A newly effective method to maximize power loss reduction in distribution networks with highly penetrated distributed generations

Duong, Thanh Long; Nguyen, Tri Phuoc; Vo, Dieu Ngoc; Le, Minh Phuong

doi:10.1016/j.asej.2020.11.003

Cited by 25 publications

(11 citation statements)

References 55 publications

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“…Also, Gaussian distribution is employed to produce new particles. To produce new particles, Gaussian walk is used based on the following equations [57]:…”

Section: Super-twisting Fractional Order Sliding Mode Controllermentioning

confidence: 99%

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Optimal Model Predictive based on Super-Twisting Fractional Order Sliding Mode Control to Regulate DC-link Voltage of DC Microgrid

Amiri

Farzinfar²,

Sadeghi³

et al. 2022

JER is an international, peer-reviewed journal that publishes f

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This paper aims to essentially regulate the DC-link voltage of DC microgrid during the disturbance conditions in power system. Hence, a novel Optimal Model Predictive Super-Twisting Fractional Order Sliding Mode Control (OMP-STFOSMC) is proposed for three-phase AC-DC converter which can effectively enhance the stability and dynamic performance of microgrid. The conventional model-predictive controllers have severely imposed the dynamic stability which leads to high overshoot, undershoot and settling-time. The sliding mode controller can be replaced instead of these conventional controllers to appropriately triumph over this problem. A main drawback of conventional sliding mode controller is related to its high frequency chattering in the control signal which can affect the system and doesn’t make it satisfactory and feasible for real applications. The proposed OMP-STFOSMC can effectively enhance the control tracking performance and reduce the high frequency chattering problem. The Stochastic Fractal Search (SFS) algorithm due to its high exploration and good evasion of local optima is used to optimally tune the controller parameters. Different operation conditions are considered to evaluate the dynamic and chattering-free performance of proposed controller. As to the simulation results with comparative analysis, it is observed that the proposed OMP-STFOSMC offers better dynamic stability characteristics.

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“…Also, Gaussian distribution is employed to produce new particles. To produce new particles, Gaussian walk is used based on the following equations [57]:…”

Section: Super-twisting Fractional Order Sliding Mode Controllermentioning

confidence: 99%

“…This process includes two statistical items wherein the one impacts each individual and other impacts all particles. On the other hand, all particles have been ranked based on their fitness values and the probability of each particle Xi can be expressed as follows [57]:…”

Section: B Updating Processmentioning

confidence: 99%

Optimal Model Predictive based on Super-Twisting Fractional Order Sliding Mode Control to Regulate DC-link Voltage of DC Microgrid

Amiri

Farzinfar²,

Sadeghi³

et al. 2022

JER is an international, peer-reviewed journal that publishes f

View full text Add to dashboard Cite

show abstract

“…Moreover, this algorithm has shown high performance compared to competitive optimization algorithms in the literature. OTCDE [17] CMSFS [18]…”

Section: Test System 1: Ieee 33-bus Systemmentioning

confidence: 99%

Optimal Placement and Sizing of DGs in Distribution Networks Using Dandelion Optimization Algorithm: Case Study of an Algerian Distribution Network

2022

IJATCSE

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The optimal placement of distributed generation (DG) in power distribution systems involves identifying the best locations for the generators to be installed and sizing them appropriately, to optimize the performance of the system. In this paper, the recently proposed nature-inspired optimization algorithm namely: Dandelion Optimizer (DO) has been used for the optimal placement and sizing of DG in the radial distribution network. The objectives are to minimize active power loss and voltage deviation and to enhance the voltage stability of the distribution network. The efficiency of the proposed method has been verified over the IEEE 33-bus and Algerian 112-bus distribution systems. The result comparisons indicated that the proposed method can obtain higher quality solutions than many other methods for the considered scenarios from the test systems. Therefore, the DO algorithm can be a very effective method for solving the optimal allocation of the DG problem.

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“…The authors in [27] presented a detail comparison of different sensitivity approaches for efficient DG allocation in radial network. Some of the developed sensitivity approaches for DG placement in distribution network that are reported in the literature are power stability index [28], novel Q-PQV bus pair method [29], chaotic maps integrated with stochastic fractal search [30], zero bus flow approach [31], power loss sensitivity (PLS) on GAMS [32], pareto optimality with game theory [33], static and dynamic network reconfiguration [34], combined power loss index [35], node voltage deviation sensitivity [36], probabilistic generation with time-varying load models [37]. All these methods mentioned above are obtained from direct approximation of the voltage stability condition derived from the two-bus transmission line model that has been widely reported in different works on steady-state voltage stability analysis [38].…”

Section: Introductionmentioning

confidence: 99%

Modified Analytical Approach for PV-DGs Integration into a Radial Distribution Network Considering Loss Sensitivity and Voltage Stability

et al. 2021

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Achieving the goals of distribution systems operation often involves taking vital decisions with adequate consideration for several but often contradictory technical and economic criteria. Hence, this paper presents a modified analytical approach for optimal location and sizing of solar PV-based DG units into radial distribution network (RDN) considering strategic combination of important power system planning criteria. The considered criteria are total planning cost, active power loss and voltage stability, under credible distribution network operation constraints. The optimal DG placement approach is derived from the modification of the analytical approach for DG placement using line-loss sensitivity factor and the multiobjective constriction factor-based particle swarm optimization is adopted for optimal sizing. The effectiveness of the proposed procedure is tested on the IEEE 33-bus system modeled using Matlab considering three scenarios. The results are compared with existing reports presented in the literature and the results obtained from the proposed approach shows credible improvement in the RDN steady-state operation performance for line-loss reduction, voltage profile improvement and voltage stability improvement.

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A newly effective method to maximize power loss reduction in distribution networks with highly penetrated distributed generations

Cited by 25 publications

References 55 publications

Optimal Model Predictive based on Super-Twisting Fractional Order Sliding Mode Control to Regulate DC-link Voltage of DC Microgrid

Optimal Model Predictive based on Super-Twisting Fractional Order Sliding Mode Control to Regulate DC-link Voltage of DC Microgrid

Optimal Placement and Sizing of DGs in Distribution Networks Using Dandelion Optimization Algorithm: Case Study of an Algerian Distribution Network

Modified Analytical Approach for PV-DGs Integration into a Radial Distribution Network Considering Loss Sensitivity and Voltage Stability

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