Pub Date : 2012-10-01DOI: 10.1109/POWERCON.2012.6401409
Po-An Chou, Chi-Cheng Chuang, R.-I. Chang
This paper is based on non-intrusive load monitoring (NILM), which uses low-frequency sensor in power circuit. Traditional process must establish a database with features before identifying what the circuit is. If the system wants to add new feature of appliances into database, it must relearn electrical data. Therefore, this paper proposes a method, which can identify appliances status and whether new appliances exist or not. It can also learn feature of appliances automatically at the same time. The proposed method combines statistics with classification techniques to simplify the feature extraction. The consequent is quite valid in the economy, accuracy and feasibility. In addition, if NILM system does not identify successfully, it might contain the unknown appliances. The unknown appliances can thus be identified. The system will be able to expand its appliances amount in the database automatically. Experiment performed with a variety of single or multiple classifications which include the unknown appliances.
{"title":"Automatic appliance classification for non-intrusive load monitoring","authors":"Po-An Chou, Chi-Cheng Chuang, R.-I. Chang","doi":"10.1109/POWERCON.2012.6401409","DOIUrl":"https://doi.org/10.1109/POWERCON.2012.6401409","url":null,"abstract":"This paper is based on non-intrusive load monitoring (NILM), which uses low-frequency sensor in power circuit. Traditional process must establish a database with features before identifying what the circuit is. If the system wants to add new feature of appliances into database, it must relearn electrical data. Therefore, this paper proposes a method, which can identify appliances status and whether new appliances exist or not. It can also learn feature of appliances automatically at the same time. The proposed method combines statistics with classification techniques to simplify the feature extraction. The consequent is quite valid in the economy, accuracy and feasibility. In addition, if NILM system does not identify successfully, it might contain the unknown appliances. The unknown appliances can thus be identified. The system will be able to expand its appliances amount in the database automatically. Experiment performed with a variety of single or multiple classifications which include the unknown appliances.","PeriodicalId":176214,"journal":{"name":"2012 IEEE International Conference on Power System Technology (POWERCON)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122809102","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-01DOI: 10.1109/POWERCON.2012.6401255
N. Chen, Qi Wang, Yi Tang, Ling-zhi Zhu, Fubao Wu, Mei Chen, N. Wang
With the fast development of wind power, the techniques related to its grid integration and control have been researched all over the world. In which, active power control of wind farm is one of the most important techniques. However, current methods are not good to satisfy the relevant requirements. For the problem, an optimal active power control method of wind farm using the information of ultra-short-term wind power prediction is proposed in this paper. In this method, a weight coefficient is defined to judge whether the generator can be adjusted or not, and used to calculate the power allocation of wind generators. Finally, by comparing with current methods, the results show that the proposed method can improve the controllability and reliability of wind power to smooth power output of wind generators and avoid frequent power adjustment.
{"title":"An optimal active power control method of wind farm using power prediction information","authors":"N. Chen, Qi Wang, Yi Tang, Ling-zhi Zhu, Fubao Wu, Mei Chen, N. Wang","doi":"10.1109/POWERCON.2012.6401255","DOIUrl":"https://doi.org/10.1109/POWERCON.2012.6401255","url":null,"abstract":"With the fast development of wind power, the techniques related to its grid integration and control have been researched all over the world. In which, active power control of wind farm is one of the most important techniques. However, current methods are not good to satisfy the relevant requirements. For the problem, an optimal active power control method of wind farm using the information of ultra-short-term wind power prediction is proposed in this paper. In this method, a weight coefficient is defined to judge whether the generator can be adjusted or not, and used to calculate the power allocation of wind generators. Finally, by comparing with current methods, the results show that the proposed method can improve the controllability and reliability of wind power to smooth power output of wind generators and avoid frequent power adjustment.","PeriodicalId":176214,"journal":{"name":"2012 IEEE International Conference on Power System Technology (POWERCON)","volume":"2017 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128234633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-01DOI: 10.1109/POWERCON.2012.6401271
P. R. Gandhi, S. K. Joshi
In this paper, the novel approach to design the power system stabilizer using artificial neural network based Non Linear Auto Regressive Moving Average-L2 (NARMA-L2) controller has been presented. The controller has been used to generate the appropriate supplementary control signal for the excitation system of synchronous generator. The signal generated has been used to damp the low frequency oscillations and improves the performance of power system dynamics. The analysis of Signal Machine Infinite Bus (SMIB) system has been carried out with NARMA-L2 controller and the performance has been compared with genetics search algorithm based Conventional Power System Stabilizer (CPSS). To reflect the effectiveness of NARMA-L2 based PSS, the non-linear simulations have been performed under various disturbances and different operating conditions.
