Energy Conversion and Management-X最新文献

Economic dispatch optimization of a metal hydride storage system for supplying heat and electricity in a residential application 住宅供热用电金属氢化物储能系统的经济调度优化

IF 7.6 Q1 ENERGY & FUELS

Energy Conversion and Management-X

Pub Date : 2026-05-01 Epub Date: 2026-01-21 DOI: 10.1016/j.ecmx.2026.101579

Carlos Muñoz , Nies Reininghaus , Julián Puszkiel , Astrid Pistoor , Michael Kroener , Alexander Dyck , Martin Vehse , Thomas Klassen , Julian Jepsen

To achieve affordable, clean energy, incorporating renewable energy into existing energy systems is the key. One challenge is the fluctuating nature of renewable resources, which can be asynchronous with energy demands. Hydrogen storage, particularly metal hydride storage, is a favorable solution for balancing supply and demand. In particular, metal hydride storage, compared with pressurized or liquefied hydrogen storage, is a favorable technology choice due to its storage energy density (50-100 kg H˙2/m³) and its low operating temperature and pressure. This paper presents a simulation-based framework to investigate the optimal design and operation of a coupled Electrolyzer-Fuel Cell-Metal Hydride system (SET-Unit) for minimizing operational and capital expenses in a residential application. The results show that integrating heat pumps with a metal-hydride storage system and photovoltaics can achieve 83% energy self-sufficiency and a 7.1-year payback period. Combining SET-Unit, gas boilers, and photovoltaics can result in 28% energy self-sufficiency, annual savings of over 2221 EUR, and a payback period of 7.4 years. The SET-Unit, combined with renewable energy sources such as photovoltaics, and the in-market available gas boilers or heat pumps, shows benefits in efficiency, annual energy cost reduction, and a relatively short payback period for the household. Using the low end of published values for capital expenses, economic feasibility can be achieved.

要获得负担得起的清洁能源，将可再生能源纳入现有能源系统是关键。其中一个挑战是可再生资源的波动性，它可能与能源需求不同步。氢的储存，特别是金属氢化物的储存，是平衡供需的一个很好的解决方案。特别是，与加压或液化氢储存相比，金属氢化物储存由于其储存能量密度（50-100 kg H˙2/m3）和较低的工作温度和压力，是一种较好的技术选择。本文提出了一个基于仿真的框架来研究耦合电解槽-燃料电池-金属氢化物系统（SET-Unit）的优化设计和运行，以最大限度地减少住宅应用中的运营和资本支出。结果表明，将热泵与金属氢化物存储系统和光伏相结合，可以实现83%的能源自给自足，投资回收期为7.1年。将SET-Unit、燃气锅炉和光伏相结合，可以实现28%的能源自给自足，每年节省超过2221欧元，投资回收期为7.4年。SET-Unit与可再生能源（如光伏）和市场上可用的燃气锅炉或热泵相结合，在效率、年度能源成本降低和家庭投资回收期相对较短等方面显示出优势。使用公布的资本支出值的低端，可以实现经济可行性。

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引用次数: 0

Carbon reduction strategy based on coordination of production stages in cement manufacturing enterprises considering locational marginal carbon emission 考虑区位边际碳排放的水泥生产企业生产阶段协调减碳策略

IF 7.6 Q1 ENERGY & FUELS

Energy Conversion and Management-X

Pub Date : 2026-05-01 Epub Date: 2026-01-14 DOI: 10.1016/j.ecmx.2026.101561

Sheng Xiang, Panpan Li, Xinyu Zhang, Hongming Yang, Shuaihao Cheng, Archie James Johnston

