@article{ author = {khalili, mohamm}, title = {A model for consumer bidding considering its role in demand side management and micro-grids operation}, abstract ={By changing the method of power system operation from centralized to decentralized control due to the development of smart grids and micro-grids, the using of ability of consumers for demand management has attracted much attention. Due to presence of different loads in feeding priority, consumers can help the micro-grid operator for better operation and supply the critical loads. This can be done by offering the amount of shifable and curtailable load in different price values so, each consumer can determine the load priority for own demand in each period of time. Demand response programs have become one of the most effective methods to improve the demand profile and reduce the energy supply costs. In this paper, a new model for demand side bidding considering load priorities has been proposed. The results show the model is indeed capable of obtaining better demand side management.}, Keywords = {demand response, demand side management, load priority, micro-grid}, volume = {1}, Number = {2}, pages = {1-7}, publisher = {انجمن مهندسی بهره وری صنعت برق ایران}, url = {http://ieijqp.ir/article-1-60-en.html}, eprint = {http://ieijqp.ir/article-1-60-en.pdf}, journal = {Iranian Electric Industry Journal of Quality and Productivity}, issn = {2322-2344}, eissn = {2717-1639}, year = {2013} } @article{ author = {Shamsnia, Ali and Hosseini, Hossein and Danyali, Saee}, title = {Modeling and simulation of PV cell-wind turbine hybrid inverter with MPPT algorithms}, abstract ={In this paper a hybrid inverter with input energy sources of sun light and wind is proposed in which use of single inverter for both of the input sources, has reduced the cost and simplify the power circuit. Since P-V characteristics of PV cell and wind turbine are almost identical, MPPT algorithm has been employed for them both to absorb maximum power from these energy sources in different weather conditions. In addition, use of a new, combined MPPT algorithm for PV cells has solved problem of tracking MPP under low light conditions. DC-DC converters placed between the sources and a common DC link, make realization of the MPPT algorithms possible. In addition to presented parts, this system includes a backup hydrogen fuel cell. The hydrogen needed for this part is produced by a catalyzer when there is extra produced electrical energy than needed by load and at the case of fewer production than load demand, the stored hydrogen drives fuel cell to compensate shortage. Inverter of this system is a full bridge single-phase one driven by SPWM switching algorithm to regulate the output voltage under small load variations. Regulation of output voltage against larger load variations is obtained using fuel cell. Also, a new model for PV cell is proposed in this paper which imitates PV cell behavior much more closely than common current source model.}, Keywords = {Renewable energies, Maximum Power Point Tracking (MPPT), PV cell, Wind turbine with PMSG, Full bridge single-phase inverter, Voltage regulation}, volume = {1}, Number = {2}, pages = {8-18}, publisher = {انجمن مهندسی بهره وری صنعت برق ایران}, url = {http://ieijqp.ir/article-1-48-en.html}, eprint = {http://ieijqp.ir/article-1-48-en.pdf}, journal = {Iranian Electric Industry Journal of Quality and Productivity}, issn = {2322-2344}, eissn = {2717-1639}, year = {2013} } @article{ author = {Sedghi, Mahdi and Aliakbar-Golkar, Masoud and Haghifam, Mahmoud-Rez}, title = {Analysis and Predicting Vegetation-Related Failure Rate of Overhead Electrical Distribution Feeders using Neural Network and Factor Analysis}, abstract ={Failure rate is an important parameter in the reliability study of power systems. Failure rate of distribution feeders is usually considered as a constant parameter in power distribution systems study however in fact, it is a variable parameter which is dependent on various internal and external factors. The historical and statistic data is used to predict the variable failure rate. In this paper, the vegetation-related variable failure rate of overhead distribution feeders is considered for analysis and prediction. Whereas the collected statistic data usually contains practical errors and noises, here the Factor Analysis is used for data mining and removing the outliers. Then, a multi-layer artificial neural network is used to predict the failure rate. Moreover, the neural network is used to analyze the input data. Case studies of a typical 32-feeder distribution network show that the factor analysis and neural network methods emphasize their results. The proposed method can be implemented to reduce complexity, remove the outliers and increase reliability of the prediction.}, Keywords = {Distribution Network, Reliability, Power Quality, Factor Analysis, Data Mining}, volume = {1}, Number = {2}, pages = {19-28}, publisher = {انجمن مهندسی بهره وری صنعت برق ایران}, url = {http://ieijqp.ir/article-1-21-en.html}, eprint = {http://ieijqp.ir/article-1-21-en.pdf}, journal = {Iranian Electric Industry Journal of Quality and Productivity}, issn = {2322-2344}, eissn = {2717-1639}, year = {2013} } @article{ author = {mahdavimazdeh, mohammad and bagherpour, morteza and soofeypour, azadeh}, title = {Evaluation of the effect of qualitative variables in forecasting Cost Estimate At Completion of projects}, abstract ={Accurate forecasting of an ongoing project cost is a major issue in project monitoring. One of the challenges faced by project managers is selection of the most accurate cost Estimate at Completion (EAC) method to improve tracking their projects. To assist in the task, This research considers the effect of some qualitative variables such as delay in payment, weather condition and material availability in the model. Besides, one forecasting algorithm is presented to obtain more accurate solutions. The model is successfully implemented through a case study.The results for model are shown to be sufficiently reliable for general application of the forecasting method.