I am a newly graduated student from the Power Engineering Department, Electrical and Computer Engineering Faculty, K.N. Toosi University of Technology. My research interests include power electronic applications in power systems, harmonic assessment, power electronic devices interaction, probabilistic evaluation of harmonics and voltage unbalance, distributed and restructured environment and its associated problems. For more information about my research please visit the research page of my personal home page.
Abstract: Renewable distributed generation introduced as an environmental friendly alternative energy supply while it provided the power system with ever-growing technical benefits such as loss reduction and feeder voltage improvement. The evaluation of the effects of small residential photovoltaic and wind DG systems on various system operating indices and the system net load is complicated by both the probabilistic nature of their output and the variety of their spatial allocations. The increasing penetration of renewable distributed generation in power systems necessitates the modeling of this stochastic structure in operation and planning studies. An advanced stochastic modeling of the system requires multivariate uncertainty analysis involving non-normal correlated random variables. Such an analysis is to epitomize the aggregate uncertainty corresponding to spatially spread stochastic variables. In this paper, an integration study of photovoltaics and wind turbines, distributed in a distribution network, is investigated based on the stochastic modeling using Archimedean copulas as a new efficient tool. The basic theory concerning the use of copulas for dependence modeling is presented and focus is given on an Archimedean algorithm. A comprehensive case study for Davarzan area in Iran is presented after reviewing Iran's renewable energy status. This study shows an application of the presented technique when large datasets, assuming 10-min interval between data points of PV, wind and load profiles, are involved where a deterministic study is not trivial.
Abstract: Additional uncharacteristic harmonics can be modulated through the STATCOM at the point of common coupling (PCC) under unbalanced non-linear loads. This paper suggests a harmonic-domain model in which the injected harmonics at the PCC is realistically evaluated. The model can be easily run with other algorithms such as Monte Carlo simulation. Further, a semi-stochastic predictive method is proposed for three-phase voltage unbalance and harmonic performance of STATCOM based on the measured data obtained from a low-voltage distribution network. Finally, the modeled STATCOM is linked with the distribution substation, applying the proposed voltage unbalance modeling to evaluate aggregate harmonics injection at the PCC.
Abstract: This book presents a set of comprehensive and relevant solutions for Electrical Engineering advanced problems which appeared in the Masters degree entrance exams in Iran by National Measurement Organization.
Abstract: This paper introduces and analyzes an extraordinary crisis in which an extremely cold weather covered a major area of the Iran during winter of 2007. This caused serious problems for the country’s energy sector and electricity distribution in Iran. This crisis, particularly in the energy distribution sector, left uncompensated for two months. Here, this situation is discussed in detail in view of the relevant data and information. It is also presented detailed events in some regional distribution areas. To further examine the issue, risk management weaknesses at that time horizon are discussed and somehow criticized. Finally, some remarks and proposals are proposed which could improve the performance of the energy generation and distribution sector during such a crisis.
Abstract: A successful asset management during time horizons of mid- and long-term strongly depends on a proper representation for the impacts of large-scale stochastic generation and flexible demand on network design. The use of stochastic methods is necessarily unavoidable in addition to the basic deterministic methods due to the aggregate uncertainty of stochastic generation outputs. In this paper, the variability of renewable generation is considered as part of the load variation. This evaluation of flexibility is a fundamentally important step, as it has a direct impact on the system’s operating costs. According to this new scheme, the contribution of this paper is centred on characterizing the variability of the stochastic distributed generation (SDG) power output more precisely by considering the realistic interdependence structure between them and between the consumers’ load profiles. This subject is thoroughly examined using some illustrative context about sizing of a small power system components to reach an optimal total cost considering large-scale wind power uncertainty.
Abstract: Anticipated high penetration of stochastic energy flows throughout the stand-alone micro grids should be optimized by using hybrid stochastic-heuristic simulation methods. It is well treated, in this way, both the uncertainty caused by the renewable power production and the non-linearity of the objective function. In this paper, a hybrid simulation procedure is employed to the problem of sizing in a hybrid power system considering wind power production uncertainty. The developed algorithm consists of a particle swarm optimization (PSO) subroutine embedded in a multivariate Monte Carlo simulation. This study is performed for Kahnouj area in south-east Iran. The system consists of fuel cells, wind turbines, some electrolyzers, a reformer, an anaerobic reactor and some hydrogen tanks. The system is assumed to be stand-alone and uses the biomass as an available subsidiary energy resource. The main objective is to minimize the total costs of the system in view of wind power uncertainty to secure the demand. PSO algorithm is used for optimal sizing of system's components for each simulation run used by Monte Carlo method. Besides, several statistical modeling and analyses are performed prior to the simulation and later on to properly interpret the results.
Abstract: This paper introduces “Copulas” analytical tool for multivariate modeling of stochastic harmonic generation mechanism. Additional stochastic harmonics can be modulated through the power inverters at the point of common coupling (PCC) under unbalanced non-linear loads. The proposed multivariate unbalance modeling via copulas is applied to evaluate aggregate harmonics injection at the PCC. Copulas have become a popular analytical tool in multivariate modeling, where recently has been applied in many fields. Here, the contributions of copulas to Monte Carlo method are described. It is first come up with modeling unbalance of three-phase active and reactive powers at a distribution substation. To introduce a firmer basis for the suggested procedure, the investigation is carried out based on the measured data for pursuing further analysis that is associated with simulating statistical correlation between stochastic harmonics and realistic unbalanced conditions for a static compensator (STATCOM) at the point of common coupling (PCC).