Cement manufacturing enterprises, recognized as one of the most significant global carbon emission sources, face substantial pressure for carbon reduction. Conventional carbon reduction strategies predominantly emphasize direct carbon emissions, yet they often overlook the considerable impact of indirect carbon emissions from purchased electricity. This oversight renders them ill-suited for the trend of electricity substitution. To address this limitation, this paper proposes a novel carbon reduction approach for cement manufacturing enterprises. The approach integrates a two-stage stochastic optimization and is centered on the dynamic collaborative control of controllable production stages. Specifically, the operational states and production rates of these controllable production stages are controlled based on the locational marginal carbon emission factor and inventory constraints, effectively reducing indirect carbon emissions without impeding the daily production target. Finally, the proposed method is verified using the IEEE 30-node system and real-world data from an actual cement manufacturing enterprise in Hunan, China. The results indicate that through the coordinated control of controllable production stages, the proposed model achieves a 15.35% reduction in indirect carbon emissions. Moreover, it demonstrates remarkable effectiveness in mitigating the impact of uncertainties (such as renewable generation fluctuations), highlighting its practical value and potential for wide-scale implementation in the cement industry.

水泥生产企业作为全球公认的最重要的碳排放源之一，面临着巨大的减碳压力。传统的碳减排战略主要强调直接碳排放，但它们往往忽视了购买电力间接碳排放的巨大影响。这种疏忽使它们不适应电力替代的趋势。为了解决这一限制，本文提出了一种新的水泥生产企业碳减排方法。该方法集成了两阶段随机优化，以可控生产阶段的动态协同控制为中心。具体而言，基于区位边际碳排放因子和库存约束对这些可控生产阶段的运行状态和生产速度进行控制，在不影响日常生产目标的情况下有效地减少间接碳排放。最后，利用IEEE 30节点系统和中国湖南某水泥生产企业的实际数据对所提方法进行了验证。结果表明，通过对可控生产阶段的协调控制，该模型实现了间接碳排放减少15.35%。此外，它在减轻不确定性（如可再生能源发电波动）的影响方面显示出显著的有效性，突出了其在水泥工业中大规模实施的实用价值和潜力。

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引用次数: 0

Reinforcement learning in pulse energy converters, process knowledge learned to transfer perspective framework 强化学习在脉冲能量转换器，过程知识学习转移的视角框架

IF 7.6 Q1 ENERGY & FUELS

Energy Conversion and Management-X

Pub Date : 2026-05-01 Epub Date: 2026-01-19 DOI: 10.1016/j.ecmx.2026.101599

Robert Baždarić, Jasmin Ćelić

The article presents the task-based methodological framework of reinforcement learning (RL) for the control of energy transfer using the example of pulse energy converters (PEC). The focus is on the evaluation aspects of RL design as reflected in the formulation of knowledge learned and the ability to transfer for safe system application. The designer’s awareness of the process knowledge that is critical to the design of the control system begins with the definition of the necessary initial knowledge about the process and continues with the transformation of the RL knowledge, including storage and internal or external transferability. The transferable knowledge is inductive knowledge and not knowledge about the hyperparameters of the higher-level RL formulation, but it does contain this information. Not as a method for modelling deterministic certainty, but for modelling deterministic uncertainty. Modelling hybrid systems provides the imaginative deterministic foundations for the implementation of heuristics and RL formulations. The mild mathematical expressions in the form of definitions, assumptions, remarks and theorems serve to support the idea of transferable knowledge formulations that start from already inherited knowledge. The emphasis is on the inductive acquisition of process knowledge and the awareness of the epistemic connotation of the learning algorithm to ontics with the clear transformation. Markov Decision Processes (MDP) is a clear mathematical tool and modelling framework that merges the mathematical spaces of process states with our probability spaces and heuristics-based decision making in real time.

