Pub Date : 2019-12-01DOI: 10.1109/isap48318.2019.9065978
{"title":"Index","authors":"","doi":"10.1109/isap48318.2019.9065978","DOIUrl":"https://doi.org/10.1109/isap48318.2019.9065978","url":null,"abstract":"","PeriodicalId":316020,"journal":{"name":"2019 20th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128705875","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 : 2019-12-01DOI: 10.1109/ISAP48318.2019.9065963
Subho Paul, N. Padhy
The current work presented in this article proposes a day ahead multi-objective optimization portfolio for a residential microgrid or a home consisting of different domestic appliances and rooftop solar panels associated with storage device. The proposed framework aims to determine synergetic source-storage-load dispatch schedule by simultaneously minimizing the electricity cost, ocular discomfort and thermal discomfort experienced by the home occupants for the following day while controlling switching of the discrete loads (like washing machine, dryer etc.) and consumption of the continuous loads (like air-conditioner, lights etc.). The entire optimization framework takes the form of a mixed integer non-linear programming and the solution technique is proposed using Genetic Algorithm. The simulation is carried out on practical data set of a residential unit to prove effectiveness of the designed method.
{"title":"A Multi-Objective Genetic Algorithm Approach for Synergetic Source-Storage-Load Dispatch in a Residential Microgrid","authors":"Subho Paul, N. Padhy","doi":"10.1109/ISAP48318.2019.9065963","DOIUrl":"https://doi.org/10.1109/ISAP48318.2019.9065963","url":null,"abstract":"The current work presented in this article proposes a day ahead multi-objective optimization portfolio for a residential microgrid or a home consisting of different domestic appliances and rooftop solar panels associated with storage device. The proposed framework aims to determine synergetic source-storage-load dispatch schedule by simultaneously minimizing the electricity cost, ocular discomfort and thermal discomfort experienced by the home occupants for the following day while controlling switching of the discrete loads (like washing machine, dryer etc.) and consumption of the continuous loads (like air-conditioner, lights etc.). The entire optimization framework takes the form of a mixed integer non-linear programming and the solution technique is proposed using Genetic Algorithm. The simulation is carried out on practical data set of a residential unit to prove effectiveness of the designed method.","PeriodicalId":316020,"journal":{"name":"2019 20th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127222752","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 : 2019-12-01DOI: 10.1109/ISAP48318.2019.9065946
Negar Dashti, M. A. Zehir, H. Gul, A. Batman, M. Bagriyanik, A. Ozdemir, U. Kucuk, F. Soares
Long-term, regular, grid-aware participants are one of the cornerstones of demand management activities that provide grid services. However, voluntary participation to demand management activities is still at low rates, while most customers are not sufficiently aware of the management potential of their flexible loads. Smart metering and data post-processing play a vital role in demand management programs to visualize consumption profiles, highlight flexibility potential and evaluate load management performance of customers. Additionally, gamification techniques can be employed to motivate users to achieve behavioral changes in their consumption profiles, providing financial and social incentives. Long-term field demonstrations and exploration of detailed evaluation metrics have been the main gaps in this area of study. This paper presents and discusses the results of a 13-month field demonstration of a gamified residential demand management platform. 4-month monitoring period is followed by a 9-month gamification period in four houses in Istanbul, Turkey.
{"title":"Detailed Evaluation of Long-term Gamified Residential Demand Management System Field Implementation","authors":"Negar Dashti, M. A. Zehir, H. Gul, A. Batman, M. Bagriyanik, A. Ozdemir, U. Kucuk, F. Soares","doi":"10.1109/ISAP48318.2019.9065946","DOIUrl":"https://doi.org/10.1109/ISAP48318.2019.9065946","url":null,"abstract":"Long-term, regular, grid-aware participants are one of the cornerstones of demand management activities that provide grid services. However, voluntary participation to demand management activities is still at low rates, while most customers are not sufficiently aware of the management potential of their flexible loads. Smart metering and data post-processing play a vital role in demand management programs to visualize consumption profiles, highlight flexibility potential and evaluate load management performance of customers. Additionally, gamification techniques can be employed to motivate users to achieve behavioral changes in their consumption profiles, providing financial and social incentives. Long-term field demonstrations and exploration of detailed evaluation metrics have been the main gaps in this area of study. This paper presents and discusses the results of a 13-month field demonstration of a gamified residential demand management platform. 4-month monitoring period is followed by a 9-month gamification period in four houses in Istanbul, Turkey.","PeriodicalId":316020,"journal":{"name":"2019 20th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"602 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133830118","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 : 2019-12-01DOI: 10.1109/ISAP48318.2019.9065948
A. Enriquez, S. Lima, O. Saavedra
Power transformers submerged in oil are very important electrical equipment in the operation of an electrical system, they fulfill the essential role of transforming a level of voltage and current to the requirements of the User / Operator of the Electrical System; A significant aspect in the operation of an electrical system is the economic factor, since a contingency in the power transformer with service interruption can lead to considerable economic losses for the agents involved. In this work of investigation, is developed and analyzed a methodology for diagnose faults in power transformers by application of K-NN classifier with weighted classification distance, the training sample is considered the real data added to the densified data by mean shift algorithm (on the DGA sample), the performance recorded in the validation process is 97.73%.
