Research Articles
Power systems
Amir Hossein Ataee-Kachoee; Hamed Hashemi Dezaki; Abbas Ketabi
Abstract
The deployment of microgrids (MGs) and smart grids to maximize the benefits from distributed generations (DGs) has increased. Although the MG framework and concept improve system flexibility and reliability, new challenges corresponding to the MG protection system appear compared to conventional passive ...
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The deployment of microgrids (MGs) and smart grids to maximize the benefits from distributed generations (DGs) has increased. Although the MG framework and concept improve system flexibility and reliability, new challenges corresponding to the MG protection system appear compared to conventional passive distribution networks. The adaptive protection schemes, which have been reported to consider various topologies in MG protection, need communication infrastructure. Also, the failure of telecommunication systems and cyber-attacks has drawn attention to unrelated protection schemes using local measurements, taking into account different topologies and related selectivity constraints. The literature shows a research gap in the development of local measurement-based protection schemes considering different operating modes and network configurations due to the unavailability of upstream substations, DGs, and other MGs sub-systems such as lines. This research attempts to fill this research gap by proposing a new protection scheme using dual setting directional overcurrent relays (DS-DOCRs) based on N-1 contingency topologies. The introduced method is applied to the distribution portion of the IEEE 30-bus test system. The Genetic Algorithm (GA) has been selected as the optimization algorithm, which is implemented in MATLAB, and the power system analyses are done in DIgSILENT. The test results show the advantages of the proposed method compared to the existing designs, only considering the limited operation modes. The test results indicate that mis-coordination for the N-1 contingency-based topologies does not appear using the proposed method.
Research Articles
Optimization
Vahid Kiani; Azadeh Soltani
Abstract
Sensor placement is a critical issue in wireless sensor networks that affects the quality of wireless sensor network coverage. In this paper, we propose an improved virtual force algorithm based on the states of matter (IVFASM) for relocating sensors of a mobile wireless sensor network. IVFASM simulates ...
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Sensor placement is a critical issue in wireless sensor networks that affects the quality of wireless sensor network coverage. In this paper, we propose an improved virtual force algorithm based on the states of matter (IVFASM) for relocating sensors of a mobile wireless sensor network. IVFASM simulates the behavior of molecules in different states of matter to improve the coverage of sensors. In the proposed IVASM algorithm, the strength of repulsive forces, the kinetic energy of the matter molecules, and attraction radius are dynamically adjusted over time according to different states of matter. As a result, in the gaseous state, sensors move rapidly apart; in the liquid state, sensors absorb each other to fill small holes gradually; in the solid state, sensors stabilize their final position. In the simulation, different states of matter led to improved coverage and fewer holes. Evaluation of the proposed method on 14 sample problems with the different numbers of sensors and comparison of the results with state of the art revealed that the proposed method can achieve a higher coverage rate in almost all sample problems. For a sample problem of 30 sensors, genetic algorithm (GA) and particle swarm optimization (PSO) achieved a coverage ratio of 69%, fuzzy redeployment algorithm (FRED) achieved a coverage ratio of 72%, classical virtual force algorithm (VFA) obtained a coverage ratio of 79%, improved virtual force algorithm based on area intensity (IVFAI) achieved a coverage ratio of 82%, and our proposed method IVFASM achieved a coverage ratio of 83%.
Research Articles
Power systems
Niloofar Mohammadi; Masoud Rashidinejad; Amir Abdollahi; Peyman Afzali
Abstract
Smart homes could have a significant impact on supplying the demand of both household consumers and smart grid. The household consumers can trade energy via peer-to-peer (P2P) energy trading to reduce their cost. In other words, each of them can participate in the smart grid as a prosumer that can both ...
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Smart homes could have a significant impact on supplying the demand of both household consumers and smart grid. The household consumers can trade energy via peer-to-peer (P2P) energy trading to reduce their cost. In other words, each of them can participate in the smart grid as a prosumer that can both produce and consume energy. On the other hand, the more participation of smart homes in the demand-side management (DSM) program could help to electricity decentralization. Also, the energy storage systems (ESSs) and distributed energy resources (DERs) can lead to further decentralization of a smart microgrid. The production of renewable energy resources, such as photovoltaic (PV) systems, are associated with uncertainty. The ESSs could able to be used as a reserve of PV systems. This paper presents a new risk-based model for P2P energy management of smart homes consist of PV system and EES and participate in the DSM program. The risk associated with the uncertainties of PVs’ production and market price has been modeled by conditional value-at-risk (CVaR). The mixed integer non-linear programming (MINLP) model of the problem has been solved by COUENNE in GAMS software. Numerical results show the expected cost of all resources and the related risk is reduced by the proposed decision making model for smart homes.
Research Articles
Power systems
mehrdad manshor; Mahmood Joorabian; afshin lashkarara
Abstract
Power management in microgrids is a major challenge due to its low total inertia and capacity. The lower the microgrid generation capacity is, the higher the share of each generation unit in total power will be, and the higher the frequency deviation in less time will be when an outage occurs. So, preventive ...