本文以脉冲能量转换器（PEC）为例，提出了基于任务的能量传递控制强化学习（RL）方法框架。重点是RL设计的评估方面，反映在制定所学知识和转移安全系统应用的能力。设计人员对过程知识的认识对控制系统的设计至关重要，这始于对过程的必要初始知识的定义，并随着RL知识的转化而继续，包括存储和内部或外部的可转移性。可转移的知识是归纳知识，而不是关于高级RL公式的超参数的知识，但它确实包含了这些信息。不是一种模拟确定性的方法，而是一种模拟确定性不确定性的方法。混合系统建模为启发式和RL公式的实现提供了想象的确定性基础。定义、假设、评论和定理等形式的温和数学表达有助于支持从已经继承的知识开始的可转移知识公式的想法。重点是过程知识的归纳获取和对学习算法的认识论内涵的认识，以及对本体的明确转化。马尔可夫决策过程（MDP）是一个清晰的数学工具和建模框架，它将过程状态的数学空间与我们的概率空间和基于启发式的实时决策相结合。

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引用次数: 0

Innovative syngas-biodiesel blends: a step towards cleaner and greener engine technology 创新的合成气-生物柴油混合物：迈向更清洁、更环保的发动机技术的一步

IF 7.6 Q1 ENERGY & FUELS

Energy Conversion and Management-X

Pub Date : 2026-05-01 Epub Date: 2026-01-20 DOI: 10.1016/j.ecmx.2026.101603

Manikandan Ezhumalai , Mohan Govindasamy , Ratchagaraja Dhairiyasamy , Deekshant Varshney , Subhav Singh

The increasing demand for sustainable and cleaner alternatives to fossil fuels has intensified research on Biodiesel and gaseous fuels for internal combustion engines. However, most existing studies focus on individual biodiesel feedstocks or diesel–syngas combinations, leaving limited understanding of the synergistic effects of blended biodiesels enriched with Syngas. This study aims to evaluate the performance, combustion, and emission characteristics of Juliflora and Pine Oil Methyl Ester Biodiesel blends integrated with hydrogen-rich Syngas in a dual-fuel compression ignition engine. Experiments were conducted on a Kirloskar SV1 engine at varying loads and syngas flow rates, and performance metrics were analyzed using Response Surface Methodology (RSM) and ANOVA. Results revealed that the J60 + P40 blend with 20 L/min syngas achieved a brake thermal efficiency of 31.2%, a 12% improvement over neat Biodiesel, while reducing brake-specific fuel consumption by 8% and smoke opacity by 25%. CO and HC emissions decreased by 18% and 22%, respectively, though NO_x increased marginally by 5% due to elevated combustion temperatures. These findings demonstrate that syngas enrichment enhances combustion efficiency and supports the utilization of cleaner energy. Future research should focus on integrating exhaust gas recirculation (EGR) or catalytic after-treatment to mitigate NO_x emissions and further optimize Biodiesel–syngas blending ratios.

对可持续和更清洁的化石燃料替代品的需求日益增长，加强了对生物柴油和内燃机气体燃料的研究。然而，大多数现有的研究都集中在单个生物柴油原料或柴油-合成气组合上，对富含合成气的混合生物柴油的协同效应了解有限。本研究的目的是在双燃料压缩点火发动机上，评估朱莉花和松木油甲酯生物柴油混合燃料与富氢合成气的性能、燃烧和排放特性。在Kirloskar SV1发动机上进行了不同负载和合成气流量的实验，并使用响应面法（RSM）和方差分析（ANOVA）对性能指标进行了分析。结果显示，J60 + P40混合20 L/min合成气实现了31.2%的制动热效率，比纯生物柴油提高了12%，同时减少了8%的制动特定燃料消耗和25%的烟雾不透明度。CO和HC的排放量分别下降了18%和22%，但由于燃烧温度的升高，NOx的排放量略微增加了5%。这些发现表明，合成气富集提高了燃烧效率，支持了清洁能源的利用。未来的研究应侧重于整合废气再循环（EGR）或催化后处理，以减少NOx排放，并进一步优化生物柴油-合成气混合比例。

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引用次数: 0

Maximizing profit and sustainability in RoR hydropower: an AI-driven hydrogen decision support model (H2-DSM) RoR水电的利润最大化和可持续性：人工智能驱动的氢决策支持模型（H2-DSM）

