Pub Date : 2020-01-30DOI: 10.1504/ijpec.2020.10026494
B. Appasani, D. Mohanta
The phasor measurement units (PMUs) have evolved as powerful extrapolations of the supervisory control and data acquisition (SCADA) systems due to their profound application in the real time monitoring of the smart grid (SG). In the SG several such PMUs continuously generate the time tagged phasor measurements which are communicated to a central monitoring station known as the phasor data concentrator (PDC). The communication system plays a pivotal role in the transfer of the phasor measurements to the PDC and thus should be highly reliable. This article presents a detailed approach for the construction of the generalised stochastic Petri nets (GSPNs) for the reliability analysis of the synchrophasor microwave communication networks. These communication networks are optimally planned to achieve maximum reliability without compromising the system observability. Results from the case studies for the North Eastern power grid of India are presented to demonstrate the efficacy of the proposed approach.
{"title":"Reliability analysis of the PMU microwave communication networks using generalised stochastic Petri nets","authors":"B. Appasani, D. Mohanta","doi":"10.1504/ijpec.2020.10026494","DOIUrl":"https://doi.org/10.1504/ijpec.2020.10026494","url":null,"abstract":"The phasor measurement units (PMUs) have evolved as powerful extrapolations of the supervisory control and data acquisition (SCADA) systems due to their profound application in the real time monitoring of the smart grid (SG). In the SG several such PMUs continuously generate the time tagged phasor measurements which are communicated to a central monitoring station known as the phasor data concentrator (PDC). The communication system plays a pivotal role in the transfer of the phasor measurements to the PDC and thus should be highly reliable. This article presents a detailed approach for the construction of the generalised stochastic Petri nets (GSPNs) for the reliability analysis of the synchrophasor microwave communication networks. These communication networks are optimally planned to achieve maximum reliability without compromising the system observability. Results from the case studies for the North Eastern power grid of India are presented to demonstrate the efficacy of the proposed approach.","PeriodicalId":38524,"journal":{"name":"International Journal of Power and Energy Conversion","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46269548","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 : 2020-01-30DOI: 10.1504/ijpec.2020.10026489
Karthik Thirumala, A. Kanjolia, Trapti Jain, A. Umarikar
This paper proposes a novel approach for classification of single and combined power quality (PQ) disturbances. The EWT-based adaptive filtering technique is employed first to decompose the signal into its individual frequency components by estimation of frequencies. The frequency estimation in this paper is done using a divide-to-conquer principle-based FFT technique and followed by an adaptive filter design. Then, some unique potential features reflecting the characteristics of disturbances are extracted from the mono-frequency components as well as the signal. A single classifier used for the classification of combined disturbances, whose characteristics are alike, gives less classification accuracy. Therefore, the use of a dual FFNN is proposed for the classification of single and combined PQ disturbances to effectively reduce the misclassification and improve the accuracy. The effectiveness of the proposed approach is evaluated on a broad range of timevarying power signals with varying degree of irregularities, noise, and fundamental frequency deviation. The results obtained for both the simulated as well as the real disturbance signals elucidate the efficiency and robustness of the proposed approach for classification of the most frequent disturbances.
