- 标题
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- 实验方案
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[IEEE 2018 IEEE Industry Applications Society Annual Meeting (IAS) - Portland, OR, USA (2018.9.23-2018.9.27)] 2018 IEEE Industry Applications Society Annual Meeting (IAS) - Design and Optimization of a Solar Power Conversion System for Space Applications
摘要： This manuscript details a design method for a 500kW solar power based microgrid system for space applications. The design method utilizes multi-objective optimization with the Genetic Algorithm considering four parameters that characterize solar power based microgrids (battery voltage, PV maximum power, PV maximum power point voltage, and number of panels per string). The final optimization metric is the ratio of daily average deliverable power to total system mass (W/kg) metric. The microgrid system is composed of a number of modular DC-DC micro-converters, of which four topologies (buck, boost, buck-boost and non-inverting buck-boost) are evaluated and compared. The non-inverting buck-boost converter is determined to be the best candidate, and the optimal system characteristics are provided and analyzed. The final system design achieves a specific power of 35.56W/kg, with optimized result of 743.7V battery voltage, 439.5W PV maximum power, 182.7V PV maximum voltage, and three panels per string. Based on the optimizations results, a prototype is designed, tested, and analyzed in terms of efficiency and low temperature reliability. The converter achieved a peak efficiency of 98.4%, a power density of 3.54W/cm3, a specific power of 3.76W/g, and operated for over 267 hours of 11-minute low temperature cycles from 0oC to -140oC.
关键词： wide band gap semiconductors,microgrids,non-inverting buck-boost,maximum power point trackers,space exploration,photovoltaic systems,design optimization,DC-DC power converters,system-level design,low temperature testing
更新于2025-09-23 15:23:52
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Design and Optimization of a Solar Power Conversion System for Space Applications
摘要： This manuscript details a design method for a 500kW solar power based microgrid system for space applications. The design method utilizes multi-objective optimization with the Genetic Algorithm considering four parameters that characterize solar power based microgrids (battery voltage, PV maximum power, PV maximum power point voltage, and number of panels per string). The final optimization metric is the ratio of daily average deliverable power to total system mass (W/kg) metric. The microgrid system is composed of a number of modular DC-DC micro-converters, of which four topologies (buck, boost, buck-boost and non-inverting buck-boost) are evaluated and compared. The non-inverting buck-boost converter is determined to be the best candidate, and the optimal system characteristics are provided and analyzed. The final system design achieves a specific power of 35.56W/kg, with optimized result of 743.7V battery voltage, 439.5W PV maximum power, 182.7V PV maximum voltage, and three panels per string. Based on the optimizations results, a prototype is designed, tested, and analyzed in terms of efficiency and low temperature reliability. The converter achieved a peak efficiency of 98.4%, a power density of 3.54W/cm3, a specific power of 3.76W/g, and operated for over 267 hours of 11-minute low temperature cycles from 0oC to -140oC.
关键词： low temperature testing,photovoltaic systems,wide band gap semiconductors,maximum power point trackers,design optimization,non-inverting buck-boost,space exploration,system-level design,DC-DC power converters,microgrids
更新于2025-09-23 15:22:29
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An On-Line Low-Cost Irradiance Monitoring Network with Sub-Second Sampling Adapted to Small-Scale PV Systems
摘要： Very short-term solar forecasts are gaining interest for their application on real-time control of photovoltaic systems. These forecasts are intimately related to the cloud motion that produce variations of the irradiance field on scales of seconds and meters, thus particularly impacting in small photovoltaic systems. Very short-term forecast models must be supported by updated information of the local irradiance field, and solar sensor networks are positioning as the more direct way to obtain these data. The development of solar sensor networks adapted to small-scale systems as microgrids is subject to specific requirements: high updating frequency, high density of measurement points and low investment. This paper proposes a wireless sensor network able to provide snapshots of the irradiance field with an updating frequency of 2 Hz. The network comprised 16 motes regularly distributed over an area of 15 m × 15 m (4 motes × 4 motes, minimum intersensor distance of 5 m). The irradiance values were estimated from illuminance measurements acquired by lux-meters in the network motes. The estimated irradiances were validated with measurements of a secondary standard pyranometer obtaining a mean absolute error of 24.4 W/m2 and a standard deviation of 36.1 W/m2. The network was able to capture the cloud motion and the main features of the irradiance field even with the reduced dimensions of the monitoring area. These results and the low-cost of the measurement devices indicate that this concept of solar sensor networks would be appropriate not only for photovoltaic plants in the range of MW, but also for smaller systems such as the ones installed in microgrids.
