با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
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71 |
Multi-objective stochastic programming energy management for integrated INVELOX turbines in microgrids: A new type of turbines
مدیریت انرژی برنامه نویسی تصادفی چند منظوره برای توربین های یکپارچه INVELOX در میکروگریدها: نوع جدیدی از توربین ها-2020 In this paper, a new type of wind turbine that is called INVELOX has been used. INVELOX has many
advantages such as six times more power generation than previous types, work at low speed, inconsiderable
maintenance and investment costs, and reduce the environmental effects of previous wind
turbines. Moreover, other renewable and nonrenewable generators are used in the energy management
and scheduling of the microgrid. The test case is a microgrid with selling and buying energy capability in
which the cost and pollution are considered as the objective functions. In the following, Uncertainties of
wind speed, solar radiation and electrical-thermal loads are investigated and a multi-objective stochastic
mixed integer linear programming is solved in the first scenario. Then, in the second scenario, the effects
of fuel cost uncertainty on generation units and objective functions have been studied. The Epsilon
constraints method and fuzzy satisfying are utilized to solve the problem and choose the best solution,
respectively. By using of INVELOX turbines, total cost and pollution of the microgrid in both deterministic
and stochastic planning are reduced from 192.68 $ to 97.23 $ and 249.28 $ to 126.38 $, as well 3334.76 Kg
to 3302.7 and 3925.63 to 3910.2 Kg respectively. Keywords: Energy management | INVELOX turbine | Microgrid | Renewable resource | Stochastic programming |
مقاله انگلیسی |
72 |
Optimal process design for integrated municipal waste management with energy recovery in Argentina
طراحی فرآیند بهینه برای مدیریت یکپارچه زباله شهری با بازیابی انرژی در آرژانتین-2020 This work presents a comprehensive mathematical model for the optimal selection of municipal waste
treatment alternatives, accounting for co-digestion of sludge and municipal solid waste. The superstructure
of alternatives includes anaerobic digestion under mesophilic or thermophilic conditions,
composting, recycling, and final disposal in a landfill. Anaerobic digesters can be fed with different
mixing ratios of sewage sludge (SS) and the organic fraction of municipal solid waste (OF). A mixedinteger
mathematical programming formulation is proposed to find the optimal process design. It
comprises nonlinear equations to estimate digestion yields according to substrate mixing ratios. Results
for cities of different sizes show that the joint treatment can increase profitability, especially in small
populations. In all cases, co-digestion of the full stream of SS and OF leads to an integrated waste-toenergy
process that maximizes the economic value and reduces environmental impacts of waste by
producing electricity, heat and fertilizer. Keywords: Co-digestion | Waste-to-Energy | Optimization | Superstructure | Process design |
مقاله انگلیسی |
73 |
A DIC method to determine the Mode I energy release rate G, the Jintegral and the traction-separation law simultaneously for adhesive joints
یک روش DIC برای تعیین میزان آزاد سازی انرژی حالت من G ، Jintegral و قانون جداسازی کشش به طور همزمان برای اتصالات چسبنده-2020 The quasi-static Mode I fracture behaviour of joints bonded with either a brittle or toughened
epoxy adhesive or a ductile polyurethane adhesive has been investigated by means of digital
image correlation (DIC). A novel method to measure the crack length using DIC analysis is
proposed. By measuring the crack tip separation, beam rotation and crack length, the energy
release rate G and the J-integral are obtained and are compared to analyse the validity of Linear
Elastic Fracture Mechanics (LEFM) methods. Simultaneously the traction-separation laws (TSLs)
for the adhesive joints were measured. The TSLs were then used as input data for FE modelling to
evaluate their accuracy by comparing with experimental results. It is shown that LEFM is valid
for the joints bonded with either the brittle or toughened epoxy adhesives but is invalid for joints
bonded with the polyurethane adhesive. The procedure proposed here to measure the crack
length via DIC shows great promise and can be automated readily in practice. Keywords: Traction-separation law (TSL) | G and J-integral | Crack length measurement | Validity of LEFM methods | Digital image correlation | Adhesive joint |
مقاله انگلیسی |
74 |
Cost-aware renewable energy management: Centralized vs. distributed generation
مدیریت انرژی تجدید پذیر آگاه از هزینه: متمرکز در مقابل تولید توزیع شده-2020 We propose optimization strategies for cooperating households equipped with renewable energy assets
and storage devices. We consider two system configurations: In the first configuration, households share
access to an energy farm, where electricity is generated from renewable sources and stored in battery
banks. In the second configuration, households are equipped with their own renewable energy sources
and storage devices, and are allowed to share energy through the grid. The developed optimization
model takes into account location and time-varying energy prices as well as energy transfer fees. To
design our strategies, we first establish performance bounds, and compare the two configurations in
terms of achievable savings and usability of renewable energy. Then, we devise real-time energy management
