Optimal integration of multi-type DG in RDS based on novel voltage stability index with future load growth

Parihar, Shradha Singh; Malik, Nitin

doi:10.1007/s12530-020-09356-z

Cited by 12 publications

(5 citation statements)

References 39 publications

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“…32 Additionally, this approach has been introduced for determining the ideal location and size of renewable energy sources. 33 In the study conducted by, 34 the goal function of minimizing power loss was used to determine the optimal DG in a RDS using GA. However, the analysis primarily focused on reducing power loss, without considering additional goals such as voltage level enhancement or system stability.…”

Section: List Of Abbreviationsmentioning

confidence: 99%

Using Arithmetic Optimization Algorithm to Allocate and Size Wind Energy Systems in RDSs

Mosaad

2024

Yanbu Journal of Engineering and Science

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Recent years have seen a marked increase in the world’s energy needs. Numerous studies have been conducted to examine distributed generation (D.G.) utilizing renewable energy sources (R.E.S.s) in order to address this need. The number of environmental problems that are resolved by the usage of traditional power plants is also decreased by these renewable sources. The ideal position and size of the RESs-DG significantly influence the bus voltage profile, power quality, and efficiency of Radial Distribution Systems (RDS) because of power losses. In this study, the use of wind energy systems as a DG source in RDS is investigated. One of the most common RESs used as DG sources, the ideal location and size for wind system, was chosen to demonstrate this enquiry. The goal of this optimization work, which used the Arithmetic Optimization Algorithm (AOA), was to increase system efficiency by minimizing power losses and improving the voltage profile and power quality. Three widely used RDS, including the IEEE 31 and 69 bus systems, have been used to evaluate how well the recommended technique has been implemented. Genetic Algorithm (GA) is offered to examine the efficacy of the recommended AOA. The findings show that the used AOA approach can pinpoint the appropriate size and positioning of a wind farm in order to reduce power loss, enhance voltage profile, and outperform other existing tactics with superiority over GA.

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Section: List Of Abbreviationsmentioning

confidence: 99%

Using Arithmetic Optimization Algorithm to Allocate and Size Wind Energy Systems in RDSs

Mosaad

2024

Yanbu Journal of Engineering and Science

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“…5 Comparison of bus voltages in presence of single and multiple Type IV DGs penetrations P+jQ indicates the system's nominal loading. The impact of system loading on the magnitude of bus voltage with optimally placed DG (at bus 6) is evaluated by incrementing load gradually at all the buses as mentioned in Table 6 [11]. At critical loading, the voltage at bus 6 got reduced from 0.9496 p.u.…”

Section: Effect Of Type IV Dg On System Voltage Profilementioning

confidence: 99%

“…Many meta-heuristics approaches such as ant lion optimization algorithm [9] and non-dominated sorting genetic algorithm-II [10] have been utilized to solve DG installation issues. A new voltage stability index has been developed for optimal integration of various types of DGs using analytical and particle swarm optimization (PSO) approach to analyse system performance [11].…”

Section: Introductionmentioning

confidence: 99%

Optimal allocation of multiple DGS in RDS using PSO and its impact on system reliability

Parihar

Malik

2021

FACTA U EE

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This article presents the distributed generator (DG) integration in a radial distribution system (RDS). The DG penetration changes the single power source to multiple power sources and bidirectional load flow which enhances the system reliability and reduces system power losses. The particle swarm optimization and gravitational search algorithm are implemented for the optimal siting and sizing of one and three DG units in the RDS to examine its impact on system reliability and loss reduction. The types of DGs considered are Type I (injects real power) and Type IV (injects reactive and real power). The constant power is the chosen load model. The reliability indices taken for the analysis of system reliability are Average Energy Not Supplied, Total Energy Not Supplied and Average System Interruption Duration Index. The efficacy of the proposed method is validated on 33-bus in the presence of single and multiple DGs. The significant decrease in system power losses with the upgraded bus voltage profile, system reliability and remarkable annual loss saving is analyzed for Type IV DG over Type I DG. The results determined are compared to other meta-heuristic approaches as well as analytical techniques to demonstrate the superiority of the proposed methodology. The results are also statistically verified.

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“…Nowadays, the load flow method 1 has been consolidated as a standard tool for the operational, planning, and reliability assessments of power distribution networks. [2][3][4] A large number of papers are available in the literature, either with a theoretical nature that focuses on the generalization and improvement of the numerical method or with a strong application-oriented nature. [5][6][7][8][9] Load flow analysis allows computing the sinusoidal steady-state response of a power network by suitably recasting the constitutive relations of the different involved elements, like transmission lines and loads, in the phasor domain, yielding a set of nonlinear algebraic equations that can be solved by an iterative algorithm.…”

Section: Introductionmentioning

confidence: 99%

“…Nowadays, the load flow method 1 has been consolidated as a standard tool for the operational, planning, and reliability assessments of power distribution networks 2–4 . A large number of papers are available in the literature, either with a theoretical nature that focuses on the generalization and improvement of the numerical method or with a strong application‐oriented nature 5–9 …”

Section: Introductionmentioning

confidence: 99%

SPICE‐compliant load flow analysis of power distribution networks with behavioral loads

Manfredi,

Trinchero,

Memon

et al. 2023

Circuit Theory & Apps

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This paper discusses an alternative and Simulation Program with Integrated Circuit Emphasis (SPICE)‐compatible solution for the steady‐state simulation of power distribution networks. It introduces two alternative auxiliary subcircuits that allow to efficiently simulate the network in any simulation tool for circuit analysis. This feature introduces remarkable benefits in terms of simplicity and generality, since it avoids the need for any iterative method, thus bridging the gap between classical industry‐standard and general‐purpose simulators based on circuital equations, such as SPICE, and dedicated tools for the load flow analysis of power systems. The approach is first demonstrated based on a simple illustrative example, for which the performance in terms of accuracy and efficiency is discussed and then applied to the standard IEEE 33‐node power distribution benchmark.

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Optimal integration of multi-type DG in RDS based on novel voltage stability index with future load growth

Cited by 12 publications

References 39 publications

Using Arithmetic Optimization Algorithm to Allocate and Size Wind Energy Systems in RDSs

Using Arithmetic Optimization Algorithm to Allocate and Size Wind Energy Systems in RDSs

Optimal allocation of multiple DGS in RDS using PSO and its impact on system reliability

SPICE‐compliant load flow analysis of power distribution networks with behavioral loads

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