Maximize the penetration level of photovoltaic systems and shunt capacitors in distribution systems for reducing active power loss and eliminating conventional power source

Kien, Le Chi; Nguyen, Thuan Thanh; Phan, Tan Minh; Nguyen, Thang Trung

doi:10.1016/j.seta.2022.102253

Cited by 7 publications

(5 citation statements)

References 36 publications

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“…Hence, the use of less energy supplied by WTs in Scenario 2 for reaching the best power loss values is a better implementation than what resulted in Scenario 1. Figures [24][25][26][27] show the total power supplied by WTs in one day of each month of the four quarters for two scenarios. While looking at Figure 24, the energy supplied by WTs in Scenario 1 in the first three months of the year is noticeably larger than that in Scenario 2.…”

Section: The Results Obtained By Woa In Casementioning

confidence: 99%

“…In [24], a modified version of particle swarm optimization (PSO) called adaptive particle swarm optimization (APSO) was used to optimize the allocation of DGs-based renewable energy for reaching the minimum value of a multi-objective function. In [25], the moth swarm algorithm (MSA) was executed to achieve the maximum penetration level of both PGs and SCs and reduce the reliance on conventional generating sources. The results obtained by MSA were then compared to two others and indicated the high capability of the applied method.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Design and Operation of Wind Turbines in Radial Distribution Power Grids for Power Loss Minimization

Phan,

Duong,

Doan

et al. 2024

Applied Sciences

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This research proposes a strategy to minimize the active power loss in the standard IEEE 85-node radial distribution power grid by optimizing the placement of wind turbines in the grid. The osprey optimization algorithm (OOA) and walrus optimization algorithm (WOA) are implemented to solve the problem. The two algorithms are validated in three study cases of placing two wind turbines (WTs) in the system for power loss reduction. Mainly, in Case 1, WTs can only produce active power, while in Case 2 and Case 3, WTs can supply both active and reactive power to the grid with different ranges of power factors. In Case 4, the best-applied methods between the two are reapplied to reach the minimum value of the total energy loss within one year. Notably, this case focuses on minimizing the total power loss for each hour in a day under load demand variations and dynamic power supply from WTs. On top of that, this case uses two different sets of actual wind power data acquired from the Global Wind Atlas for the two positions inherited from the previous case. Moreover, the utilization of wind power is also evaluated in the two scenarios: (1) wind power from WTs is fully used for all values of load demand, (2) and wind power from WTs is optimized for each load demand value. The results in the first three cases indicate that the WOA achieves better minimum, mean, and maximum power losses for the two cases than the OOA over fifty trial runs. Moreover, the WOA obtains an excellent loss reduction compared to the Base case without WTs. The loss of the base system is 224.3 kW, but that of Case 1, Case 2, and Case 3 is 115.6, 30.6 kW, and 0.097 kW. The placement of wind turbines in Case 1, Case 2, and Case 3 reached a loss reduction of 48.5%, 84.3%, and 99.96% compared to the Base case. The optimal placement of WTs in the selected distribution power grid has shown huge advantages in reducing active power loss, especially in Case 3. For the last study case, the energy loss in a year is calculated by WSO after reaching hourly power loss, the energy loss in a month, and the season. The results in this case also indicate that the optimization of wind power, as mentioned in Scenario 2, results in a better total energy loss value in a year than in Scenario 1. The total energy loss in Scenario 2 is reduced by approximately 95.98% compared to Scenario 1. So, WOA is an effective algorithm for optimizing the placement and determining the power output of wind turbines in distribution power grids to minimize the total energy loss in years.