algorithms by incorporating forecasting techniques in the proposed framework. Simulation
results show that the proposed strategies outperform existing solutions by up to 10%. It is also shown
that cooperative strategies outperform greedy approaches by up to 6.8%. Keywords: Energy storage | Energy allocation | Cooperative strategies | Non-convex optimization |
مقاله انگلیسی |
75 |
Linear energy storage and dissipation laws during rock fracture under three-point flexural loading
قوانین ذخیره سازی و اتلاف انرژی خطی در هنگام شکستگی سنگ تحت بارگذاری خمشی سه نقطه ای-2020 To investigate the energy storage and dissipation characteristics during rock flexure fracturing, a
series of single cyclic loading–unloading flexural fracture tests was conducted on rectangular
rock beams using the three-point loading technique. The results show that under different experimental
unloading levels, the elastic and dissipation energies increase linearly as the input
energy increases. On this basis, the linear energy storage and dissipation laws were obtained,
which were immune to the experimental unloading level. The flexural energy storage coefficient
and flexural energy dissipation coefficient were subsequently introduced to characterize the
potentials of the rock for storing and dissipating energy, respectively. A positive or negative
relationship between the two coefficients and the rock mechanics properties (the brittleness
index and average flexural strength) was observed. The influence of pre-existing rock flaws on the
linear energy storage and dissipation laws was discussed. In addition, highly quadratic increases
in the elastic energy, dissipation energy, and input energy were observed with an increasing
experimental unloading level. For the energy characteristics at rock failure (the failure point of
the rock specimen), the peak input energy, peak elastic energy, and peak dissipation energy
varied considerably under different experimental unloading levels, while the associated peak
elastic dissipation index (the ratio of peak elastic energy to peak dissipation energy) remained
constant. Similar to the flexural energy storage coefficient, the mean value of peak elastic dissipation
index is also positively related to the rock mechanics properties. The linear evolution law
of energy storage and dissipation not only permits a quantitative determination of the energy
parameters at rock failure (the peak elastic energy and peak dissipation energy), but also relates
the energy properties with the rock mechanics properties. Keywords: Rock mechanics | Flexural fracture | Energy storage | Linear energy storage law | Three-point loading |
مقاله انگلیسی |
76 |
Predicted direct solar radiation (ECMWF) for optimized operational strategies of linear focus parabolic-trough systems
تابش مستقیم خورشیدی پیش بینی شده (ECMWF) برای استراتژی های عملیاتی بهینه شده سیستم های سهموی-تمرکز خطی -2020 Day-ahead forecasts of direct normal irradiance (DNI) from the Integrated Forecasting System (IFS), the
global model of the European Centre for Medium-Range Weather Forecasts (ECMWF), are used to
simulate a concentrating solar power (CSP) plant through the System Advisor Model (SAM) to assess the
potential value of the IFS in the electricity market. Although DNI forecasting from the IFS still demands
advances towards cloud and aerosol representation, present results show substantial improvements with
the new operational radiative scheme ecRad (cycle 43R3). A relative difference of approximately 0.12% for
the total annual energy availability is found between forecasts and local measurements, while approximately
10.6% is obtained for the previous version. Results of electric energy injection to the grid from a
simulated linear focus parabolic-trough system shows correlations coefficients of approximately 0.87
between hourly values of electric energy based on forecasted and measured DNI, while 0.92 are obtained
for the daily values. In the context of control strategy, four operational strategies are given for different
weather scenarios to handle the energy management of a CSP plant, including the effect of thermal
energy storage capacity. Charge and discharge operational strategies are applied accordingly to the
predicted energy availability. Keywords: Short-term forecasts | ECMWF | Direct normal irradiance | Concentrating solar power | System advisor model | Operational strategies |
مقاله انگلیسی |
77 |
Utilizing renewable energy sources efficiently in hospitals using demand dispatch
استفاده از منابع انرژی تجدید پذیر با کارآیی در بیمارستان ها با استفاده از تقاضای ارسال -2020 Health centers and hospitals can be categorized as one of the major consumers of electrical energy in
building sectors. Due to their competitive environment, they need to decrease their costs, including
energy costs. On the other hand, environmental problems, lack of fossil fuels, and high energy consumption
lead to using alternative energy generation methods like renewable energy sources (RESs). In
this paper, we consider that the hospital can produce part of its energy from RESs for cost reduction and
we implement demand dispatch energy program for using RESs efficiently. The challenge is that the
main goal of hospital is providing health services not energy cost reduction. Therefore, we present a biobjective
formulation for using RESs in hospitals in a way to minimize costs and dissatisfaction by
scheduling the activities of the hospital by considering hospital’s specific constraints and limitations.
