A Hybrid Heuristic and Evolutionary Algorithm for Distribution Substation Planning

Mazhari, Seyed Mahdi; Monsef, Hassan; Romero, Rubén

doi:10.1109/jsyst.2013.2290973

Cited by 23 publications

(24 citation statements)

References 40 publications

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“…The second and third terms consider the total required costs for installing/expanding switches and medium voltage feeders, respectively [12]. In this term, is a variable that indicates the total construction/reinforcement cost of a branch located between nodes by conductor .…”

Section: B Description Of the Terms Employedmentioning

confidence: 99%

“…Finally, the last term of (1) considers total penalties imposed on the distribution utility because of undelivered services [12]. It is assumed that supply interruptions are caused by feeder and substation outages, which are calculated through (4).…”

Section: B Description Of the Terms Employedmentioning

confidence: 99%

“…Besides these, several heuristic and meta-heuristic algorithms have been proposed to separately solve substation expansion planning (SEP) or optimal feeder routing. Solving these problems separately can decrease the computational burden of DSP, yet the optimality of the solutions is affected [12]- [14].…”

Section: Introductionmentioning

confidence: 99%

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A Multi-Objective Distribution System Expansion Planning Incorporating Customer Choices on Reliability

Mazhari

Monsef

Romero³

2016

IEEE Trans. Power Syst.

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This paper proposes a new multi-objective framework for primary distribution system planning (DSP). Further consideration is devoted to early DSP formulations in order to assess the risk imposed by probabilistic customer choices on reliability (CCOR). The CCOR is a buy/sell strategy that permits customers to pay the electricity price equiponderant to the reliability level provided by the distribution utility over the contract period. A Monte Carlo-based simulation is carried out to examine the effects of the probability of a customer's interest in adopting the CCOR on profit-at-risk. Furthermore, the DSP was conducted to simultaneously minimize both total planning cost and profit-at-risk. The resultant optimization problem is solved through the non-dominated sorting genetic algorithm (NSGA-II) accompanied by a fuzzy decision making method to select the best result among the obtained Pareto optimal set of solutions. The developed method is applied to an actual large-scale distribution system with about 140 000 customers, followed by a discussion on results.Index Terms-Customer choices on reliability (CCOR), distribution system planning (DSP), Monte Carlo simulation, non-dominated sorting genetic algorithm (NSGA-II), power system reliability, profit-at-risk. NOTATIONThe notation used throughout this paper is reproduced below for quick reference.Sets:Set of load points (electrical domains).Set of network nodes.Set of existing and candidate substations.Set of existing and candidate branches.Set of conductor types.Set of selected substations (existing and proposed).

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Section: B Description Of the Terms Employedmentioning

confidence: 99%

Section: B Description Of the Terms Employedmentioning

confidence: 99%

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A Multi-Objective Distribution System Expansion Planning Incorporating Customer Choices on Reliability

Mazhari

Monsef

Romero³

2016

IEEE Trans. Power Syst.

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Section: Introductionmentioning

confidence: 99%

“…The substation capacity planning was in conjunction with distribution system design in [15]- [18]. The algorithm of [15] did not consider the increase of failure rate of transformers with age and their salvage value at the end of the study period. In [16]- [18], lifetime of transformers was assumed to be a fixed value and interruption costs due to transformer failures were not examined.…”

Section: Introductionmentioning

confidence: 99%

Optimal Capacity Management of Substation Transformers Over Long-Run

Humayun

Sousa

Safdarian

et al. 2016

IEEE Trans. Power Syst.

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The management of transformers' capacity is a vital task for planners and asset managers due to their high cost. This paper proposes an optimization model for capacity management of transformers in a substation over long-run. The model considers the present worth costs of investment, losses, maintenance, reliability, and the salvage value of transformers for providing the optimal selection and scheduling of multistage transformer installations and their refurbishments. In the optimization model, growing failure rate of transformers along with their age is incorporated and the cumulative loss-of-life (LOL) of transformers is also used in determining their salvage value. The developed model is applied for planning and management of transformer capacities for a residential load dominant two-transformer primary distribution substation over a period of 40 years. The simulations are performed for various case studies representing the situations encountered by utilities. An extensive sensitivity analysis is also conducted for several conditions of the system parameters. The numerical results indicate the worth of inclusion of variable failure rate and LOL of transformers in their capacity management.

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Optimal MV/LV transformer allocation in distribution network for power losses reduction and cost minimization: A new multi‐objective framework

Khandani

Askarzadeh

2020

Int Trans Electr Energ Syst

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Among distribution network planning (DNP) problems, medium voltage (MV) to low voltage (LV) transformer allocation is one of the most important and challenging ones. This article presents a multi‐objective optimization framework for solving MV/LV transformer allocation problem considering two goals: power losses and investment cost. Transformer allocation problem has been solved in three scenarios: (1) base case, (2) mid‐term planning, and (3) long‐term planning. In order to effectively and efficiently solve this nonlinear problem, multi‐objective crow search algorithm (MOCSA) and multi‐objective particle swarm optimization (MOPSO) have been applied and compared in terms of Pareto front. Simulation results show that solving transformer allocation problem in multi‐objective framework results in a set non‐dominated solutions which provide a trade‐off between losses and cost. Moreover, MOCSA produces more promising results than MOPSO.

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A Hybrid Heuristic and Evolutionary Algorithm for Distribution Substation Planning

Cited by 23 publications

References 40 publications

A Multi-Objective Distribution System Expansion Planning Incorporating Customer Choices on Reliability

A Multi-Objective Distribution System Expansion Planning Incorporating Customer Choices on Reliability

Optimal Capacity Management of Substation Transformers Over Long-Run

Optimal MV/LV transformer allocation in distribution network for power losses reduction and cost minimization: A new multi‐objective framework

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