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Distribution Network Power Loss Analysis Considering Uncertainties in Distributed Generations
Distribution network loss analysis is crucial for the economic operation in residential distribution networks. The increasing level of distributed generation (DG) has considerably improved the overall sustainability but raised the uncertainty in system losses and exacerbated voltage profiles. This paper presents a nodal distribution loss analysis approach in which the losses induced by loads and DGs are calculated recursively. In order to characterize the uncertainty, the Latin hypercube sampling (LHS)-based approach is presented for obtaining DG output samples. Further, the LHS-based sampling and loss analysis methods are combined into a proposed stochastic framework for loss analysis, which takes into account the DG output uncertainty. Case studies on a 36-bus radial distribution network verified the stochastic loss analysis method. Compared with the simple random sampling method, the proposed LHS-based stochastic loss analysis method can reach the same accuracy level for nodal voltages and losses more efficiently.
Distribution Network Power Loss Analysis Considering Uncertainties in Distributed Generations
Distribution network loss analysis is crucial for the economic operation in residential distribution networks. The increasing level of distributed generation (DG) has considerably improved the overall sustainability but raised the uncertainty in system losses and exacerbated voltage profiles. This paper presents a nodal distribution loss analysis approach in which the losses induced by loads and DGs are calculated recursively. In order to characterize the uncertainty, the Latin hypercube sampling (LHS)-based approach is presented for obtaining DG output samples. Further, the LHS-based sampling and loss analysis methods are combined into a proposed stochastic framework for loss analysis, which takes into account the DG output uncertainty. Case studies on a 36-bus radial distribution network verified the stochastic loss analysis method. Compared with the simple random sampling method, the proposed LHS-based stochastic loss analysis method can reach the same accuracy level for nodal voltages and losses more efficiently.
Distribution Network Power Loss Analysis Considering Uncertainties in Distributed Generations
Hongmei Li (author) / Hantao Cui (author) / Chunjie Li (author)
2019
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
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