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- 摘要
- 关键词
- 实验方案
- 产品
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[IEEE 2018 IEEE Energy Conversion Congress and Exposition (ECCE) - Portland, OR, USA (2018.9.23-2018.9.27)] 2018 IEEE Energy Conversion Congress and Exposition (ECCE) - High-Efficiency Weight-Optimized Fault-Tolerant Modular Multi-Cell Three-Phase GaN Inverter for Next Generation Aerospace Applications
摘要： The aircraft industry demands a significant increase in terms of efficiency and gravimetric power density of power converters for next generation aerospace applications. Between the two minimum targets, i.e. an efficiency > 98 % and a gravimetric power density > 10 kW/kg, the specification concerning the converter weight is the most challenging to fulfill. Since cooling systems and magnetic components dominate the weight breakdown of conventional converter concepts, multi-cell topologies, enabling improved semiconductors performance and reduced filtering requirements, are foreseen as promising solutions for the power electronics on board of More Electric Aircraft. On the other hand, the necessary simultaneous operation of a high number of cells inevitably limits the reliability of multi-cell converters if redundancy is not provided. In this paper, a favorable scaling trend of power density with respect to reliability, aiming to guarantee fault-tolerant operation without affecting the performance figures, is identified in modular multi-cell converters. Thus, a 45 kW weight-optimized modular multi-cell three-phase inverter featuring a redundant power stage is optimized, achieving an efficiency of 99 % and a gravimetric power density of 22.8 kW/kg.
关键词： Multi-Objective Optimization,Figure of Merit of Power Semiconductors,Power Converters Reliability,Modular Multi-Cell Inverter,More Electric Aircraft
更新于2025-09-23 15:23:52
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Multi-objective optimization of a solar assisted heat pump-driven by hybrid PV
摘要： The role of renewable energy sources becomes more and more important in modern times. Solar energy utilization in the building sector is one attractive solution for covering heating and electricity needs. In this direction, the investigation of a solar heating-electricity production system ideal for building applications is investigated in this study. This cogeneration system includes hybrid PV (or PV/T) collectors and a heat pump which is driven totally (heat and electricity) by the solar collector. The system is designed properly in order to produce net electricity production except for the need of the heat pump. This system is optimized using an innovative multi-objective procedure with heating and electricity production as the objective functions. The optimization is performed in steady-state conditions for seven different working fluids in the heat pumps. The optimum design points for all the working fluids are compared and finally, R32 is selected as the most suitable choice with R1234yf to be the second one. In the optimum design conditions, 10 m2 of hybrid PV collector are able to feed the heat pump and finally 4.33 kWth of heating and 0.53 kWel of net electricity to be produced. The next step in this study is the investigation of the system with R32 for all the winter period in the climate conditions of Athens (Greece). Six different typical days (one for every month from November to April) are examined and the final results are given. For January, which is a representative winter month, it is found that the daily heating and electricity production is 34.9 kWh and 5.13 kWh respectively. Moreover, the mean daily energy efficiency is found 60.53% while the exergy 9.26% for this month.
关键词： Working fluid investigation,Cogeneration,Space heating,Multi-objective optimization,PVT
更新于2025-09-23 15:23:52
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[IEEE 2018 International Conference and Exposition on Electrical And Power Engineering (EPE) - Iasi (2018.10.18-2018.10.19)] 2018 International Conference and Exposition on Electrical And Power Engineering (EPE) - Metaheuristic Algorithms based Multi-objective Optimization for Image Segmentation
摘要： In this paper a multi-threshold image segmentation procedure based on nature-inspired multi-objective optimization is proposed. The Particle Swarm Optimization, Black Hole and Gravitational Search algorithms were adapted for multi-objective optimization. The Root Mean Square Error and the number of segmented regions were used as optimization criteria. The three procedures were applied for human silhouettes detection in video sequences and the obtained results are compared. Concerning the algorithms performances, the experiments revealed that the results of multi-objective Black Hole algorithm based segmentation are better than those of the other two algorithms, at least for the test images used in this experiment.