Abstract: The probabilistic study of harmonics is becoming an important issue in power systems since the usage of power electronic devices is necessarily unavoidable. This has become more important due to the need for more reliable harmonic studies which consider the stochastic nature of produced harmonics in electrical power systems. This provides a probabilistic remedy that needs to be incorporated in the harmonic analyzes. This paper briefly reviews the related literature, and presents a tangible view on the probabilistic aspects, methods and standards of harmonics in electrical power systems. Then, a semi-stochastic method is proposed to predict and simulate the three-phase voltage unbalance, leading to an analytical tool for prediction of harmonic performance of STATCOM. This method is developed based on the measured data obtained from a low voltage distribution network. Finally, the modeled STATCOM is linked with the distribution substation, applying the proposed voltage unbalance modeling to evaluate uncharacteristic harmonics injected by the STATCOM at the PCC. This investigation on STATCOM illustrates the proper application of the probabilistic methods in practical and theoretical situations.
Abstract: Power systems use STATCOM for compensating purposes that is subjected to the high switching frequencies. Various PWM techniques make selective harmonic elimination possible, which effectively control the harmonic content of voltage source inverters. On the other hand, distribution systems have to supply unbalanced nonlinear loads, transferring oscillations to the DC-side of the converter in a realistic operating condition. Thus, additional uncharacteristic harmonics are modulated through the STATCOM at the point of common coupling (PCC). This requires more attention when switching angles are calculated offline using the optimal-PWM technique. This paper suggests a harmonic-domain model in order to realistically evaluate the injected harmonics at the PCC. This model properly takes into account the DC capacitor effect, effects of other possible varying parameters such as voltage unbalance as well as network harmonics, and effects of operating conditions on the STATCOM harmonic performance. The model is programmed, and can be easily run with other algorithms such as Monte Carlo simulation. Further, a semi-stochastic method is proposed to predict and simulate the three-phase voltage unbalance, leading to an analytical tool for prediction of harmonic performance of STATCOM. The predictive method is developed based on the measured data obtained from a low-voltage distribution network. Finally, the modeled STATCOM is linked with the distribution substation, applying the proposed voltage unbalance modeling to evaluate aggregate harmonics of the load.
Abstract: A New technique for modeling and simulation of three-phase voltage unbalance is proposed in this paper. The presented algorithm uses wavelet transform and three-phase load flow, for deterministic predictive analysis, and utilizes copulas for Monte Carlo simulation of random variations of voltage unbalance factor (VUF). This semi-stochastic method is developed based on the measured data obtained from a 20/0.4-kV distribution substation located in Tehran. Comparison of simulated results and recorded data shows a good agreement.
Abstract: In the competitive electricity markets, accurate price forecasting embody crucial information for producers and consumers when planning bidding strategies in order to maximize their benefits and utilities, respectively. This paper presents a succinct survey of energy price forecasting techniques and models. The two major groups of the models are the stationary and non-stationary time series models according to proposed classification. Using of Wavelet Transform and Hidden Markov Models (HMMs) have been recently proposed among these groups respectively. These two time series models have differently upgraded price forecasting. This paper proposes WT-based models and HMMs in detail with a modeling and simulation of the later in the Spanish electicity market.
Abstract: Many methods and models have been developed to forecast the energy prices in the market environment since the restructuring of the electricity power industry. This paper presents a brief overview of different techniques and models in the literature of energy price forecasting. Then it compares and classifies different models and methods to verify whether these are suitable for different purposes of forecasting or not. Classification is based on the type of the models, suitability with respect to power market, time horizon, level of accuracy and forecasting aim. Based on this approach, a complementary classification of price forecasting models is proposed, which can be used for choosing the suitable method for certain cases. Also, the use of Hidden Markov Models (HMM), as an interesting method, is proposed in detail with a modeling and simulation by using the Spanish electricity market data.
Abstract: Power systems use STATCOM for compensating purposes that is subjected to the high switching frequencies. Various PWM techniques make selective harmonic elimination possible, which effectively control the harmonic content of voltage source inverters. On the other hand, distribution systems have to supply unbalanced nonlinear loads, transferring oscillations to the DC-side of the converter in a realistic operating condition. Thus, additional uncharacteristic harmonics are modulated through the STATCOM at the point of common coupling (PCC). This requires more attention when switching angles are calculated offline using the optimal-PWM technique. This thesis suggests a harmonic-domain model in order to realistically evaluate the injected harmonics at the PCC. This model properly takes into account the DC capacitor effect, effects of other possible varying parameters such as voltage unbalance as well as network harmonics, and effects of operating conditions on the STATCOM harmonic performance. The model is programmed, and can be easily run with other algorithms such as Monte Carlo simulation. Further, a semi-stochastic method is proposed to predict and simulate the three-phase voltage unbalance, leading to an analytical tool for prediction of harmonic performance of STATCOM. The predictive method is developed based on the measured data obtained from a low-voltage distribution network. Finally, the modeled STATCOM is linked with the distribution substation, applying the proposed voltage unbalance modeling to evaluate aggregate harmonics injection at the PCC.