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Section: The Results Obtained By Woa In Casementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Design and Operation of Wind Turbines in Radial Distribution Power Grids for Power Loss Minimization

Phan,

Duong,

Doan

et al. 2024

Applied Sciences

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“…Voltage instability may result in voltage collapse, which can lead to extensive power outages and have a profound impact on the electrical system [2]. A viable solution to enhance the voltage stability of electrical power systems is the installation of devices such as shunt capacitors for compensating reactive power [3]. However, the efficiency of shunt capacitors is highly dependent on the choice of their location and capacity in the electrical power systems.…”

Section: Introductionmentioning

confidence: 99%

Influence of Load Models and DG Operational Power Factor on Optimization of Shunt Capacitor Placement in Distribution Grids Considering Voltage Stability

Van-Y Pham

2024

jes

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The paper proposes a mathematical model of mixed-integer nonlinear programming (MINLP) to optimize the location and size of shunt capacitors in power distribution grids with distributed generation (DG), considering voltage stability constraints. At the same time, the paper also analyzes the influence of the load models, such as voltage-dependence load (ZIP load) and constant power load, together with DG’s operating power factor on the optimal solution. The objective function of the proposed optimization formulation is minimizing the total expenses, including the capital investment of capacitors and the expense incurred by network energy loss. This MINLP model includes constraints in the current and critical loading conditions, such as the system of power flow equations, nodal voltage limits, branch thermal limits, capacitor-related constraints, and restrictions of minimum security level. The proposed optimization model was evaluated on a modified IEEE 33-node distribution grid using the KNITRO commercial solver with the GAMS programming language. The calculation results show that the voltage stability constraints, load models, and operational power factor of the DG units have an essential influence on the optimal position and capacity of the shunt capacitors.

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“…The research problem of optimizing DG in modern power electronic distribution networks aims to address these challenges and maximize the benefits of DG systems while ensuring a reliable and stable power supply 14 . A reasonable DG optimization scheme can reduce line loss, 15 and operating costs 16 while optimizing voltage, but DG integration at some buses will lead to overvoltages, 17 overcurrents, 18 and other problems. Besides, it is crucial for building a sustainable, resilient, and efficient power grid that effectively harnesses renewable energy sources while accommodating the uncertainties associated with DG and load demand 19 .…”

Section: Introductionmentioning

confidence: 99%

A line loss reduction optimization for renewable energy‐based distribution networks using a probabilistic approach

Jiang,

Han,

et al. 2023

Circuit Theory & Apps

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SummaryThe large integration of distributed generation (DG) and electric vehicles (EVs) facilitates daily life and reduces carbon emissions. However, it brings problems such as increased uncertainty and power electronic permeability to the distribution network. In this context, it is important to solve the line loss optimization problem as closely as possible to the real situation. Therefore, this paper solves the line loss optimization problem based on a probabilistic model of three‐phase unbalanced modern power electrical distribution network. Firstly, the paper proposes a frequency domain model of the distribution network and the optimization problem model. Then, to deal with the uncertainty of the system, the point estimation method (PEM) and Monte Carlo Simulation (MCS) are used. Finally, this paper proposes two optimization schemes considering the power quality when single and multiple DGs are integrated. The simulation results demonstrate that the PEM using the Gram–Charlier series expansion of the fourth‐order statistical moments to estimate the probability density function (PDF) is significantly less time consuming than the traditional MCS method while maintaining accuracy. The comparative analysis reveals that under the optimization scheme with single DG integration, the expected value of system line loss and expected line loss rate are reduced from 283.95 kW to 218.96 kW (22.89% reduction) and from 13.44% to 10.68%, respectively. Under the dual DG integrated optimization scheme, the expected value of line losses and expected line loss rate are reduced from 283.95 kW to 208.88 kW (26.4% reduction) and from 13.44% to 10.25%, respectively. However, after taking the uncertainty into account, the operational reliability of the system has been enhanced under different scenarios. In addition, it is found that the optimization approach incorporating multiple DG units can effectively mitigate the system line loss under diverse operational scenarios while enhancing the system's DG integration capability.

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Maximize the penetration level of photovoltaic systems and shunt capacitors in distribution systems for reducing active power loss and eliminating conventional power source

Cited by 7 publications

References 36 publications

Optimal Design and Operation of Wind Turbines in Radial Distribution Power Grids for Power Loss Minimization

Optimal Design and Operation of Wind Turbines in Radial Distribution Power Grids for Power Loss Minimization

Influence of Load Models and DG Operational Power Factor on Optimization of Shunt Capacitor Placement in Distribution Grids Considering Voltage Stability

A line loss reduction optimization for renewable energy‐based distribution networks using a probabilistic approach

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