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Power management in microgrids is a major challenge due to its low total inertia and capacity. The lower the microgrid generation capacity is, the higher the share of each generation unit in total power will be, and the higher the frequency deviation in less time will be when an outage occurs. So, preventive actions can be more reasonable and affordable than corrective actions for microgrid power and frequency control. In this regard, a new primary frequency response-constrained unit commitment model is presented here to prevent excessive frequency deviations by more commitment of higher inertia power plants and more contribution of renewable energy resources or energy storage systems’ fast inertia response. To have a mixed-integer linear programming model, the primary frequency response constraints are linearized. The model is solved by the combination of two commercial solvers named MOSEK and YALMIP in the MATLAB 2018 environment. The proposed model is examined on a real isolated microgrid (an island). The results show that by activating the primary frequency support of distributed energy resources, the power can be managed with lower costs because there will be less need to start up fast (and expensive) gas turbine generation units. In addition, although comparing the model with others shows the more expensive management procedure, better frequency stability is obtained in contingencies.
Original Article
Control
mehdi fadaie; karim abbaszadeh; Alireza Siadatan
Abstract
Mono-Inverter Dual Parallel (MIDP) motors in transportation systems are the most effective method to manage energy consumption and reduce the volume, weight, and cost of electric motor drives. Unbalancing the load torques and changing the speed in unequal loading are the main problems in these systems. ...
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Mono-Inverter Dual Parallel (MIDP) motors in transportation systems are the most effective method to manage energy consumption and reduce the volume, weight, and cost of electric motor drives. Unbalancing the load torques and changing the speed in unequal loading are the main problems in these systems. Hence, the latest methods of optimal control such as Model Predictive Control (MPC) have been proposed. However, these methods do not lead to accurate control of MIDP systems because the cost function is evaluated by the limited number of control signals or solved online after a long time-consuming. This paper deals with designing the current and speed controllers of the MIDP system through an effective MPC method in order to reduce the computing time of the control signals and improve the motor performance in any situation. Pontryagin’s principle and the Lagrange method are used in designing the current and speed controllers respectively. These controllers constantly generate control signals as linear-parametric functions through the offline solving of the quadratic-linear cost function. After driving and simplifying the mathematical equations, the proposed method simulates. The simulation results of the proposed method are compared with the known Finite Control Set-Model Predictive Control (FCS-MPC) method in the MIDP motors. These results validate the prompt and accurate performance of the proposed controllers in transient and steady states.
Original Article
Industrial Electronics
omid qorbani; Esmaeil Najafiaghdam
Abstract
Ultrasonic process tomography obtains the distribution of the two-phase flow based on ultrasound propagation in different fluids, thus is valuable to industrial monitoring and measurement. Ultrasonic process tomography can do a non-intrusively exploration of the multi-phase flow hydrodynamics. In this ...
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Ultrasonic process tomography obtains the distribution of the two-phase flow based on ultrasound propagation in different fluids, thus is valuable to industrial monitoring and measurement. Ultrasonic process tomography can do a non-intrusively exploration of the multi-phase flow hydrodynamics. In this paper, a dual-mode ultrasonic process tomography is presented that fuses by reflection-mode tomography and time-of-flight ultrasonic tomography. In this method, a 32-digit array of ultrasonic sensors have been used for flow measurement. The two-phase flow rate that involves liquid and gas phases, have been calculated through a simple algebraic algorithm with obtained data from sensors. Simulation results depict that the measurement technique is independent of the fluid flow pattern and the system error also has been decreased. The invention of the article is about a simple algebraic method for image reconstruction which a special case is not considered in it and simultaneously, the image reconstruction error has been reduced. The relative error of the reconstructed images is presented by MATLAB simulation and it is much lower than the conventional methods. For a gas bubble with ultrasonic wave reflection time from its surface, the simulation results depict the SIE factor is less than 2%.
Research Articles
Optimization
Davoud Mirzaei; Saeid Amini
Abstract
In this paper, an ultrasonic horn based on the PSO algorithm for emulsion homogenization is optimized and fabricated. The application of various ultrasonic instruments such as horns in different industrial procedures is increasingly expanding and developing. Horn is a tool that has played a crucial role ...
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In this paper, an ultrasonic horn based on the PSO algorithm for emulsion homogenization is optimized and fabricated. The application of various ultrasonic instruments such as horns in different industrial procedures is increasingly expanding and developing. Horn is a tool that has played a crucial role in the energy transfer to fluid. Longitudinal frequency, vibration amplitude, length-to-diameter ratio, a distance of frequency from other frequency modes, wide distribution of cavitation along with the horn’s length, and increasing the area of acoustic energy transfer are the main characteristics of the horn design procedure. Therefore considering these important features with using the PSO algorithm and electro-mechanical circuit method to finding resonance frequency, the design procedure of the optimized horn is performed. The definition of the objective function is based on the horn’s amplification factor, and the rest of the other characteristics are defined as design constraints. The simulation results show a 15% improvement in the natural frequency compared to the target frequency and a suitable frequency distance of 2.5 kHz between the previous and next modes. According to the barbell part of the horn, the amplification factor of 14 was obtained for the proposed horn, the frequency and amplitude of the vibration were evaluated. The experimental results were very close in terms of amplification factor and frequency to the simulation results with reasonable accuracy.
