On the Determination of Meshed Distribution Networks Operational Points after Reinforcement

Vita, Vasiliki; Lazarou, Stavros; Serițan, George

doi:10.3390/app9173501

Cited by 8 publications

(2 citation statements)

References 36 publications

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“…In this paper, the dynamic probabilistic characteristics of the node voltage amplitude are analyzed, with consideration of uncoordinated and coordinated charging [38]. In the case of uncoordinated charging, the owner is accustomed to charge the EV immediately after the last trip.…”

Section: Scenario 4: Dlf Analysis With Ev Integrationmentioning

confidence: 99%

Probabilistic Load Flow Algorithm of Distribution Networks with Distributed Generators and Electric Vehicles Integration

et al. 2019

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Probabilistic Load Flow (PLF) calculations are important tools for analysis of the steady-state operation of electrical energy networks, especially for electrical energy distribution networks with large-scale distributed generators (DGs) and electric vehicle (EV) integration. Traditional PLF has used the Cumulant Method (CM) and Latin Hypercube Sampling (LHS) method. However, traditional CM requires that each input variable be independent of one another, and the Cholesky decomposition adopted by the traditional LHS has limitations in that it is only applicable for positive definite matrices. To solve these problems, taking into account the Q-MCS theory of LHS, this paper proposes a CM PLF algorithm based on improved LHS (ILHS-CM). The cumulants of the input variables are obtained based on sampling results. The probability distribution of the output variables is obtained according to the Gram-Charlier series expansion. Moreover, DGs, such as wind turbines, photovoltaic (PV) arrays, and EVs integrated into the electrical energy distribution networks are comprehensively considered, including correlation analysis and dynamic load flow analysis for EV-coordinated charging. Four scenarios are analyzed based on the IEEE-30 node network, including with/without DGs and EVs, error analysis and performance evaluation of the proposed algorithm, correlation analysis of DGs and EVs, and dynamic load flow analysis with EV integration. The results presented in this paper demonstrate the effectiveness, accuracy, and practicability of the proposed algorithm.

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Section: Scenario 4: Dlf Analysis With Ev Integrationmentioning

confidence: 99%

Probabilistic Load Flow Algorithm of Distribution Networks with Distributed Generators and Electric Vehicles Integration

et al. 2019

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“…The process is iterative to cover all applicable cases, and the optimal result (optimal loading per node) is stored for each operational point. Following the same line of thought, Vita et al 10 propose a calculation algorithm that creates operational points and evaluates the performance of distribution lines after reinforcement, considering that EV charging is completely controlled. Models using fuzzy set theory for charging schemes were also proposed.…”

Section: Introductionmentioning

confidence: 99%

Transmission expansion planning in presence of electric vehicles at the distribution level

Gouveia

Costa

Sagredo

et al. 2020

Int Trans Electr Energ Syst

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SUMMARY The planning of the transmission network is an issue that, over the years, has received much attention, particularly due to the impact that this infrastructure has on the safe and reliable functioning of electrical systems. The search for solutions addressing climate change has led to several changes in the functioning of electrical systems, particularly concerning the increasing integration of renewable electricity production. However, in recent years, changes in the load side of the electrical system have also emerged. In particular, electric mobility has been developing, and a high penetration of electric vehicles (EVs) is expected in near future. This consumption is supplied by the distribution system but will impact the transmission network. Naturally, the amount of energy used by EVs is subject to uncertainties, which makes the problem complex. Those uncertainties cannot be easily modeled using statistical distributions because of the reduced history of available information. The transmission system operator (TSO) needs an efficient tool to analyze the adequacy of the transmission network to supply the distribution networks with high penetration of EVs. In this paper, a methodology based on symmetric/constrained fuzzy power flow is proposed to find the optimal investment policy at the transmission level while satisfying the technical constraints. The concept of dual variables provided by Lagrange multipliers, the natural result of the nonlinear optimization problem, is used to obtain the most promising reinforcement options considering the actual structure of the transmission network. The proposed model is tested on an IEEE 14‐bus system.

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A novel PSO algorithm for DG insertion problem

M'dioud

Bannari²,

Elkafazi³

2022

Energy Syst

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On the Determination of Meshed Distribution Networks Operational Points after Reinforcement

Cited by 8 publications

References 36 publications

Probabilistic Load Flow Algorithm of Distribution Networks with Distributed Generators and Electric Vehicles Integration

Probabilistic Load Flow Algorithm of Distribution Networks with Distributed Generators and Electric Vehicles Integration

Transmission expansion planning in presence of electric vehicles at the distribution level

A novel PSO algorithm for DG insertion problem

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