{"title":"Empirical wavelet transform and dual feed-forward neural network for classification of power quality disturbances","authors":"Karthik Thirumala, A. Kanjolia, Trapti Jain, A. Umarikar","doi":"10.1504/ijpec.2020.10026489","DOIUrl":"https://doi.org/10.1504/ijpec.2020.10026489","url":null,"abstract":"This paper proposes a novel approach for classification of single and combined power quality (PQ) disturbances. The EWT-based adaptive filtering technique is employed first to decompose the signal into its individual frequency components by estimation of frequencies. The frequency estimation in this paper is done using a divide-to-conquer principle-based FFT technique and followed by an adaptive filter design. Then, some unique potential features reflecting the characteristics of disturbances are extracted from the mono-frequency components as well as the signal. A single classifier used for the classification of combined disturbances, whose characteristics are alike, gives less classification accuracy. Therefore, the use of a dual FFNN is proposed for the classification of single and combined PQ disturbances to effectively reduce the misclassification and improve the accuracy. The effectiveness of the proposed approach is evaluated on a broad range of timevarying power signals with varying degree of irregularities, noise, and fundamental frequency deviation. The results obtained for both the simulated as well as the real disturbance signals elucidate the efficiency and robustness of the proposed approach for classification of the most frequent disturbances.","PeriodicalId":38524,"journal":{"name":"International Journal of Power and Energy Conversion","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49147452","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 : 2020-01-01DOI: 10.1504/IJPEC.2020.10027791
R. V. Vamja, R. Maurya, Shaikh Mohammed Suhel
{"title":"Implementation of PWM technique with soft starting algorithm for three-phase induction motor drives","authors":"R. V. Vamja, R. Maurya, Shaikh Mohammed Suhel","doi":"10.1504/IJPEC.2020.10027791","DOIUrl":"https://doi.org/10.1504/IJPEC.2020.10027791","url":null,"abstract":"","PeriodicalId":38524,"journal":{"name":"International Journal of Power and Energy Conversion","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66809434","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 : 2020-01-01DOI: 10.1504/IJPEC.2020.10027810
M. Elsisi, M. Ismail, A. Bendary
{"title":"Optimal design of battery charge management controller for hybrid system PV/wind cell with storage battery","authors":"M. Elsisi, M. Ismail, A. Bendary","doi":"10.1504/IJPEC.2020.10027810","DOIUrl":"https://doi.org/10.1504/IJPEC.2020.10027810","url":null,"abstract":"","PeriodicalId":38524,"journal":{"name":"International Journal of Power and Energy Conversion","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66809504","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 : 2020-01-01DOI: 10.1504/IJPEC.2020.10027792
R. K. Saket, D. N. Vishwakarma, S. Singh
{"title":"An intelligent scheme for categorising fault events in compensated power network using K-nearest neighbour technique","authors":"R. K. Saket, D. N. Vishwakarma, S. Singh","doi":"10.1504/IJPEC.2020.10027792","DOIUrl":"https://doi.org/10.1504/IJPEC.2020.10027792","url":null,"abstract":"","PeriodicalId":38524,"journal":{"name":"International Journal of Power and Energy Conversion","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66809492","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 : 2020-01-01DOI: 10.1504/ijpec.2020.10027377
S. Tounsi
{"title":"Finite element validation of the analytical model of variable reluctance motor","authors":"S. Tounsi","doi":"10.1504/ijpec.2020.10027377","DOIUrl":"https://doi.org/10.1504/ijpec.2020.10027377","url":null,"abstract":"","PeriodicalId":38524,"journal":{"name":"International Journal of Power and Energy Conversion","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"66809392","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 : 2019-10-11DOI: 10.1504/ijpec.2021.10038988
Sambit Dash, Umamani Subudhi
In this paper, a novel method for classification of power quality events is illustrated. 15 types of power quality events consisting of single and multi-stage disturbances are considered for study. A database of the synthetic PQ events is generated in MATLAB using mathematical models. The generated signals are passed through a novel Modified Stockwell transform consisting of second order gaussian window which provides the ST matrix. From the ST matrix various statistical features such as energy and standard deviation of the magnitude and phase contour are extracted and given as input to Support Vector Machine (SVM). Furthermore, to improve the performance of SVM, a novel meta-heuristic technique called Whale Optimization Algorithm (WOA) is used to tune the hyper parameters of the SVM classifier. The performance of the proposed method is analyzed under noisy and noiseless conditions. It is observed that WOA tuned SVM provides improved classification accuracy than other widely used meta-heuristic optimization algorithms such as Particle Swarm Optimization (PSO) tuned SVM and Genetic Algorithm (GA) tuned SVM. Further, two novel circuits for generation of sag, swell and interrupt are developed and the proposed technique is validated on real time signals obtained from the circuits.
