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International journal of electrical power & energy systems v.99, 2018년, pp.385 - 393   SCIE
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Risk aversion model of distribution network planning rules considering distributed generation curtailment

Garry, A. (Corresponding author. ) ; Cadoux, F. ; Alvarez-Herault, M.-C. ; Hadjsaid, N. ;
  • 초록  

    Abstract In the coming years, the massive deployment of distributed generation connected to the distribution network may increase the required investments in the network components to prevent voltage and current violations. Generation curtailment may make it possible to defer such investments and to increase the capacity of the distribution network to accommodate new generators. Currently, investment decisions only consider classical upgrade solutions such as the reinforcement of existing assets or the creation of new ones. The valorization of generation curtailment and its integration with the planning method are a major challenge, mainly because of the high level of uncertainties. This paper focuses on the problem of reverse power flows at an HV/MV substation, which may occasionally be larger than its nominal power. We propose a stochastic algorithm, based on real generation and load profiles, to create a decision investment abacus for the Distribution System Operator (DSO). This abacus enables the DSO to simply make a trade-off between an upgrade of the HV/MV substation by adding a transformer and generation curtailment with the associated risk. We also discuss the main terms of the curtailment contract between the stakeholders and their expected efficiency in minimizing the global cost. Highlights The production curtailment is integrated in the distribution planning process. Probabilistic seasons-based models for production are compared to random draws. The uncertainties are taken into account using risk indicators. Simple abacus shows the interest of curtailment for both the DSO and the producer. The gap between the curtailment and the reinforcement frontiers is large.


  • 주제어

    Distribution network planning .   Power curtailment .   Smart grids.  

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