}, Keywords = {Cost, Earned Value Management, Estimate At Completion, Performance, Project monitoring, forecasting }, volume = {1}, Number = {2}, pages = {29-37}, publisher = {انجمن مهندسی بهره وری صنعت برق ایران}, url = {http://ieijqp.ir/article-1-26-en.html}, eprint = {http://ieijqp.ir/article-1-26-en.pdf}, journal = {Iranian Electric Industry Journal of Quality and Productivity}, issn = {2322-2344}, eissn = {2717-1639}, year = {2013} } @article{ author = {}, title = {Solving Reactive power dispatch and planning via multi objective Pareto Honey Bee Mating Optimization based fuzzy theory}, abstract ={The key of Reactive Power Planning (RPP), or Var planning and reactive power dispatch, are the optimal allocation of reactive power sources considering location and size. Traditionally, the locations for placing new Var sources were either simply estimated or directly assumed. Recent research works have presented some rigorous optimization based methods in RPP. The reactive power dispatch and planning is a large-scale non-convex, nonlinear programming (NLP) problem with real and discrete variables that presents a high degree of complexity for application in real electric power systems (EPS). This paper addresses an improved Honey Bee Mating Optimization (HBMO) with strength Pareto front to find the feasible optimal solution of the RPP problem with various generator constraints in power systems. For practical generator operation, many nonlinear constraints of the generator, such as ramp rate limits, generation limits, transmission line loss and non-smooth cost functions are all considered using the proposed method. Effectiveness of the proposed method is demonstrated for two different systems, including 6 and 54 unit generating in comparison with the performance of the other recently optimization algorithms reported in the literature in terms of the solution quality and computation efficiency. The results analysis confirms that the proposed approach has an excellent capability to determine optimal solution of the RPP problems over the other existing methods and enhances efficiently the solutions quality of the power systems.}, Keywords = {HBMO, Pareto front, Optimization, Reactive power planning, Non-linear constrains.}, volume = {1}, Number = {2}, pages = {38-48}, publisher = {انجمن مهندسی بهره وری صنعت برق ایران}, url = {http://ieijqp.ir/article-1-39-en.html}, eprint = {http://ieijqp.ir/article-1-39-en.pdf}, journal = {Iranian Electric Industry Journal of Quality and Productivity}, issn = {2322-2344}, eissn = {2717-1639}, year = {2013} } @article{ author = {Samadi, Mahdi and Javidi, Mohammad hossein and Ghazizadeh, Mohammad Sadegh}, title = {Dynamic Modeling of Investment on Generation Expansion Planning Considering Demand Response}, abstract ={Attention has been paid to the Demand Response (DR) programs in recent years to improve the power system operation. Demand Response affects market clearing price, which is the main motivation for investment, and thus the trend of investment on generation expansion will be affected. So far, the demand has been considered inelastic for modeling the investment on generation expansion. However, increasing the deployment of smart grid has waived this assumption. In this paper, we have used stochastic dynamic programming for modeling the generation expansion problem. We have considered both the renewable resources and demand response in modeling. In the proposed model, the uncertainty in generation and the accuracy of the price responsive demand performance are considered. In this regard, the market clearing price is determined by interaction between price and the price responsive demand. Some long-term indices are proposed and using the simulation results, they are evaluated. The achieved results, quantitatively confirm that the demand response results in decreasing the price and the outages and therefore improving the reliability.}, Keywords = {Demand Response, Generation Investment, Renewable energy, Stochastic Dynamic Programming}, volume = {1}, Number = {2}, pages = {49-57}, publisher = {انجمن مهندسی بهره وری صنعت برق ایران}, url = {http://ieijqp.ir/article-1-43-en.html}, eprint = {http://ieijqp.ir/article-1-43-en.pdf}, journal = {Iranian Electric Industry Journal of Quality and Productivity}, issn = {2322-2344}, eissn = {2717-1639}, year = {2013} } @article{ author = {AhmadiJirdehi, Mehdi and TarafdarHagh, Mehrdad and Zare, Kazem}, title = {Simultaneous Process of Measurements and Parameters Errors in Dynamic State Estimation}, abstract ={The accurate performance of the state estimation (SE) in power systems depends on the correct values of inputs including of measurements and lines parameters. On the other hand, errors occurrence in measurements and lines parameters values is not out of prospect which if these errors are not identified and corrected, inaccuracy estimation of state variables are obtained. In this paper, an efficient and useful method is proposed in dynamic state estimation (DSE) based on filter kalman (KF) that is capable to identify and correct of simultaneous measurements and lines parameters errors in power system. In the proposed method, after the errors identification by normalized residual and Lagrange multipliers vectors, the correct values of erroneous measurements and lines parameters using proposed functions substituted of incorrect values. Finally, the proposed method is applied on IEEE 14-bus test system in various scenarios of errors occurrence and various indexes are presented for evaluation of the proposed algorithm. Simulation results in these scenarios show the very high accuracy and efficiency of the proposed algorithm.}, Keywords = {Dynamic state estimation, Kalman filter, Identification and correction of errors, Measurements and lines parameters errors}, volume = {1}, Number = {2}, pages = {58-67}, publisher = {انجمن مهندسی بهره وری صنعت برق ایران}, url = {http://ieijqp.ir/article-1-50-en.html}, eprint = {http://ieijqp.ir/article-1-50-en.pdf}, journal = {Iranian Electric Industry Journal of Quality and Productivity}, issn = {2322-2344}, eissn = {2717-1639}, year = {2013} }