Frequency response of prime movers during restoration

Adibi, M. M.; Borkoski, J. N.; Kafka, R.J.; Volkmann, T.L.

doi:10.1109/59.761908

Cited by 70 publications

(36 citation statements)

References 1 publication

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“…But it is assumed that the load demand change occurs in both areas and the sum of the column entries of the DPM matrix is more than unity. FRI 5 , FRI 6 , FRI 7 and FRI 8 or ε 1 , ε 2 , ε 3 , ε 4 , ε 5 , ε 6 , ε 7 , and ε 8 are calculated are tabulated in Table 3 and Table 5.…”

Section: Casementioning

confidence: 99%

“…A lot of studies have been made related to LFC in a deregulated environment over last decades. These studies try to modify the conventional LFC system to take into account the effect of bilateral contracts on the dynamics [3] and improve the dynamical transient response of the system [4][5][6][7] under various operating conditions. With the restructured electric utilities, the Load-Frequency Control requirements especially the nominal frequency in an interconnected power system besides maintaining the net interchange of power between control areas at predetermined values should be enhanced to ensure the quality of the power system.…”

Section: Introductionmentioning

confidence: 99%

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Power System Restoration Assessment Indices computation for a Restructured Power System with Bacterial Foraging Optimized Load - Frequency Controller

Thirunavukarasu¹,

Paramasivam²,

Chidambaram³

2013

IJCA

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This paper proposes, various design procedures for computing Power System Restoration Assessment Indices (PSRAI) for a Two-Area Hydro-Thermal Reheat Interconnected Power System (TAHTRIPS) in a restructured environment with a loadfrequency controller optimized using Bacterial Foraging Optimization (BFO) algorithm. In the restructured scenario, as various types of apparatus with large capacity may enhance fast power consumption which causes serious problem in the frequency oscillations. The oscillation of system frequency may sustain and grow to cause stability problems in the system if no adequate damping is provided. The disturbances to the power system due to a small load change can even result in wide deviation in system frequency which is referred as load-frequency control problem. Quick system restoration is of prime importance not only based on the time of restoration and also stability limits also plays a very vital role in power system restoration problems due to unexpected load variations in power systems. The simple conventional Proportional plus Integral (P-I) controllers are still popular in power industry for frequency regulation as in case of any change in system operating conditions new gain values can be computed easily even for multi-area power systems. This paper focus on the computation of various PSRAI for TAH(with mechanical governor) -TRIPS and TAH (with Electric governor)-TRIPS unit based on the settling time concept, The design of the Proportional plus Integral (PI) controller gains are tuned using Bacterial Foraging Optimization (BFO) algorithm. These controllers are implemented to achieve a fast restoration time in the output responses of the system when the system experiences with various step load perturbations. In this paper the PRSAI are calculated for different types of possible transactions and the necessary remedial measures to be adopted are also suggested.

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Section: Casementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Power System Restoration Assessment Indices computation for a Restructured Power System with Bacterial Foraging Optimized Load - Frequency Controller

Thirunavukarasu¹,

Paramasivam²,

Chidambaram³

2013

IJCA

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“…where n G is the number of conventional generation units; P Gi is the active output power of unit i in the restored system; P min_j is the minimum output power of wind farm j; 4f max is the maximum variation allowed which is 0.5 Hz in this paper; and df i is the transient frequency response coefficient of unit i [21]. The minimum output power of wind farm j can be formulated as:…”

Section: Constraintsmentioning

confidence: 99%

“…In this section, a robust optimization model [20,21] is proposed to optimize the dispatched power of wind farms, in order to ensure the security of the restored system.…”

Section: Robust Optimization Model Of Dispatched Powermentioning

confidence: 99%

Optimized dispatch of wind farms with power control capability for power system restoration

Xie

Liu

et al. 2017

J. Mod. Power Syst. Clean Energy

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As the power control technology of wind farms develops, the output power of wind farms can be constant, which makes it possible for wind farms to participate in power system restoration. However, due to the uncertainty of wind energy, the actual output power can't reach a constant dispatch power in all time intervals, resulting in uncertain power sags which may induce the frequency of the system being restored to go outside the security limits. Therefore, it is necessary to optimize the dispatch of wind farms participating in power system restoration. Considering that the probability distribution function (PDF) of transient power sags is hard to obtain, a robust optimization model is proposed in this paper, which can maximize the output power of wind farms participating in power system restoration. Simulation results demonstrate that the security constraints of the restored system can be kept within security limits when wind farm dispatch is optimized by the proposed method.

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“…where P BSUni and P NBSUnj are the active rated power of BSU i and NBSU j, respectively; ∆ f max is the permitted frequency drop; f di and f dj are the frequency response rate of BSU i and NBSU j, which can be obtained from reference [24].…”

Section: Maximum Power Constraint To Load Pick-up At One Timementioning

confidence: 99%

An Optimal Source-Load Coordinated Restoration Method Considering Double Uncertainty

Jiang

Chen

2018

Energies

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Abstract:The security of power system restoration is severely affected by uncertain factors, especially the start-up time of generating unit and the amount of load pick-up. Solving the optimization restoration problem is challenging since it needs to determine different priorities in which units and loads are restored with the consideration of double uncertainty. Therefore, an optimal source-load coordinated restoration method that is based on information gap decision theory (IGDT) is proposed. Firstly, the time-domain restoration characteristics of black-start unit (BSU), non-black-start unit (NBSU), and load are described with analysis of double uncertainty. On this basis, a coupled multi-objective optimization model is built with double uncertainty, in which source-load coordinated restoration is realized. Then, IGDT is adopted to convert the uncertainty optimization model to a certain one with robustness, which tolerates the most uncertainty and still meets the desired requirement. Finally, the optimization model is solved by non-dominated genetic algorithm II (NSGA-II). The effectiveness and robustness of the proposed method is further illustrated through a case study based on the IEEE 39-bus system.

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Frequency response of prime movers during restoration

Cited by 70 publications

References 1 publication

Power System Restoration Assessment Indices computation for a Restructured Power System with Bacterial Foraging Optimized Load - Frequency Controller

Power System Restoration Assessment Indices computation for a Restructured Power System with Bacterial Foraging Optimized Load - Frequency Controller

Optimized dispatch of wind farms with power control capability for power system restoration

An Optimal Source-Load Coordinated Restoration Method Considering Double Uncertainty

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