IF 7.6 Q1 ENERGY & FUELS

Energy Conversion and Management-X

Pub Date : 2026-05-01 Epub Date: 2026-02-10 DOI: 10.1016/j.ecmx.2026.101660

Eduardo Rodríguez Fernández-Arroyo, Alberto Casalderrey Area, Diego Quiñoy Peña

This study addresses the critical challenge of optimizing constrained Run-of-River (RoR) Hydropower Plant (HPP) assets within the volatile net-zero energy transition. The central hypothesis argues that an Artificial Intelligence (AI)-driven Hydrogen Decision Support Model (H₂-DSM) is an essential catalyst for ensuring the economic and environmental sustainability of Power-to-Hydrogen (P2H) hybridization. The model overcomes RoR operational rigidities—such as flow demodulation and ecological mandates—by deploying a multi-step iterative forecasting loop that functions as a high-fidelity digital twin. By deploying advanced ensemble learning algorithms validated through a rigorous annual loop test, the H₂-DSM enables real-time techno-economic arbitrage with high predictive fidelity (R² > 940 ‰). The simulation identifies a strategic equilibrium of 1,777 annual hours where green hydrogen production surpasses the profitability of direct electricity sales, achieving a Production Levelized Cost of Hydrogen (PLCOH) of 3.86 €/kg. This performance transforms hybridized assets into a “virtual battery,” effectively decoupling physical river flows from economic grid obligations to hedge against market volatility while achieving an optimized reduction of 149,060 kg CO₂ eq for a single 450 kW unit, while demonstrating a full decarbonization potential of 672,486.75 kg CO₂ eq if the facility is fully utilized. These results provide the quantitative evidence necessary to unlock private capital for decentralized renewable hubs, emphasizing the environmental-economic nexus of Hydropower 4.0.

本研究解决了在不稳定的净零能源转型中优化受约束的河流（RoR）水电站（HPP）资产的关键挑战。核心假设认为，人工智能（AI）驱动的氢决策支持模型（H2-DSM）是确保电力到氢（P2H）杂交经济和环境可持续性的重要催化剂。该模型通过部署多步骤迭代预测循环，作为高保真数字孪生体，克服了RoR操作的刚性，例如流量解调和生态要求。通过部署经过严格的年度循环测试验证的先进集成学习算法，H2-DSM实现了具有高预测保真度（R2 > 940‰）的实时技术经济套利。模拟确定了每年1777小时的战略平衡，其中绿色氢气生产超过直接电力销售的盈利能力，实现了3.86欧元/公斤的氢气生产平准化成本（PLCOH）。这种性能将混合资产转变为“虚拟电池”，有效地将物理河流从经济电网义务中分离出来，以对冲市场波动，同时为单个450千瓦机组实现149,060千克二氧化碳当量的优化减排，同时充分利用该设施，显示出672,486.75千克二氧化碳当量的完全脱碳潜力。这些结果为为分散的可再生能源中心释放私人资本提供了必要的定量证据，强调了水电4.0的环境与经济关系。

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引用次数: 0

A novel simulation–optimization framework for techno-economic analysis and optimal design of wind energy systems with NPV maximization 基于NPV最大化的风能系统技术经济分析与优化设计的仿真优化框架

