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نتیجه جستجو - سیستم قدرت

تعداد مقالات یافته شده: 52
ردیف عنوان نوع
1 Thermal management of the waste energy of a stand-alone hybrid PV-windbattery power system in Hong Kong
مدیریت حرارتی انرژی زائد یک سیستم قدرتمند هیبریدی PV-بادگیر مستقل در هنگ کنگ-2020
This paper firstly investigated the thermal management of wasted energy from a stand-alone hybrid solar-windbattery power system. The total dump load or waste power can be up to 50% of total system power yield, and therefore waste energy management is urgent with high necessity. A new phase change material (PCM: Ba (OH)2·8H2O) with high storage capacity is introduced for the thermal management of hybrid power system. Different renewable energy configurations with different battery storage capacities are simulated and investigated. For different scenarios, the ratio of the captured thermal energy from waste energy to total solar/ wind power output ranges from 24.45% to 72.48% regarding all system losses. The cases without battery bank are featured by high thermal energy amount/ percentage (waste energy) and high power supply failure. Typical results show that, the total yearly renewable power output is 173,877 kWh with only 51.99% directly for demand load, and 57,672 kWh with 33.17% can be effectively stored in the thermal storage tank as heat, which can supply about 136 people’ heat demand per year. Compared with the water tank, the PCM thermal storage tank can save much space and land because of its high energy density. Appropriate thermal management of standalone hybrid solar-wind-battery power systems is necessary and feasible.
Keywords: Solar-wind-battery system | Dump load | Thermal energy | Heat | Energy losses
مقاله انگلیسی
2 Energy management of hybrid electric vehicles: A review of energy optimization of fuel cell hybrid power system based on genetic algorithm
مدیریت انرژی وسایل نقلیه الکتریکی هیبریدی: مروری بر بهینه سازی انرژی سیستم قدرت هیبریدی سلول سوختی بر اساس الگوریتم ژنتیکی-2020
Under the background of current environmental pollution and serious shortage of fossil energy, the development of electric vehicles driven by clean new energy is the key to solve this problem, especially the hybrid electric vehicle driven by fuel cell is the most effective solution. Many scholars have found that the output performance of hybrid system is an important reason to determine the life of fuel cell. Unreasonable output will affect the control characteristics of the drive system, resulting in a series of serious consequences such as the reduction of the life of fuel cell hybrid power system. Therefore, the energy management strategy and performance optimization of hybrid system is the key to ensure the normal operation of the system. At present, many excellent researchers have carried out relevant research in this field. Genetic algorithm is a heuristic algorithm, which has better optimization performance. It can easily choose satisfactory solutions according to the optimization objectives, and make up for these shortcomings by using its own characteristics. These characteristics make genetic algorithm have outstanding advantages in the iterative optimization of energy management strategy. This paper analyzes and summarizes the optimization effect of genetic algorithm in various energy management strategies, aiming to analyze and select the optimization rules and parameters, optimization objects and optimization objectives. This paper hopes to provide guidance for the optimal control strategy and structural design of the fuel cell hybrid power system, contribute to the research on improving the energy utilization efficiency of the hybrid power system and extending the life of the fuel cell, and provide more ideas for the optimization of energy management in the future.
Keywords: Fuel cell hybrid electric vehicle | Energy management strategy | Hybrid power system | Genetic algorithm |Optimization parameters and objectives
مقاله انگلیسی
3 Reinforcement learning in sustainable energy and electric systems: a survey
یادگیری تقویتی در سیستم های انرژی پایدار و الکتریکی: یک نظرسنجی-2020
The dynamic nature of sustainable energy and electric systems can vary significantly along with the en- vironment and load change, and they represent the features of multivariate, high complexity and uncer- tainty of the nonlinear system. Moreover, the integration of intermittent renewable energy sources and energy consumption behaviours of households introduce more uncertainty into sustainable energy and electric systems. The operation, control and decision-making in such an environment definitely require increasing intelligence and flexibility in the control and optimization to ensure the quality of service of sustainable energy and electric systems. Reinforcement learning is a wide class of optimal control strate- gies that uses estimating value functions from experience, simulation, or search to learn in highly dy- namic, stochastic environment. The interactive context enables reinforcement learning to develop strong learning ability and high adaptability. Reinforcement learning does not require the use of the model of system dynamics, which makes it suitable for sustainable energy and electric systems with complex non- linearity and uncertainty. The use of reinforcement learning in sustainable energy and electric systems will certainly change the traditional energy utilization mode and bring more intelligence into the system. In this survey, an overview of reinforcement learning, the demand for reinforcement learning in sustain- able energy and electric systems, reinforcement learning applications in sustainable energy and electric systems, and future challenges and opportunities will be explicitly addressed.
