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Background: Environmental health has become a worldwide debating issue among researchers, scientists, and governments. Although fossil fuels have been the greatest energy resources for the human, their consumption leads to injecting greenhouse gases into the air, which can affect the existence of all living species dramatically. In fact, fossil fuels consumption pollutes the environment because of the injection of greenhouse gases which result in global warming. On the other hand, reductions in fossil fuel and drinking water resources have highlighted the importance of energy management and loss reduction in brand-new management strategies and manufacturing methods. Distribution transformers are one of the most used devices in power distribution networks. Hence, it seems to be logical to consider transformer losses as a definitive factor in design and construction procedures. Furthermore, such design procedures require powerful tools to solve complex non-linear equations and find the best solutions in the shortest time. Researchers and scientists have always had a great challenge regarding finding the best solutions for their analysis. In actuality, it is hard to solve complex non-linear problems by means of traditional calculation methods even if a researcher employs a powerful computer. For this reason, metaheuristic optimization algorithms have found great popularity among scientists. These algorithms seek the best solution through a solution pool at an appropriate pace. Therefore, a researcher can save more time and energy in solving an intricate problem. Objective: In this paper, the authors aim to modify the conventional Teaching-Learning Based Optimization (TLBO) algorithm to design an optimum distribution transformer by consideration of the transformer Total Owning Cost (TOC). The TOC consists of operational and initial manufacturing costs of a distribution transformer. The used raw materials affect the manufacturing cost and it would be decreased if the copper and iron volumes are reduced in the construction instruction. However, the operational cost that includes iron and copper losses must not be forgotten in design analysis. Indeed, loss consideration is of great significance to keep energy from frittering away and as a result, protects environmental resources. Materials and Methods: A novel approach based on an optimization technique for distribution transformer design problems is presented in this paper. The entire expenses of a transformer consist of transformer construction and operating costs. In other words, by reducing copper and iron volumes, the initial cost of a transformer will be decreased. Due to the electromagnetic and electrical losses in transformers, the initial cost of a transformer is not its entire design problem and the operating cost must be considered in the design algorithm. Appropriate limits on efficiency, voltage regulation, temperature rise, no-load current and winding fill factor are the constraints on the transformer design problems in the international standards. With respect to these constraints, the transformer designer can minimize the volume of the core and windings. In this paper, the Conditional Teaching-Learning Based Optimization (CTLBO) algorithm determines the appropriate transformer properties, while transformer construction cost and its operating cost are selected as an objective function for optimization method. In order to attain a suitable voltage regulation, transformer impedance is chosen as an optimization constraint. Results: The result of the paper demonstrates the proposed algorithm ability in reducing the Total Owning Cost (TOC) during transformer lifetime, which could be useful for energy distribution companies. In addition, the result analysis proves that the total losses of the transformer are reduced by the proposed approach in comparison to conventional design techniques. Then, more energy will be saved in the power grid when the proposed transformer is utilized in the power network. Conclusion: In this paper, a suitable method to design an optimum distribution transformer is proposed which enables manufacturers to construct their product based on the proposed method. In this way, it can be claimed that not only more money will be saved during the transformer operation, but also the energy consumption will be decreased drastically. Therefore, world resources will remain for future generations.

The power system operation, stability, and reliability are strongly dependent on the network protection system performance. On the other hand, the penetration of the renewable energy power plants into power grids drastically affects power networks and smart grids’ stability and reliability because of their fast dynamics in comparison to conventional power generators. Hence, power networks are considered as a complex cyber–physical energy system with vast interactions and communications among consumers and generators. In this condition, a reliable monitoring and control system can augment the safety, security, and operation of such an intricate system. Suitable time coordination between the operations of power grids protection relays is one of the most challenging issues to protect the power system properly. In this paper, a reliable supervisor system (RSS) with fast and precise control ability is proposed to improve power systems and smart grids protection system operations. The device utilizes a safe robust communication way which provides a condition for the available relays on two sides of a line to share their data. For this reason, the proposed device is able to diagnose the fault on a short transmission line quickly upon the event occurrence. In other words, fast communication between two sides of a short transmission line helps the protection system to work faster in the presence of a fault. In addition, quick handshaking and data sharing of the network different points provided by the RSS enable grid circuit breakers to disconnect a fault from the system as fast as possible. The proposed system, then, can easily find a defect location and disconnect a faulty line from the grid. According to the experimental results provided in this paper, the RSS can effectively corroborate the network stability.

