NSGA-II with local search for a multi-objective reactive power compensation problem

Pires, Dulce F.; Antunes, Carlos Henggeler; Martins, António Gomes

doi:10.1016/j.ijepes.2012.05.024

Cited by 92 publications

(37 citation statements)

References 43 publications

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“…In the area of energy, the NSGA-II algorithm has been widely used in the reactive power planning problem [15,16,17,18,19], the optimal power flow problem [20,21,22] and the GEP problem [6,23].…”

Section: Methodsmentioning

confidence: 99%

A multi-step multi-objective generation expansion planning model-A case study in Mexico

Palácios¹,

Valdés²,

Batres³

2018

SGCE

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Planning in the energy sector implies multiple and conflicting objectives. Multi-objective models allow the analysis of the inter-relationships and trade-off solutions to be obtained. This paper presents a mixed integer linear model for multi-step multi-objective generation expansion planning (MMGEP). The MMGEP problem is defined as the problem of determining the answers to the following questions: What types of generation technologies are to be added to the grid? What is the capacity of each new generation plant? Where will the plant be located? When will the plant be located? The MMGEP objectives are to minimize the global cost of the system, minimize the environmental impact and maximize the social profits. The proposed model is based on a real power system in Mexico for the planning period between 2017 and 2037. The problem was solved using the NSGA-II algorithm.

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Section: Methodsmentioning

confidence: 99%

A multi-step multi-objective generation expansion planning model-A case study in Mexico

Palácios¹,

Valdés²,

Batres³

2018

SGCE

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“…The PT categorizations have designated in this paper by DG placement (DGP) . Followed by VAR compensation and power quality (VPQ) [53][54][55][56][57][58][59][60][61][62][63][64][65][66][67][68][69][70]. Moreover, component (protection and automation devices) placement, modern grid reinforcement and upgrades (CRU) [71][72][73][74][75][76][77][78][79][80][81][82][83][84][85][86][87][88][89].…”

Section: Paper Contributionmentioning

confidence: 99%

Multi-Objective Planning Techniques in Distribution Networks: A Composite Review

2017

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Distribution networks (DNWs) are facing numerous challenges, notably growing load demands, environmental concerns, operational constraints and expansion limitations with the current infrastructure. These challenges serve as a motivation factor for various distribution network planning (DP) strategies, such as timely addressing load growth aiming at prominent objectives such as reliability, power quality, economic viability, system stability and deferring costly reinforcements. The continuous transformation of passive to active distribution networks (ADN) needs to consider choices, primarily distributed generation (DG), network topology change, installation of new protection devices and key enablers as planning options in addition to traditional grid reinforcements. Since modern DP (MDP) in deregulated market environments includes multiple stakeholders, primarily owners, regulators, operators and consumers, one solution fit for all planning scenarios may not satisfy all these stakeholders. Hence, this paper presents a review of several planning techniques (PTs) based on mult-objective optimizations (MOOs) in DNWs, aiming at better trade-off solutions among conflicting objectives and satisfying multiple stakeholders. The PTs in the paper spread across four distinct planning classifications including DG units as an alternative to costly reinforcements, capacitors and power electronic devices for ensuring power quality aspects, grid reinforcements, expansions, and upgrades as a separate category and network topology alteration and reconfiguration as a viable planning option. Several research works associated with multi-objective planning techniques (MOPT) have been reviewed with relevant models, methods and achieved objectives, abiding with system constraints. The paper also provides a composite review of current research accounts and interdependence of associated components in the respective classifications. The potential future planning areas, aiming at the multi-objective-based frameworks, are also presented in this paper.Keywords: active distribution network (ADN); distributed generation (DG); distributed energy resources (DERs); distribution network planning (DP); multi-objective optimization (MOO); multi-criteria decision analysis (MCDA); distributed generation placement (DGP); volt-ampere reactive power (VAR) compensation and power quality (VPQ); component reinforcement and up gradation (CRU); network (distribution) topology change and reconfiguration (NTR); planning techniques (PT); multiple objective planning (MOP); multi-objective planning techniques (MOPTs); future distribution networks (FDNs)

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“…For example, it is possible to prevent a generator from delivering the reactive power absorbed by the loads by making other parts of the system deliver it. This is called reactive power compensation [16][17][18][19][20][21][22]. But also, if a power does not satisfy Tellegen's theorem, then the power delivered by the generator will not necessarily be nullified by making a section of the network deliver the power absorbed by other part of the network.…”

Section: The Energy Conservation Law and Tellegen's Theoremmentioning

confidence: 99%

Electric powers that fulfill Tellegen’s theorem and those that do not: Analysis of consequences

Redondo¹,

Melchor²,

Quintela³

et al. 2013

International Journal of Electrical Power & Energy Systems

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NSGA-II with local search for a multi-objective reactive power compensation problem

Cited by 92 publications

References 43 publications

A multi-step multi-objective generation expansion planning model-A case study in Mexico

A multi-step multi-objective generation expansion planning model-A case study in Mexico

Multi-Objective Planning Techniques in Distribution Networks: A Composite Review

Electric powers that fulfill Tellegen’s theorem and those that do not: Analysis of consequences

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