Optimal power dispatch in hybrid power system for medium- and large-scale practical power systems using self-adaptive bonobo optimizer algorithm

Wind Engineering, Journal Year: 2024, Volume and Issue: 48(6), P. 1118 - 1140

Published: May 28, 2024

Incorporating renewable energy sources (RESs) introduces a notable amount of uncertainty in the optimal planning and operation electrical power grids. Under these circumstances, this paper proposes application recently introduced metaheuristic optimization technique to solve stochastic flow (OPF) problem involving wind solar sources. The self-adaptive bonobo optimizer (SaBO) is used minimize three distinct objective functions: (i) Total generation cost (TGC) minimization, including both thermal wind/solar costs, (ii) Power loss (iii) Combined emissions effect minimization. costs associated with included direct reserves penalty from overestimation underestimation available power, respectively. performance proposed algorithm evaluated on two systems: modified IEEE 30-bus Algerian DZA 114-bus test systems. To demonstrate efficacy SaBO, obtained results have been compared those Kepler (KOA) other published optimizers under same case studies constraints. comparative clearly show superiority SaBO over all well-known algorithms provided literature for solving OPF problem. This evidenced by minimizing total 781.2363 $/h 16,706.1630 DZA-114-bus system. Furthermore, integration RES led 2.33% 11.67% reduction systems, respectively, their initial configurations without RESs. promising findings highlight powerful non-linear complex problems

Language: Английский

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Improving power system performance by integrating TCSC and SVC devices in the presence of stochastic renewable energy generators

Wind Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 31, 2025

This paper investigates the application of advanced metaheuristic algorithms Blood-Sucking Leech Optimizer (BSLO), Bonobo (BO), and Electric Eel Foraging Optimization (EEFO) to solve optimal power flow (OPF) problem with stochastic renewable energy generators (REGs), specifically photovoltaic (PVGs) wind (WGs). Two scenarios are examined: Scenario 1 evaluates proposed performance without Flexible AC Transmission Systems (FACTS), focusing on minimizing Total Generation Cost (TGC), Active Power Loss (APL), a combined objective TGC Emissions (TGCE). The including both thermal REG costs, in which cost related PV generation encompasses direct, reserve, penalty costs due overestimation underestimation available power. 2 introduces Thyristor-Controlled Series Capacitor (TCSC) Static Var Compensator (SVC) evaluate their impact three functions. is evaluated modified IEEE 30-bus system. results show that BSLO algorithm consistently achieves best TGC, APL, TGCE values at 781.1209 $/h, 1.9960 MW, 810.7376 respectively. These outcomes highlight its effectiveness competitive first scenario. integration FACTS devices second scenario 6.73% reduction APL insertion TCSC, 1.86% SVC, 6.10% TCSC compared value case (1.9960 MW). study comprehensively analyzes how different optimization techniques enhance system integration.

Language: Английский

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Optimizing power network expansion with pumped hydro energy storage using a multi-objective enhanced spider wasp optimizer approach

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 18, 2025

Integrating energy storage systems, particularly pumped hydro (PHES), is crucial for enhancing grid reliability and ensuring a balanced supply demand. This study explores the impact of PHES integration on power network expansion planning (PNEP). Four technologies are analyzed, including those proposed by Electric Power Research Institute (EPRI), Energy Information Administration (EIA), Bonneville (BPA), Swan Lake case, to assess their economic strategies. The analysis incorporates planned infrastructure components such as renewable sources, transmission lines Thyristor-controlled series compensators. problem framed comprehensive multi-objective optimization model designed minimize cost while maximizing benefits integrating various technologies. Enhanced Spider Wasp Optimizer (ESWO) suggested solution this challenge. ESWO employs variable reduction technique simplify complexity improve performance. Simulations conducted Garver IEEE 24-bus system indicate that BPA technology significantly facilitates expansion. In network, case achieves ranging from 1.23 24.84% compared other For system, BPA's 3.37% EPRI 5.56% EIA. results also highlight algorithm's efficiency in managing complexities PNEP with integrated considerations.

Language: Английский

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Enhancing power system stability by coordinating a wind turbine voltage regulator and lead-lag power system stabilizer using GOOSE optimization

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 30, 2025

Integrating wind energy into power systems can negatively impact stability by reducing oscillation damping. Wind Turbine Voltage Regulators (WT VRs) are designed to manage reactive and maintain voltage stability; however, they often do not coordinate effectively with Power System Stabilizers (PSS) from synchronous generators (SG). This study utilizes the GOOSE Optimization Algorithm (GOA) optimize gains of WT proportional-integral virtual regulator PI-VR) SG proportional-integral-type lead-lag PSS (PI-type LL-PSS), enhance system performance. The GOA performance compared Osprey (OOA) Particle Swarm Optimizer (PSO). PI-type LL-PSS is proportional-integral-derivative PID-PSS configurations, highlighting its robustness. Testing scenarios include step changes, sags, three-phase short-circuit faults, using metrics like integral time absolute error, settling time, standard deviation for robustness evaluation. Statistical analysis shows several benefits proposed methodology: (i) A 48.85% improvement in coordinating PI-VR versus OOA, (ii) 24.40% boost over OOA LL-PSS, (iii) 14.4% enhancement when PID-PSS, (iv) 34.23% increase instead PSO LL-PSS.

