Research output: Contribution to journal › Article

Abstract

The design of future electricity grids will allow for renewable energy generators to be effectively incorporated into the network. Current methods of economic dispatch were not designed to accommodate the level of volatility and uncertain nature of sources such as wind and solar; here we demonstrate how an optimisation algorithm called message passing, which is based on principled statistical physics methodologies and is inherently probabilistic, could be an alternative way of considering source volatility efficiently and reliably. The algorithm iteratively passes probabilistic messages in order to find an approximate global optimal solution with moderate computational complexity and inherently consider source volatility. We demonstrate the capabilities of message passing as a distribution algorithm in the presence of uncertainty on synthetic benchmark IEEE networks and show how the volatility increase effects distribution costs

Original language

English

Pages (from-to)

221-228

Journal

International Journal of Smart Grid and Clean Energy

title = "Optimal distribution in smart grids with volatile renewable sources using a message passing algorithm",

abstract = "The design of future electricity grids will allow for renewable energy generators to be effectively incorporated into the network. Current methods of economic dispatch were not designed to accommodate the level of volatility anduncertain nature of sources such as wind and solar; here we demonstrate how an optimisation algorithm called message passing, which is based on principled statistical physics methodologies and is inherently probabilistic, couldbe an alternative way of considering source volatility efficiently and reliably. The algorithm iteratively passes probabilistic messages in order to find an approximate global optimal solution with moderate computationalcomplexity and inherently consider source volatility. We demonstrate the capabilities of message passing as a distribution algorithm in the presence of uncertainty on synthetic benchmark IEEE networks and show how the volatility increase effects distribution costs",

author = "Elizabeth Harrison and David Saad and Wong, {K. Y. Michael}",

In: International Journal of Smart Grid and Clean Energy, Vol. 5, No. 4, 31.10.2016, p. 221-228.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Optimal distribution in smart grids with volatile renewable sources using a message passing algorithm

AU - Harrison, Elizabeth

AU - Saad, David

AU - Wong, K. Y. Michael

PY - 2016/10/31

Y1 - 2016/10/31

N2 - The design of future electricity grids will allow for renewable energy generators to be effectively incorporated into the network. Current methods of economic dispatch were not designed to accommodate the level of volatility anduncertain nature of sources such as wind and solar; here we demonstrate how an optimisation algorithm called message passing, which is based on principled statistical physics methodologies and is inherently probabilistic, couldbe an alternative way of considering source volatility efficiently and reliably. The algorithm iteratively passes probabilistic messages in order to find an approximate global optimal solution with moderate computationalcomplexity and inherently consider source volatility. We demonstrate the capabilities of message passing as a distribution algorithm in the presence of uncertainty on synthetic benchmark IEEE networks and show how the volatility increase effects distribution costs

AB - The design of future electricity grids will allow for renewable energy generators to be effectively incorporated into the network. Current methods of economic dispatch were not designed to accommodate the level of volatility anduncertain nature of sources such as wind and solar; here we demonstrate how an optimisation algorithm called message passing, which is based on principled statistical physics methodologies and is inherently probabilistic, couldbe an alternative way of considering source volatility efficiently and reliably. The algorithm iteratively passes probabilistic messages in order to find an approximate global optimal solution with moderate computationalcomplexity and inherently consider source volatility. We demonstrate the capabilities of message passing as a distribution algorithm in the presence of uncertainty on synthetic benchmark IEEE networks and show how the volatility increase effects distribution costs

UR - http://doi.org/10.17036/researchdata.aston.ac.uk.00000272