Keywords: Reinforcement learning | Sustainable energy and electric systems | Deep reinforcement learning | Power system | Integrated energy system
مقاله انگلیسی
4 An optimal method of the energy consumption for fuel cell hybrid tram
یک روش بهینه برای مصرف انرژی برای تراموائی هیبریدی سلول سوختی-2020
Energy conservation running for vehicle has been a promising research hotspot in the many universities and research institutions. In order to improve the energy utilization rate in the vehicle running process, an optimization method of the energy consumption and recycle based on fuel cell (FC)/supercapacitor (SC) hybrid tram is proposed in this paper. In the method, a tram operation energy management strategy based on Pontriagin’s minimum principle (PMP) can effectively was proposed what adjusts the output power of FC and SC and decreases hydrogen consumption. In addition, a tram breaking velocity curve with maximum energy recovery and the allocation strategy between regenerative force and mechanical braking force be also studied in this paper. According to the simulation results, it could be obtained that the Energy conservation rate is about 5% higher than the un-optimized, it will effectively decrease hydrogen consumption.
Keywords: Fuel cell | Hybrid power system | Energy management strategy | Energy utilization rate
مقاله انگلیسی
5 Variable structure battery-based fuel cell hybrid power system and its incremental fuzzy logic energy management strategy
سیستم قدرت هیبریدی سلول سوختی مبتنی بر باتری ساختار متغیر و استراتژی مدیریت انرژی منطق فازی افزایشی آن-2020
A hybrid power system consists of a fuel cell and an energy storage device like a battery and/or a supercapacitor possessing high energy and power density that beneficially drives electric vehicle motor. The structures of the fuel cell-based power system are complicated and costly, and in energy management strategies (EMSs), the fuel cell’s characteristics are usually neglected. In this study, a variable structure battery (VSB) scheme is proposed to enhance the hybrid power system, and an incremental fuzzy logic method is developed by considering the efficiency and power change rate of fuel cell to balance the power system load. The principle of VSB is firstly introduced and validated by discharge and charge experiments. Subsequently, parameters matching of the fuel cell hybrid power system according to the proposed VSB are designed and modeled. To protect the fuel cell as well as ensure the efficiency, a fuzzy logic EMS is formulated via setting the fuel cell operating in a high efficiency and generating an incremental power output within the affordable power slope. The comparison between a traditional deterministic rules-based EMS and the designed fuzzy logic was implemented by numerical simulation in three different operation conditions: NEDC, UDDS, and user-defined driving cycle. The results indicated that the incremental fuzzy logic EMS smoothed the fuel cell power and kept the high efficiency. The proposed VSB and incremental fuzzy logic EMS may have a potential application in fuel cell vehicles.
