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Title Optimal Sizing For Microgrids Integrating Distributed Flexibility With The Perth West Smart City As A Case Study
ID_Doc 40523
Authors Essayeh C.; Morstyn T.
Year 2023
Published Applied Energy, 336
DOI http://dx.doi.org/10.1016/j.apenergy.2023.120846
Abstract With the decreasing cost of green technologies and the increasing ambitions to reach the net-zero carbon emissions target, more communities are engaged in renewable deployment and energy-intensive technologies such as heat pumps and electric vehicles will be intensively adopted in the near future. The integration of these appliances in lower grid levels will likely require grid reinforcements. However, some of these appliances are flexible and there is an opportunity to explore their flexibility potential to optimise the investment costs further. This paper proposes an optimal design strategy for a grid-connected site that returns the renewable generation and storage's optimal sizing capacities and the required network reinforcement capacity. The novelty of the work is integrating network upgrade costs and considering flexibility from distributed flexible resources across planning and operation. The problem is formulated as a mixed integer piecewise linear problem, with the capacities of generation, storage and network upgrade as decision variables. The piecewise linear cost function related to the upgrade costs figuring in the objective function is then recast as a mixed-integer problem, and the flexible resources are modelled through an approximation method as a single virtual flexible asset. The application of the strategy on the Perth West smart city project as a case study demonstrates the importance of considering flexibility in the planning phase. The costs related to the storage system can decrease by up to 76%, and the overall costs by up to 35%, with the highest levels of savings, reached for the highest rates of electric vehicle adoption. © 2023 The Author(s)
Author Keywords Battery storage system; Electric vehicles; Flexible assets; Grid reinforcement; Microgrid; Optimal sizing


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