Optimal reactive power dispatch: a review, and a new stochastic voltage stability constrained multi‐objective model at the presence of uncertain wind power generation

Mohseni‐Bonab, Seyed Masoud; Rabiee, Abbas

doi:10.1049/iet-gtd.2016.1545

Cited by 99 publications

(81 citation statements)

References 66 publications

(78 reference statements)

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“…The generated scenarios for load demand, price, and wind are shown in Figures 5-7, respectively. The relationship between wind speed and wind power is derived from [26] which is shown in Equation (21). This function transforms the wind speed to electricity power for a wind turbine.…”

Section: Modeling Load Demand Price and Wind Speed Uncertaintiesmentioning

confidence: 99%

Optimal Charging of Plug-In Electric Vehicle: Considering Travel Behavior Uncertainties and Battery Degradation

et al. 2019

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The negative environmental impacts of using fossil fuel-powered vehicles underlined the need for inventing an alternative eco-friendly transportation fleet. Plug-in electrical vehicles (PEVs) are introduced to cut the continuing increase in energy use and carbon emission of the urban mobility. However, the increased demand for mobility, and therefore energy, can create constraints on the power network which can reduce the benefits of electrification as a certain and reliable source. Thus, the rise in the use of electric vehicles needs electric grids to be able to feed the increased energy demand while the current infrastructure supports it. In this paper, we introduce a methodological framework for scheduling smart PEVs charging by considering the uncertainties and battery degradation. This framework includes an economic model for charging and discharging of PEVs which has been implemented in a 21-node sample distribution network with a wind turbine as a distributed generation (DG) unit. Our proposed approach indicates that the optimal charging of the PEVs has a high impact on the distribution network operation, particularly under the high market penetration of PEVs. Thus, the smart grid to vehicle (G2V) charging mode is a potential solution to maximize the PEV’s owner profit, while considering the battery degradation cost of the PEVs. The simulation result indicates that smart charging effectuation is economical.

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Section: Modeling Load Demand Price and Wind Speed Uncertaintiesmentioning

confidence: 99%

Optimal Charging of Plug-In Electric Vehicle: Considering Travel Behavior Uncertainties and Battery Degradation

et al. 2019

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“…The model can be transformed into two deterministic sub-models [40][41][42][43][44][45]. The first sub-model is (where c ± jt ≥ 0, ω + jtk ≥ 0, b + rt > 0 and f ± > 0):…”

Section: Methodsmentioning

confidence: 99%

A Multistage Distribution-Generation Planning Model for Clean Power Generation under Multiple Uncertainties—A Case Study of Urumqi, China

2018

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In this research, a multistagedistribution-generation planning (MDGP) model is developed for clean power generation in the regional distributed generation (DG) power system under multiple uncertainties. The developed model has been applied for sustainable energy system management at Urumqi, China. Various scenarios are designed to reflect variations indemand modes of districts, seasonal limits, potentials of energy replacement, and clean power generation. The model can provide an effective linkage between economic cost and stability of DG power systems. Different power generation schemes would be obtained under different seasonal scenarios and system-failure risk levels. On the other hand, net system costs would be obtained and analyzed. The results indicate that the traditional power generation can be replaced by renewable energy power in DG power systems to satisfy the environmental requestsofthe city of Urumqi. The obtained solutions can help decision-makers get feasible decision alternatives to improve clean power planning in the Urumqi area under various uncertainties.

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“…In,15 treats the stochastic MO‐ORPD under load and wind uncertainties considering two objectives in minimizing real power loss and voltage stability. In, the MO‐ORPD problem is treated considering minimization of active power losses and O&M (operation and maintenance) cost of wind farms as objectives. A trade‐offs between the minimization of active power losses and the number of control adjustments, the MO‐ORPD is formulated as MINLP and solved by different GAMS solvers with, the different solutions are compared.…”

Section: Introductionmentioning

confidence: 99%

Stochastic multi‐objective optimal reactive power dispatch considering load and renewable energy sources uncertainties: a case study of the Adrar isolated power system

Naidji

Boudour

2020

Int Trans Electr Energ Syst

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Optimal reactive power dispatch (ORPD) is a particular case of the optimal power flow (OPF) which consists in determining the state of an electric power system by optimizing a specific objective function and satisfying a set of some operating constraints. In this paper, the purpose is to solve deterministic and stochastic multi‐objective ORPD (MO‐ORPD) problem under load and renewable energy sources (RES) uncertainties. The uncertainty is modelled using stochastic scenario‐based approach (SSBA). The objectives to be minimized are active power loss and cumulative voltage deviation from their corresponding nominal values. The MO‐ORPD is solved using sum weighed method, and fuzzy satisfying method is used to select the best compromise solution among Pareto front of non‐dominated solutions. In this paper, quantum‐behaved particle swarm optimization differential mutation (QPSODM) algorithm is proposed to solve the ORPD problem. The proposed methodology has been examined and confirmed on the IEEE 14‐bus and the practical Adrar's isolated power system. The performance of the proposed methodology is compared with recent algorithms. Simulation results show that the proposed methodology can solve the MO‐ORPD including RES effectively and can give best and logic results. Furthermore, a sensitivity analysis is carried out to show the performance of the proposed algorithm comparing to own developed algorithms particle swarm optimization (PSO) and quantum PSO (QPSO).

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Optimal reactive power dispatch: a review, and a new stochastic voltage stability constrained multi‐objective model at the presence of uncertain wind power generation

Cited by 99 publications

References 66 publications

Optimal Charging of Plug-In Electric Vehicle: Considering Travel Behavior Uncertainties and Battery Degradation

Optimal Charging of Plug-In Electric Vehicle: Considering Travel Behavior Uncertainties and Battery Degradation

A Multistage Distribution-Generation Planning Model for Clean Power Generation under Multiple Uncertainties—A Case Study of Urumqi, China

Stochastic multi‐objective optimal reactive power dispatch considering load and renewable energy sources uncertainties: a case study of the Adrar isolated power system

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