{"title":"Multiple power quality event detection and classification using modified S-transform and WOA tuned SVM classifier","authors":"Sambit Dash, Umamani Subudhi","doi":"10.1504/ijpec.2021.10038988","DOIUrl":"https://doi.org/10.1504/ijpec.2021.10038988","url":null,"abstract":"In this paper, a novel method for classification of power quality events is illustrated. 15 types of power quality events consisting of single and multi-stage disturbances are considered for study. A database of the synthetic PQ events is generated in MATLAB using mathematical models. The generated signals are passed through a novel Modified Stockwell transform consisting of second order gaussian window which provides the ST matrix. From the ST matrix various statistical features such as energy and standard deviation of the magnitude and phase contour are extracted and given as input to Support Vector Machine (SVM). Furthermore, to improve the performance of SVM, a novel meta-heuristic technique called Whale Optimization Algorithm (WOA) is used to tune the hyper parameters of the SVM classifier. The performance of the proposed method is analyzed under noisy and noiseless conditions. It is observed that WOA tuned SVM provides improved classification accuracy than other widely used meta-heuristic optimization algorithms such as Particle Swarm Optimization (PSO) tuned SVM and Genetic Algorithm (GA) tuned SVM. Further, two novel circuits for generation of sag, swell and interrupt are developed and the proposed technique is validated on real time signals obtained from the circuits.","PeriodicalId":38524,"journal":{"name":"International Journal of Power and Energy Conversion","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42396659","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 : 2019-09-18DOI: 10.1504/IJPEC.2019.10012581
S. Bouslimani, S. Drid, L. Chrifi-Alaoui
This paper deals with control and diagnosis of the synchronous generator (SG) used in a wind energy conversion system under inter turn short-circuit fault. In the first part of this paper, a speed sensorless control of the synchronous generator is presented. In this case speed estimation is carried out using model reference adaptive system (MRAS). In the second part, the MRAS observer is associated with the Luenberger observer in order to estimate the stator resistances according d and q axis. The stability of the system is proved by using Lyapunov theory. Finally, the proposed new hybrid observer MRAS-Luenberger is used to detect the turn-to-turn short circuit faults. The Park's vector approach (PVA) is adopted to take decision if there are faults. The proposed technique is tested on dSPACE DS1103 and the results confirm the efficacy to detect the fault by observing the shape. This method gives us the right information for the fault isolation.
{"title":"Sensorless control and diagnosis of synchronous generator used in wind energy conversion system under inter turn short-circuit fault","authors":"S. Bouslimani, S. Drid, L. Chrifi-Alaoui","doi":"10.1504/IJPEC.2019.10012581","DOIUrl":"https://doi.org/10.1504/IJPEC.2019.10012581","url":null,"abstract":"This paper deals with control and diagnosis of the synchronous generator (SG) used in a wind energy conversion system under inter turn short-circuit fault. In the first part of this paper, a speed sensorless control of the synchronous generator is presented. In this case speed estimation is carried out using model reference adaptive system (MRAS). In the second part, the MRAS observer is associated with the Luenberger observer in order to estimate the stator resistances according d and q axis. The stability of the system is proved by using Lyapunov theory. Finally, the proposed new hybrid observer MRAS-Luenberger is used to detect the turn-to-turn short circuit faults. The Park's vector approach (PVA) is adopted to take decision if there are faults. The proposed technique is tested on dSPACE DS1103 and the results confirm the efficacy to detect the fault by observing the shape. This method gives us the right information for the fault isolation.","PeriodicalId":38524,"journal":{"name":"International Journal of Power and Energy Conversion","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48417667","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 : 2019-09-18DOI: 10.1504/ijpec.2019.10024033
B. Ramachandran, G. Bellarmine
Due to their high energy capacity and potential mass deployment, battery electric vehicles (BEVs) will have a significant impact on power distribution networks. There are issues for the distribution network operator if BEV charging is allowed to take place without any control on the time of day, duration or charging rate. Specifically, the network voltage may fall below prescribed limits at times of peak demand and power flows may cause a thermal overload of assets. The existing literature on scheduling charging/discharging of BEVs makes use of decentralised/centralised control architectures to study the effect of charging/discharging of BEVs on distribution network. This paper presents a teaching-learning algorithm method to optimally charge and discharge the BEVs and hence mitigate the adverse impacts on the distribution network by considering the driving behaviour of car owners. This approach has resulted in reduced transformer loading even when using V2G and G2V modes of operation of the BEVs and hence has prevented transformer aging in low voltage distribution networks.