{"title":"Stability analysis using non linear auto regressive moving average controller based power system stabilizer","authors":"P. R. Gandhi, S. K. Joshi","doi":"10.1109/POWERCON.2012.6401271","DOIUrl":"https://doi.org/10.1109/POWERCON.2012.6401271","url":null,"abstract":"In this paper, the novel approach to design the power system stabilizer using artificial neural network based Non Linear Auto Regressive Moving Average-L2 (NARMA-L2) controller has been presented. The controller has been used to generate the appropriate supplementary control signal for the excitation system of synchronous generator. The signal generated has been used to damp the low frequency oscillations and improves the performance of power system dynamics. The analysis of Signal Machine Infinite Bus (SMIB) system has been carried out with NARMA-L2 controller and the performance has been compared with genetics search algorithm based Conventional Power System Stabilizer (CPSS). To reflect the effectiveness of NARMA-L2 based PSS, the non-linear simulations have been performed under various disturbances and different operating conditions.","PeriodicalId":176214,"journal":{"name":"2012 IEEE International Conference on Power System Technology (POWERCON)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128782689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-01DOI: 10.1109/POWERCON.2012.6401445
R. Xezile, N. Mbuli, J. Pretorius, S. Chowdhury
The Upington distribution network is remotely located from the main transmission system. It is characterized by long lines supplying relatively small amounts of loads. The fault levels at various points in this network can be characterized as very low. These two aspects can lead to this network being characterized as very weak. As a result, faults taking place at various locations in the system tend to cause severe voltage dips. A concentrating solar power plant (CSP) is being planned for commissioning in the area. The presence of the CSP plant will greatly change the fault levels, and network strength, at various locations in the vicinity of the CSP plant. In this paper, a study is conducted to assess the severity of a voltage dip at a particular power station before and after commissioning of a CSP plant. A 3-phase transmission fault recorded historically is simulated. It is shown that the presence of the CSP plant has substantially beneficial effect on the voltage dip performance of the system.
{"title":"Impact of transmission faults on the voltage dip performance of a weak upington distribution network with a CSP plant connected","authors":"R. Xezile, N. Mbuli, J. Pretorius, S. Chowdhury","doi":"10.1109/POWERCON.2012.6401445","DOIUrl":"https://doi.org/10.1109/POWERCON.2012.6401445","url":null,"abstract":"The Upington distribution network is remotely located from the main transmission system. It is characterized by long lines supplying relatively small amounts of loads. The fault levels at various points in this network can be characterized as very low. These two aspects can lead to this network being characterized as very weak. As a result, faults taking place at various locations in the system tend to cause severe voltage dips. A concentrating solar power plant (CSP) is being planned for commissioning in the area. The presence of the CSP plant will greatly change the fault levels, and network strength, at various locations in the vicinity of the CSP plant. In this paper, a study is conducted to assess the severity of a voltage dip at a particular power station before and after commissioning of a CSP plant. A 3-phase transmission fault recorded historically is simulated. It is shown that the presence of the CSP plant has substantially beneficial effect on the voltage dip performance of the system.","PeriodicalId":176214,"journal":{"name":"2012 IEEE International Conference on Power System Technology (POWERCON)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129932457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-01DOI: 10.1109/POWERCON.2012.6401437
T. Ikegami, K. Kataoka, Y. Iwafune, K. Ogimoto
High penetration of variable sources of renewable power generation, such as photovoltaic (PV) systems will lead to supply-demand imbalances in the entire power system. Activation of residential power usage, storage, and generation by sophisticated scheduling and control using a home energy management system (HEMS) will be needed to balance power supply and demand in the near future. In this study, we improved a part of our optimum operation-scheduling model relevant to the operation of a heat pump water heater (HPWH). Using this new model, the optimal demand controls of an HPWH were analyzed with four types of objective functions. It was found that the most economical operation schedule using current electricity rates was not the same as schedules utilizing other objective functions. These results showed that we need to harmonize the objectives of demand control with incentive rewards for consumers in the future.