With the help of the proposed model, hospitals will decrease energy costs while maintaining comfort of
patients and surgeons at the same time. The model is solved using real data of a hospital in Iran, and
sensitivity analysis on different parameters is done. The proposed model will cause reduction in energy
cost of the hospital by implementing demand dispatch program for using RESs in the hospital. Keywords: Renewable energy sources | Demand dispatch | Energy management | Health centers | Hospitals | Bi-objective |
مقاله انگلیسی |
78 |
Renewable energy powered membrane technology: Energy buffering control system for improved resilience to periodic fluctuations of solar irradiance
فن آوری غشایی با انرژی قابل تجدید: سیستم کنترل بافر انرژی برای بهبود مقاومت در برابر نوسانات دوره ای تابش خورشیدی-2020 Energy management is required to enable autonomous photovoltaic-powered membrane (PV-membrane)
desalination systems to make the optimal use of solar energy. In this paper, a novel charge
controller based on pre-set voltage sensing thresholds was designed to optimise the energy from PV
panels and supercapacitors (SCs). The control algorithms were established from the data derivations with
high-temporal-resolution (1s) solar irradiance (SI) source, allowing for resilient system operation under
variable conditions. The impacts of ramp rates, in both SI and PV output voltage (VPV) on the system,
were systematically investigated. Under a worst-case scenario, with a rapid ramp rate of DVPV ¼ 2 V/s,
the charge controller enabled the SCs to bridge the power gap to 6 min 20 s, permitting an additional 10 L
of permeate water produced. The state-of-charge of the SCs varied from 11 to 86%, regardless of the
magnitude of the ramp rate. The combination of the voltage thresholds (Vpump_on ¼ 160 V and
Vpump_off ¼ 90 V) was determined to result in optimum system performance, realising a high permeate
production at low specific energy consumption. It is concluded that the proposed charge controller is an
effective method to enhance system resilience under worst-case solar conditions. Keywords: Ramp rates | Charge controller | Supercapacitors | Photovoltaic | Reverse osmosis | Energy fluctuation |
مقاله انگلیسی |
79 |
Energy-efficient and damage-recovery slithering gait design for a snake-like robot based on reinforcement learning and inverse reinforcement learning
طراحی راه رفتن لغزنده با صرفه جویی در مصرف انرژی و آسیب دیدگی برای یک ربات مار مانند بر اساس یادگیری تقویتی و یادگیری تقویتی معکوس-2020 Similar to real snakes in nature, the flexible trunks of snake-like robots enhance their movement
capabilities and adaptabilities in diverse environments. However, this flexibility corresponds to a
complex control task involving highly redundant degrees of freedom, where traditional modelbased
methods usually fail to propel the robots energy-efficiently and adaptively to unforeseeable
joint damage. In this work, we present an approach for designing an energy-efficient and damagerecovery
slithering gait for a snake-like robot using the reinforcement learning (RL) algorithm and the
inverse reinforcement learning (IRL) algorithm. Specifically, we first present an RL-based controller for
generating locomotion gaits at a wide range of velocities, which is trained using the proximal policy
optimization (PPO) algorithm. Then, by taking the RL-based controller as an expert and collecting
trajectories from it, we train an IRL-based controller using the adversarial inverse reinforcement
learning (AIRL) algorithm. For the purpose of comparison, a traditional parameterized gait controller
is presented as the baseline and the parameter sets are optimized using the grid search and Bayesian
optimization algorithm. Based on the analysis of the simulation results, we first demonstrate that
this RL-based controller exhibits very natural and adaptive movements, which are also substantially
more energy-efficient than the gaits generated by the parameterized controller. We then demonstrate
that the IRL-based controller cannot only exhibit similar performances as the RL-based controller, but
can also recover from the unpredictable damage body joints and still outperform the model-based
controller, which has an undamaged body, in terms of energy efficiency.Videos can be viewed at
https://videoviewsite.wixsite.com/rlsnake. Keywords: Snake-like robot | Reinforcement learning | Inverse reinforcement learning | Motion planning | Damage recovery |
مقاله انگلیسی |
80 |
Probabilistic energy management with emission of renewable microgrids including storage devices based on efficient salp swarm algorithm
مدیریت انرژی احتمالی با انتشار میکروگریدهای تجدیدپذیر از جمله دستگاههای ذخیره سازی بر اساس الگوریتم کارآمد شمع نمکی-2020 In this paper, the efficient salp swarm algorithm (ESSA) is proposed to solve the energy management
(EM) with emission problem of renewable micro-grid (MG) including storage devices. Because of the
uncertainties in the renewable energy sources (RESs), load demand and market prices, the probabilistic
approach based on (2m þ 1) point estimate method and ESSA is employed to solve the probabilistic EM
problem. The proposed ESSA can be derived by introducing two modifications on the conventional salp
swarm algorithm (SSA) to improve the balance between exploration and exploitation, speed up the
convergence and avoiding the stuck in local optima of the SSA. The ESSA is employed to solve the
deterministic and probabilistic EM with emission problem. Where the multi-objective optimization
problem of cost and emission functions is transferred into a single objective function to minimize the
total operating cost of the MG. The proposed ESSA is evaluated using a typical grid-connected MG with
energy storage devices and compared with other methods. The results verify the superiority of the ESSA
to solve the EM problem of the MG over other methods. Keywords: Efficient salp swarm algorithm | Probabilistic energy management | Micro-grid | Emission | Renewable energy sources | 2m þ 1 point estimate method |
مقاله انگلیسی |