فهرست مطالب

International Journal of Smart Electrical Engineering
Volume:6 Issue: 4, Autumn 2017

  • تاریخ انتشار: 1396/08/23
  • تعداد عناوین: 6
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  • Hamed Haggi *, Fardin Hasanzad, Masoud Golkar Pages 127-134
    Environmental concerns and depletion of nonrenewable resources has made great interest towards renewable energy resources. Cleanness and high potential are factors that caused fast growth of wind energy. However, the stochastic nature of wind energy makes the presence of energy storage systems (ESS) in wind integrated power systems, inevitable. Due to capability of being used in large-scale systems and the lower capital cost, compressed air energy storage (CAES) is one of the favorable storage systems. This paper proposes a model for security-constrained unit commitment (SCUC) with integration of large-scale CAES and wind generation. The SCUC problem is formulated as a mixed-integer linear program (MIP) in which a lossless dc representation of transmission network is used and it has been solved by CPLEX solver using General Algebraic Modeling System (GAMS) optimization package. The IEEE RTS 96-bus systems is used to validate the performance of the proposed method.
  • MohammadEsmaeil Nazari *, Morteza Mohammad Ardehali Pages 135-142

    The integration of renewable wind and pumped storage with thermal power generation allows for dispatch of wind energy by generation companies (GENCOs) interested in participation in energy and ancillary services markets. However, to realize the maximum economic profit, optimal coordination and accounting for reduction in cost for environmental emission is necessary. The goal of this study is to develop a simulation model for maximizing economic profit from coordination of renewable wind and pumped storage with thermal power generation for a GENCO with participation in energy and ancillary services markets with considerations for environmental emission and uncertainty associated with wind power based on a newly developed GA-based heuristic optimization algorithm. It is determined that for a GENCO with 13 MW wind farm capacity and 1662 MW thermal units, for meeting an average demand of 1129 MW, the utilization of 120 MW pumped storage in a coordinated wind-pumped storage-thermal system results in reduction of environmental emission by 13.54%, which leads to an increase in profit by 2.10%, as compared with operation with no pumped storage unit.

    Keywords: Coordinated wind-pumped storage-thermal, energy, spinning reserve markets, environmntal emission, Genetic Algorithm, wind uncertainty
  • Morteza Aien *, Mahmud Fotuhi Firuzabad Pages 143-151
    Hastening the power industry toward smart operation juxtaposed with the unrivaled restructuring and privatization agendas, some of the ubiquitous smart grid advantages are glanced more and more. Recently, the vehicle to grid (V2G) technology, as one of these beneficial aspects, has found a worldwide attention due to its important advantages. The V2G technology can raise the system operation efficiency, if well committed. Unit commitment (UC) is an operation problem to find the optimal schedule of generation units. In a typical UC problem, the generation units have two operational states, producing power or not, while a V2G may have an additional state i.e. consuming power due to its capability of having bi-directional power flow. In this work, this feature is modeled by the third state i.e. -1 for V2G power consumption. In addition, this work considers different cost function coefficients for different time intervals. The binary particle swarm optimization (BPSO) method is used to solve this sophisticated problem. The proposed methodology is justified through two dimensionally different case studies. What makes the results particularly interesting is that when V2Gs are taken into account, the total operation cost of the system decreases and also the V2G owners can obtain considerable profits.
    Keywords: particle swarm optimization, Plug-in electric vehicles, Unit commitment, vehicle to grid
  • Amin Ranjabaran *, Mahmoud Ebadian, MohammadSadegh Ghazizadeh Pages 153-161

    In this paper, a new control strategy is proposed for implementation in low-voltage microgrids with balanced/ unbalanced load circumstances. The proposed scheme contains, the power droop controllers, inner voltage and current loops, the virtual impedance loop, the voltage imbalance compensation. The proposed strategy balances the voltage of the single-phase critical loads by compensating the imbalanced voltage drop on the feeders. In addition, this strategy has also shown to be capable of restoring critical loads’ voltage to nominal values. This method also shares the real and reactive load accurately between DG units, based on their capacity. The simulation results in MATLAB /SIMULINK environment show the efficiency of the proposed approach in improving power sharing among DG units and decreasing voltage imbalance

    Keywords: islanded microgrid, droop control method, critical load, voltage imbalance compensation
  • Seyed MohammadAli Naseri Gavareshk *, Somayeh Hasanpour Darban, Amin Noori, Mahdi Besharatifar Pages 163-169

    Restructuring in the power industry is followed by splitting different parts and creating a competition between purchasing and selling sections. As a consequence, through an active participation in the energy market, the service provider companies and large consumers create a context for overcoming the problems resulted from lack of demand side participation in the market. The most prominent challenge for customers on demand side, is bidding strategy selection manner for attending in the competitive market. In this regard, they attempt to pay the least expense for purchasing the energy, while tolerating the least risk. In this paper, bidding strategy of service provider companies and the large consumers in the power market is proposed under the eligibility traces algorithm. In this algorithm, the demand side customers are considered as agents of Reinforcement Learning (RL). These agents learn through interaction with environment to bid such that earn the highest benefit.

    Keywords: Power market, bidding strategy, demand side, service provider companies, reinforcement learning, elgibility traces
  • Vahid Chakeri *, Mehrdad Tarafdar Hagh Pages 171-175
    With the dramatic growth of nonlinear loads, it is desired to improve active filters performance and enhance their capacity. One of the most favorable methods is applying distributed active filter system (DAFS) in which leads to minimizing the cost, weight & size .The main purpose of this paper is to determine the locations and sizes of distributed active filter system (DAFS) With emphasis on reducing losses.    Minimizing the total losses can have a significant impact on reducing costs. Therefore, placement has been studied by total line losses & minimized loss allocation while satisfying harmonic voltages, total harmonic voltage distortions within IEEE-519 recommended limits. Finally, A typical 37-bus distribution system is selected to verify the validity of the proposed procedures.
    Keywords: Distributed active filter system, particle swarm optimization, Optimal placement, Total harmonic distortion, Loss allocation, Loss reduction