{"title":"Optimal demand controls for a heat pump water heater under different objective functions","authors":"T. Ikegami, K. Kataoka, Y. Iwafune, K. Ogimoto","doi":"10.1109/POWERCON.2012.6401437","DOIUrl":"https://doi.org/10.1109/POWERCON.2012.6401437","url":null,"abstract":"High penetration of variable sources of renewable power generation, such as photovoltaic (PV) systems will lead to supply-demand imbalances in the entire power system. Activation of residential power usage, storage, and generation by sophisticated scheduling and control using a home energy management system (HEMS) will be needed to balance power supply and demand in the near future. In this study, we improved a part of our optimum operation-scheduling model relevant to the operation of a heat pump water heater (HPWH). Using this new model, the optimal demand controls of an HPWH were analyzed with four types of objective functions. It was found that the most economical operation schedule using current electricity rates was not the same as schedules utilizing other objective functions. These results showed that we need to harmonize the objectives of demand control with incentive rewards for consumers in the future.","PeriodicalId":176214,"journal":{"name":"2012 IEEE International Conference on Power System Technology (POWERCON)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130233491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-01DOI: 10.1109/POWERCON.2012.6401266
Z. Bajramovic, I. Turkovic, A. Mujezinović, A. Carsimamovic, A. Muharemovic
Investigations of the electromagnetic interference indicate that disconnecting switching of the off-loaded busbars is one of the most important sources of electromagnetic interference in the secondary circuits of a power station. Disconnector's contacts in air-insulated substations (AIS) move slowly causing numerous strikes and restrikes between contacts. Every strike causes high-frequency currents (from a few hundred kHz to a few MHz) tending to equalize potentials at the contacts. These travelling current and voltage waves are the most important sources of electromagnetic coupling to the secondary circuits of instrument transformers, on whose ends high-speed and low-power electronic devices are connected. During disconnector switching malfunctioning of auxiliary circuits can occurred. In this paper results of measurements of overvoltages in the secondary circuits in the AIS Grabovica (Hydro Power Plant - HPP Grabovica) and AIS Kakanj are presented. In order to reduce overvoltages in secondary circuits, measures for mitigation of electromagnetic interference are presented.
{"title":"Overvoltages in secondary circuits of air-insulated substation due to disconnector switching","authors":"Z. Bajramovic, I. Turkovic, A. Mujezinović, A. Carsimamovic, A. Muharemovic","doi":"10.1109/POWERCON.2012.6401266","DOIUrl":"https://doi.org/10.1109/POWERCON.2012.6401266","url":null,"abstract":"Investigations of the electromagnetic interference indicate that disconnecting switching of the off-loaded busbars is one of the most important sources of electromagnetic interference in the secondary circuits of a power station. Disconnector's contacts in air-insulated substations (AIS) move slowly causing numerous strikes and restrikes between contacts. Every strike causes high-frequency currents (from a few hundred kHz to a few MHz) tending to equalize potentials at the contacts. These travelling current and voltage waves are the most important sources of electromagnetic coupling to the secondary circuits of instrument transformers, on whose ends high-speed and low-power electronic devices are connected. During disconnector switching malfunctioning of auxiliary circuits can occurred. In this paper results of measurements of overvoltages in the secondary circuits in the AIS Grabovica (Hydro Power Plant - HPP Grabovica) and AIS Kakanj are presented. In order to reduce overvoltages in secondary circuits, measures for mitigation of electromagnetic interference are presented.","PeriodicalId":176214,"journal":{"name":"2012 IEEE International Conference on Power System Technology (POWERCON)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130395607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The wind power data have very strong nonlinearity and non-stationarity, but the traditional method mainly focuses on the nonlinear problem of the wind power data and doesn't analysis the non-stationary problem. This paper proposed the combining method of atomic sparse decomposition and artificial neural network (ANN) to research the short-term forecasting of the wind power. Firstly, wind power data samples were decomposed into non-orthogonal atom sequences and residual sequences. Then ANN was used to model and predict the residual sequences, and the atom sequences adopt the adaptive prediction. Finally, the forecasting results were stacked and reconstructured. The generation power of an actual wind farm was forecasted by this method. The results show that the combining method of atomic sparse decomposition and ANN can reduce non-stationary behavior of the signal, produce sparser decomposition effect and better predict the variation tendency of the wind power.