Keywords: Fuel cell vehicles | Hybrid fuel cell/battery power | system | Variable structure battery (VSB) | Incremental fuzzy logic energy | management | Maintain efficiency and lifespan
مقاله انگلیسی
6 An automatic algorithm of identifying vulnerable spots of internet data center power systems based on reinforcement learning
یک الگوریتم خودکار برای شناسایی نقاط آسیب پذیر سیستم های قدرت مرکز داده اینترنتی بر اساس یادگیری تقویتی-2020
The internet data center (IDC) power system provides power guarantee for cloud computing and other information services, so its importance is self-evident. However, the occurrence time of malignant destructive events such as lightning strikes, errors in operation and cyber-attacks is unpredictable. But the loss can be minimized by formulating coping strategies in advance. So, identifying the vulnerable spots of the IDC power system come to be the key to guarantee the normal operation of information systems. Generally, the IDC power network can be modelled as a graph G, and then, the methods of finding nodes’ centrality can be applied to analyse the vulnerability. By our experience, it is not the best approach. Unlike the previous approaches, we do not solve the issue as the traditional graph problem. Instead, we fully utilize the characteristics of the IDC power network and apply reinforcement learning techniques to identify the vulnerability of the IDC power network. To our best knowledge, it is the first applying of artificial intelligence in traditional IDC power network. In this article, we propose PFEM, a parallel fault evolution model for the IDC power network, which can accelerate the process of electrical fault evolution. Moreover, we designed an algorithm which can automatically find the vulnerable spots of the IDC power network. The experiment on a real IDC power network demonstrate that the impact of vulnerable devices derived from our proposed algorithm after failure is about 5% higher than that of other algorithms, and tripping single-digit electrical devices of the IDC power system with our proposed algorithm will lead to loss of all loads.
Keywords: Internet data center | Power system | Vulnerability | Reinforcement learning | Maintenance
مقاله انگلیسی
7 An optimized energy management strategy for fuel cell hybrid power system based on maximum efficiency range identification
یک استراتژی مدیریت انرژی بهینه برای سیستم قدرتمند هیبریدی سلول سوختی بر اساس شناسایی حداکثر برد بهره وری-2020
This study proposes an optimized energy management strategy (EMS) based on maximum efficiency range (MER) identification for a fuel cell/battery hybrid sightseeing car. And the aim of this study is to optimize hydrogen consumption of hybrid system and make sure that the power distribution between the fuel cell (FC) system and battery is optimal. FC system has the MER and is also a strongly coupled system. The MER of FC system will move with the change of operating conditions, and consequently, a parameter identification technique is needed to estimate the boundary powers of MER. This goal is achieved in this paper by using a forgetting factor recursive least square (FFRLS) online identification approach. Then the sequential quadratic programming (SQP) algorithm is used to solve the majorization problem of equivalent consumption minimum strategy (ECMS) so that the FC system operates as much as possible in the MER, while ensuring that the battery state of charge (SOC) fluctuates within the limited range. This helps to improve the efficiency, performance, and durability of the FC system and reduce the equivalent hydrogen consumption of the battery. A reduce-scale test platform is designed to verify the feasibility of the proposed optimized ECMS (OECMS). In addition, the conventional ECMS and rulebased state machine control (SMC) strategy are utilized in this paper to highlight the advantages of the proposed strategy. The experiment results show that the proposed OECMS helps to improve FC performance and optimize system hydrogen consumption.
Keywords: Fuel cell (FC) | Fuel cell/battery hybrid sightseeing car | Forgetting factor recursive least square (FFRLS) | Online identification | Equivalent consumption minimum strategy | (ECMS) | Reduce-scale test platform
مقاله انگلیسی
8 Implementation of AI Based Power Stabilizer Using Fuzzy and Multilayer Perceptron In MatLab
اجرای تثبیت کننده قدرت مبتنی بر هوش مصنوعی با استفاده از پرسپترون فازی و چند لایه در MatLab-2020
Systematic investigation of an Automatic Voltage Regulator (AVR) indicates one significant tradeoff in the effectiveness of Excitation System i.e. rapid response with high gain of the AVR induces undesirable damped oscillations in an Electrical power system, which slow down the rotor speed; To overcome this problem, Power system stabilizer (PSS) is used in parallel with excitation system (ES), by injecting extra stabilizing signals to minimize the side effect induced by AVR. The PSS must be self-tuned for adjusting parameters and managing different loading conditions. Therefore, this work is mainly focused on Multilayer Perceptron (MLP) feed-forward neural network and fuzzy logic system controllers to tune and adjust the PSS parameters to achieve better enhancement instability for varying load conditions. In this research work, PSS is designed with different controllers in MATLAB/ Simulink. The development of the PSS is achieved by using different controllers like ProportionIntegrator (PI), Proportion-Integrator-Differentiator (PID) and Artificial Intelligence (AI) based fuzzy and MLP controller. Simulation test results of Voltage and Frequency show the robustness of MLP type PSS as compared to PI, PID, and Fuzzy PSS in terms of minimized overshoot peak value, settling time and rise time for varying loading conditions.