关键词： nature-inspired algorithms,human locomotion,video processing,multi-objective optimization
更新于2025-09-23 15:22:29
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Laser Pouch Motors: Selective and Wireless Activation of Soft Actuators by Laser-powered Liquid-to-gas Phase Change
摘要： A joint optimization problem of link-layer energy efficiency (EE) and effective capacity (EC) in a Nakagami-m fading channel under a delay-outage probability constraint and an average transmit power constraint is considered and investigated in this paper. First, a normalized multi-objective optimization problem (MOP) is formulated and transformed into a single-objective optimization problem (SOP), by applying the weighted sum method. The formulated SOP is then proved to be continuously differentiable and strictly quasiconvex in the optimum average input power, which turns out to be a cup shape curve. Furthermore, the weighted quasiconvex tradeoff problem is solved by first using Charnes–Cooper transformation and then applying Karush–Kuhn–Tucker (KKT) conditions. The proposed optimal power allocation, which includes the optimal strategy for the link-layer EE-maximization problem and the EC-maximization problem as extreme cases, is proved to be sufficient for the Pareto optimal set of the original EE–EC MOP. Moreover, we prove that the optimum average power level monotonically decreases with the importance weight, but strictly increases with the normalization factor, the circuit power and the power amplifier efficiency. Simulation results confirm the analytical derivations and further show the effects of fading severeness and transmission power limit on the tradeoff performance.
关键词： energy efficiency,weighted sum method,delay-outage probability constraint,Quality-of-service,effective capacity,multi-objective optimization problem
更新于2025-09-23 15:21:01
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An environmentally conscious photovoltaic supply chain network design under correlated uncertainty: A case study in Iran
摘要： As the destructive impacts of unbridled use of fossil fuels threaten the quality of life, moving towards renewable energy like solar power has precipitated. While such movements are commendable, environmental impacts of its infrastructure development should not be overlooked. In this sense, this paper addresses a multi-objective robust mathematical model to study an environmentally conscious solar photovoltaic supply chain under correlated uncertainty. The proposed model aims at minimizing the environmental impacts of included activities in the concerned supply chain in addition to minimizing the conventional cost objective. To quantify and assess the relevant environmental impacts, a life cycle assessment-based model is accomplished employing the ReCiPe 2008 approach embedded in the SimaPro software tool. The augmented ?-constraint procedure is deployed to optimize the proposed multi-objective model, which is able to attain compromise solutions from the Pareto-optimal set. Correlated uncertainty whose importance is underlined in the real-life situations of the photovoltaic industry is also tackled exploiting a robust optimization method. Ultimately, the validity of the presented model is vindicated through discussing a case study. The acquired results endorse the effectiveness and usefulness of the model and offer prominent practical and managerial insights.
关键词： Environmental responsibility,Multi-objective optimization,Correlated uncertainty,Solar energy,Life cycle assessment,Photovoltaic supply chain
更新于2025-09-23 15:21:01
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Nuevo enfoque para la localización óptima de reconectadores en sistemas de distribución considerando la calidad del servicio y los costos de inversión
摘要： This article presents a new methodology for the optimal placement of reclosers on electric power distribution systems. The methodology simultaneously considers the installation of reclosers normally closed and open, in order to fault isolation and service restoration, respectively. The problem is described by a multi-objective mathematical model, where the first objective function minimizes the unserved energy level of the system (NENS) and the second one minimizes the investment costs of the project. The set of constraints considers operational criteria of the system. As a solution strategy the concept of operational areas is introduced, which reduce computational effort considering that the NENS by area remains constant. In the problem solution, a Non-dominated Sorting Genetic Algorithm II (NSGA-II) is employed. The results show the validity of the proposed methodology and its applicability to real distribution systems.
关键词： distribution systems,NSGA-II Algorithm,reclosers,reliability,multi-objective optimization
更新于2025-09-23 15:21:01
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Optimal Design of Standalone Photovoltaic System Based on Multi-Objective Particle Swarm Optimization: A Case Study of Malaysia
摘要： This paper presents a multi-objective particle swarm optimization (MOPSO) method for optimal sizing of the standalone photovoltaic (SAPV) systems. Loss of load probability (LLP) analysis is considered to determine the technical evaluation of the system. Life cycle cost (LCC) and levelized cost of energy (LCE) are treated as the economic criteria. The two variants of the proposed PSO method, referred to as adaptive weights PSO (AWPSOc f ) and sigmoid function PSO (SFPSOc f ), are implemented using MATLAB software to the optimize the number of PV modules in (series and parallel) and number of the storage battery. The case study of the proposed SAPV system is executed using the hourly meteorological data and typical load demand for one year in a rural area in Malaysia. The performance outcomes of the proposed AW/SFPSOc f methods give various con?gurations at desired levels of LLP values and the corresponding minimum cost. The performance results showed the superiority of SFPSOc f in terms of accuracy is selecting an optimal con?guration at ?tness function value 0.031268, LLP value 0.002431, LCC 53167 USD, and LCE 1.6413 USD. The accuracy of AW/SFPSOc f methods is veri?ed by using the iterative method.