{"title":"Short term power forecasting of a wind farm based on atomic sparse decomposition theory","authors":"Mingjian Cui, Xiaotao Peng, Junli Xia, Yuanzhan Sun, Ziping Wu","doi":"10.1109/POWERCON.2012.6401362","DOIUrl":"https://doi.org/10.1109/POWERCON.2012.6401362","url":null,"abstract":"The wind power data have very strong nonlinearity and non-stationarity, but the traditional method mainly focuses on the nonlinear problem of the wind power data and doesn't analysis the non-stationary problem. This paper proposed the combining method of atomic sparse decomposition and artificial neural network (ANN) to research the short-term forecasting of the wind power. Firstly, wind power data samples were decomposed into non-orthogonal atom sequences and residual sequences. Then ANN was used to model and predict the residual sequences, and the atom sequences adopt the adaptive prediction. Finally, the forecasting results were stacked and reconstructured. The generation power of an actual wind farm was forecasted by this method. The results show that the combining method of atomic sparse decomposition and ANN can reduce non-stationary behavior of the signal, produce sparser decomposition effect and better predict the variation tendency of the wind power.","PeriodicalId":176214,"journal":{"name":"2012 IEEE International Conference on Power System Technology (POWERCON)","volume":"441 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126994706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-01DOI: 10.1109/POWERCON.2012.6401319
Yin Xu, Laijun Chen, Ying Chen, Zhenquan Sun
The EMT simulation for wind farms provides an alternative approach to study interaction between wind farms and power systems. To build up an EMT model of the DFIG, thoroughly considerations should be paid to the characteristics of the back-to-back PWM converter, which plays a crucial role in determining the dynamic behaviors of the DFIG. However, the detailed models of the PWM converters are so complicated that simulations with them may be very time-consuming. Therefore, an accurate and efficient model for the DFIG containing the PWM converters is highly required for the fast EMT simulations of power systems integrated with wind power. In this paper, a modified switching-function model of the three-phase PWM VSC is proposed and applied to the modeling of the DFIG. The accuracy and efficiency of the function model are verified under various cases in PSCAD.
{"title":"A fast transient simulation model of the DFIG based on the switching-function model of the VSC","authors":"Yin Xu, Laijun Chen, Ying Chen, Zhenquan Sun","doi":"10.1109/POWERCON.2012.6401319","DOIUrl":"https://doi.org/10.1109/POWERCON.2012.6401319","url":null,"abstract":"The EMT simulation for wind farms provides an alternative approach to study interaction between wind farms and power systems. To build up an EMT model of the DFIG, thoroughly considerations should be paid to the characteristics of the back-to-back PWM converter, which plays a crucial role in determining the dynamic behaviors of the DFIG. However, the detailed models of the PWM converters are so complicated that simulations with them may be very time-consuming. Therefore, an accurate and efficient model for the DFIG containing the PWM converters is highly required for the fast EMT simulations of power systems integrated with wind power. In this paper, a modified switching-function model of the three-phase PWM VSC is proposed and applied to the modeling of the DFIG. The accuracy and efficiency of the function model are verified under various cases in PSCAD.","PeriodicalId":176214,"journal":{"name":"2012 IEEE International Conference on Power System Technology (POWERCON)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114785238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-01DOI: 10.1109/POWERCON.2012.6401331
Guomin Luo, Daming Zhang
Partial discharge (PD) is caused by the deterioration of insulation materials. Its detection and accurate measurement are very important to prevent insulation breakdown and catastrophic failures. Detection of PDs in metal-clad apparatus via TEV method is a promising approach in non-intrusive on-line tests. However, the electrical interference from background environment is the major barrier of improving its measuring accuracy. The combination of wavelet analysis that reveals local features and entropy that measures disorder can just fulfill the requirements of PD signal analysis and is thus investigated in this paper. Then a wavelet-entropy based PD recognition method is proposed. The pulse features that are characterized by wavelet entropy are employed as the input pattern of a classifier constructed with feed-forward back-propagation neural network. Finally, some PD groups with noisy interferences are tested by trained network. The recognition rate of real PD pulses demonstrates the proposed wavelet-entropy based method is effective in PD signal de-noising.