Index Terms: Artificial Intelligence | Fuzzy Logic | MLP | Synchronous Generator | Power System Stabilizer(PSS)
مقاله انگلیسی
9 طراحی مشاهده گرهای نوع لوئنبرگر برای میرا نمودن نوسانات سیستم قدرت
سال انتشار: 2019 - تعداد صفحات فایل pdf انگلیسی: 6 - تعداد صفحات فایل doc فارسی: 21
طراحی مشاهده گرهای نوع لوئنبرگ کامل و از مرتبه ی مینیمال برای برآورد تقریبی وضعیت یک سیستم قدرت تک ماشینه با شین بی نهایت ارائه شده است. تخمینگر از خروجی سیستم برای ارائه ی برآوردهایی از اطلاعات وضعیت سیستم استفاده نموده و راهبرد کنترل فیدبک حالت بهینه برای فراهم نمودن تثبیت لازم و میرا نمودن نوسانات سیستم قدرت را ارائه می دهد. چیدمان موقعیت قطب حلقه بسته در صفحه ی s براساس روش مکان هندسی متقارن قطب ها در به حداقل رساندن شاخص عملکرد درجه دوم، تعیین می شود. موقعیت قطب های مشاهده گر نیز به نحوی تعیین می شود که وضعیت آن، به شیوه ای سریع تر وضعیت سیستم را دنبال کند. شبیه سازی کامپیوتری دو کنترل کننده ی آزمایشی، عملکرد رضایت بخش در گستره ی وسیعی از شرایط عملیاتی را نشان می دهد.
کلیدواژه: مشاهده گر حالت | قانون کنترل بهینه | مکان هندسی متقارن ریشه ها | شین بی نهایت تک-ماشینه | MATLAB
مقاله ترجمه شده
10 قابلیت‌اطمینان سیستم قدرت همراه با نفوذ زیاد باد تحت محدودیت پایداری فرکانسی
سال انتشار: 2018 - تعداد صفحات فایل pdf انگلیسی: 10 - تعداد صفحات فایل doc فارسی: 33
این پژوهش، روشی جدید جهت ارزیابی قابلیت‌اطمینان یک سیستم توان با نفوذ بالای تولید باد را ارائه می‌دهد که نه تنها تأثیر تناوب، بلکه مشخصه‌ی اینرسی پایین توان باد نیز در آن در نظر گرفته می‌شود. در صورتی‌که تولید باد به‌تدریج جایگزین تولید متداول باشد، پایداری و قابلیت‌اطمینان سیستم دارای تأثیر منفی می‌شوند. بعضی از معیارهای استفاده‌شده جهت مقابله با چالش‌های حاصل از افزایش نفوذ باد از عملیات ژنراتورهای بادی در سطح‌های پایین‌تر نسبت به خروجی قابل‌دسترس آنها و فراهم کردن اینرسی تشکیل شده است، بنابراین تولید باد می‌تواند به تنظیم فرکانس سیستم کمک نماید. به‌غیر از این معیارها، عامل دیگری که مقداری از توان باد را محدود می‌کند و می‌تواند در درون شبکه نیز جذب شود، اعمال استاندارد فرکانسی نام دارد و این عامل بر قابلیت‌اطمینان سیستم در حضور نفوذ باد نیز تأثیر‌گذار می‌باشد. دیدگاه ارزیابی قابلیت‌اطمینان ارائه‌شده در این پژوهش، با استفاده از کانولوشن گسسته توسعه داده شده است و بر روی یک سیستم IEEE RTS-79 با اصلاحات مناسب پیاده‌سازی گردیده است. جهت نشان دادن اثربخشی روش پیشنهادی، قابلیت‌اطمینان سیستم توان حاوی و بدون در نظر گرفتن اثرات تناوب باد و اینرسی پایین با یکدیگر مقایسه شده‌اند.
کلمات کلیدی: تنظیم فرکانس | تناوب | اینرسی | محدودیت نفوذ | قابلیت‌اطمینان | تولید باد.
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