Primary power distribution systems planning taking into account reliability, operation and expansion costs

Cossi, Antônio Marcos; Silva, L.G.W. Da; Lázaro, Rubén Augusto Romero; Mantovani, José Roberto Sanches

doi:10.1049/iet-gtd.2010.0666

Cited by 65 publications

(56 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Planning components associated to each PT in reviewed work are designated with symbols A, B, C, and D, respectively, also shown in an overarching diagram as in Figure 1. The color coding allocated to each PT in the arrangement order includes green (A) for DGP ; orange (B) for VPQ [53][54][55][56][57][58][59][60][61][62][63][64][65][66][67][68][69][70]; blue (C) for CRU [71][72][73][74][75][76][77][78][79][80][81][82][83][84][85][86][87][88][89] and purple (D) for NTR [90][91][92][93][94][95][96][97][98][99][100]. It is important to note that date o...…”

Section: Composite Review Of Mop Techniques With Taxonomymentioning

confidence: 99%

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

2017

View full text Add to dashboard Cite

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)

show abstract

Section: Composite Review Of Mop Techniques With Taxonomymentioning

confidence: 99%

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

2017

View full text Add to dashboard Cite

show abstract

“…The decision maker can then select the best or final solution among the Pareto points based on the expert knowledge or a meta-heuristic technique such as fuzzy satisfying method. References [19][20][21][22] use this technique for various multi-objective problems. Given an optimisation problem with two objectives, a Pareto point corresponds to a solution in which by fixing the value of each objective, there is no better solution for the other one.…”

Section: Generating the Pareto Frontmentioning

confidence: 99%

Optimal distributed static series compensator placement for enhancing power system loadability and reliability

Dorostkar-Ghamsari

Fotuhi‐Firuzabad

Aminifar

et al. 2015

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

Distributed static series compensator (DSSC) is a member of the family of distributed flexible AC transmission system devices that can be attached directly to conductors of transmission lines. DSSCs are able to compensate for and adjust the line reactance; thus, they could be widely used in stability-limited transmission systems. Owing to economic matters, the optimal placement of DSSCs is of a great interest from practical viewpoints. This study presents an approach to find the optimal locations of DSSCs to enhance the system loadability and reliability using the DC load flow model. The optimisation problem is solved using the mixed-integer linear programming. A compromise between improving the system loadability and reliability is fulfilled and a wide range of non-dominated optimal solutions is calculated. The final solution is then selected using the fuzzy satisfying method. Numerical studies are conducted on the IEEE reliability test system (IEE-RTS). Nomenclature

show abstract

“…8). 4 Complementary, DGs setpoint also can be defined as function of the day. The day/load level control can be automatically realized by a local device (does not need online communications between DGs and DNOs), defining the optimal operation mode according to the day (e.g., working days, weekends, holidays) and the load level (e.g., stratified in 1h steps).…”

Section: Feeder #1mentioning

confidence: 99%

“…In [3] is shown a technical planning methodology at electrical power substation level, using Particle Swarm Optimization algorithm to find the optimal placement of power substations, considering the presence of DGs, to reduce the peak demand. In [4] is shown a methodology to combine network expansion costs reduction and network reliability, when occurs a permanent fault. In [5] is proposed a mixed-integer optimization model to decide between centralized and decentralized generation sources for new energy infrastructure development.…”

Section: Introductionmentioning

confidence: 99%

Electrical distribution network operation with a presence of distributed generation units in a Pre Smart Grid environment using a clustering-based methodology

2015

View full text Add to dashboard Cite

Technical planning methodologies applied to electrical distribution networks presented in the literature generally consider that the distributed generation units (DGs) are operating in their standard operation mode, i.e., the distribution network operators (DNOs) have no control over the active power dispatched by DGs and there is no injection of reactive power into the electrical distribution network. Furthermore, such methodologies generally consider only balanced loads connected to electrical distribution networks. Some others methodologies that have control over the power dispatched by DGs consider that the Smart Grid philosophy is completely implemented. However, it is a distant prospect in many developing countries. In that ideal scenario, there is a constant and online communication between DGs and DNOs control centers. In this paper, the authors propose a new technical planning methodology, based on a clustering method, that considers the occurrence of unbalanced electrical distribution loads, the absence of DNO control over the active power dispatched by DGs and the absence of online communications between DGs and DNOs. The proposed methodology can be implemented in a short and medium term (called Pre Smart Grid). In that period of time, the Smart Grid philosophy will not be completely implemented.

show abstract

Primary power distribution systems planning taking into account reliability, operation and expansion costs

Cited by 65 publications

References 20 publications

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

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

Optimal distributed static series compensator placement for enhancing power system loadability and reliability

Electrical distribution network operation with a presence of distributed generation units in a Pre Smart Grid environment using a clustering-based methodology

Contact Info

Product

Resources

About