{"title":"Impact of battery electric vehicles on low voltage distribution networks","authors":"B. Ramachandran, G. Bellarmine","doi":"10.1504/ijpec.2019.10024033","DOIUrl":"https://doi.org/10.1504/ijpec.2019.10024033","url":null,"abstract":"Due to their high energy capacity and potential mass deployment, battery electric vehicles (BEVs) will have a significant impact on power distribution networks. There are issues for the distribution network operator if BEV charging is allowed to take place without any control on the time of day, duration or charging rate. Specifically, the network voltage may fall below prescribed limits at times of peak demand and power flows may cause a thermal overload of assets. The existing literature on scheduling charging/discharging of BEVs makes use of decentralised/centralised control architectures to study the effect of charging/discharging of BEVs on distribution network. This paper presents a teaching-learning algorithm method to optimally charge and discharge the BEVs and hence mitigate the adverse impacts on the distribution network by considering the driving behaviour of car owners. This approach has resulted in reduced transformer loading even when using V2G and G2V modes of operation of the BEVs and hence has prevented transformer aging in low voltage distribution networks.","PeriodicalId":38524,"journal":{"name":"International Journal of Power and Energy Conversion","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48842778","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 : 2019-09-18DOI: 10.1504/ijpec.2019.10024038
J. Kumar, Ashu Verma, T. Bhatti
This paper presents a fuzzy logic-based priority list method to solve the unit commitment problem. The priority list order is selected according to the maximum output power rating of the generating units while satisfying all the constraints over a period of time. The turn on (commitment) and turn off (de-commitment) decision of thermal generating units is handled by priority list order with fuzzy logic algorithm. A fuzzy optimisation-based approach is developed to find the optimal solution by using fuzzy operations and if-then rules. The objective of the optimisation is to achieve minimum operating cost by scheduling of generator units. In solving the unit commitment problem, reliability and feasibility constraints are checked for the planning interval. This method is implemented on standard IEEE 69-bus, 11-thermal generator system. Use of the fuzzy logic controller with priority list method enables the handling of uncertainties in load forecast in an efficient manner.
{"title":"A priority list-based fuzzy logic controller for short-term unit commitment problem","authors":"J. Kumar, Ashu Verma, T. Bhatti","doi":"10.1504/ijpec.2019.10024038","DOIUrl":"https://doi.org/10.1504/ijpec.2019.10024038","url":null,"abstract":"This paper presents a fuzzy logic-based priority list method to solve the unit commitment problem. The priority list order is selected according to the maximum output power rating of the generating units while satisfying all the constraints over a period of time. The turn on (commitment) and turn off (de-commitment) decision of thermal generating units is handled by priority list order with fuzzy logic algorithm. A fuzzy optimisation-based approach is developed to find the optimal solution by using fuzzy operations and if-then rules. The objective of the optimisation is to achieve minimum operating cost by scheduling of generator units. In solving the unit commitment problem, reliability and feasibility constraints are checked for the planning interval. This method is implemented on standard IEEE 69-bus, 11-thermal generator system. Use of the fuzzy logic controller with priority list method enables the handling of uncertainties in load forecast in an efficient manner.","PeriodicalId":38524,"journal":{"name":"International Journal of Power and Energy Conversion","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48724158","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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