This paper deals with the optimal design of V-shape interior permanent-magnet motor (V-IPM) for the electric vehicle application. The magnetic equivalent circuit (MEC) is used to obtain the performing parameters of the studied motor. The applied analytical model is verified using finite-element analysis (FEA). Considering the voltage and current limits, the maximum torque per ampere (MTPA) is applied to determine the optimum number of turns per slot to have a wider constant torque region. The consideration of the MTPA for the machine design increases the electric motor volume. The volume minimization is targeted in the objective function of the optimization problem. The optimization is executed over three different driving cycles for a 50-kW V-IPM motor. The efficiency and power factor are the constraints of the optimization problem. The optimal designs are compared against each other in terms of their efficiency and power density. The simulation results depict how the magnet and iron volume vary in different driving cycles.

In some applications such as electric vehicles, electric motors should operate in a wide torque and speed ranges. An efficiency map is the contour plot of the maximum efficiency of an electric machine in torque-speed plane. It is used to provide an overview on the performance of an electric machine when operates in different operating points. The electric machine losses in different torque and speed operating points play a prominent role in the efficiency of the machines. In this paper, an overview about the change of various loss components in torque-speed envelope of the electric machines is rendered to show the role and significance of each loss component in a wide range of torque and speeds. The research gaps and future research subjects based on the conducted review are reported. The role and possibility of the utilization of the computational intelligence-based modeling of the losses in improvement of the loss estimation is discussed. Refereed/Peer-reviewed

Robustness, low cost and high torque density are the main characteristics of switched reluctance machines (SRM) that have made them promising for a variety of applications. In this paper a small diameter, long stack length (small aspect ratio) 6kW SRM is designed. In the first step, the dimensions of the studied SRM are derived based on conventional sizing equations. The significance of the rotor and stator pole arcs and also the effective torque zone as a constraint of the design are discussed. A finite-element study is carried out to validate the analytical model of the proposed SRM. The performance of the machine is comprehensively studied in different operating speeds. Simulation results demonstrate the capability of the machine for operation over a wide speed range.pa Refereed/Peer-reviewed

Selection of electrical machine is a key issue in electrical and hybrid electrical vehicles (HEVs and EVs). As far as HEVs and EVs are concerned, mechanical ruggedness of electrical machine is of utmost importance. For these reasons, the application of switched reluctance (SR) machine in EVs and HEVs is a viable option. In this study, an SR generator (SRG) has been utilised to work as a battery charger in EVs. The current ripple of the SRG is the greatest issue when it works as a battery charger. Therefore, a power converter and a smart search control (SSC) approach are proposed in this study to decrease the current ripple when the output power has a maximum quantity. During the system operation, the SSC method determines the value of excitation angle, turn-on and turn-off angles for each phase of SRG. The simulation and experimental results demonstrate the eligibility of the SSC system and power converter to obtain the acceptable charging current in maximum generated power during battery charging.

Step-up DC-DC converters play a determinative role in traction vehicles by providing the required DC- link voltage for traction drives supplied by battery packages or fuel cells. Bi-directional converters are preferred to be used in the construction of battery-based traction drives to charge batteries when drivetrains system work in the generation mode. However, due to the fact that fuel-cells cannot be charged electrically, the bi-directional structure is not required for fuel cell-based traction drives. The proposed step up converter benefits from the resonance between its elements to provide the soft- switching condition for the converter switches. The resonance assists to transmit high power from input and to output while there is no high-frequency transformer or coupled inductor in the converter topology. In brief, the generated resonance not only leads to a high power density converter but also result in a soft-switching which means higher efficiency in comparison to previously introduced high-step up converters working in hard switching condition. So, the proposed high-efficiency high power density high step-up (HHH) converter could be employed as a reliable DC-DC converter for traction vehicles supplied by fuel cells. Refereed/Peer-reviewed

Acoustic transmitters used in underwater communication system typically utilizes the PIEZO-Electric elements in their construction. The PIEZO-Electric sends data when it is supplied by an AC voltage in an operating period. The water depth in a location where the transmitters are operated determines the required supply voltage level of the transmitter. A high-efficiency high step-up high-power density (HHH) converter plays a critical role in supplying PIEZO-Electric transmitters in underwater applications. Moreover, the PIEZO-Electric transmitters (PZETs) must occupy a small space for underwater applications. Hence, a DC-DC HHH converter is proposed in this paper which is able to operate in zero voltage switching (ZVS) conditions; while the absence of a transformer or any coupled inductor in the topology significantly improves the power density. In this paper, when the DC-DC HHH converter increases voltage level to the desired value, a full-bridge converter provides required AC voltage to supply the PZETs. Simulation results demonstrate the effectiveness and high efficiency of the proposed converter during supplying a PZET. Also, a converter prototype is implemented to demonstrate the performance of the converter in the provision of soft switching as well as boosting.