{"title":"K-NN and Mean-Shift Algorithm Applied in Fault Diagnosis in Power Transformers by DGA","authors":"A. Enriquez, S. Lima, O. Saavedra","doi":"10.1109/ISAP48318.2019.9065948","DOIUrl":"https://doi.org/10.1109/ISAP48318.2019.9065948","url":null,"abstract":"Power transformers submerged in oil are very important electrical equipment in the operation of an electrical system, they fulfill the essential role of transforming a level of voltage and current to the requirements of the User / Operator of the Electrical System; A significant aspect in the operation of an electrical system is the economic factor, since a contingency in the power transformer with service interruption can lead to considerable economic losses for the agents involved. In this work of investigation, is developed and analyzed a methodology for diagnose faults in power transformers by application of K-NN classifier with weighted classification distance, the training sample is considered the real data added to the densified data by mean shift algorithm (on the DGA sample), the performance recorded in the validation process is 97.73%.","PeriodicalId":316020,"journal":{"name":"2019 20th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125949557","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 : 2019-12-01DOI: 10.1109/ISAP48318.2019.9065965
M. Sugimura, T. Senjyu, N. Krishna, P. Mandal, M. Abdel-Akher, A. Hemeida
A program called demand response (DR) is recently attracted attention because of the background of constraints on energy supply and the weakness of centralized energy systems, etc., appeard after the Great East Japan Earthquake. Real-Time Pricing (RTP) is a type of DR allows consumers to adjust the power consumption by reflecting the wholesale electricity price formed according to time in the electricity rate. In this paper, Photovoltaic (PV) and Wind Generator (WG) and Diesel Generator (DG) are used as the main power sources in Aguni-Island in Okinawa prefecture, where the peak demand is 1 MW. This study presents the operation schedule of DG and Battery Energy Storage System (BESS). It also evaluates the optimal capacity method of the equipment when DR is taken into consideration.
{"title":"Sizing and Operation Optimization for Renewable Energy facilities with Demand Response in Micro-grid","authors":"M. Sugimura, T. Senjyu, N. Krishna, P. Mandal, M. Abdel-Akher, A. Hemeida","doi":"10.1109/ISAP48318.2019.9065965","DOIUrl":"https://doi.org/10.1109/ISAP48318.2019.9065965","url":null,"abstract":"A program called demand response (DR) is recently attracted attention because of the background of constraints on energy supply and the weakness of centralized energy systems, etc., appeard after the Great East Japan Earthquake. Real-Time Pricing (RTP) is a type of DR allows consumers to adjust the power consumption by reflecting the wholesale electricity price formed according to time in the electricity rate. In this paper, Photovoltaic (PV) and Wind Generator (WG) and Diesel Generator (DG) are used as the main power sources in Aguni-Island in Okinawa prefecture, where the peak demand is 1 MW. This study presents the operation schedule of DG and Battery Energy Storage System (BESS). It also evaluates the optimal capacity method of the equipment when DR is taken into consideration.","PeriodicalId":316020,"journal":{"name":"2019 20th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125469990","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 : 2019-12-01DOI: 10.1109/ISAP48318.2019.9065947
Shipra Tiwari, Omar Hanif, S. Sarangi
DC-DC converters are generally modeled using small-signal approximations considering small perturbations around a steady-state point. However, this is limited to a certain range of operation which in the presence of harmonic content in addition to dc offset might not provide an accurate result. Generalized Average modeling takes into account the harmonic contents along with the dc values and this can be used for alternating components such as inductor current in a Dual Active Bridge converter. The transfer function is derived which is an open-loop stable system, and in order to establish closed-loop stability, fractional order PI controller is used in this paper. Further, the optimization technique is applied in order to optimize the control variables as the degree of freedom has increased due to the incorporation of fractional powers. These optimized values are used to establish the closed-loop stable operation of a DAB converter and the technique is validated through MATLAB simulations. The entire results are shown in the figures with specifications tabulated and confirm the accurate setpoint tracking with the ripples in range.
