Generation capability curves for wind farms

Enrique, Eduardo H.

doi:10.1109/sustech.2014.7046227

Cited by 5 publications

(2 citation statements)

References 1 publication

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“…URVA kapabilitas generator memberikan batasan jumlah pembangkitan daya aktif dan daya reaktif dari generator [1]. Kurva kapabilitas generator digunakan untuk menentukan batas pengoperasian stabilitas steady state generator dan menentukan setting sistem proteksi yang digunakan [2][3][4][5].…”

Section: Pendahuluanunclassified

Pembentukan Kurva Kapabilitas Generator Menggunakan Pendekatan Sistem Modified Single Machine to Infinite Bus (M-SMIB) untuk Batasan Optimisasi Sistem Pembangkitan

Rusilawati¹

2020

eltikom

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Kurva kapabilitas generator memberikan batasan jumlah pembangkitan daya aktif dan daya reaktif dari generator dan juga digunakan untuk memberikan batasan pada operasi Optimal Power Flow (OPF). Kurva kapabilitas generator biasanya diberikan oleh pabrikan generator. Dalam prakteknya dapat terjadi generator sudah mencapai batas pembangkitan maksimumnya sebelum mencapai nilai yang tertera pada kurva kapabilitas yang diberikan pabrikan generator. Hal ini dapat terjadi karena letak beban yang terlalu jauh dari pembangkit atau variasi nilai beban yang selalu berubah-ubah, sehingga mempengaruhi nilai batas pembangkitan maksimum generator. Dalam penelitian ini, kurva kapabilitas generator dibentuk menggunakan pendekatan sistem Modified Single Machine to Infinite Bus (M-SMIB), yaitu suatu metode untuk menentukan batas kestabilan steady state generator setiap saat terjadi perubahan pada letak dan nilai beban. Selanjutnya dilakukan optimisasi pada sistem pembangkitan dengan batasan kurva kapabilitas generator yang diperoleh sehingga pembagian beban pada setiap unit pembangkit selalu berada dalam batas kestabilan steady state generator dan batas keamanan pengoperasiannya . Penelitian diaplikasikan pada sistem pembangkitan IEEE 4 bus 2 generator.

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Section: Pendahuluanunclassified

Pembentukan Kurva Kapabilitas Generator Menggunakan Pendekatan Sistem Modified Single Machine to Infinite Bus (M-SMIB) untuk Batasan Optimisasi Sistem Pembangkitan

Rusilawati¹

2020

eltikom

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“…This methodology can be implemented in Volt/VAr control schemes when the estimation of DG capability is required. The work presented in [9] proved that, in the case of a wind farm the maximum generating power cannot be obtained by the aggregation of the capability curve for each wind turbine due to the presence of impedances in the collector system, the substation and transmission lines. The paper determines the overall generating capability of a wind farm by incorporating these impedances to determine the maximum active and reactive power at the pint of common coupling.…”

Section: Protection Against Loss-of-field or Excitationmentioning

confidence: 99%

New Algorithm With Fuzzy Inference in Fpga to Field Loss Protection for Wind Turbine

Araújo¹,

Trondoli²

2016

International Journal of Power and Energy Systems

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The present study aims to present the contribution of a new algorithm for synchronous generators wind protection and the assessment of the effectiveness of the performance of the Loss of Field Protection Fuzzy (LOEPF), using fuzzy inference implemented in reconfigurable computing with high-level optimization of logical operations. A new model of sub-and overexcitation by the wind generator capacity curve for the steady-state stability limit is introduced, serving as the basis for the development of this new algorithm and the evaluation of the effectiveness of the same. The LOEPF algorithm is implemented in Field Programmable Gate Array (FPGA) with acquisition of voltage and current signals, for carrying out the tests of various conditions of simulated faults by means of a test box Doble F6150 compared with the results obtained with the use of a commercial relay. The results obtained in tests of the new algorithm showed superior performance compared to conventional protection, reducing lag time and time of trip. This feature allows for fast data throughput and processing allowing the relay handling samples high-frequency data and computational efficiency.

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Computing the feasible operating region of active distribution networks: Comparison and validation of random sampling and optimal power flow based methods

Contreras

Rudion

2021

IET Generation Trans & Dist

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The feasible operating region (FOR) indicates the operation points that an active distribution network can achieve at the interconnection point with the transmission grid when operating flexible assets within it; without disturbing the stability of the grid itself. Even though the concept is not new, many novel methods to compute the FOR efficiently have been proposed in recent years, resulting in two main schools of thought: random sampling (RS) and optimal power flow (OPF) methods. Both approaches have their merits, yet no wide‐ranging analysis regarding scenarios in which each method could be best applied has been done so far. This paper focuses on performing such a comparison; however, capability charts of flexibility providing units and grids are usually modelled as irregular convex polygons, requiring some adaptation of the RS‐methods to allow for a proper comparison of the resulting feasible operating region. Correspondingly, new methods to adapt the extraction of random samples from generic capability charts are proposed in the paper. Using models of two radial distribution grids, both OPF‐ and RS‐based methods are compared and validated. Results show that RS methods are adequate for assessing small grids, especially with the proposed improvements, while OPF‐based methods excel in larger grids.

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Generation capability curves for wind farms

Cited by 5 publications

References 1 publication

Pembentukan Kurva Kapabilitas Generator Menggunakan Pendekatan Sistem Modified Single Machine to Infinite Bus (M-SMIB) untuk Batasan Optimisasi Sistem Pembangkitan

Pembentukan Kurva Kapabilitas Generator Menggunakan Pendekatan Sistem Modified Single Machine to Infinite Bus (M-SMIB) untuk Batasan Optimisasi Sistem Pembangkitan

New Algorithm With Fuzzy Inference in Fpga to Field Loss Protection for Wind Turbine

Computing the feasible operating region of active distribution networks: Comparison and validation of random sampling and optimal power flow based methods

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