关键词： pyranometer,irradiance monitoring network,very short-term solar forecasting,microgrids,cloud enhancement,wireless sensor network,lux-meter
更新于2025-09-23 15:21:01
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[IEEE 2019 IEEE Asia-Pacific Conference on Applied Electromagnetics (APACE) - Melacca, Malaysia (2019.11.25-2019.11.27)] 2019 IEEE Asia-Pacific Conference on Applied Electromagnetics (APACE) - 3D Printed Waveguide Phase Shifter for Butler Matrix Network
摘要： The smart grid vision has resulted in many demand side innovations such as nonintrusive load monitoring techniques, residential micro-grids, and demand response programs. Many of these techniques need a detailed residential network model for their research, evaluation, and validation. In response to such a need, this paper presents a sequential Monte Carlo (SMC) simulation platform for modeling and simulating low voltage residential networks. This platform targets the simulation of the quasi-steady-state network condition over an extended period such as 24 h. It consists of two main components. The first is a multiphase network model with power flow, harmonic, and motor starting study capabilities. The second is a load/generation behavior model that establishes the operating characteristics of various loads and generators based on time-of-use probability curves. These two components are combined together through an SMC simulation scheme. Four case studies are presented to demonstrate the applications of the proposed platform.
关键词： power quality,network simulation,microgrids,Demand response,low voltage residential networks
更新于2025-09-23 15:19:57
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Fully decentralized robust backstepping voltage control of photovoltaic systems for DC islanded microgrids based on disturbance observer method
摘要： In this paper, a new backstepping-based nonlinear technique for control of photovoltaic systems in DC islanded microgrids (MGs) is proposed. In contrast to most existing droop/non-droop control strategies that require an exact model of the system including line impedances, loads, other distributed generation units (DGUs) parameters, and even the MG configuration, the proposed method is taking dynamics and uncertainties into account using a designed disturbance observer. Moreover, the proposed method rapidly reaches the reference values and exhibits a more accurate robust performance using local quantities measurement, irrespective of parametric uncertainties, unmodeled dynamics, unknown loads, disturbances, and the number/structure of DGs within the MG. Finally, a low-voltage DC MG is built where the robust performance of the proposed method for different operating conditions including load variation, tracking capability, nonlinear loads, and plug-play of DGs is verified.
关键词： robust control,Backstepping control,disturbance observer,photovoltaic systems,microgrids
更新于2025-09-23 15:19:57
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Decentralized Optimal Control of a Microgrid with Solar PV, BESS and Thermostatically Controlled Loads
摘要： Constructing microgrids with renewable energy systems could be one feasible solution to increase the penetration of renewable energy. With proper control of the battery energy storage system (BESS) and thermostatically controlled loads (TCLs) in such microgrids, the variable and intermittent energy can be smoothed and utilized without the interference of the main power grid. In this paper, a decentralized control strategy for a microgrid consisting of a distributed generator (DG), a battery energy storage system, a solar photovoltaic (PV) system and thermostatically controlled loads is proposed. The control objective is to maintain the desired temperature in local buildings at a minimum cost. Decentralized control algorithm involving variable structure controller and dynamic programming is used to determine suitable control inputs of the distributed generator and the battery energy storage system. The model predictive control approach is utilized for long-term operation with predicted data on solar power and outdoor temperature updated at each control step.
关键词： control of renewable power systems,thermostatically controlled loads,variable structure control,battery energy storage systems,decentralized control,model predictive control,solar PV,optimal control,control of microgrids
更新于2025-09-23 15:19:57
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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) - PV system performance evaluation by clustering production data to normal and non-normal operation.
