Planning of a Resilient Underground Distribution Network Using Georeferenced Data
Abstract
:1. Introduction
2. Resilience on Power Distribution Networks
3. Planning Distribution Networks
3.1. Types of Distribution Network Topology
3.2. Network Planning Based on Theory Graphs
4. Problem Formulation
Algorithm 1 Planning of a Resilent Distribution Network 

Algorithm 2 Routing of MV network and Switching Equipment Allocation 

5. Analysis and Results
5.1. Case Study
5.2. Results
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Nomenclature  Description 

${X}_{st},{Y}_{st}$  Street point positions (Latitude and Longitude) 
${X}_{s},{Y}_{s}$  Residential customers’ locations (Latitude and Longitude) 
${X}_{box},{Y}_{box}$  Manhole’s position (Latitude and Longitude) 
${X}_{tra},{Y}_{tra}$  Transformer’s position (Latitude and Longitude) 
${X}_{rec},{Y}_{rec}$  RMUs positions (Latitude and Longitude) 
$dis{t}_{box},dis{t}_{ub},dis{t}_{tra},dis{t}_{MV},dis{t}_{rec}$  Distance matrix (variable dimension) 
$G1,G2$  Connectivity matrix 
$kl,km,kn,kp,kj$  Variables for loop control 
$tmp,su{m}_{tmp},k{1}_{tmp},k{2}_{tmp}$  Temporary variables 
$\left[user\phantom{\rule{4pt}{0ex}}ibu\right]$  Residential customers connected to the nearest manhole 
$de{m}_{us}$  Residential customer’ demand 
${D}_{boxes}$  Associated manhole demand 
n  Number of residential customers 
m  Capacity Restriction 
$primary$  Number of primary feeders 
$path1,path2$  Connectivity route for medium Voltage grid and tielines 
${d}_{mbox},{d}_{mMV}$  Route selection criteria 
$loc,flag,rpos,cpos,z$  Complementary variables 
Item  Parameter  Value 

Medium Voltage network  Primary feeders  3 
Voltage level  11 kV  
Installation Type  Underground Network  
Network Configuration  Radial with tie points using RMU  
Conductor size and type  XLPE insulated power cable 3 × 95 mm^{2} 15 kV  
Ring Main Units  1 to 4 switchgear cubicles  
Low Voltage network  Distribution Transformers  Oil Immersed distribution Transformers 11/0.22 kV 
Distribution Transformers Rating  kVA {30, 50, 75, 100, 160, 250, 350, 500, 750, 1000}  
Voltage level  0.22 kV  
Installation Type  Underground Network  
Network Configuration  Radial  
Conductor size and type  XLPE insulated power cable 2 kV  
Deployment features  end users information  1155 closedfeatures from OSM 
Total demand  13.029 MW  
Associated junction boxes per transformer  # {5, 10, 15,20}  
Coverage LV network  100%  
Coverage MV network  100% 
Scenario Per Cluster #  Primary Feeder Description  Distance Transformer to End User Average  Coverage LV %  Distribution Transformer #  End Users Per Primary Feeder #  MV Grid Length km  MV Grid Voltage Drop % 

SCENARIO A  PRIMARY FEEDER A  100  100  32  466  2.524  <1.2 
PRIMARY FEEDER B  100  100  30  452  2.94  <1.2  
PRIMARY FEEDER C  100  100  20  237  2.04  <1.2  
TOTAL  100  100  82  1155  7.484  <1.2  
SCENARIO B  PRIMARY FEEDER A  200  100  22  318  2.572  <1.2 
PRIMARY FEEDER B  200  100  13  306  1.799  <1.2  
PRIMARY FEEDER C  200  100  20  531  2.234  <1.2  
TOTAL  200  100  55  1155  6.605  <1.2  
SCENARIO C  PRIMARY FEEDER A  300  100  19  444  2.568  <1.2 
PRIMARY FEEDER B  300  100  11  245  1.507  <1.2  
PRIMARY FEEDER C  300  100  18  466  2.039  <1.2  
TOTAL  300  100  48  1155  6.114  <1.2  
SCENARIO D  PRIMARY FEEDER A  400  100  16  422  2.038  <1.2 
PRIMARY FEEDER B  400  100  12  249  2.032  <1.2  
PRIMARY FEEDER C  400  100  15  484  1.792  <1.2  
TOTAL  400  100  43  1155  5.862  <1.2 
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Valenzuela, A.; Inga, E.; Simani, S. Planning of a Resilient Underground Distribution Network Using Georeferenced Data. Energies 2019, 12, 644. https://doi.org/10.3390/en12040644
Valenzuela A, Inga E, Simani S. Planning of a Resilient Underground Distribution Network Using Georeferenced Data. Energies. 2019; 12(4):644. https://doi.org/10.3390/en12040644
Chicago/Turabian StyleValenzuela, Alex, Esteban Inga, and Silvio Simani. 2019. "Planning of a Resilient Underground Distribution Network Using Georeferenced Data" Energies 12, no. 4: 644. https://doi.org/10.3390/en12040644