Distribution systems are subject to increasing penetration of dispersed generation. The energy injections of the generators impact on many technical issues, including energy losses occurring in the grid. Given the technical and economic importance of losses, several statistical approaches are proposed in the literature to evaluate the effects of dispersed generation on the energy lost in distribution networks. In principle, these approaches require a great number of load flow calculations. This paper provides a novel index aiming to avoid complex and computationally expensive statistical analysis for loss assessment. Such an index does not require any detailed characterisation of the energy flows over the network (load flow calculations). The performance of the index is tested using a model of a real medium voltage network in a wide set of generation scenarios. Each scenario is defined by a Monte Carlo algorithm that was developed ad hoc for this study. Moreover, advanced convergence criteria are provided to optimise the number of scenarios to process.
Dispersed generation impact on distribution network losses
DELFANTI, MAURIZIO;MERLO, MARCO;FALABRETTI, DAVIDE
2013-01-01
Abstract
Distribution systems are subject to increasing penetration of dispersed generation. The energy injections of the generators impact on many technical issues, including energy losses occurring in the grid. Given the technical and economic importance of losses, several statistical approaches are proposed in the literature to evaluate the effects of dispersed generation on the energy lost in distribution networks. In principle, these approaches require a great number of load flow calculations. This paper provides a novel index aiming to avoid complex and computationally expensive statistical analysis for loss assessment. Such an index does not require any detailed characterisation of the energy flows over the network (load flow calculations). The performance of the index is tested using a model of a real medium voltage network in a wide set of generation scenarios. Each scenario is defined by a Monte Carlo algorithm that was developed ad hoc for this study. Moreover, advanced convergence criteria are provided to optimise the number of scenarios to process.File | Dimensione | Formato | |
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