Optimal Allocation of Renewable Energy Resources Considering Uncertainty in Load Demand and Generation

Ramadan, Ashraf; Ebeed, Mohamed; Kamel, Salah; Nasrat, Loai

doi:10.1109/cpere45374.2019.8980092

Cited by 19 publications

(22 citation statements)

References 9 publications

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“…In another article [33], a hybrid approach called Harmony Search Algorithm (HSA) and the Particle Artificial Bee Colony algorithm (PABC) has been used to determine the optimal siting and sizing of DG and SC. In [34], authors consider the uncertainties of the system and proposed lightning attachment procedure optimization (LAPO) for finding the best placement of renewable energy resources (wind and solar PV units) in the radial distribution network (RDN). Authors in [35] developed a new hybrid optimization approach based on Artificial Bee Colony (ABC) and Artificial Immune System (AIS) to find the optimal sitting and sizing of DG and SC.…”

Section: B Literature Reviewmentioning

confidence: 99%

“…• The 3 rd scenario is investigated in this study to find the optimal placement and capacity of 2DG and 2SC in the three test systems under uncertainty of load condition according to the load uncertainty considering normal probability density function (PDF) as given [34] in represented in Eq (15). For the studied cases, the power flow computations are performed using the Forward-Backwards Sweep Algorithm (FBSA) [37].…”

Section: B Studied Scenariosmentioning

confidence: 99%

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A Hybrid Local Search-Genetic Algorithm for Simultaneous Placement of DG Units and Shunt Capacitors in Radial Distribution Systems

et al. 2020

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Controlling active/reactive power in distribution systems has a great impact on its performance. The placement of distributed generators (DGs) and shunt capacitors (SCs) are the most popular mechanisms to improve the distribution system performance. In this line, this paper proposes an enhanced genetic algorithm (EGA) that combines the merits of genetic algorithm and local search to find the optimal placement and capacity of the simultaneous allocation of DGs/SCs in the radial systems. Incorporating local search scheme enhances the search space capability and increases the exploration rate for finding the global solution. The proposed procedure aims at minimizing both total real power losses and the total voltage deviation in order to enhance the distribution system performance. To prove the proposed algorithm ability and scalability, three standard test systems, IEEE 33 bus, 69 bus, and 119-bus test distribution networks, are considered. The simulation results show that the proposed EGA can efficiently search for the optimal solutions of the problem and outperforms the other existing algorithms in the literature. Moreover, an economic based cost analysis is provided for light, shoulder and heavy loading levels. It was proven, the proposed EGA leads to significant improvements in the technical and economic points of view.

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Section: B Literature Reviewmentioning

confidence: 99%

Section: B Studied Scenariosmentioning

confidence: 99%

A Hybrid Local Search-Genetic Algorithm for Simultaneous Placement of DG Units and Shunt Capacitors in Radial Distribution Systems

et al. 2020

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“…The ORPD on PCC is considered to minimize the power losses in a windfarm. A lightning attachment procedure optimization was introduced by Ramadan [28]. The paper explained the uncertainty of the wind speed and the solar irradiance which are modeled using Weibull PDF and Lognormal PDF to reduce the power losses of IEEE30 standard at different 25 scenarios.…”

Section: Introductionmentioning

confidence: 99%

“…• ORPD without RERs is simply solved by FPSOGSA algorithm and the uncertainty of solar irradiance, wind speed and load demand at different scenarios is not considered. • ORPD containing uncertainties of RERs was not tested based on IEEE30 standards with 13 control variables [26,28]. • The voltage stability index was not discussed in [26,28] for the scenario-based approach.…”