Language: Английский

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Optimizing Economic Dispatch with Renewable Energy and Natural Gas Using Fractional-Order Fish Migration Algorithm

Fractal and Fractional, Journal Year: 2024, Volume and Issue: 8(6), P. 350 - 350

Published: June 12, 2024

This work presents a model for solving the Economic-Environmental Dispatch (EED) challenge, which addresses integration of thermal, renewable energy schemes, and natural gas (NG) units, that consider both toxin emission fuel costs as its primary objectives. Three cases are examined using IEEE 30-bus system, where thermal units (TUs) replaced with NGs to minimize emissions costs. The system constraints include equality inequality conditions. A detailed modeling is performed, also incorporates pressure pipelines flow velocity procedure limitations. To obtain Pareto optimal solutions emissions, three optimization algorithms, namely Fractional-Order Fish Migration Optimization (FOFMO), Coati Algorithm (COA), Non-Dominated Sorting Genetic (NSGA-II) employed. investigated validate effectiveness proposed when applied sources (RESs) units. results from Case III, installed in place two (TUs), demonstrate economic dispatching approach presented this study significantly reduces levels 0.4232 t/h achieves lower cost 796.478 USD/MWh. Furthermore, findings indicate FOFMO outperforms COA NSGA-II effectively addressing EED problem.

Language: Английский

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Yenilenebilir Enerji Kaynaklarını İçeren Optimal Güç Akışı İçin Uygunluk Mesafe Dengesi Tabanlı Üçgenleme Topolojisi Toplama İyileştiricisi

Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, Journal Year: 2024, Volume and Issue: 28(2), P. 221 - 234

Published: Aug. 7, 2024

Günümüzde talep edilen ve tüketilen enerji miktarında çok yoğun artışların olması ile birlikte, yenilenebilir kaynaklarından üretiminde artışlar olmaktadır. Bir elektrik şebekesinde kaynaklarının dahil edilerek kullanılması birlikte ağın ekonomik verimli çalışabilmesi için en uygun şeklide planlanması problemini de ortaya çıkarmaktadır. Bu tez çalışmasında, olan rüzgâr gücü entegreli güç sistemleri problemlerinden optimal akışı problemi ele alınmıştır. Optimal doğrusal olmayan yapıya çeşitli kısıtlamalara sahip olan, kontrol parametrelerin değerlerinin belirlendiği bir optimizasyon problemidir. Ayrıca, güneş rüzgar enerjisinin doğasını birleştirmek problemin karmaşıklığını artırmaktadır. tür problemlerin çözümünde yapay zeka tekniklerinden sezgisel arama algoritmaları tercih edilmektedir. çalışmasında probleminin çözümü Üçgenleme topolojisi toplama iyileştiricisi (ÜTTİ) algoritmasının öncelikle mesafe uygunluk dengesi tabanlı geliştirilmesi gerçekleştirilmiştir. Geliştirilen algoritma edildiği probleminde uygulanmış olup, literatürdeki farklı algoritmaların sonuçları karşılaştırılmıştır. Elde edile sonuçlar, önerilen algoritmanın bu sistemi etkili olduğunu açık şekilde göstermektedir.

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Transient voltage problem analysis of multi-level transmission cross section limit coupling characteristics based on cluster analysis

Published: May 17, 2024

Language: Английский

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Optimizing power management for wind energy integration with SVC support using hybrid optimization

Electrical Engineering, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 18, 2024

Language: Английский

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Exploring Evolutionary Algorithms for Optimal Power Flow: A Comprehensive Review and Analysis

Electricity, Journal Year: 2024, Volume and Issue: 5(4), P. 712 - 733

Published: Oct. 3, 2024

It has been more than five decades since optimum power flow (OPF) emerged as one of the most famous and frequently used nonlinear optimization problems in systems. Despite its long-standing existence, OPF problem continues to be widely researched due critical role electrical network planning operations. The general formulation is complex, representing a large-scale model with nonconvex characteristics, incorporating both discrete continuous control variables. inclusion factors such transformer taps shunt capacitors, integration renewable energy sources like wind further complicates system’s design solution. To address these challenges, variety classical, evolutionary, improved techniques have developed. These not only provide new solution pathways but also enhance quality existing solutions, contributing reductions computational cost operational efficiency. Multi-objective approaches are employed modern balance trade-offs between competing objectives minimization, loss reduction, environmental impact. This article presents an in-depth review various wide array algorithms, traditional applied solve problems, paying special attention multi-objective strategies.

Language: Английский

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Hyper-FDB-INFO Algorithm for Optimal Placement and Sizing of FACTS Devices in Wind Power-Integrated Optimal Power Flow Problem

Energies, Journal Year: 2024, Volume and Issue: 17(23), P. 6087 - 6087

Published: Dec. 3, 2024

In this study, firstly, the balance between exploration and exploitation capabilities of weighted mean vectors (INFO) algorithm was developed using fitness–distance (FDB) method. Then, FDB-INFO with a hyper-heuristic method to create beginning optimal population by Linear Population Reduction Success History-based Adaptive Differential Evolution (LSHADE) novel Hyper-FDB-INFO presented. Finally, applied solve placement sizing FACTS devices for power flow (OPF) problem incorporating wind energy sources. Moreover, determining is an additional minimize total cost generation reducing losses system. The experimental results showed that more effective solver than SHADE-SF, INFO, Hyper-INFO algorithms integrating OPF problem.

Language: Английский

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