Majlesi Journal of Energy Management <p>The scope of MJEM is ranging from mathematical foundation to practical engineering design in all areas of energy management. The editorial board is international and original unpublished papers are welcome from throughout the world. The journal is devoted primarily to research papers, but very high quality survey and tutorial papers are also published.</p> <p>There is no publication charge for the authors.</p> Majlesi Publications Corporation en-US Majlesi Journal of Energy Management 2322-3073 Frequency control of load in island microgrid by using the model pridictive control (MPC) <p>One of the most important issues of the microgrid in the form of seperation from network is power, the frequency and voltage control. In this paper, a control-based method of model pridictive control is presented for control of load frequency in the microgrid network. The proposed controller is located in the second frequency control loop and, by applying the control signal to the sources, the frequency disturbances are mimicd after the power changes in the microgrid. The simulation results in the MATLAB / Simulink environment show that the proposed controller has a better performance in comparison with the proportional-integral controller based on Zigler-Nicoles based PI (ZN-PI), proportional-integral controller based on fuzzy logic,(Fuzzy-PI), proportional-derivative-integral controller of fractional times base on Canonical Particle Swarm Optimization based Proportional Integral differential (CPSO-PID) and proportional-derivative-integral controller based on optimal particle algorithm, so that 1) frequency fluctuations decreases in terms of the oscillation range and its number effectively; 2) it is more resistant than the certainty of the microgrid parameters; and has better function in the parameters change to the other one.</p> Alireza Sedaghati ##submission.copyrightStatement## 2018-11-02 2018-11-02 7 4 Energy management and optimization in smart homes with two-way interchange of energy between electric vehicle and smart home. <p>In this paper, two basic steps are taken to optimize and manage the energy of the smart home . In the first step, To provide a mathematical model and energy pattern to determine the temperature of the air conditioner thermostat with regard to climate change, so that ultimately the cost of consumed electricity is minimized and the welfare level of the smart home inhabitants will not fall below the definition. For this purpose, the neural network method has been estimated to have an instantaneous price for electricity in the coming days, with external temperature information outside the home and the current price of electricity in recent days. Then, using the PSO algorithm, the thermostat setting temperature is determined to optimize energy consumption and minimize the cost of consumable electricity. In the second step, while extracting the equivalent electric vehicle load and power consumption to charge it, the technical and economical analysis of providing smart home power supply through the storage battery of the electric vehicle is considered, so that according to the instantaneous electricity price calculated in the first step At a time when the cost of purchasing electric power from the &nbsp;electric network is high, the battery will provide electric power to the smart home power. Economic analysis results show savings on the cost of purchasing electrical energy with the proposed idea of this paper.</p> <p>&nbsp;</p> Hossein Tavakoli Seyed mehdi Hakimi ##submission.copyrightStatement## 2018-12-14 2018-12-14 7 4 DFIG-based wind turbine system using four-level FSVM strategy <p><strong>Abstract—</strong>Traditional direct vector command (DVC) structures which include proportional-integral (PI) regulators of a doubly fed induction generator (DFIG) driven have some disadvantages such as parameter tuning complications, mediocre dynamic performances and reduced robustness. Thus, based on analysis of the DFIG model supplied by new modulation technique, this article addresses a four-level space vector modulation (SVM) based on fuzzy logic algorithm (FSVM). The classical DVC command with SVM technique has large ripples on the stator active and stator reactive developed by the DFIG. In order to solve this disadvantage, the DVC command with FSVM technique is proposed. Simulation results show the effectiveness of the proposed command scheme especially in power ripples behavior, reference tracking test and robustness against generator parameters variations.</p> Habib BENBOUHENNI BOUDJEMA Zinelaabidine Abdelkader BELAIDI ##submission.copyrightStatement## 2018-11-02 2018-11-02 7 4 Determining the location and capacity of combined heat and power generation units (CHP) andstatic voltage compensator (SVC) in energy hub <p>The purpose of present study was to optimal positioning of SVC and CHP simultaneously, in a way that lead to highest profit and the lowest losses in the system.This method increases the efficiency of entire transmission system and has a significant effect on the power quality and energy hub. For this purpose, neural network method was used to optimize energy cost and hub.Neural network is considered as an intelligent and efficient method of optimization and the results of simulations indicated the effectiveness of the method in optimized positioning</p> Mehdi Rezaeiheydari Ehsan Esfandiyari ##submission.copyrightStatement## 2018-11-02 2018-11-02 7 4 Various Pollutions of Power Line Insulators <p class="MJEE-Abstract">This paper deals with all types of pollutions for power line insulators. In many different references including IEEE standards and various articles, a list of different types of pollutions are introduced. But those lists are not complete and other cases should be added to them. In this paper, all parts of an insulator are introduced and different types of insulator pollutions and the reasons behind existence of these pollutants are identified as well. Furthermore, appropriate pictures for various types of insulator pollutions are provided to give an accurate understanding of these pollutions for future works, and this also make us able to adopt preventive measures according to the type of pollution in order to reduce or remove the pollution resources of insulators and other system equipment.&nbsp; Moreover, with the aim of washing polluted insulators these pictures help to choose a suitable fluid with low cost, significant clearing feature and desirable for environmental applications.</p> <p>&nbsp;</p> <p><strong>&nbsp;</strong></p> Morteza Hadipour Mohsen Aghazadeh Shiran ##submission.copyrightStatement## 2018-11-02 2018-11-02 7 4 Impact of Renewable Energy Resource Based Distributed Generation on Distribution Network Loss and voltage Profile <p class="MJEE-Abstract"><span lang="EN-US">This article addresses an optimal allocation of Distributed Generation (DG) in a distribution network for minimization of network loss due to the active component of current. For this work, Combined Power Loss Sensitivity (CPLS) analysis is utilized to identify the appropriate position/location <span style="letter-spacing: -.3pt;">of </span>DG. <span style="letter-spacing: -.2pt;">However,</span> the appropriate size of<span style="letter-spacing: -.55pt;"> DG</span> is determined through a nature-inspired; population-based Bird Swarm Algorithm (BSA). Secondly, the influence of DG penetration level on network loss and voltage profile is investigated and presented. In this regard, three types of DG technologies (solar, wind and biomass) are developed for loss reduction. The performance of CPLS and BSA methodology is successfully evaluated on IEEE 33 and 69 bus standard systems. The results attained with the planned approach are compared with the existing methods in the literature. </span></p> Sabarinath G ##submission.copyrightStatement## 2019-02-02 2019-02-02 7 4