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Recent advances on power distribution system planning: a state-of-the-art survey

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Abstract

The rise in installation/reinforcement and maintenance costs of power distribution systems enforces the planner to adopt an optimal strategy during system planning. The planning should be uch that the designed system should economically and reliably take care of spatial and temporal load growth, and service area expansion in the planning horizon. Mathematically, this planning is a multivariable multi-objective optimization problem. During the past decade or so, several planning algorithms have been developed. The purpose of this survey is to present a comprehensive review of all the developments in the planning technology, which includes all the reported optimization models and solution strategies. This state-of-the art survey is systematically organized to serve as a stepping stone for future researchers as well as a planning guide for the engineers. The various planning models are grouped in a three-level classification structure starting with two broad categories, i.e., planning without and with reliability considerations. The tree grows further with subdivisions. The last level of this classification tree consists of different planning models and solution strategies. Comprehensive discussions on each planning model are presented.

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Abbreviations

\(C^B\) :

Cost coefficient of binary variables

\(y\) :

Binary decision variables

\(C^C\) :

Cost coefficient of continuous variables

\(P_j\) :

Power flow in branch \(j\)

\(S_{af}\) :

Set of all facilities (substations, feeders)

\(S_{br}\) :

Set of all branches

\(C_k^p\) :

Cost coefficient for \(k\)th policy

\(\eta _{sg} (\eta _{st} )\) :

Number of stages (states)

\(C_S (i,j)\) :

Cost of \(j\)th reinforcement plan for \(i\)th year

\(C_{Tr} (i-1,j),(i,m)\) :

Transfer cost from state (\(i-1,j\)) to state (\(i\),\(m)\)

\(C_{Scen_j }\) :

Cost coefficient for \(j\)th scenario

\(scen_j\) :

\(j\)th conductor replacement scenario

\(t_a\) :

Number of planning years

\(wt_i\) :

Weight of \(i\)th scenario

\(C_i^{s}\) :

Cost coefficient for \(i\)th scenario

Ap(Ip,Fp):

Admissible (implementable, feasible) policies

\(C_j^{EP}\) :

Cost coefficient for \(j\)th expansion plan

\(S_{EP}\) :

set of expansion plans

\(C_j^{CP}\) :

Cost coefficient for \(j\)th construction plan

\(S_{CP}\) :

Set of construction plans

\(C_i^{ss} (C_{i,j}^{fb} )\) :

Installation cost of substation \(i\) (branch ij)

\(E_s (E_{br} )\) :

Set of existing substations (branches)

\(wt_i ,wt_{i,j}\) :

Weighting factors (\(\gg \)0)

\(P_{\max _i } (P_{\max _{i,j} } )\) :

Capacity of Substation \(i\) (branch ij,)

\(\tilde{C}^B(\tilde{C}^C)\) :

Fuzzy cost coefficient of binary (continuous) variables

\(\tilde{P}\) :

Fuzzy power flow

\(C^{out}\) :

Outage cost

\(\lambda (d)\) :

Failure rate (repair duration)

\(l_{j}\) :

Length of feeder branch \(j\)

\(S_{Ceq}\) :

Set of control equipments

\(S_{st}\) :

Set of substation source transformers

\(C^{\mathrm{int}}(C^{dur})\) :

Cost per customer interruption (duration)

\(N_{C-sub}\) :

Number of substation customer

\(C^{LR}(L_{j,k}^R )\) :

Cost of load reallocation (amount of load transfer from substation \(j\) to \(k)\)

\(S_S (S_k^{LR} )\) :

Set of substations (substations for load reallocation for \(k\)th substation)

\(L_{total} (\eta _b )\) :

Total load (number of branches)

\(NDL_{avg} (NDL_i )\) :

Average non-delivered load (non-delivered load due to fault at branch \(i)\)

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  1. N. C. Sahoo

    Present address: School of Electrical Sciences, Indian Institute of Technology, Bhubaneswar, Odisha, India

Authors and Affiliations

  1. Department of Electrical Engineering, National Institute of Technology, Rourkela, India

    S. Ganguly

  2. Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Tronoh, Malaysia

    N. C. Sahoo

  3. Department of Electrical Engineering, Indian Institute of Technology, Kharagpur, India

    D. Das

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Ganguly, S., Sahoo, N.C. & Das, D. Recent advances on power distribution system planning: a state-of-the-art survey. Energy Syst 4, 165–193 (2013). https://doi.org/10.1007/s12667-012-0073-x

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