考虑需求响应方案的储氢能源枢纽多目标概率规划

IF 4.3 3区 工程技术 Q2 ENERGY & FUELS
Shahriar Karimian, Majid Moazzami, Bahador Fani, Ghazanfar Shahgholian
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引用次数: 0

摘要

本文为集成能源枢纽(EH)开发了一个随机双目标能源管理系统(EMS),该系统由光伏(PV)阵列、风力涡轮机(WTs)、双燃料锅炉、热电联产(CHP)发电、电动汽车(EV)充电基础设施和储氢系统组成,并与主电网互联。拟议的EMS框架同时最大限度地减少运营支出(OPEX)和碳排放,同时通过概率建模和需求响应计划(DRPs)解决可再生能源发电和负荷需求的不确定性。引入了一种新的改进的多目标蚱蜢优化算法(MMOGOA),该算法具有自适应突变算子来解决这一复杂的优化问题,在基线场景下,与传统的moea(非主导排序遗传算法[NSGA-II]和MOPSO)相比,具有优越的收敛特性,OPEX降低了7.2%。综合模拟表明,需求响应计划(DRP)的实施显著降低了成本(18.87%)和排放(14.62%),而不确定性的引入增加了成本(10%)和排放(4.38%),MMOGOA在所有运营机制中始终保持着性能优势。研究结果定量地强调了优化DRP参与和管理不确定性对于提高能源管理系统(ems)的效率和可持续性的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Multiobjective Probabilistic Planning of Energy Hub With Hydrogen Storage Technologies Considering Demand Response Programs

Multiobjective Probabilistic Planning of Energy Hub With Hydrogen Storage Technologies Considering Demand Response Programs

This paper develops a stochastic bi-objective energy management system (EMS) for an integrated energy hub (EH) comprising photovoltaic (PV) arrays, wind turbines (WTs), a dual-fuel boiler, combined heat and power (CHP) generation, electric vehicle (EV) charging infrastructure, and hydrogen storage systems, interconnected with the main grid. The proposed EMS framework simultaneously minimizes operational expenditures (OPEX) and carbon emissions while addressing uncertainties in renewable generation and load demand through probabilistic modeling and demand response programs (DRPs). A novel modified multi-objective grasshopper optimization algorithm (MMOGOA) with adaptive mutation operators is introduced to solve this complex optimization problem, demonstrating superior convergence characteristics and 7.2% lower OPEX compared to conventional MOEAs (Non-dominated Sorting Genetic Algorithm [NSGA-II] and MOPSO) in baseline scenarios. Comprehensive simulations reveal that demand response program (DRP) implementation achieves significant reductions (18.87% in costs and 14.62% in emissions), while uncertainty incorporation increases costs by 10% and emissions by 4.38%, with MMOGOA consistently maintaining performance dominance across all operational regimes. The results quantitatively highlight the importance of optimizing DRP participation and managing uncertainties to improve the efficiency and sustainability of energy management systems (EMSs).

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来源期刊
International Journal of Energy Research
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
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