{"title":"Fractional Order PI Control of Dual Active Bridge Converter Using Generalized Average Modelling","authors":"Shipra Tiwari, Omar Hanif, S. Sarangi","doi":"10.1109/ISAP48318.2019.9065947","DOIUrl":"https://doi.org/10.1109/ISAP48318.2019.9065947","url":null,"abstract":"DC-DC converters are generally modeled using small-signal approximations considering small perturbations around a steady-state point. However, this is limited to a certain range of operation which in the presence of harmonic content in addition to dc offset might not provide an accurate result. Generalized Average modeling takes into account the harmonic contents along with the dc values and this can be used for alternating components such as inductor current in a Dual Active Bridge converter. The transfer function is derived which is an open-loop stable system, and in order to establish closed-loop stability, fractional order PI controller is used in this paper. Further, the optimization technique is applied in order to optimize the control variables as the degree of freedom has increased due to the incorporation of fractional powers. These optimized values are used to establish the closed-loop stable operation of a DAB converter and the technique is validated through MATLAB simulations. The entire results are shown in the figures with specifications tabulated and confirm the accurate setpoint tracking with the ripples in range.","PeriodicalId":316020,"journal":{"name":"2019 20th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127957053","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 : 2019-12-01DOI: 10.1109/ISAP48318.2019.9065942
Sangeeta Das, D. Das, A. Patra
This paper presents a framework for operation of the distribution network with distributed generation in floating mode. The term ‘floating mode’ is aimed at making the distribution network draw negligible power from the grid along with the reduction of power losses and improvement of voltage profile. Under floating mode operation, the distribution network remains connected with the grid to allow the grid to dictate the voltage and frequency. If load demand increases, the grid can supply the additional load power and if the load demand decreases, the excess power from the network will be fed back to the grid. This proposed approach is achieved in detail using dispatchable DGs operating at lagging power factor considering three load levels. Fuzzy max-min principle is used to find the optimal location of DGs. The optimization of the DG sizing is achieved using a combination of fuzzy maxmin technique with genetic algorithm. Effectiveness of the proposed methodology is presented through an example of a 60 node distribution network.
{"title":"Operation of Distribution Network with Distributed Generation in Floating Mode","authors":"Sangeeta Das, D. Das, A. Patra","doi":"10.1109/ISAP48318.2019.9065942","DOIUrl":"https://doi.org/10.1109/ISAP48318.2019.9065942","url":null,"abstract":"This paper presents a framework for operation of the distribution network with distributed generation in floating mode. The term ‘floating mode’ is aimed at making the distribution network draw negligible power from the grid along with the reduction of power losses and improvement of voltage profile. Under floating mode operation, the distribution network remains connected with the grid to allow the grid to dictate the voltage and frequency. If load demand increases, the grid can supply the additional load power and if the load demand decreases, the excess power from the network will be fed back to the grid. This proposed approach is achieved in detail using dispatchable DGs operating at lagging power factor considering three load levels. Fuzzy max-min principle is used to find the optimal location of DGs. The optimization of the DG sizing is achieved using a combination of fuzzy maxmin technique with genetic algorithm. Effectiveness of the proposed methodology is presented through an example of a 60 node distribution network.","PeriodicalId":316020,"journal":{"name":"2019 20th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122218007","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 : 2019-12-01DOI: 10.1109/ISAP48318.2019.9065972
B. S. Torres, L. D. da Silva, C. Salomon, A. R. Aoki, L. R. Ferreira, G. Lambert-Torres, J. S. Filho
The ever-increasing demand for power supply with reliability and quality has leading the power utilities to stablish new operation procedures, automatism and more flexible infrastructures. In this context, the concept of smart grids emerges, aiming to meet the consumers in an efficient way, with high levels of continuity and quality. The smart grids structure has made possible that systemic restoring can be improved by the introduction of other types of electric power supply and electric network automation. This paper presents a comparative analysis between methodologies for automatic restoration in smart grids aiming to verify the quality of their response and consistency of results for several contingency situations. The analysis is accomplished by performing simulation in a real distribution system and testing the different methodologies.
