Abstract：Big data and renewable resources access have brought opportunities and challenges for the urban multi-energy system (UMES) planning. An urban multi-energy system planning method incorporating energy supply reliability and wind-photovoltaic generators uncertainty is proposed. Firstly, typical scenarios and their probabilities are generated based on the improved DBSCAN algorithm, which solves the problem of poor quality of a large number of historical data that may exist in actual conditions. Secondly, the expected failure time of N-1 in the energy distribution line is obtained by the failure outage model of the distribution channel. Finally, considering the relevant constraints of urban electricity distribution network, natural gas distribution network and power to gas (PtG), a N-1 reliability assessment algorithm for radial network is proposed with the objective of maximizing the total profit of UMES. And a mixed integer quadratic programming model is established. The optimal construction time, type and location of energy source, distribution channel and PtG can be obtained by using the proposed model. The case analysis results show the validity of DBSCAN algorithm and reliability assessment algorithm, and prove that the PtG can make the natural gas distribution network be effectively supported by the electricity distribution network when the N-1 failure occurs, which significantly improves the reliability of the system power supply.
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2019, Vol. 34 