摘要： Cloud service providers are typically faced with three significant problems when running their cloud data centers, i.e., rising electricity bills, growing carbon footprints, and unexpected power outages. To mitigate these issues, running cloud data centers in smart microgrids (SMGs) is a good choice, since SMGs can enhance the energy efficiency, sustainability, and reliability of electrical services. Thus, in this paper, we investigate the problem of energy management for cloud data centers in SMGs. To be specific, we would minimize the time average expected energy cost (including electricity bill, battery depreciation cost, the total generation cost of conventional generators, and revenue loss due to the unfinished workloads) with the consideration of three practical factors, i.e., the ramping constraints of backup generators, the charging and discharging efficiency parameters of batteries, and two kinds of data center workloads. A stochastic programming is formulated by integrating the constraints associated with workload allocation, electricity buying/selling, battery management, backup generators, and power balancing. To solve the stochastic programming problem, an online algorithm is designed, and the algorithmic performance is analyzed. Simulation results show the advantages of the designed algorithm over other baselines.
关键词： energy cost,uncertainty,smart microgrids,Cloud data centers
更新于2025-09-23 15:19:57
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[IEEE 2019 21st International Conference on Transparent Optical Networks (ICTON) - Angers, France (2019.7.9-2019.7.13)] 2019 21st International Conference on Transparent Optical Networks (ICTON) - Open Standard Test Framework for Photonic Integrated Circuits
摘要： Cloud service providers are typically faced with three significant problems when running their cloud data centers, i.e., rising electricity bills, growing carbon footprints, and unexpected power outages. To mitigate these issues, running cloud data centers in smart microgrids (SMGs) is a good choice, since SMGs can enhance the energy efficiency, sustainability, and reliability of electrical services. Thus, in this paper, we investigate the problem of energy management for cloud data centers in SMGs. To be specific, we would minimize the time average expected energy cost (including electricity bill, battery depreciation cost, the total generation cost of conventional generators, and revenue loss due to the unfinished workloads) with the consideration of three practical factors, i.e., the ramping constraints of backup generators, the charging and discharging efficiency parameters of batteries, and two kinds of data center workloads. A stochastic programming is formulated by integrating the constraints associated with workload allocation, electricity buying/selling, battery management, backup generators, and power balancing. To solve the stochastic programming problem, an online algorithm is designed, and the algorithmic performance is analyzed. Simulation results show the advantages of the designed algorithm over other baselines.
关键词： Cloud data centers,energy cost,uncertainty,smart microgrids
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) - Development and Mass Production of Bifacial Q.ANTUM p-Cz PERC Cells
摘要： Cloud service providers are typically faced with three significant problems when running their cloud data centers, i.e., rising electricity bills, growing carbon footprints, and unexpected power outages. To mitigate these issues, running cloud data centers in smart microgrids (SMGs) is a good choice, since SMGs can enhance the energy efficiency, sustainability, and reliability of electrical services. Thus, in this paper, we investigate the problem of energy management for cloud data centers in SMGs. To be specific, we would minimize the time average expected energy cost (including electricity bill, battery depreciation cost, the total generation cost of conventional generators, and revenue loss due to the unfinished workloads) with the consideration of three practical factors, i.e., the ramping constraints of backup generators, the charging and discharging efficiency parameters of batteries, and two kinds of data center workloads. A stochastic programming is formulated by integrating the constraints associated with workload allocation, electricity buying/selling, battery management, backup generators, and power balancing. To solve the stochastic programming problem, an online algorithm is designed, and the algorithmic performance is analyzed. Simulation results show the advantages of the designed algorithm over other baselines.
关键词： energy cost,uncertainty,smart microgrids,Cloud data centers
更新于2025-09-16 10:30:52
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Fault Tolerant Control System for Photovoltaic Panels Application
摘要： The paper presents a solution to control the power delivery system in a microgrid in which the primary energy source is using photovoltaic panels. The proposed mathematical models describe the operation of the main system blocks and are used as reference models in the fault detection mechanism. Using a complex control strategy, the generated power is controlled and the effects of the disturbances which occur in the system, including the faults, are rejected, making the proposed solution a robust and a fault tolerant one. The integrated control solution contains algorithms for the appropriate control of both the boost DC/DC converter and of the single phase inverter blocks. The proposed approaches are directed toward developing algorithms suitable for real-time implementation on 32 bit ARM processors.
关键词： Power Delivery System,Power Electronics Control,32 bit ARM (Advanced RISC Machine) processor,Microgrids,Renewable Energy Systems,Single Phase Inverter,Fault Detection
更新于2025-09-12 10:27:22