{"title":"Recognition of partial discharge using wavelet entropy and neural network for TEV measurement","authors":"Guomin Luo, Daming Zhang","doi":"10.1109/POWERCON.2012.6401331","DOIUrl":"https://doi.org/10.1109/POWERCON.2012.6401331","url":null,"abstract":"Partial discharge (PD) is caused by the deterioration of insulation materials. Its detection and accurate measurement are very important to prevent insulation breakdown and catastrophic failures. Detection of PDs in metal-clad apparatus via TEV method is a promising approach in non-intrusive on-line tests. However, the electrical interference from background environment is the major barrier of improving its measuring accuracy. The combination of wavelet analysis that reveals local features and entropy that measures disorder can just fulfill the requirements of PD signal analysis and is thus investigated in this paper. Then a wavelet-entropy based PD recognition method is proposed. The pulse features that are characterized by wavelet entropy are employed as the input pattern of a classifier constructed with feed-forward back-propagation neural network. Finally, some PD groups with noisy interferences are tested by trained network. The recognition rate of real PD pulses demonstrates the proposed wavelet-entropy based method is effective in PD signal de-noising.","PeriodicalId":176214,"journal":{"name":"2012 IEEE International Conference on Power System Technology (POWERCON)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124387752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2012-10-01DOI: 10.1109/POWERCON.2012.6401257
F. Ruiz-Rodriguez, M. Gómez-González, F. Jurado
Loads and distributed generation production can be modeled as random variables. This paper shows that the proposed method can be applied for the keeping of voltages within desired limits at all load buses of a distribution system with small-scale biomass based energy systems. To measure the performance of this distribution system, this work has formulated a probabilistic model that considers the random nature of lower heat value of biomass and load. The Cornish-Fisher expansion is employed for estimating quantiles of a random variable. This paper proposes a new method that utilizes discrete particle swarm optimization and probabilistic radial load flow. It is evidenced the reduction in computation time accomplished by the more efficient probabilistic load flow in comparison to Monte Carlo simulation. Satisfactory solutions are reached in a smaller number of iterations. Hence, convergence is rapidly attained and computational cost is low enough than that required for Monte Carlo simulation.
{"title":"Location of small-scale biomass based energy systems using probabilistic load flow and metaheuristic techniques","authors":"F. Ruiz-Rodriguez, M. Gómez-González, F. Jurado","doi":"10.1109/POWERCON.2012.6401257","DOIUrl":"https://doi.org/10.1109/POWERCON.2012.6401257","url":null,"abstract":"Loads and distributed generation production can be modeled as random variables. This paper shows that the proposed method can be applied for the keeping of voltages within desired limits at all load buses of a distribution system with small-scale biomass based energy systems. To measure the performance of this distribution system, this work has formulated a probabilistic model that considers the random nature of lower heat value of biomass and load. The Cornish-Fisher expansion is employed for estimating quantiles of a random variable. This paper proposes a new method that utilizes discrete particle swarm optimization and probabilistic radial load flow. It is evidenced the reduction in computation time accomplished by the more efficient probabilistic load flow in comparison to Monte Carlo simulation. Satisfactory solutions are reached in a smaller number of iterations. Hence, convergence is rapidly attained and computational cost is low enough than that required for Monte Carlo simulation.","PeriodicalId":176214,"journal":{"name":"2012 IEEE International Conference on Power System Technology (POWERCON)","volume":"25 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131923271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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