JOURNAL OF ENERGY MANAGEMENT
Year:2019 | Volume:9 | Issue:2 |Papers Count:10

In this paper, a bidirectional DC-DC converter with high power density for energy storage application is proposed. The presented converter provides power transfer in both directions only with adjusting phase shift angle. Zero voltage switching (ZVS) in both turn on and turn off moments of all switches is the major capability of the converter that makes it suitable for high power applications. ZVS of the converter is provided without any auxiliary devices. High frequency transformers are employed in the converter construction to match the converter two sides voltage. Moreover, transformer leakage inductance along with external auxiliary inductance acts as energy storage in power transfer from one side of the converter to the other side. Operation principle of the converter in steady state is analyzed and then, its dynamic model is derived. ZVS criteria of the proposed converter are studied and finally, experimental measurement results of laboratory scale prototype are presented.

To offer indoor services to occupants in the context of smart buildings, one can’ t help considering information concerning the identity and location of the occupants. This paper proposes an indoor positioning system (IPS) based on Wi-Fi fingerprint and K-nearest neighbors (KNN) methods. The positioning of a mobile device (MD) using Wi-Fi technology involves online and offline phases. In this paper, the offline phase includes data collection in WiFi-based Nonintrusive SMS (WinSMS) context while the online phase involves updating the structure of the collected radio map and online positioning. In online positioning, the proposed Weighted Differential Coordinate Probabilistic-KNN (WDCP-KNN) method based on probabilistic weighting of generalized Reference Points (RPs) and differential coordinates is used. Experiments in a complex indoor environment with real values indicate that the proposed method reduces the positioning error compared to other methods and is also comparable in terms of computational complexity.

The design of three-phase induction motors is a challenge in electrical engineering. Therefore, new design techniques are continuously provided. Since the design of the induction motors is carried out for different purposes, it is difficult to find a method that can addresses all the targets. Nowadays, the normal methods used to solve multi-objective problems are the optimization strategies. In this paper, the meta-heuristic optimization method has been used to design the squirrel cage induction motors with the aim of increasing efficiency and reducing costs. In this way, modeling of induction motor is done accurately and to solve this optimization problem, a new method of Multi-objective optimization of the Salp Swarm Algorithm (MSSA) has been provided. This algorithm is inspired by the social behavior of Salps. The proposed method is applied to the data of an induction motor of 2. 5 KW with IE2 efficiency. The results of single-objective and multi-objective optimization exhibit that the design of an induction motor with two objective functions increases the efficiency and reduces the cost. Additionally, the MSSA algorithm is compared with the methods of genetic algorithms for indirect sorting (NSGA-II) and multi-object particle optimization algorithms (MOPSO). The MSSA algorithm has a convergence rate and a set of optimal response sets which demonstrates a good performance in optimal design of the induction motor to increase efficiency and reduce its costs.

Condition monitoring (CM) and Fault Detection (FD) of wind turbine lead to increase in reliability and availability of turbine. IGBT open circuit of wind turbine converter will bring about depletion in output current of converter and as a result, reduction in production of wind turbine power. In this research, back to back converter IGBT open-gate fault for wind turbine based on DFIG is detection at first and then it is isolated. The proposed method is low cost and it does not use extra sensor for fault detection and isolation. Fault detection is based on model-based strategy, for residual generation an observer based on Kalman model are used, this model is based on the extraction grid side and rotor side DFIG three-phase currents state matrix and then residual evaluation is conducted. Fault location is determined on signal-based strategy and mean feature extraction of time signal. To evaluate the suggested structure, a 2. 5MW wind turbine simulator is used according to real data. Simulations have shown that the proposed method, diagnostics the synchronous and multiple faults in one LEG or different LEGs of grid side and rotor side.

The integrated planning of distribution system reveals a complex and non-linear problem being integrated with integer and discontinues variables. Due to these technical and modeling complexities, many researchers tend to optimize the primary and secondary distribution networks individually which depreciates the accuracy of the results. Accordingly, the integrated planning of these networks is put forward to guarantee reliable and accurate results. Different approaches are contemplated for distribution network planning studies. Genetic algorithm stands as one the widely deployed approaches. Due to the existing uncertainties in probabilistic planning of large distribution networks, the conventional genetic algorithm is aligned with high computational burden and hence, might lose its efficiency. To annihilate these issues, the ongoing study contributes to an improved approach ending to reduced computational efforts and accurate result. Being inspired based on a traditional approach for placement of distribution transformers and mixing it with the genetic algorithm, a heuristic method is devised which reduces the search space, sensibly. Accordingly, the optimal solutions are more swiftly attained in probabilistic planning of distribution networks. To represent the existing uncertainties, a set of scenarios is defined based on parameters probability distribution functions. The aggregated effects of these scenarios are introduced as the expected values of the investigated variables. Efficiency of the proposed approach is explored on two test systems within which the obtained results are discussed in depth.

Today, smart grids are one of the important topics in the field of electrical engineering. In this paper, after identifying the communication layers among the components of a smart home in the introduction, some of the most important communication protocols ruling will be abbreviately discussed over the smart homes. Then, applying the household electrical load management program by smart homes, the effectiveness of this method will be showed in reforming power consumption, especially during peak hours. To clarify this issue, a house with a certain number of electric vehicles is studied in three different modes and the black-out effect of the load has been also considered in one of these three modes. Therefore, the results will be discussed using the accurate modeling of the problem regarding household electrical load management and performing simulations via GAMS software, and consequently the effects of considering different electricity tariffs on the proposed method results will be also analyzed.

In this research, a comparison of biodiesel produced by ultrasound and heat methods was investigated. Methanol was used as the alcohol with molarity 3, 6 and 9 and KOH 0. 5, 1 and 1. 5 wt. % As a catalyst. In ultrasound technique, five vibrating pulse levels and three time levels were used. The results indicate that biodiesel produced by ultrasound in some properties includes a flash point of about 9% increased and the amount of viscosity, carbon residue and water content in fuel decreased by 27%, 50% and 5%, respectively. The biodiesel cloud point produced by the heat treatment method-2 and ultrasound waves 7 was obtained. It should be noted that the fuel produced in both methods can be used as a standard fuel in the engine. It was also found that ultrasonic waves are more appropriate than heat treatment due to the need for less time and better quality characteristics.

In this paper, a forced-circulation solar water heater system is simulated for different hot water consumption profiles using flat plate collectors as well as evacuated tube collectors. The profiles studied are the actual samples of hot water consumption profiles for different commercial centers and institutions. Dynamic simulation outputs of system thermal performance are used as economic analysis inputs of solar water heater to evaluate the effect of hot water consumption profiles on the economic performance of system. The results show that profiles allocating large amounts of hot water consumption from 6 to 10 a. m. increase the cost of providing required energy for the auxiliary system. As a result, the system payback time increases. According to the simulation findings, changing profiles in the system can moderately increase the annual life cycle saving by 61% and 31% for the flat plate and evacuated tube collectors respectively.