Energy storage optimisation for transmission network expansion planning

MacRae, C 2017, Energy storage optimisation for transmission network expansion planning, Doctor of Philosophy (PhD), Science, RMIT University.


Document type: Thesis
Collection: Theses

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Title Energy storage optimisation for transmission network expansion planning
Author(s) MacRae, C
Year 2017
Abstract The electrical transmission network connects electrical power generation to centres of customer demand. Integrating energy storage systems (ESS) in to the transmission network is a challenging problem for network planners.

Here, an electricity transmission network expansion and energy storage planning model (TESP) that determines the location and capacity of energy storage systems in the network for the pur- poses of demand shifting and transmission upgrade deferral is described. This problem is sig- nificantly harder than the standard network expansion models that are typically considered in the literature as the benefit of storage can only be understood by including multiple time inter- vals in the model. The addition of the time dimension leads to much larger mixed integer linear programming problems.

This increase in size and complexity of the optimisation problem is addressed by developing a Benders decomposition approach for the TESP. The model is tested against well known test systems under two different demand scenarios; the first is characterized by a short period of peak demand, the second by a long period. Benders decomposition is shown to be an effective means to render the problem more tractable when compared to the standard mixed integer linear programming approach. It is found that installation of ESS is an effective means of transmission upgrade deferral. However storage is unlikely to be installed where circuit installation is of comparatively low cost.

A hybrid exact/meta-heuristic algorithm that combines Benders decomposition and a Bees Algorithm inspired evolutionary approach is then presented. The algorithm is tested using a transmission network expansion and energy storage planning model. The Bee-Benders hybrid algorithm (BBHA) is shown to be an effective hybrid matheuristic algorithm that exhibits equiva- lent performance to its component parts in the segments of the problem domain where those parts are strongest, and significantly improves upon the individual approaches where neither compo- nent part has a pronounced advantage. The algorithm may be applied to readily decomposable mixed integer programming problems and does not rely on any special problem structure.

The research is directed towards formulation and algorithm development with emphasis on the use of decomposition based on mathematical programming ideas. Both test and real world data sets have been used to test the models, however as assembling comprehensive and clean data sets is beyond the scope of this thesis, the conclusions do not include specific recommendations for the future development of the Australian, or any other electricity grid.
Degree Doctor of Philosophy (PhD)
Institution RMIT University
School, Department or Centre Science
Subjects Optimisation
Operations Research
Keyword(s) transmission expansion planning
operations research
energy storage
power transmission
optimisation
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Created: Mon, 19 Mar 2018, 12:25:26 EST by Denise Paciocco
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