A dynamic fuzzy interactive approach for DG expansion planning

Jahromi, Majid Esmi; Ehsan, Mehdi; Meyabadi, Abbas Fattahi

doi:10.1016/j.ijepes.2012.06.017

Cited by 38 publications

(21 citation statements)

References 41 publications

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“…To deal with that, many methods have been proposed [9]. Cost modeling is a common approach in planning [10][11][12] that determines the siting and sizing problems together. Other methods use different indices [13][14][15][16][17][18], such as voltage regulation, environmental factors, power loss related, maximum DG capacity, and so on, to assess the performance of the system after the new unit is installed.…”

Section: Nomenclature B(l)mentioning

confidence: 99%

Investigation on Impacts of Alternative Generation Siting in Power Grids from the View of Complex Network Theory

Xiang

Liu

et al. 2016

Electric Power Components and Systems

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Section: Nomenclature B(l)mentioning

confidence: 99%

Investigation on Impacts of Alternative Generation Siting in Power Grids from the View of Complex Network Theory

Xiang

Liu

et al. 2016

Electric Power Components and Systems

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“…Based on a large amount of historical data analysis, stochastic output is abstracted into multiple scenarios with their probability of occurrence, and then substituted it into multi-objective planning model [32,33]. Reference [34] put forward a dynamic fuzzy interactive approach for expansion planning in a long term period.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Credible Capacity for Intermittent Distributed Energy Resources in Active Distribution Network

et al. 2017

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Abstract:The irregularity and randomness of distributed energy sources' (DERs) output power characteristic usually brings difficulties for grid analysis. In order to reliably and deterministically evaluate intermittent distributed generation's active power output, a credible capacity index for active distribution network (ADN) is proposed. According to the definition, it is a certain interval that the stochastic active power output of DERs may fall in with larger probability in all kinds of possible dynamic and time varying operation scenarios. Based on the description and analysis on the time varying scenarios, multiple scenarios considered dynamic power flow method for and are proposed. The method to calculate and evaluate credible capacity based on dynamic power flow (DPF) result is illustrated. A study case of an active distribution network with DERs integrated and containing 32 nodes is selected; multiple operation scenarios with various fractal dimension are established and used. Results of calculated credible capacity based on several groups of scenarios have been analyzed, giving the variance analysis of groups of credible capacity values. A deterministic value with the maximum occurrence probability representing credible capacity is given. Based on the same network case, an application of credible capacity to grid extension planning is given, which contributes to expenditure and cost reduction. The effectiveness and significance of the proposed credible capacity and solution method have been demonstrated and verified.

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“…In summary, the main difference between these papers is the algorithm used: the methodologies presented in [7][8][9][10][11][12][13] use genetic based algorithms; in [14][15][16][17][18][19][20], particle swarm optimization (PSO)-based algorithms were applied. There are still some others less used algorithms: successive elimination [21], mixed-integer linear programming [22], artificial neural network [23], chaotic local search with modified honey bee mating optimization [24], Bellman-Zadeh [25], bacterial foraging optimization [26], dynamic programming [27] and hierarchical agglomerative clustering [28].…”

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

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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.

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A dynamic fuzzy interactive approach for DG expansion planning

Cited by 38 publications

References 41 publications

Investigation on Impacts of Alternative Generation Siting in Power Grids from the View of Complex Network Theory

Investigation on Impacts of Alternative Generation Siting in Power Grids from the View of Complex Network Theory

Assessment of Credible Capacity for Intermittent Distributed Energy Resources in Active Distribution Network

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

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