考虑不确定性的住宅微电网光-风混合系统的技术经济设计

IF 4.3 3区工程技术 Q2 ENERGY & FUELS

International Journal of Energy Research Pub Date : 2025-07-21 DOI:10.1155/er/5413946

Mehrdad Ahmadi Kamarposhti, Hassan Shokouhandeh, Rachid Outbib, Ilhami Colak, El Manaa Barhoumi

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引用次数: 0

摘要

本文提出了一个基于概率成本的并网光伏-风能混合系统设计模型，利用概率密度函数（pdf）和蒙特卡罗模拟（MCS）来解决可再生能源发电和负荷需求的不确定性。所提出的基于场景的方法具有创新的目标函数，结合加权场景成本，允许通过不供电（ENS）惩罚来控制负载减少，同时通过断电概率（LPSP）约束来增强系统可靠性。为了优化，我们开发了一种动态参数秃鹰搜索（DP-BES）算法，通过MATLAB仿真证明了其优于鲸鱼优化算法（WOA），粒子群优化（PSO）和灰狼优化（GWO）方法的性能，与独立PV（33%）或风能（25%）系统相比，混合PV - wind配置实现了最大的成本降低（41%）。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Techno-Economic Design of a Hybrid Photovoltaic–Wind System for a Residential Microgrid Considering Uncertainties Using Dynamic Parameters Bald Eagle Algorithm

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Techno-Economic Design of a Hybrid Photovoltaic–Wind System for a Residential Microgrid Considering Uncertainties Using Dynamic Parameters Bald Eagle Algorithm

This paper presents a probabilistic cost-based model for grid-connected photovoltaic (PV)–wind hybrid system design, employing probability density functions (PDFs) and Monte Carlo simulation (MCS) to address renewable generation and load demand uncertainties. The proposed scenario-based approach features an innovative objective function incorporating weighted scenario costs, allowing controlled load shedding through energy not supplied (ENS) penalties while enforcing system reliability via a loss of power supply probability (LPSP) constraint. For optimization, we develop a dynamic parameter bald eagle search (DP-BES) algorithm, demonstrating through MATLAB simulations its superior performance over Whale Optimization Algorithm (WOA), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO) methods, with the hybrid PV–wind configuration achieving maximum cost reduction (41%) compared to standalone PV (33%) or wind (25%) systems.

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来源期刊

International Journal of Energy Research 工程技术-核科学技术

CiteScore

9.80

自引率

8.70%

发文量

1170

审稿时长

3.1 months

期刊介绍： The International Journal of Energy Research (IJER) is dedicated to providing a multidisciplinary, unique platform for researchers, scientists, engineers, technology developers, planners, and policy makers to present their research results and findings in a compelling manner on novel energy systems and applications. IJER covers the entire spectrum of energy from production to conversion, conservation, management, systems, technologies, etc. We encourage papers submissions aiming at better efficiency, cost improvements, more effective resource use, improved design and analysis, reduced environmental impact, and hence leading to better sustainability. IJER is concerned with the development and exploitation of both advanced traditional and new energy sources, systems, technologies and applications. Interdisciplinary subjects in the area of novel energy systems and applications are also encouraged. High-quality research papers are solicited in, but are not limited to, the following areas with innovative and novel contents: -Biofuels and alternatives -Carbon capturing and storage technologies -Clean coal technologies -Energy conversion, conservation and management -Energy storage -Energy systems -Hybrid/combined/integrated energy systems for multi-generation -Hydrogen energy and fuel cells -Hydrogen production technologies -Micro- and nano-energy systems and technologies -Nuclear energy -Renewable energies (e.g. geothermal, solar, wind, hydro, tidal, wave, biomass) -Smart energy system