Transient stability assessment in large-scale power systems based on the sparse single index model

2020 ◽  
Vol 184 ◽  
pp. 106291 ◽  
Author(s):  
Jiaqing Lv
Keyword(s):  
Power Systems ◽  
Large Scale ◽  
Transient Stability ◽  
Stability Assessment ◽  
Single Index ◽  
Index Model ◽  
Single Index Model

ANALISIS PORTOFOLIO OPTIMAL DENGAN MENGGUNAKAN MODEL INDEKS TUNGGAL PADA SAHAM IDX BUMN20 DI BURSA EFEK INDONESIA JANUARI 2018-JANUARI 2019

2019 ◽  
Vol 4 (2) ◽  
Author(s):  
Mochamad Andik Firmansyah
Keyword(s):  
Stock Exchange ◽  
Optimal Portfolio ◽  
Rate Of Return ◽  
Portfolio Risk ◽  
Expected Return ◽  
Purposive Sampling ◽  
Single Index ◽  
Index Model ◽  
Market Return ◽  
Single Index Model

Penelitian ini bertujuan untuk menentukan level of expected return dan the best risk of optimal portfolio  formation dengan menggunakan Single Index Model pada saham IDX BUMN 20 yang tercatat di Indonesia Stock Exchange dari bulan Januari 2018 sampai January 2019. Saham IDX BUMN 20 yang tercatat di Indonesia Stock Exchange dengan populasi sebanyak 20 perusahaan. Dengan menggunakan populasi sebesar 20 perusahaan maka peneliti menggunakan purposive sampling, dan ternyata hanya 18 perusahaan saja yang ditemukan memenuhi kriteria penelitian ini. Penelitian ini juga menggunakan metode Kuantitatif Deskriptif. Analisa data pada penelitian ini untuk menentukan saham-saham mana saja yang termasuk the optimal portfolio, dan juga the level of proportion of 1 funds yang termasuk juga dalam kategori the optimal portfolio dan the level of expected return serta the best risk of the optimal portfolio yang terbentuk dengan menggunakan Single Index Model. Hasil dari penelitian ini menunjukan bahwa terdapat 5 perusahaan dengan kategori the optimal portfolio dari 18 sampel perusahaan pada saham IDX BUMN 20 dengan tingkat tertinggi dari level of proportion of 1 funds ditemukan pada PTBA share sat 1.89333 or 189,333%, di lain pihak dengan tingkat terendah adalah pada TLKM shares at -2.13488 or -213.488% yang berarti bahwa saham TLKM adalah negatif dan harus dijual dalam jangka waktu pendek sebesar 213,488% dari dana yang dimiliki oleh para inventor dan menghasilkan rate of return yang diharapkan dari formasi optimal portfolio sebesar 0.17583 or 17.583% lebih tinggi dari yang diharapkan oleh market return sebesar 0.00264 or 0.264% dan memiliki tingkat portfolio risk borne sebesar 0.10384 or 10,384%, lebih kecil dari the risk of market sebesar 0.03367 or 3,367% dan beta market sebesar 1.Kata Kunci : Portfolio, Optimal Portfolio, Single Index Model.

ANALISIS DIVERSIFIKASI INTERNASIONAL : PEMBENTUKAN PORTOFOLIO OPTIMAL INDEKS SAHAM DUNIA (Studi Kasus Pada Indeks Saham Aktif Dunia Versi The Wall Street Journal)

2019 ◽  
Vol 6 (02) ◽  
Author(s):  
Rony Mahendra ◽  
Erwin Dyah Astawinetu
Keyword(s):  
Wall Street Journal ◽  
Optimal Portfolio ◽  
Stock Index ◽  
Wall Street ◽  
Expected Return ◽  
Single Index ◽  
Index Model ◽  
Single Index Model ◽  
Stock Indices ◽  
The Wall Street Journal

The research objective is to establish an optimal portfolio and know the difference between risk and return stock index portfolio candidates and non-candidates. Method used in the preparation of this research portfolio is the single index model, while the samples of this study are active world stock indices version of The Wall Street Journal during the period August 2012 - August 2016 and The Global Dow is used as the benchmark stock index. In establishing the optimal portfolio is used two perspectives: the Rupiah perspective and the U.S. Dollar perspective. The results showed there were three stock indices from the perspective of Rupiah and 8 share index menurutperspektif U.S. Dollar that make up the optimal portfolio, with the cut-of-pointsebesar 0,01393menurut Rupiah perspective and the perspective of 0.0078 US Dollars Based on the perspective of return expectations Rupiah obtained by 0.0258 with a risk of 0.06512. Berdarkan perspective of US Dollars, obtained return expectations at 0.0154 with a risk of 0.0292. From the test results showed that the hypothesis, the return on both perspectives there are significant differences between the index of the candidate, with a non-candidate. Then the risk of stock index, among the candidates, with a non-candidate, the Rupiah perspective there is no difference, but in the perspective of US Dollars, there are significant differences.Keywords: Single Index Model, candidate portfolio, optimal portfolio, expected return, excess return to beta, cut-off-point

scholarly journals Power System Transient Stability Assessment Based on Snapshot Ensemble LSTM Network

2021 ◽  
Vol 13 (12) ◽  
pp. 6953
Author(s):  
Yixing Du ◽  
Zhijian Hu
Keyword(s):  
Power Systems ◽  
Power System ◽  
Transient Stability ◽  
Short Term Memory ◽  
Risk Function ◽  
Stability Margin ◽  
Risk Level ◽  
Stability Assessment ◽  
Lstm Network ◽  
Hierarchical Assessment

Data-driven methods using synchrophasor measurements have a broad application prospect in Transient Stability Assessment (TSA). Most previous studies only focused on predicting whether the power system is stable or not after disturbance, which lacked a quantitative analysis of the risk of transient stability. Therefore, this paper proposes a two-stage power system TSA method based on snapshot ensemble long short-term memory (LSTM) network. This method can efficiently build an ensemble model through a single training process, and employ the disturbed trajectory measurements as the inputs, which can realize rapid end-to-end TSA. In the first stage, dynamic hierarchical assessment is carried out through the classifier, so as to screen out credible samples step by step. In the second stage, the regressor is used to predict the transient stability margin of the credible stable samples and the undetermined samples, and combined with the built risk function to realize the risk quantification of transient angle stability. Furthermore, by modifying the loss function of the model, it effectively overcomes sample imbalance and overlapping. The simulation results show that the proposed method can not only accurately predict binary information representing transient stability status of samples, but also reasonably reflect the transient safety risk level of power systems, providing reliable reference for the subsequent control.

scholarly journals Asymptotic normality of conditional distribution estimation in the single index model

2017 ◽  
Vol 9 (1) ◽  
pp. 162-175
Author(s):  
Diaa Eddine Hamdaoui ◽  
Amina Angelika Bouchentouf ◽  
Abbes Rabhi ◽  
Toufik Guendouzi
Keyword(s):  
Distribution Function ◽  
Confidence Interval ◽  
Asymptotic Normality ◽  
Conditional Distribution ◽  
Conditional Distribution Function ◽  
Single Index ◽  
Index Model ◽  
Single Index Model ◽  
Distribution Estimation

AbstractThis paper deals with the estimation of conditional distribution function based on the single-index model. The asymptotic normality of the conditional distribution estimator is established. Moreover, as an application, the asymptotic (1 − γ) confidence interval of the conditional distribution function is given for 0 < γ < 1.

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