p.u and 0.02 p.u, respectively. Furthermore, the settling time and the peak overshoot were considered to measure the effect on the frequency deviation and on the tie-line response. For the first case study, the settling times for the frequency deviation in area-1, the frequency deviation in area-2, and the tie-line power flow were 8.5 s, 5.5 s, and 3.0 s, respectively. In comparison, these values were 8.7 s, 6.1 s, and 5.5 s, using PSO; 8.7 s, 7.2 s, and 6.5 s, using FA; and 9.0 s, 8.0 s, and 11.0 s using GSA. Similarly, for case study II, these values were: 5.5 s, 5.6 s, and 5.1 s, using the proposed algorithm; 6.2 s, 6.3 s, and 5.3 s, using PSO; 7.0 s, 6.5 s, and 10.0 s, using FA; and 8.5 s, 7.5 s, and 12.0 s, using GSA. Thus, the proposed algorithm performed better than the other techniques.

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Section: Lfc In a Maps With Conventional Sourcesmentioning

confidence: 99%

Section: Domain Key Problems Addressed Referencesmentioning

confidence: 99%

Load Frequency Control Using Hybrid Intelligent Optimization Technique for Multi-Source Power Systems

et al. 2021

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“…The modelling of open market multi-source power system presented in [40][41]. In the structure of deregulated power system each area consisting of thermal-hydro combination.…”

Section: Deregulated Power System Modelmentioning

confidence: 99%

“…In the structure of deregulated power system each area consisting of thermal-hydro combination. The modelling of multi area deregulated power system presented in [40,41]. The poles and zeros are established by the (11) (12) 2N+1 is the order of filter and , are the lower and higher cut-off frequencies (13) Fractional Order derivative and integral is linear operator as given in equation 14, 15) (14(15)…”

Section: Deregulated Power System Modelmentioning

confidence: 99%

Fractional Order Sliding Mode Controller Fed Load-Frequency Control of Multi-Area Deregulated Power System Network

Kumar¹,

Scholar²,

Ganesh³

et al. 2020

IJEAT

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This paper presents a Fractional Order Sliding Mode Controller (FOSMC) for load frequency control of multi area power system in deregulated environment. In deregulated power system the design of controller is more complicated due to contracted and un-contracted load demands. This proposed controller shall take care of system nonlinearities and uncertainties under bilateral contract scenario for sudden load disturbances. The performance of proposed controller compared to PI controller and without any controller.

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“…However, the coordinated frequency and voltage regulation of a 50‐Hz frequency‐based isolated hμG are unexplored so far. Again, most of the earlier works 27‐29 are focused on active power balance of a 60‐Hz–based system with ALFC, whereas this work focuses on apparent power balance introducing a novel integral square of weighted absolute error function (ISWAE). Hence, this work is motivated towards putting an earliest effort to study the performances of proposed (50‐Hz–based) hμG with PID controllers, using a novel QSHO algorithm.…”

Section: Introductionmentioning

confidence: 99%

Coordinated regulation of voltage and load frequency in demand response supported biorenewable cogeneration‐based isolated hybrid microgrid with quasi‐oppositional selfish herd optimisation

Barik

Das

2019

Int Trans Electr Energ Syst

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Summary This work is the earliest attempt towards coordinated regulation of both frequency and voltage of an isolated multisource‐based hybrid microgrid with demand response support using a modified selfish herd optimisation. It is a maiden effort to propose a 50‐Hz system frequency‐based hybrid microgrid model, utilising biorenewable sustainable energy sources like sunrays, wind, waste waters, and agricultural and domestic wastes, with available support from demand response contributors for a dual objective of waste and power management. The intermittency of these resources due to climatic variations creates a great challenge to meet the timely consumer demands of the microgrid with reliable quality power supply. To overcome these issues, the performances of the proposed system are studied considering different typical Indian‐climatic scenarios round the year with real‐time recorded data. Initially, the system performances are compared proposing a new objective function called integral square of weighted absolute error in order to minimise the net deviation in system apparent power, using six controllers tuned with four‐popular/recent optimisation algorithms and four‐objective functions in MATLAB. Then, the simulation results are analysed for five different extreme scenarios of both source and load variations in the proposed system using a novel quasi‐oppositional selfish herd optimisation and reported adaptive performances with demand response support. Finally, the sensitivity of the proposed system with variation in system inertia and load damping factor are analysed to study the robustness of the proposed system.

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Renewable energy source-based multiarea AGC system with integration of EV utilizing cascade controller considering time delay

Cited by 51 publications

References 23 publications

Load Frequency Control Using Hybrid Intelligent Optimization Technique for Multi-Source Power Systems

Load Frequency Control Using Hybrid Intelligent Optimization Technique for Multi-Source Power Systems

Fractional Order Sliding Mode Controller Fed Load-Frequency Control of Multi-Area Deregulated Power System Network

Coordinated regulation of voltage and load frequency in demand response supported biorenewable cogeneration‐based isolated hybrid microgrid with quasi‐oppositional selfish herd optimisation

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