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Epidemic Algorithm Based Optimal Power Flow in Electric Grids

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Soft Computing Applications (SOFA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 633))

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Abstract

Time-triggering and distributed nature of the grid are emerging as the major challenge in managing energy in distribution grids. This investigation presents an event triggered distributed optimal power flow (OPF) algorithm for energy grids. To generate the event triggers, we use the epidemic algorithm. The buses are classified into three: infected, susceptible, and dead. The network works in two modes: normal and optimization mode. In the normal mode, only event detection happens and when there are no event triggers, the system is said to be in normal mode. In optimization mode, event triggers that can be a change in generation or demand beyond a threshold value that necessitates the re-optimization of the network, the optimization mode begins. In this mode, the infected node which is infected by change in bus variable intimates it to the energy management application. The energy management application on sensing this change, will initiate the graph grammars which are a set of rules to change the bus nature by detecting the effect of the change on the particular bus. The network is re-optimized using a DC OPF formulation as it is convex and can be solved using simple matrix inversion on the stationary conditions. As a result, the solution of DCOPF problem becomes that of solving a system of linear equations of the form \(Ax=b\), which is solved using Krylov’s method or the Arnoldi algorithm in a distributed fashion. Each node solves the problem of its one-hop neighbours in parallel and this leads to a distributed implementation resulting significant reduction in complexity. The propossed approach is illustrated on a simple 3 bus network.

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Abbreviations

i, j:

indices of bus

\(\theta \) :

load angles

B :

admittance matrix

\(x_{ij}\) :

reactance of line ij

\(D_t\) :

Vector of active demand at time t

\(P_t\) :

Vector of active power generation at time t

\(P_{Gg}\) :

Power generated by the generator g

g :

indices for generator

t :

time indices

\(C(P_{Gg})\) :

Generation cost of the generator g in dollars

\(\mathscr {T}\) :

Set of all time

\(\lambda \) :

Lagrange Multiplier

\(\mathscr {G}\) :

set of all generators

\(\mathscr {K}_m\) :

Krylov’s Space

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Authors and Affiliations

  1. Department of Electrical and Electronics Engineering, Kalasalingam University, Virudhunagar, India

    K. Muniyasamy

  2. International Research Center, Kalasalingam University, Virudhunagar, India

    Seshadhri Srinivasan

  3. Department of Electrical and Electronics Engineering, KLN College of Engineering, Sivagangai, India

    S. Parthasarathy

  4. Department of Instrumentation and Control Engineering, Kalasalingam University, Virudhunagar, India

    B. Subathra

  5. University of Oradea, Oradea, Romania

    Simona Dzitac

Authors
  1. K. Muniyasamy
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  2. Seshadhri Srinivasan
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  3. S. Parthasarathy
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  4. B. Subathra
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  5. Simona Dzitac
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Corresponding author

Correspondence to Seshadhri Srinivasan .

Editor information

Editors and Affiliations

  1. Department of Automatics and Applied Informatics, Faculty of Engineering, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

  2. University of Canberra, Canberra, Aust Capital Terr, Australia

    Lakhmi C. Jain

  3. Department of Automatics and Applied Informatics, Faculty of Engineering, Aurel Vlaicu University of Arad, Arad, Romania

    Marius Mircea Balas

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Muniyasamy, K., Srinivasan, S., Parthasarathy, S., Subathra, B., Dzitac, S. (2018). Epidemic Algorithm Based Optimal Power Flow in Electric Grids. In: Balas, V., Jain, L., Balas, M. (eds) Soft Computing Applications. SOFA 2016. Advances in Intelligent Systems and Computing, vol 633. Springer, Cham. https://doi.org/10.1007/978-3-319-62521-8_6

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  • DOI: https://doi.org/10.1007/978-3-319-62521-8_6

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  • Online ISBN: 978-3-319-62521-8

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