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Power Systems Resilience pp 119–138Cite as

Resilience Thorough Microgrids

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Part of the book series: Power Systems ((POWSYS))

Abstract

Currently the number of Microgrids (MGs) is continuously increased in distribution network . In this view, the future advanced distribution network can be regarded as clusters of MGs. Hence the MGs is the building blocks of smart distribution networks. There are many technical, economic and social reason for MGs implementation. One of the main advantages of MGs is the ability to encounter with abnormal conditions in the network such as occurrence of natural disasters with island operation capability. Based on the above discussion, the problem of optimal planning of distribution network based-on MGs is an interesting topic. In this chapter the optimal MG-based smart distribution grid planning problem is formulated and tested on a planning area. While the natural disasters are low probability and high impact phenomena, there are not enough historical data to extract an accurate component failure model. In this chapter the initial geographical area of MGs is supposed as input data in a large scale Greenfield study area and based on the resiliency constraints and index, the optimal configuration of total distribution network including MGs is determined. The distribution network configuration is planned such that all MGs meet the predefined requirement based on definition and supply the predefined critical loads within each MGs. In this work the optimal size and site of network elements and its configuration is determined by a multi-objective optimization algorithm. The effect of the natural disasters on resilient MG-based distribution network planning, the geographical data for disasters is modelled to give a geographical map that joins the spatial risk index with distribution network component location. The main goal of this work is to propose a framework for optimal MG-based resilient distribution networks.

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Abbreviations

\( B_{di} \) :

Binary decision variable for DGs

\( (\cos \varphi_{ave} )_{ic} \) :

Power factor of cth cluster connected to ith DG

\( (\cos \varphi )_{ick} \) :

Power factor of kth load of cth cluster supplied by ith DG

\( C_{Dept.} \) :

Depreciation value

\( C_{DGi,fuel} \) :

Fuel price for DG unit

\( C_{DGi}^{Levelized} \) :

Levelized cost of energy

\( C_{DGi,O\& M}^{Var.} \) :

O&M fixed cost

\( C_{DERi,O\& M}^{Var.} \) :

O&M variable cost

\( C_{DGi}^{Cap} \) :

Capital cost for DG

\( C_{i} \) :

Current temperature

\( C_{LVF,ic}^{Cap} \) :

LV feeder capital cost from ith DG to cth Cluster

\( C_{LVF,kic}^{Cap} \) :

LV feeder cost for kth load of cth cluster connected to ith DG

\( C_{tax} \) :

Tax rate

\( C_{v} \) :

Voltage temperature

\( Co_{cost}^{colony} \) :

Colonies cost coefficient

\( D_{rate} \) :

Discount rate

\( Dist_{\hbox{max} } \) :

Max distance or max feeder length (m)

\( Dist_{ck} \) :

Distance between kth load and cth cluster (m)

\( Dist_{ic} \) :

Distance between ith DG and cth Cluster (m)

F :

Cost function

\( f_{DGi,cap.} \) :

Capacity factor

\( f_{ELC} \) :

Energy loss cost factor (USD/kWh)

\( f_{rec.}^{Cap} \) :

Capital recovery factor

\( F_{{DG_{MG} }} \) :

Cost of DG in MG

\( F_{{LVF_{MG} }} \) :

Cost of LV feeder in MG

\( H_{DGi,rate} \) :

Heat rate

\( i_{LOSS,ck} \) :

Loss index for feeder from cth cluster to kth load point

\( i_{LOSS,ic} \) :

Loss index for feeder from ith DG to cth cluster

\( I(s_{i} ) \) :

PV current

I ms :

Max current

I sc :

Short circuit current

k :

Weibull PDF shape factor

l :

Distance

l t :

Life time

\( L_{DGi} \) :

Connected load to DG (kW)

\( LF_{ave} \) :

Average annual load factor

\( MD_{\hbox{max} } \) :

Max elec. distance (m.kW)

N :

PV number

N c :

Number of countries

N DG :

Number of DG units

N i :

Number of clusters

N I :

Number of imperialists

N L :

Total number of loads

N Li :

Number of load blocks supplied by ith DG

ND :

Number of decades

P :

Turbine output power

P r :

Rated power turbine

P k :

Block demand (kW)

P DGi :

Rated capacity of DG (kW)

PF c :

Customer power factor

PF D :

DG power factor

R :

Line resistance (Ω)

R rev :

Revolution rate

S :

Demand

s :

Scale factor

s i :

Solar irradiance

s ave :

Average radiation

\( T \) :

Time period (years)

\( T^{\prime} \) :

Ambient air temperature

T n :

Nominal operating cell temperature

T cell :

Cell temperature

V :

LV line voltage (kV)

\( V(s_{i} ) \) :

PV voltage

V max :

Maximum permitted voltage drop value

V ms :

Max voltage

V oc :

Open circuit voltage

x :

x coordinate of certain load or source point

X :

Line reactance (Ω)

y :

y coordinate of certain load or source point

µ :

MG’s number

γ :

Mean of demand

σ :

Variance of demand

ν :

Wind speed

η :

Efficiency

α :

Alpha PDF shape parameter

β :

Beta PDF shape parameter

ρ :

Specific resistance

λ :

Failure rate

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Azarshahr Branch, Islamic Azad University, Azarshahr, Iran

    Shahram Mojtahedzadeh

  2. Smart Distribution Grid Research Lab, Azarbaijan Shahid Madani University, Tabriz, Iran

    Sajad Najafi Ravadanegh

  3. Electric Transmission and Distribution Research Lab, Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran

    Mahmoudreza Haghifam

  4. Department of Electrical Engineering, Seraj Higher Education Institute, Tabriz, Iran

    Naser Mahdavi Tabatabaei

Authors
  1. Shahram Mojtahedzadeh
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  2. Sajad Najafi Ravadanegh
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  3. Mahmoudreza Haghifam
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  4. Naser Mahdavi Tabatabaei
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Corresponding author

Correspondence to Sajad Najafi Ravadanegh .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, Seraj Higher Education Institute, Tabriz, Iran

    Naser Mahdavi Tabatabaei

  2. Department of Electrical Engineering, Azarbaijan Shahid Madani University, Tabriz, Iran

    Sajad Najafi Ravadanegh

  3. Faculty of Electronics, Communications and Computers, University of Pitesti, Pitesti, Arges, Romania

    Nicu Bizon

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Mojtahedzadeh, S., Najafi Ravadanegh, S., Haghifam, M., Mahdavi Tabatabaei, N. (2019). Resilience Thorough Microgrids. In: Mahdavi Tabatabaei, N., Najafi Ravadanegh, S., Bizon, N. (eds) Power Systems Resilience. Power Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-94442-5_5

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  • DOI: https://doi.org/10.1007/978-3-319-94442-5_5

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  • Online ISBN: 978-3-319-94442-5

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