IF 7.6 Q1 ENERGY & FUELS

Energy Conversion and Management-X

Pub Date : 2026-05-01 Epub Date: 2026-02-05 DOI: 10.1016/j.ecmx.2026.101643

Ahmed Shaban , Nasr Al-Hinai , Suzan Abdelhady

The traditional techno-economic analysis of wind energy projects typically relies on commercially available turbines, often leading to suboptimal performance in low-to-medium wind speed regions. Moreover, wake losses increasingly reduce per-turbine output as wind farm size grows and become denser. This study proposes a modular two-phase simulation–optimization framework that sequentially optimizes wind turbine design and wind farm layout for site-specific, investment-oriented planning. In Phase 1, a nonlinear optimization model determines the NPV-maximizing turbine configuration, including hub height, rotor diameter, and rated power. In Phase 2, techno-economic simulations using the System Advisor Model (SAM) evaluate candidate layouts under wake effects and land-use constraints. Polynomial regression surrogates, constructed within a systematically sampled spacing design space, approximate layout performance and guide a deterministic optimization model, with final layouts revalidated in SAM. The framework is applied to two onshore sites, Fayoum (Egypt) and Duqm (Oman), where the optimized turbine configurations are benchmarked against commercial alternatives using single-turbine SAM simulations. At both locations, the optimized turbine design outperforms all considered commercial machines in NPV. For the Fayoum site, the optimized turbine achieves a 28.9% capacity factor and 4.26 GWh annual energy production, while the optimized 42-turbine layout attains a validated net present value of $14.022 million and reduces wake losses by 34.2% relative to a dense baseline. A Monte Carlo analysis under wind-speed uncertainty supported the robustness of the optimized design. Overall, the framework provides a scalable, data-driven approach for integrated wind energy system design in wind-constrained environments.

风能项目的传统技术经济分析通常依赖于商业上可用的涡轮机，这往往导致在低至中等风速区域的性能不理想。此外，随着风电场规模的扩大和密度的增加，尾流损失会越来越多地降低每台涡轮机的输出。本研究提出了一个模块化的两阶段模拟优化框架，该框架依次优化风力涡轮机设计和风电场布局，以实现特定地点的投资导向规划。在第一阶段，非线性优化模型确定了npv最大化涡轮配置，包括轮毂高度、转子直径和额定功率。在第二阶段，使用系统顾问模型（SAM）进行技术经济模拟，评估尾流效应和土地利用限制下的候选布局。在系统采样的间距设计空间中构建多项式回归代理，近似布局性能并指导确定性优化模型，并在SAM中重新验证最终布局。该框架应用于两个陆上站点，Fayoum（埃及）和Duqm（阿曼），在那里，优化的涡轮机配置通过单涡轮SAM模拟与商业替代方案进行基准测试。在这两个地点，优化的涡轮机设计在净现值方面优于所有考虑的商用机器。对于Fayoum基地，优化后的涡轮机实现了28.9%的容量系数和4.26 GWh的年发电量，而优化后的42台涡轮机布局实现了1402.2万美元的有效净现值，相对于密集基线减少了34.2%的尾流损失。在风速不确定条件下的蒙特卡罗分析验证了优化设计的鲁棒性。总体而言，该框架为风力受限环境下的集成风能系统设计提供了一种可扩展的、数据驱动的方法。

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引用次数: 0

A thermoelectric generation-cooling system for enhancing heat dissipation: Optimization by Taguchi method with/without Thomson effect 一种增强散热的热电发电冷却系统：带/不带汤姆逊效应的田口法优化

IF 7.6 Q1 ENERGY & FUELS

Energy Conversion and Management-X

Pub Date : 2026-05-01 Epub Date: 2026-01-30 DOI: 10.1016/j.ecmx.2026.101617

Wei-Hsin Chen , Wei-Cheng Bai , Ding Luo , Liwen Jin , Alvin B. Culaba , Jo-Shu Chang

Efficient thermal management is essential for the performance and reliability of compact energy and electronic systems. This study proposes a self-powered thermoelectric generation-cooling (TEG-TEC) system that integrates a thermoelectric generator (TEG) with a thermoelectric cooler (TEC) to enhance heat dissipation using only available waste heat. The TEG converts part of the temperature difference into electrical power that directly drives the TEC, eliminating the need for external electricity. A Taguchi-based three-dimensional numerical model is employed to optimize four design factors: TEC thermoelectric couples, heat-transfer surface area, element length, and convection coefficient, each at four levels. An L16 orthogonal array requires only 16 simulations to explore the design space. Under the prescribed thermal boundary conditions, the optimized configuration achieves a maximum cooling capacity of 53.91 W, whereas a standalone TEG module delivers only 0.99 W. The internal power-amplification coefficient of performance, defined as COP_P =

