Optimal sizing and allocation of DGs for real power loss reduction and voltage profile improvement in radial L.V networks

Al-Maghalseh, Maher; Odeh, Sari; Saleh, Aws

doi:10.1109/honet.2017.8102213

Cited by 8 publications

(8 citation statements)

References 10 publications

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“…In general, during the last decades, the annual growth rate of distributed generation based on solar photovoltaic increased higher than 40% [2]. Many studies have shown that the received benefits will depend on the site and rated power of distributed generation units (DGUs) in general and PVDGUs in particular [2][3][4][5][6]. Proper installation of DGUs can reduce total power losses and improve voltage profile and power quality [7,8].…”

Section: Importance Of Solar Photovoltaic For Distribution Powermentioning

confidence: 99%

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Improved Coyote Optimization Algorithm for Optimally Installing Solar Photovoltaic Distribution Generation Units in Radial Distribution Power Systems

Nguyen

Pham²,

Kien

et al. 2020

Complexity

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This paper proposes an improved coyote optimization algorithm (ICOA) for optimizing the location and sizing of solar photovoltaic distribution generation units (PVDGUs) in radial distribution systems. In the considered problem, four single objectives consisting of total power losses, capacity of all PVDGUs, voltage profile index, and harmonic distortions are minimized independently while satisfying branch current limits, voltage limits, and harmonic distortion limits exactly and simultaneously. The performance of the proposed ICOA method has been improved significantly since two improvements were carried out on the two new solution generations of the conventional coyote optimization algorithm (COA). By finding four single objectives from two IEEE distribution power systems with 33 buses and 69 buses, the impact of each proposed improvement and two proposed improvements on the real performance of ICOA has been investigated. ICOA was superior to COA in terms of capability of finding higher quality solutions, more stable search ability, and faster convergence speed. Furthermore, we have also applied five other metaheuristic algorithms consisting of biogeography-based optimization (BBO), genetic algorithm (GA), particle swarm optimization algorithm (PSO), sunflower optimization (SFO), and salp swarm algorithm (SSA) for dealing with the same problem and evaluating further performance of ICOA. The result comparisons have also indicated the outstanding performance of ICOA because it could find much better results than these methods, especially SFO, SSA, and GA. Consequently, the proposed ICOA is a very effective method for finding the optimal location and capacity of PVDGUs in radial distribution power systems.

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Section: Importance Of Solar Photovoltaic For Distribution Powermentioning

confidence: 99%

“…Parameters such as impedance represented the characteristics of the lines and are not affected by over temperature. (5) Loads: this includes nonlinear loads and linear loads.…”

Section: Assumptionmentioning

confidence: 99%

Improved Coyote Optimization Algorithm for Optimally Installing Solar Photovoltaic Distribution Generation Units in Radial Distribution Power Systems

Nguyen

Pham²,

Kien

et al. 2020

Complexity

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“…Required Capacity 7.75 * 1. 2 (20) The schematic diagram for the grid connected system design is shown in Figure 6. It exhibits 15 panels connected at input A of the inverter, and 14 panels connected at input B.…”

Section: Grid Connected System Designmentioning

confidence: 99%

“…[1]. This paper is an extension of work previously presented in 2017 [2]. This paper presents a thorough technical and economic analysis of standalone and grid connected photovoltaic (PV) systems.…”

Section: Introductionmentioning

confidence: 99%

The Impacts of Distribution Generators’ Size and Location on Power Efficiency and Voltage Profile in Radial LV Networks

Al-Maghalseh¹

2018

Adv. sci. technol. eng. syst. j.

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This paper presents analytical methods for optimum allocation of distribution generators in a radial distribution network. The aim is to increase power efficiency and reduce loss of power. The ideal size of each distribution generator unit at the identified locations has been carefully selected by making adjustments to loss saving equations and the voltage on a radial feeder. The experimental system is located in the governorate of Bethlehem specifically within the district served by the Jerusalem Distribution Electricity Company (JDECO). The NEPLAN simulator has been utilized in the verification process of the aforementioned experimental system. It entails of several nodes and 400 V-buses that feed up to five household loads. The size and location of each has been carefully chosen. Consequently, significant loss saving, and voltage profile improvement have been reported. Hence, the use of Renewable Distribution Generators (DGs) systems is highly desirable for various reasons including increased system reliability, decreased loss of power, and enhanced voltage profile. Notably, cutting back on the use of conventional fuel will in turn reduce the negative environmental impacts.

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“…Kazem [12] presented an economic analysis and optimum design for PV standalone pumping system for rural areas in Oman. Maghalseh [13] studied the optimum sizing and location for the PV systems to improve the voltage profile and reduce losses in the grid. A considerable amount of literature has been published on PV grid connected and standalone systems [2,[14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Generation unit sizing, economic analysis of grid connected and standalone PV power plant

Al-Maghalseh

2019

International Journal of Energy Applications and Technologies

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This paper presents a design for a grid connected PV system with the capacity of 1.5 MVA, as well as a standalone PV system with the capacity of 50 kVA in the West Bank industrial zone, Palestine. The factors affecting the design and size of the system are also presented and evaluated. To ensure adequate, reliable and economical system design, over and under sizing energy has been avoided. Furthermore, a numerical analysis will be carried out to evaluate the effects of the grid-connected system on the network, with respect to the voltage profile, power flow, and energy losses. The results have shown a good enhancement in the total energy losses and voltage profile in reference to load and generation capacity. However, the voltage profile is enhanced on buses located close to the proposed PV plant while the profile enhancements decrease when moving closer to the source buses. The maximum increase in voltage profile is 0.4% which is satisfactory in our case. Furthermore, the power losses were clearly decreased with installed of PV systems. Finally, an economic analysis for both systems will be presented. It was found that the total income of the project is expected to be around $616,923 per year. Further, the payback period is expected to be .5 years and the Net Present Value (NPV) is about $3,885,125.91. The Internal Rate of Return (IRR) for the project during a 20-year lifespan is about 26%.

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Optimal sizing and allocation of DGs for real power loss reduction and voltage profile improvement in radial L.V networks

Cited by 8 publications

References 10 publications

Improved Coyote Optimization Algorithm for Optimally Installing Solar Photovoltaic Distribution Generation Units in Radial Distribution Power Systems

Improved Coyote Optimization Algorithm for Optimally Installing Solar Photovoltaic Distribution Generation Units in Radial Distribution Power Systems

The Impacts of Distribution Generators’ Size and Location on Power Efficiency and Voltage Profile in Radial LV Networks

Generation unit sizing, economic analysis of grid connected and standalone PV power plant

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