Optimal Location and Capacity of the Distributed Energy Storage System in a Distribution Network

Given the current situation of large-scale energy storage system (ESS) access in distribution network, a practical distributed ESS location and capacity optimization model is proposed. Firstly, a weighted voltage sensitivity is proposed to select the grid-connected node set of ESS. On this basis, the distributed ESS location model is established, which aims at reducing voltage deviation and active power loss of the distribution network. Then, an ESS partition method based on the improved flame propagation model is proposed, and the partition results are obtained by constructing the flammability of nodes, the wind direction of flame propagation, speed of flame propagation and other indicators. Based on partition results, the capacity optimization model is established with the maximum annual net income of energy stored in the partition as the objective function. Finally, the improved IEEE-33 bus distribution network is used to demonstrate the effectiveness and feasibility of the proposed model.

[1]  Hasan Mehrjerdi,et al.  Simultaneous load leveling and voltage profile improvement in distribution networks by optimal battery storage planning , 2019, Energy.

[2]  Álvaro Gomes,et al.  A multi-objective evolutionary algorithm for reactive power compensation in distribution networks , 2009 .

[3]  Jin Yang,et al.  Comparison of centralised and distributed battery energy storage systems in LV distribution networks on operational optimisation and financial benefits , 2017 .

[4]  Zhang Yu,et al.  Capacity Plan of Battery Energy Storage System in User Side Considering Power Outage Cost , 2012 .

[5]  C. Borges,et al.  Active distribution network integrated planning incorporating distributed generation and load response uncertainties , 2011, 2012 IEEE Power and Energy Society General Meeting.

[6]  Margot P. C. Weijnen,et al.  Integration of societal outage cost into infrastructure design and maintenance optimisation , 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

[7]  Yang Kai.  Cycle-life Energy Analysis of LiFePO_4 Batteries for Energy Storage , 2013 .

[8]  Magdy M. A. Salama,et al.  A planning model for siting, sizing and timing of distribution substations and defining the associated service area , 2002 .

[9]  Carl D. Parker,et al.  Lead-acid battery energy-storage systems for electricity supply networks , 2001 .

[10]  Markus Mueller,et al.  A Numerical and Graphical Review of Energy Storage Technologies , 2014 .

[11]  R. Hemmati,et al.  Electric vehicle charging station with multilevel charging infrastructure and hybrid solar-battery-diesel generation incorporating comfort of drivers , 2019 .

[12]  Marko Aunedi,et al.  Business case for distributed energy storage , 2017 .

[13]  Yong Wang,et al.  Combining Multiobjective Optimization With Differential Evolution to Solve Constrained Optimization Problems , 2012, IEEE Transactions on Evolutionary Computation.

[14]  Yan Zhimin.  Value assessment model of battery energy storage system in distribution network , 2013 .

[15]  Yasser Abdel-Rady I. Mohamed,et al.  Optimum Microgrid Design for Enhancing Reliability and Supply-Security , 2013, IEEE Transactions on Smart Grid.

[16]  Tomonobu Senjyu,et al.  Determination methodology for optimising the energy storage size for power system , 2009 .

[17]  Wan Guo-cheng.  CALCULATION OF CUSTOMER'S OUTAGE COST CONSIDERING FEEDER AUTOMATION , 2005 .

[18]  M. Paolone,et al.  Optimal location and sizing of distributed storage systems in active distribution networks , 2013 .