Find optimal capacity and location of distributed generation units in radial distribution networks by using enhanced coyote optimization algorithm

Pham, Thai Dinh; Nguyen, Thang Trung; Dinh, Bach Hoang

doi:10.1007/s00521-020-05239-1

Cited by 45 publications

(32 citation statements)

References 44 publications

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“…Normally, a distribution line connecting Bus a and Bus b as shown in Figure 2 has three conductors with the same impedance and loads of phase A, phase B, and phase C at the receiving Bus b. Te three series impedances are represented as Z ab A , Z ab B and Z ab C in which each impedance has two parts, resistance and reactance shown in equation (1). Similarly, the load of phases is represented as S b A , S b B , S b C at Bus b, and mathematically formulated in equation (2).…”

Section: Unbalanced Distribution Systemsmentioning

confidence: 99%

“…Because of that, many countries have invested signifcantly in research to integrate DGUs into the electricity distribution systems to gain benefts like fexibility, reliability, environmental friendliness, economic benefts, etc [1]. Numerous studies have shown that selecting and connecting the suitable DGUs to the distribution system can achieve positive results such as reduced power losses, enhanced voltage profle, improved power quality, reduced fuel cost, and increased reliability and security of the system [2]. However, to maximize benefts, the determination of position and capacity for DGUs must be taken seriously [3].…”

Section: Introductionmentioning

confidence: 99%

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Optimal Placement of Photovoltaic Distributed Generation Units in Radial Unbalanced Distribution Systems Using MATLAB and OpenDSS-Based Cosimulation and a Proposed Metaheuristic Algorithm

Pham

Nguyen

Kien

2022

International Transactions on Electrical Energy Systems

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In this paper, an improved slime mould algorithm (ISMA) is proposed for finding the optimal location and sizing of photovoltaic distributed generation units (PVDGUs) in unbalanced distribution systems (UDSs). The proposed method is developed by changing the control variable update mechanism of the original slime mould algorithm (SMA). Total power losses on distribution lines and voltage deviation index of all buses are minimized under the consideration of various constraints. The location and sizing of PVDGUs found by ISMA are added into the cosimulation between MATLAB and OpenDSS for reaching other remaining parameters of UDSs. In addition, sunflower optimization (SFO), social-ski drive (SSD), cuckoo search algorithm (CSA), salp swarm algorithm (SSA), bonobo optimizer (BO), and SMA are also run for finding PVDGUs placement solution on the unbalanced three-phase IEEE 123-bus test feeder. As a result, the proposed ISMA can reduce the power loss up to 78.88% and cut the voltage deviation up to 1.4779 pu while that of others is from 69.10% to 78.87% and from 1.5759 to 1.4996 pu. Thus, ISMA should be used to place PVDGUs in UDSs meanwhile the cosimulation between MATLAB and OpenDSS should be applied as a power flow calculation tool for UDSs.

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Section: Unbalanced Distribution Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Placement of Photovoltaic Distributed Generation Units in Radial Unbalanced Distribution Systems Using MATLAB and OpenDSS-Based Cosimulation and a Proposed Metaheuristic Algorithm

Pham

Nguyen

Kien

2022

International Transactions on Electrical Energy Systems

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“…However, the real performance of COA for engineering problems such ass ORPD has not been demonstrated persuasively, since there has been no application so far. However, COA has not achieved good results for other problems in engineering, and it has been suggested to be modified [57][58][59]. For the cases of solving benchmark functions, many functions have real optimal solutions with zero values, and construction of COA has produced solutions around the real ones.…”

Section: Contributions and Paper Organizationmentioning

confidence: 99%

Optimal Reactive Power Generation for Transmission Power Systems Considering Discrete Values of Capacitors and Tap Changers

Kien¹,

Hien²,

Nguyen³

2021

Applied Sciences

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In this paper, an improved coyote optimization algorithm (ICOA) is developed for determining control parameters of transmission power networks to deal with an optimal reactive power dispatch (ORPD) problem. The performance of ICOA method is superior to its conventional coyote optimization algorithm (COA) thanks to modifications of two new solution generations of COA. COA uses a center solution to generate an update step size in the first solution generation and produced one new solution by using random factors to diversify the search space in the second solution generation. By tackling the drawbacks of COA, ICOA can reduce control parameters and computation steps, shorten execution time, and provide better results. ICOA is compared to its conventional COA for three standard IEEE systems of 30-, 57-, and 118-buses with continuous and discrete control variables. Moreover, three other algorithms such as water cycle algorithm (WCA), salp swarm algorithm (SSA), and sunflower optimization algorithm (SFOA) have been also implemented for further investigation of the real performance of the proposed method. All the applied methods are metaheuristic algorithms based on population and randomization. The result comparison from the test systems has indicated that ICOA can provide higher solution quality than other methods with reasonable execution time. Therefore, ICOA is a reliable tool for finding optimal solutions of the ORPD problem.

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“…Coyote optimization algorithm (COA) [30] is proposed for optimal integration of DGs in RDNs considering multi-objective function, formed using real power loss, operating cost and voltage stability. In [31], an improved variant of COA as enhanced coyote optimization algorithm (ECOA) is proposed for solving simultaneous optimal network reconfiguration and DG allocation problem. In [32], harmony search algorithm (HSA) is pursued for solving simultaneous optimal network reconfiguration and DG allocation problem in unbalanced RDNs.…”

Section: Introductionmentioning

confidence: 99%

Future search algorithm for optimal integration of distributed generation and electric vehicle fleets in radial distribution networks considering techno-environmental aspects

Janamala

Kumar²,

Pandraju³

2021

SN Appl. Sci.

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In this paper, a new nature-inspire meta-heuristic algorithm called future search algorithm (FSA) is proposed for the first time to solve the simultaneous optimal allocation of distribution generation (DG) and electric vehicle (EV) fleets considering techno-environmental aspects in the operation and control of radial distribution networks (RDN). By imitating the human behavior in getting fruitful life, the FSA starts arbitrary search, discovers neighborhood best people in different nations and looks at worldwide best individuals to arrive at an ideal solution. A techno-environmental multi-objective function is formulated using real power loss, voltage stability index. The active and reactive power compensation limits and different operational constraints of RDN are considered while minimizing the proposed objective function. Post optimization, the impact of DGs on conventional energy sources is analyzed by evaluating their greenhouse gas emission. The effectiveness of the proposed methodology is presented using different case studies on Indian practical 106-bus agriculture feeder for DGs and 36-bus rural residential feeder for simultaneous allocation of DGs and EV fleets. Also, the superiority of FSA in terms of global optima, convergence characteristics is compared with various other recent heuristic algorithms.

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Find optimal capacity and location of distributed generation units in radial distribution networks by using enhanced coyote optimization algorithm

Cited by 45 publications

References 44 publications

Optimal Placement of Photovoltaic Distributed Generation Units in Radial Unbalanced Distribution Systems Using MATLAB and OpenDSS-Based Cosimulation and a Proposed Metaheuristic Algorithm

Optimal Placement of Photovoltaic Distributed Generation Units in Radial Unbalanced Distribution Systems Using MATLAB and OpenDSS-Based Cosimulation and a Proposed Metaheuristic Algorithm

Optimal Reactive Power Generation for Transmission Power Systems Considering Discrete Values of Capacitors and Tap Changers

Future search algorithm for optimal integration of distributed generation and electric vehicle fleets in radial distribution networks considering techno-environmental aspects

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