The piezoelectric elements are the most important component of the acoustic transmitters in underwater communication systems. A special DC/AC power supply which produces an AC high voltage level with the frequency of the 30–50 kHz is required to energize the piezoelectric senders. The transmitters must send data in a few milliseconds and stop working about a second to receive data. For this reason, the designed converter must have acceptable power density to energize the piezoelectric actuators during data sending. On the other hand, the small size of the power supplies is another prominent characteristic of a converter because the communication system engineers prefer to have a device that occupies minimum space. In this paper, a DC-DC boost converter increases the input DC voltage level up to 5 times. After that, a full-bridge converter (FBC) is used to step up the boost converter output and provide the required AC voltage for the piezoelectric transmitters. A robust controller is designed to control the power converter switches. With respect to the proposed controller operation and construction, the converter can successfully drive the piezoelectric in noisy and harsh environments. Finally, the simulation and experimental results demonstrate the effectiveness of the designed combined converter and robustness of the proposed controller.

Rapid grows of solar energy systems in recent years makes the application of photovoltaic panels as energy source a prominent option. This is due to its sustainability, decreasing cost, very low pollution of the atmosphere. Pioneering research in the field that makes it the fastest growing energy source in the world. In Iran there is a lot of potential places for use of solar energy. On the other hand, a lot of these places are far from power grid and for their power they depend on diesel generators. In this paper we evaluated the implementation of solar energy with proposing a photovoltaic (PV) system. A case study was done on a small village in Bushehr province, Iran to assess alternative energy sources in comparison with solar energy. The two other options for power source beside solar panels which was considered in this paper is connecting the village to the power grid with a distribution line or installing diesel generators to power the village. It has been shown that the solar power can compete with its old rivals.

Wind turbine systems need a suitable control system to achieve the best performance and efficiency during its operation, which is dependent on many unpredictable factors. Grid side and rotor side converters play a vital role in the system, hence they require suitable control algorithms and appropriate control parameters. In this paper control parameters is determined by smart line search enhanced by teaching-learning based optimization (SLS-TLBO) algorithm, which improves the reliability of the wind turbine system. To acquire the accurate input power control in a wide range of wind speed, drive train control system needs an appropriate pitch angle controller. In order to reach this goal fuzzy logic controller, which is well known for its capability in dealing with nonlinear systems is applied to pitch angle controller. A 30MW Doubly Fed Induction Generator (DFIG) wind turbine in connection with the IEEE 6 bus power system has been analyzed to validate the proposed control algorithms. The simulation result proves the accuracy of the controllers.

Nowadays, the technology of manufacturing electrical vehicles (EVs) and hybrid electrical vehicles (HEVs) is the most important issue for manufacturers and consumers thereof. The main parts of these cars are their motors and battery packages. Low cost, ruggedness and suitable torque/mass ratio are some of the switched reluctance (SR) machine features that make it superior to permanent magnet and induction machines. The current ripple is the most important characteristic to insure the maximum battery life time. When SR machine works as a generator, the minimum ripple of output current and the level of generated power are considered to be of utmost importance. The suitable control strategy with a combined converter is proposed, in order to achieve these objectives. In this paper, a switched reluctance generator (SRG) operates in battery charging mode while working in HEV. Simulation results demonstrated the eligibility of the proposed control system and power converter to attain the acceptable charging current ripple in appropriate generated power.

With the advancements of photovoltaic panels Solar power plants extend their grip further in the power system every day. It is necessary that these new power plants work together with classic power plants. In this paper the simultaneous operation of a solar power plant with a steam power plant in a power system has been considered. The solar power plant operates with incremental conductance maximum power point tracking (IncCon MPPT) with direct control which is implemented through a boost converter. The inverter of solar power plant is manipulated to perform active power filtering in addition to converting DC power to AC. A d-q reference frame controller is used to perform the active power filtering. The steam power plant is also uses a PSS to stabilize the power system and damp power transients. A metaheuristic method called smart line search teaching learning based optimization (SLS-TLBO) is used to optimize the PSS parameter. In this paper, it is shown that the simultaneous operation of solar power plant can enhance the performance of the power system.

In this paper a new effectual optimization approach is proposed which optimizes the power system stabilizers (PSSs) parameters in a multi-machine power system. The PSS parameters are established for four PSSs which are linked to four synchronous generators. There is an increased demand for development of such algorithm, so that made researchers look for algorithms not only being metaheuristic, but also inherit desired properties of so-called deterministic approaches. To accomplish this objective, a novel method called smart line search (SLS) has been proposed in this paper and has been combined with Teaching Learning based optimization (TLBO). Being so new-found, SLS tries to take benefits of gradient methods using weighted stochastic selection approach which not only leads to unraveling of new local optimums, but also with a performance rather more speedy than conventional algorithms so far used. The performance of the proposed approach is also compared with other method. By observing the simulation results in two-area four-machine power system and compare with each of old algorithm, have been seen that new method is positively effective on damping time and also power frequency and oscillation when the fault occurs.