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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
The feasible operation region (FOR) allows capturing the aggregated flexibility potential of DER within radial distribution networks, while respecting the technical restrictions of both plants and grid. This thesis proposes a novel approach to compute the FOR, the Linear Flexibility Aggregation (LFA) method, based on the solution of a sequence of linear OPF. With the objective of reducing the computation time, without compromising the accuracy of the assessed FOR. It is shown that the proposed method provides a considerable reduction in processing time compared to similar methods, e.g. Monte-Carlo simulations or non-linear OPF-based methods.
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
The feasible operation region (FOR) allows capturing the aggregated flexibility potential of DER within radial distribution networks, while respecting the technical restrictions of both plants and grid. This thesis proposes a novel approach to compute the FOR, the Linear Flexibility Aggregation (LFA) method, based on the solution of a sequence of linear OPF. With the objective of reducing the computation time, without compromising the accuracy of the assessed FOR. It is shown that the proposed method provides a considerable reduction in processing time compared to similar methods, e.g. Monte-Carlo simulations or non-linear OPF-based methods.