关键词： levelized cost of energy (LCE),multi-objective optimization,particle swarm optimization,standalone PV system,loss of load probability (LLP),life cycle cost (LCC)
更新于2025-09-19 17:13:59
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Design of domestic photovoltaics manufacturing system under global constraints and uncertainty: Case economic aspects
摘要： As global political discourse is taking place where the need for a cleaner energy mix is constantly highlighted, manufacturing strategies are becoming more relevant. Thus, the photovoltaics system design is a crucial aspect related with the overall sustainability. In fact, various countries are considering the potential to locally manufacture different elements of the photovoltaics (PV) value chain and the strategies to incentivize a local manufacturing base. This paper develops a mathematical programming approach for the optimal design of a PV manufacturing value chain considering diverse criteria linked to economic and environmental performance such as minimum sustainable price, transportation capacity, among others, and considering uncertainty. In addition, the proposed methodology involves the dependence over time of supply chain variables and economic parameters such as inflation, electricity cost, and weighted average cost of capital, to determine the manufacturing system topology under uncertain conditions. Our results highlight the importance of planning models to develop markets policies related to supply chains, production level changes and imposed tariffs all while involving uncertainty in economic parameters, which is an improvement compared to planning models that use deterministic formulations. Finally, the proposed methodology and results can encourage decision-making considering probable variations in different parameters.
关键词： Uncertainty,Expected value,Solar photovoltaics,Worst case,Manufacturing photovoltaics system,Multi-objective optimization
更新于2025-09-19 17:13:59
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Reliability analysis and design of a single diode solar cell model using polynomial chaos and active subspace
摘要： In recent times, photovoltaic power systems are being used worldwide with a high rate of adoption as a source of clean energy. It is therefore important to study the impact of environmental uncertainties on the yielding power of these solar cells. This paper considers the problem of reliability analysis/design for the yield power in a single diode solar cell when there are uncertainties in the outdoor conditions (e.g. temperature, irradiance) with polynomial chaos and active subspace methods. With the polynomial chaos based surrogate modeling of the yield power, one can accurately and efficiently compute the mean and variance of the yielding power. Following this, reliability design is formulated as a bi-objective optimization problem involving (A) maximization of the mean power yield and (B) minimization of the power yield variation under temperature and irradiance uncertainties. The active subspace method is used to simplify the bi-objective formulation. It is found that utilizing the active subspace method can simplify the bi-objective nonlinear design problem to a bi-objective linear optimization one. Our simulation result shows that the bi-objective linear optimization problem results in a higher mean and lower variance in the maximum power point (MPP) than the direct non-linear design approach.
关键词： Polynomial chaos,Single diode solar cell,Active subspace,Reliability,Multi-objective optimization
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - A new approach for Multi junction solar cells from off the shelf individual cells: GaAs/Si
摘要： Interference is one of the major obstacles to improving the performance in wireless communication systems. As the ever-growing data traffic is carried over extremely dense networks, how to deal with interference becomes even more relevant. In this paper, we investigate a network with N pairs of users transmitting on the same channel simultaneously from the energy efficiency (EE) perspective. For such an interference network, we aim to address two issues: what is the EE tradeoff between users and how to design energy-efficient resource allocation scheme? To answer these two questions, we formulate a non-concave multi-objective optimization problem (MOOP) to investigate the EE tradeoff, taking into account the minimum data rate requirement of each user. The weighted Tchebycheff method is utilized to solve the MOOP by converting it into a single-objective optimization problem, which is then solved by the Dinkelbach method and the concave-convex procedure method. Based on the above, a power control algorithm is developed for the interference network to achieve at least a local optimum. The proposed algorithm is compared with the orthogonal bandwidth sharing, where each user orthogonally shares the whole bandwidth without interfering each other. In this scenario, the weighted Tchebycheff and the Dinkelbach methods are also utilized to develop the optimal bandwidth allocation and power control algorithm. The performance of the proposed algorithms is verified by numerical results, which show that it is better to share the bandwidth orthogonally rather than non-orthogonally if the interference between each user pair is stronger than a given threshold.
关键词： multi-objective optimization,energy efficiency,Interference channel,bandwidth allocation and power control
更新于2025-09-19 17:13:59