فهرست مطالب

Majlesi Journal of Energy Management
Volume:6 Issue: 2, Jul 2017

  • تاریخ انتشار: 1396/03/10
  • تعداد عناوین: 5
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  • Rasoul Sarvestani, Ehsan Esfandia, Mohammadreza Zareh Pages 1-8
    This paper presents a novel approach based on fuzzy logic controller to track optimum operational point of dish-stirling system in uniform irradiance condition. The proposed method considers all details of system including thermo mechanical and electrical aspects of dish stirling system where previous studies use a simple model to assess this issue. Multi parallel dish stirling systems have more extremum operation points in partially condition system. Hence, this study utilize fuzzy logic controller to find global maximum power point tracking of system when all aspects of system are taken in to account. Finally In order to validate the proposed method, a comprehensive case study has been conducted on dish stirling systems. Simulation results show the accuracy of the proposed method in different conditions in comparison with previous methods.
    Keywords: Dish Stirling System, Maximum Power Point Tracking, Partially Shaded Condition, Particle Swarm Optimization
  • Ali Rostami, afshar bali, asghar khosroabadi, Koroush shahbazi Pages 9-15
    This paper presents a new passive parameter for islanding detection of distributed generation (DG), based on processing the rate of change of active power over reactive power (dP/dQ) parameter with discrete Fourier transform (DFT). During the islanding and non-islanding events, the active and reactive powers at DG output changes. However, in grid-connected mode the voltage and frequency of power system are determined by main grid, therefore, there is no considerable change in the active and reactive powers at DG output. While, in islanding mode the voltage and frequency of the islanded power system are determined by DG units, therefore, if there is significant value of the power mismatch between generation and load demand, the output powers of DG have great changes. However, if there is no difference between the DG generation and total load demand, the power deviations at DG output cannot detect the islanding and other events accurately. Hence, the ratio of rate of change of active power to rate of change of reactive power and for its analysis the DFT is used. The performance of the proposed parameter has been tested on the real power system using MATLAB/Simulink. The understudy DG is synchronous type and installed in the west regional electric company (WREC) network. Simulation results show that, the proposed parameter can precisely differentiate between islanding and transient events and it reduces the non-detection zone (NDZ) up to 0.02 MW and 0.02 MVAr power mismatch. The NDZ of the proposed parameter is very smaller than anti-islanding protection relays of the understudy DG.
    Keywords: Islanding Detection, Active Power, Reactive Power, Discrete Fourier Transform
  • Morteza Khalilian, Goretani, Mohammadreza Gholamzadeh Pages 17-25
    Energy crisis is one of the issues that is of great interest to today's societies. Optimizing the energy system in terms of resource diversity and the size of each unit can greatly improve the economic and technical efficiency of the feeding system. In this paper, a feasibility study and also economic optimization for a system independent of the network for the central regions of Iran is presented (Case Study of Varzaneh Region). HOMER software has been used for measurement as well as optimization tools. Renewable and non-renewable energy sources (fossil fuels), energy storage methods, and the ability to use them on a cost-efficient basis. Sensitivity analysis is performed for wind speed, solar radiation and fuel costs. An agricultural farm with an energy consumption of 10 kWh/d and a maximum load of 1 kW load is considered as an autonomous load.
    Keywords: Renewable Energy Resources, Battery, Wind Turbine, Energy Storage System, Fossil Fuels
  • Gholamreza Ghorbani Pages 27-34
    Nowadays, planning for the optimal use of electrical vehicles and their connection to the power grid has become of growing interest. The load resulting from long charging time requirements of such vehicles would lead to increased load of distribution grid and endanger system security and extra voltage across the distribution grids. On the other hand, the penetration of photovoltaic resources and uncertainty in their generation would affect the quality of consumers’ electricity. In order to solve this problem, the present paper applies the smart load structure with a back-to-back converter for voltage adjustment so that the grid would be able to support the exchange of active power with load-serialized converter. The quantities of active and reactive power in this system are determined using the possible load dispersion and Monte Carlo simulation. The simulation results indicate the efficiency of this method in improving the quality of consumers’ electricity.
  • Ali Moghtadaei Esfahan, Mohammad Hosein Vafaee Pages 35-40
    This paper proposes a new application with the aim of determining the optimum Distribution Static Compensator (DSTATCOM) capacity and location in radial distribution systems. In the process of optimization, the presence of distributed generations (DGs) is also considered as a constant source of active power production with various compounds. Optimization includes three functions of reducing the total power losses, improving the voltage profile and minimizing the cost of installation of DSTATCOM. To solve this problem, multi-objective particle swarm optimization algorithm (MOPSO) has been used. This method uses Pareto optimal solutions to solve the problem. In addition, a fuzzy-based mechanism is employed to extract the best solution among three different objective functions. The proposed method has been implemented on the IEEE 33 bus radial distribution system (RDS) and the results obtained by the proposed method are compared with the other existing technique
    Keywords: radial distribution system, distribution static synchronous compensator (DSTATCOM), multi-objective particle swarm optimization algorithm (MOPSO), fuzzy-based mechanism