Abstract
This paper deals with the problem of optimal allocation (siting and sizing) of storage resources in unbalanced three-phase low voltage microgrids. The siting and sizing problem is formulated as a mixed, non-linear, constrained optimization problem whose objective function deals with economic issues and whose constraints involve technical limitations of both network and distributed resources. Emphasis is given to the power quality issue with particular attention to unbalance reduction and voltage profile improvement. Technological issues, such as those related to the preservation of batteries’ lifetime, were also taken into account. The planning problem is solved by means of a genetic algorithm which includes an inner algorithm based on sequential quadratic programming. In order to limit the processing time while maintaining reasonable accuracy, the genetic algorithm search space is significantly reduced identifying a subset of candidate buses for the siting of the storage resources. The Inherent Structure Theory of Networks and the Loading Constraints Criterion were used to identify the candidate buses. The proposed method has been applied to a low voltage test network demonstrating the effectiveness of the procedure in terms of computational burden while also preserving the accuracy of the solution.
Highlights
One of the most important drivers of a sustainable electrical power grid is the optimal integration of its distributed energy resources
The planning problem is solved by means of a genetic algorithm which includes an inner algorithm based on sequential quadratic programming
As an example, when reducing the limit on unbalance factor, the set of the candidate unbalance factor, the set of the candidate buses provided by the Inherent Structure Theory of Networks (ISTN) still allowed a faster buses provided by the ISTN still allowed a faster identification of the location buses able to satisfy identification of the location buses able to satisfy the constraints and provided a better objective the constraints and provided a better objective function value than that obtained with the genetic algorithm (GA)
Summary
One of the most important drivers of a sustainable electrical power grid is the optimal integration of its distributed energy resources. An unbalanced LV microgrid is considered and the allocation (siting and sizing) problem is formulated as a mixed, non-linear, constrained optimization problem whose objective function deals with economic issues and whose constraints take into account technical requirements of both network and distributed resources This planning problem is quite complex and involves mathematical models of high dimension. The complexity is mainly related to the use of a three-phase model used to solve Power Quality problems such as voltage deviations and unbalances, and to meet technical constraints such as limits on line currents, transformer and converter capability, storage’s rating and lifetime requirements All of these complexities are handled in an optimization framework which minimizes the overall operation and planning costs.
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