{"title":"A Study of Distribution System Self-Healing Considering Intelligent Approaches","authors":"B. S. Torres, L. D. da Silva, C. Salomon, A. R. Aoki, L. R. Ferreira, G. Lambert-Torres, J. S. Filho","doi":"10.1109/ISAP48318.2019.9065972","DOIUrl":"https://doi.org/10.1109/ISAP48318.2019.9065972","url":null,"abstract":"The ever-increasing demand for power supply with reliability and quality has leading the power utilities to stablish new operation procedures, automatism and more flexible infrastructures. In this context, the concept of smart grids emerges, aiming to meet the consumers in an efficient way, with high levels of continuity and quality. The smart grids structure has made possible that systemic restoring can be improved by the introduction of other types of electric power supply and electric network automation. This paper presents a comparative analysis between methodologies for automatic restoration in smart grids aiming to verify the quality of their response and consistency of results for several contingency situations. The analysis is accomplished by performing simulation in a real distribution system and testing the different methodologies.","PeriodicalId":316020,"journal":{"name":"2019 20th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132383534","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 : 2019-12-01DOI: 10.1109/ISAP48318.2019.9065985
Dogan Urgun, C. Singh
This paper proposes a new approach for evaluation of power systems reliability using Monte Carlo Simulation. Using standard Monte Carlo Simulation, a composite of Convolutional Neural Networks (CNN) and Importance Sampling (IS) is proposed for computing power system reliability indices. It is shown that the computational efficiency can be dramatically increased if the machine learning techniques are used in conjunction with well-known variance reduction technique of importance sampling. The IEEE Reliability Test System (IEEE-RTS) is used for studying the proposed method. The results of case studies show that CNNs together with importance sampling provide a good classification accuracy while reducing computation time substantially.
{"title":"Composite Power System Reliability Evaluation Using Importance Sampling and Convolutional Neural Networks","authors":"Dogan Urgun, C. Singh","doi":"10.1109/ISAP48318.2019.9065985","DOIUrl":"https://doi.org/10.1109/ISAP48318.2019.9065985","url":null,"abstract":"This paper proposes a new approach for evaluation of power systems reliability using Monte Carlo Simulation. Using standard Monte Carlo Simulation, a composite of Convolutional Neural Networks (CNN) and Importance Sampling (IS) is proposed for computing power system reliability indices. It is shown that the computational efficiency can be dramatically increased if the machine learning techniques are used in conjunction with well-known variance reduction technique of importance sampling. The IEEE Reliability Test System (IEEE-RTS) is used for studying the proposed method. The results of case studies show that CNNs together with importance sampling provide a good classification accuracy while reducing computation time substantially.","PeriodicalId":316020,"journal":{"name":"2019 20th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"494 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127926386","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 : 2019-12-01DOI: 10.1109/ISAP48318.2019.9065971
Enos Bright Masereka, W. Kitagawa, T. Takeshita
Directional Overcurrent Relays (DOCR) are widely used in meshed distribution and sub-transmission networks to provide inexpensive primary protection and in transmission systems as the second line of protection to distance and/or differential protection relays that serve as the primary protection system. DOCR operation settings (current Pick-up $I_{pickup}$ and Time Multiplier Setting TMS) must ensure that the protection system maintains selectivity during fault isolation at all times. For optimal setting and coordinated operation of DOCR relays, this paper proposes a modified objective function and is tested using a genetic algorithm to obtain the optimal settings for the IEEE 8-bus test grid.
{"title":"Optimal Coordination of Directional Overcurrent Relays Considering a Modified Objective Function Using Genetic Algorithm","authors":"Enos Bright Masereka, W. Kitagawa, T. Takeshita","doi":"10.1109/ISAP48318.2019.9065971","DOIUrl":"https://doi.org/10.1109/ISAP48318.2019.9065971","url":null,"abstract":"Directional Overcurrent Relays (DOCR) are widely used in meshed distribution and sub-transmission networks to provide inexpensive primary protection and in transmission systems as the second line of protection to distance and/or differential protection relays that serve as the primary protection system. DOCR operation settings (current Pick-up $I_{pickup}$ and Time Multiplier Setting TMS) must ensure that the protection system maintains selectivity during fault isolation at all times. For optimal setting and coordinated operation of DOCR relays, this paper proposes a modified objective function and is tested using a genetic algorithm to obtain the optimal settings for the IEEE 8-bus test grid.","PeriodicalId":316020,"journal":{"name":"2019 20th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"360 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116692493","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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