Q_{C, T E G} / P_{TEG}

, reaches 50.38 for the best self-powered loop. In addition, the maximum thermal stress in the TEG module is reduced from 957.46 MPa in the standalone case to 936.69 MPa with the coupled TEG-TEC configuration, improving mechanical reliability. The Thomson effect reduces cooling performance by approximately 45%, underscoring the importance of incorporating Thomson heating into accurate TEG-TEC modeling. The proposed TEG-TEC configuration thus provides a compact, energy-efficient solution for low-load, space-constrained cooling while conceptually bridging waste-heat-driven power generation and active thermoelectric cooling.

高效的热管理对于紧凑型能源和电子系统的性能和可靠性至关重要。本研究提出了一种自供电热电发电-冷却（TEG-TEC）系统，该系统将热电发电机（TEG）与热电冷却器（TEC）集成在一起，仅利用可用的余热来增强散热。TEG将部分温差转换成电能，直接驱动TEC，无需外部电力。采用基于田口的三维数值模型对TEC热电偶、传热表面积、元件长度和对流系数四个设计因素进行了四个层面的优化。L16正交阵列只需要16次模拟来探索设计空间。在规定的热边界条件下，优化配置的最大制冷量为53.91 W，而独立的TEG模块的制冷量仅为0.99 W。最佳自供电回路的内部功率放大性能系数为COPP = QC,TEG/PTEG，达到50.38。此外，TEG模块的最大热应力从独立情况下的957.46 MPa降低到耦合TEG- tec配置下的936.69 MPa，提高了机械可靠性。汤姆逊效应降低了大约45%的冷却性能，强调了将汤姆逊加热纳入精确的TEG-TEC建模的重要性。因此，拟议的TEG-TEC配置为低负荷、空间受限的冷却提供了一种紧凑、节能的解决方案，同时在概念上连接了废热驱动发电和主动热电冷却。

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引用次数: 0

Validation of a novel Real-LIFE test protocol on two log wood stoves 在两个原木炉灶上验证一种新的现实生活测试方案

IF 7.6 Q1 ENERGY & FUELS

Energy Conversion and Management-X

Pub Date : 2026-05-01 Epub Date: 2026-01-16 DOI: 10.1016/j.ecmx.2026.101578

Claudia Schön , Juho Louhisalmi , Kamil Krpec , Hans Hartmann , Isaline Fraboulet , Benjamin Cea , Jarkko Tissari

The use of log wood stoves is common in residential homes and are tested in a type test procedure following EN 16510-1:2022 at optimal combustion condition. Since this does not represent real-life operation, a novel test protocol was developed and validated using two different log wood stoves. The new test protocol includes the ignition phase (two batches) at natural draught, followed by three batches at nominal load, two batches at partial load and one final batch at overload. Typical emission parameters such as carbon monoxide (CO), nitrogen oxides (NO_X), organic gaseous carbon (OGC) emissions were recorded as well as TPM emissions in the hot undiluted flue gas. This study shows that it is challenging to get similar emission results for the same stove in different laboratories even when using the same fuel and well-defined test protocol, differences in results are due to measurement uncertainty, differences in appliance operations and not following exactly the defined Real-LIFE test protocol. Coefficients of variation for TPM, CO, OGC and NO_X were 17.8 %, 20.1 %, 30.6 % and 8.7 %, respectively for stove A and 32.7 %, 13.9 %, 19.6 % and 10.0 %, respectively for stove B based on two to three repetitions per lab. The novel test protocol showed that combustion appliances may behave differently in different combustion phases, and this emphasizes the importance of measuring different combustion conditions in official testing to ensure that the appliances work properly in the field and that the measured emissions cover the whole operating range.

