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Electrical Grid Stability Simulated Data Data Set
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Abstract: The local stability analysis of the 4-node star system (electricity producer is in the center) implementing Decentral Smart Grid Control concept.

Data Set Characteristics:  

Multivariate

Number of Instances:

10000

Area:

Physical

Attribute Characteristics:

Real

Number of Attributes:

14

Date Donated

2018-11-16

Associated Tasks:

Classification, Regression

Missing Values?

N/A

Number of Web Hits:

2103


Source:

-- Creator and donor: Vadim Arzamasov (vadim.arzamasov '@' kit.edu),
Department of computer science,
Karlsruhe Institute of Technology;
Karlsruhe, 76131; Germany
-- Date: November, 2018


Data Set Information:

The analysis is performed for different sets of input values using the methodology similar to that described in [Schäfer, Benjamin, et al. 'Taming instabilities in power grid networks by decentralized control.' The European Physical Journal Special Topics 225.3 (2016): 569-582.]. Several input values are kept the same: averaging time: 2 s; coupling strength: 8 s^-2; damping: 0.1 s^-1


Attribute Information:

11 predictive attributes, 1 non-predictive(p1), 2 goal fields:
1. tau[x]: reaction time of participant (real from the range [0.5,10]s). Tau1 - the value for electricity producer.
2. p[x]: nominal power consumed(negative)/produced(positive)(real). For consumers from the range [-0.5,-2]s^-2; p1 = abs(p2 + p3 + p4)
3. g[x]: coefficient (gamma) proportional to price elasticity (real from the range [0.05,1]s^-1). g1 - the value for electricity producer.
4. stab: the maximal real part of the characteristic equation root (if positive - the system is linearly unstable)(real)
5. stabf: the stability label of the system (categorical: stable/unstable)


Relevant Papers:

Arzamasov, Vadim, Klemens Böhm, and Patrick Jochem. 'Towards Concise Models of Grid Stability.' Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), 2018 IEEE International Conference on. IEEE, 2018
(Section V-A)



Citation Request:

We thank Dr. Benjamin Schäfer for helping us with the initial version of the code used for simulations.


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