Section: Introductionmentioning

confidence: 99%

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Fractional PSOGSA Algorithm Approach to Solve Optimal Reactive Power Dispatch Problems With Uncertainty of Renewable Energy Resources

et al. 2020

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The optimal reactive power dispatch (ORPD) is a major tool, and it plays a vital role for enhancement of the power system performance. ORPD is one multimodal, non-convex, and non-linear problem. Many elegant benefits can be obtained by using the renewable energy resources (RERs), but many technical issues related to the RERs including the stochastic characteristics of these resources due to continuous variations of solar irradiance and the wind speed lead to increasing the uncertainties of system. Thus, solving the ORPD problem with RERs is a crucial task. The contribution of the paper includes application a modified hybrid algorithm for solving the ORPD considering the uncertainties of the RERs and the load demand. The proposed algorithm is based on Fractional Calculus with Particle Swarm Optimization Gravitational Search Algorithm (FPSOGSA) which aims to enhance the searching capabilities of the conventional PSOGSA algorithm and overcome its tendency to stagnation. The proposed algorithm is tested on IEEE 30-bus system for reducing power losses and voltage deviation as well as enhancing voltage stability. The scenario-based method is employed to produce a set of scenarios from the uncertainties of load, wind speed and solar irradiance. The simulation results verify the effectiveness of the proposed algorithm for solving the ORPD problem with and without considering the uncertainties in the system. Furthermore, the proposed algorithm is superior compared with the state-of-the-art techniques in terms of the reduction of power losses and voltage deviations as well as the stability enhancement.

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Dynamic fuzzy learning based hybrid GWO-CSA for optimal planning of PV, BESS and DSTATCOM with network reconfiguration

Sujatha,

Usha,

Geetha

2024

Discov Appl Sci

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The proposed approach is on the optimal planning issue of photovoltaic distributed generation (PV-DG) and DSTATCOM device with integrated battery energy storage systems (BESS) considering network reconfiguration by applying hybrid Grey-Wolf crow-search algorithm (GWO-CSA) encompassing dynamic fuzzy learning (DFL) optimization technique. Considering the stochastic nature of solar irradiance and variations, when solar energy is inadequate, BESS acts as backup energy storage device to meet essential load requirements. Network reconfiguration is to reduce power loss by changing the network tie switches using optimization algorithm. The principal objective of the proposed research work is to reduce the total power loss, enhance the voltage profile, improve the voltage stability index, and perform network reliability analysis. The beneficial effect of the proposed method is validated on Standard IEEE 69 and Standard 118 bus systems. It found that for the IEEE 69 bus system, the overall Real power loss values decreased to 12.82% and overall Reactive power loss increased to 78.18%. The total voltage deviation index (TTVDI), and total voltage stability index (TTVSI) values decreased to 17.94% and − 0.75% respectively. The reliability indices like SAIDI, SAIFI, CAIDI, CAIFI, and AENS values decreased by 56%, 3.54%, − 3.09%, 0.55% and 30% respectively. Similarly, for IEEE 118 bus system overall Real power loss, overall Reactive power loss, TTVDI, and TTVSI decreased to 9.53%, − 0.11%, 24.64%, and 3.87%. The reliability indices like SAIDI, SAIFI, CAIDI, CAIFI, and AENS values decreased by 2.4%, 1.0%, 1.54%, 0.94%, and 10.1% respectively. Further, the proposed approach of DFL-based hybrid GWO-CSA considers the reconfiguration with PV-DG, DSTATCOM and BESS enhances the overall performance compared to other scenarios.

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Optimal Allocation of Renewable Energy Resources Considering Uncertainty in Load Demand and Generation

Cited by 19 publications

References 9 publications

A Hybrid Local Search-Genetic Algorithm for Simultaneous Placement of DG Units and Shunt Capacitors in Radial Distribution Systems

A Hybrid Local Search-Genetic Algorithm for Simultaneous Placement of DG Units and Shunt Capacitors in Radial Distribution Systems

Fractional PSOGSA Algorithm Approach to Solve Optimal Reactive Power Dispatch Problems With Uncertainty of Renewable Energy Resources

Dynamic fuzzy learning based hybrid GWO-CSA for optimal planning of PV, BESS and DSTATCOM with network reconfiguration

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