原木炉灶的使用在住宅中很常见，并在最佳燃烧条件下按照EN 16510-1:2022的型式试验程序进行测试。由于这并不代表实际操作，因此开发了一种新的测试方案，并使用两种不同的原木炉灶进行了验证。新的测试方案包括自然吃水下的点火阶段（两批），随后是标称负荷下的三批，部分负荷下的两批和过载下的最后一批。记录了典型的排放参数，如一氧化碳（CO）、氮氧化物（NOX）、有机气态碳（OGC）排放以及热未稀释烟气中的TPM排放。这项研究表明，即使使用相同的燃料和定义明确的测试方案，在不同的实验室对同一炉子获得相似的排放结果也是具有挑战性的，结果的差异是由于测量不确定性，器具操作的差异以及不完全遵循定义的实际测试方案。在每个实验室重复2 - 3次的基础上，炉A的TPM、CO、OGC和NOX的变异系数分别为17.8%、20.1%、30.6%和8.7%，炉B的变异系数分别为32.7%、13.9%、19.6%和10.0%。新的测试方案表明，燃烧器具在不同的燃烧阶段可能表现不同，这强调了在官方测试中测量不同燃烧条件的重要性，以确保器具在现场正常工作，并确保测量的排放量覆盖整个工作范围。

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引用次数: 0

Optimizing stand-alone hybrid PV/Diesel Generator system with a focus on reliability, cost, and environmental considerations 优化独立的混合光伏/柴油发电系统，重点是可靠性，成本和环境考虑

IF 7.6 Q1 ENERGY & FUELS

Energy Conversion and Management-X

Pub Date : 2026-05-01 Epub Date: 2026-01-14 DOI: 10.1016/j.ecmx.2026.101562

Mohammad Reza Gharib , Amir Mohammadbeigi

HRESs have been extensively demonstrated to provide reliable electricity in areas where extending the power grid is not feasible due to geographical constraints. However, it is important to note that these systems are not entirely free of emissions. This study examines an HRES consisting of PV and a DG. This work proposes three scenarios labeled Multi-Objective NPC vs. LPSP and Multi-Objective Emission vs. LPSP. The first scenario investigates NPC and LPSP, while the second scenario evaluates Total CO₂ Emission and LPSP to design a PV/DG power generation system for a remote university in Torbat Heydarieh, Iran. To solve the optimization problem, three well-known multi-objective optimization methods, namely MOHS, MOGWO, and MOPSO, are utilized to identify the appropriate dimensions of the components in a hybrid system. According to the calculations made in the first scenario, the cost of fuel and diesel generators accounts for over 80% of the NPC of the proposed system. By changing the LPSP value from 0 to 10 percent, the NPC is reduced by nearly 30 percent. In the second scenario, the cost of fuel and diesel generators accounts for more than 60% of the NPC of the system. Additionally, by changing the LPSP value from 0 to 10 percent, the Total CO2 Emissions are reduced by nearly 35 percent. A complete sensitivity analysis reveals the influence of interest rates and fuel prices on the NPC. Using MATLAB software, the numerical modeling outcomes obtained from the MOGWO method were compared to similar results generated by the MOHS and MOPSO approaches.

HRESs已被广泛证明可以在由于地理限制而无法扩展电网的地区提供可靠的电力。然而，值得注意的是，这些系统并非完全没有排放。本研究考察了由PV和DG组成的HRES。这项工作提出了三种场景，分别是多目标NPC vs. LPSP和多目标排放vs. LPSP。第一个方案调查NPC和LPSP，而第二个方案评估总二氧化碳排放量和LPSP，为伊朗Torbat Heydarieh的一所偏远大学设计光伏/DG发电系统。为了解决优化问题，利用MOHS、MOGWO和MOPSO三种著名的多目标优化方法来确定混合系统中部件的合适尺寸。根据第一种方案的计算，燃料和柴油发电机的成本占拟议系统NPC的80%以上。通过将LPSP值从0更改为10%，NPC减少了近30%。在第二种情况下，燃料和柴油发电机的成本占系统NPC的60%以上。此外，通过将LPSP值从0改变为10%，二氧化碳总排放量减少了近35%。一个完整的敏感性分析揭示了利率和燃料价格对全国人大的影响。利用MATLAB软件，将MOGWO方法得到的数值模拟结果与MOHS和MOPSO方法得到的相似结果进行了比较。

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引用次数: 0

Design and Performance Analysis of a Hybrid Solar-Wind Tree System with IoT based Real-Time Monitoring in Bangladesh 孟加拉国基于物联网实时监测的混合太阳能风树系统设计与性能分析

IF 7.6 Q1 ENERGY & FUELS

Energy Conversion and Management-X

Pub Date : 2026-05-01 Epub Date: 2026-01-27 DOI: 10.1016/j.ecmx.2026.101566

Arman Jahan Eva, Al Amin, Md Nasir Uddin, Tamim Ahmed, Abu Anas Nasim, Md Sahadat Hossain Sani, Md Shamsul Arefin

The global transition toward renewable energy has intensified interest in hybrid energy solutions that combine solar and wind power to enhance sustainability and reliability. Several studies have examined such integrated systems, however, most existing designs remain expensive, visually unsuitable for public spaces, and lack real-time monitoring or optimization capabilities, particularly in developing nations such as Bangladesh. Despite Bangladesh’s favorable solar irradiance and moderate wind potential, rural and urban public areas lack an efficient, decorative, and smart energy infrastructure. To address this gap, we propose a novel IoT-enabled hybrid solar wind energy tree tailored for public and rural settings in Bangladesh. Unlike conventional solutions, our proposed design integrates both energy sources into a visually appealing and self-sustaining structure capable of live monitoring and remote management. The system uses low-cost hardware (Arduino Nano, ESP8266, INA226 sensors) and simulation tools (COMSOL Multiphysics for structural integrity, HOMER Pro for cost analysis and MATLAB Simulink for performance modeling) using MPPT. A prototype was implemented for economic evaluation under site-specific conditions in Rajbari, Bangladesh (23°40.8′N, 89°31.3′E) demonstrating a Levelized Cost of Energy (LCOE) $0.11/kWh to $0.18/kWh for a single unit, which is approximately 50% lower than a standalone solar system. The community-scale configuration achieved a daily energy generation of up to 165 kWh under optimal conditions with an LCOE of $0.2997/kWh. This integrated solution offers a scalable, cost-effective, and environmentally friendly pathway to decentralized energy access in developing regions.

随着全球向可再生能源的转变，人们对结合太阳能和风能以提高可持续性和可靠性的混合能源解决方案的兴趣日益浓厚。然而，大多数现有的设计仍然昂贵，视觉上不适合公共空间，缺乏实时监控或优化能力，特别是在孟加拉国等发展中国家。尽管孟加拉国拥有良好的太阳辐照度和中等风力潜力，但农村和城市公共区域缺乏高效、美观和智能的能源基础设施。为了解决这一差距，我们提出了一种为孟加拉国公共和农村环境量身定制的新型物联网混合太阳能风能树。与传统解决方案不同，我们提出的设计将两种能源整合到一个具有视觉吸引力和自我维持能力的结构中，能够实时监控和远程管理。该系统采用低成本硬件（Arduino Nano, ESP8266， INA226传感器）和仿真工具（COMSOL Multiphysics用于结构完整性，HOMER Pro用于成本分析，MATLAB Simulink用于性能建模），使用MPPT。在孟加拉国Rajbari（23°40.8'N, 89°31.3'E）的特定条件下实施了一个原型进行经济评估，表明单个单元的平准化能源成本（LCOE）为0.11美元/千瓦时至0.18美元/千瓦时，比独立太阳能系统低约50%。在最佳条件下，社区规模的配置实现了高达165千瓦时的日发电量，LCOE为0.2997美元/千瓦时。这一综合解决方案为发展中地区的分散式能源获取提供了一条可扩展、具有成本效益和环境友好的途径。

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