Pub Date : 2013-05-21DOI: 10.1109/ENERGYTECH.2013.6645343
K. Shenai
The field-failures of a power converter depends on the reliability characteristics of circuit components, package and interconnect parasitics, thermal management and cooling, load characteristics, and the field operating environment, among other factors. In this paper, power supply field-reliability improvement by careful screening of power MOSFET's is reported. A new power MOSFET screening criteria is proposed that leads to dramatic improvement in the mean-time-between-failure (MTBF) of compact computer/telecom power supplies. Using the new screening criteria, nearly an order of magnitude improvement in power supply MTBF is demonstrated.
{"title":"Power MOSFET screening to improve field-reliability of power supplies","authors":"K. Shenai","doi":"10.1109/ENERGYTECH.2013.6645343","DOIUrl":"https://doi.org/10.1109/ENERGYTECH.2013.6645343","url":null,"abstract":"The field-failures of a power converter depends on the reliability characteristics of circuit components, package and interconnect parasitics, thermal management and cooling, load characteristics, and the field operating environment, among other factors. In this paper, power supply field-reliability improvement by careful screening of power MOSFET's is reported. A new power MOSFET screening criteria is proposed that leads to dramatic improvement in the mean-time-between-failure (MTBF) of compact computer/telecom power supplies. Using the new screening criteria, nearly an order of magnitude improvement in power supply MTBF is demonstrated.","PeriodicalId":154402,"journal":{"name":"2013 IEEE Energytech","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133067082","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 : 2013-05-21DOI: 10.1109/ENERGYTECH.2013.6645316
Adeeb Ahmed, Y. Sozer, M. Hamdan
An adaptive flux weakening control scheme is proposed for the surface permanent magnet synchronous machine (PMSM). The method adaptively controls the demagnetizing current with changes in speed or load torque. The method does not require DC bus voltage sensing of the power converter and unsusceptible to the motor parameter changes. No requirement of bus voltage makes it suitable for voltage sensor less control in battery operated hybrid electric drives where supply voltage changes with state of charge (SoC) of the battery pack. The control scheme is mostly suitable for variable speed operation where rapid speed changes occur. Response time is made faster by incorporating necessary alteration in previous methods. Faster response time on controlling the demagnetizing currents ensures more energy efficient operation. Simulation and experimental results are presented to demonstrate the functionality of the proposed scheme.
{"title":"Flux weakening control for surface mount permanent magnet synchronous motor (PMSM) drives with rapid load and speed varying applications","authors":"Adeeb Ahmed, Y. Sozer, M. Hamdan","doi":"10.1109/ENERGYTECH.2013.6645316","DOIUrl":"https://doi.org/10.1109/ENERGYTECH.2013.6645316","url":null,"abstract":"An adaptive flux weakening control scheme is proposed for the surface permanent magnet synchronous machine (PMSM). The method adaptively controls the demagnetizing current with changes in speed or load torque. The method does not require DC bus voltage sensing of the power converter and unsusceptible to the motor parameter changes. No requirement of bus voltage makes it suitable for voltage sensor less control in battery operated hybrid electric drives where supply voltage changes with state of charge (SoC) of the battery pack. The control scheme is mostly suitable for variable speed operation where rapid speed changes occur. Response time is made faster by incorporating necessary alteration in previous methods. Faster response time on controlling the demagnetizing currents ensures more energy efficient operation. Simulation and experimental results are presented to demonstrate the functionality of the proposed scheme.","PeriodicalId":154402,"journal":{"name":"2013 IEEE Energytech","volume":"298 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114575298","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 : 2013-05-21DOI: 10.1109/ENERGYTECH.2013.6645333
Y. Li, M. Cheng, E. Bakhoum
In the past, most of the operating strategies of energy harvesting devices focus only on the resonant frequency of its first mode. The resonant frequency in this mode is fine tuned with an attached proof mass. This paper presents a new approach of operating energy harvesting devices in different vibration modes. With this operation strategy, the harvested power can be increased. The resonant frequencies of adopted piezoelectric devices in different modes can be fine tuned with the same mechanism. A mathematical model that estimates resonant frequencies of piezoelectric cantilevers is proposed for various scenarios. The theoretical results have also been validated by experiments with different mass moving along the experimental cantilever. Other important factors, such as resistive loads, that affect output power are discussed as well.
{"title":"Operation of energy harvesting devices in different vibration modes","authors":"Y. Li, M. Cheng, E. Bakhoum","doi":"10.1109/ENERGYTECH.2013.6645333","DOIUrl":"https://doi.org/10.1109/ENERGYTECH.2013.6645333","url":null,"abstract":"In the past, most of the operating strategies of energy harvesting devices focus only on the resonant frequency of its first mode. The resonant frequency in this mode is fine tuned with an attached proof mass. This paper presents a new approach of operating energy harvesting devices in different vibration modes. With this operation strategy, the harvested power can be increased. The resonant frequencies of adopted piezoelectric devices in different modes can be fine tuned with the same mechanism. A mathematical model that estimates resonant frequencies of piezoelectric cantilevers is proposed for various scenarios. The theoretical results have also been validated by experiments with different mass moving along the experimental cantilever. Other important factors, such as resistive loads, that affect output power are discussed as well.","PeriodicalId":154402,"journal":{"name":"2013 IEEE Energytech","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121879527","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 : 2013-05-21DOI: 10.1109/ENERGYTECH.2013.6645329
I. Sharma, Kankar Bhattacharya
This paper presents modeling of interruptible loads (ILs) in an unbalanced distribution system. These ILs are then incorporated in the local distribution company's (LDC's) operational framework so as to optimally select the location (node and phase) and amount of IL for a given incentive rate offered by the LDC. The ILs are selected from the contracted customers from the LDC's perspective of minimizing the total cost of energy drawn from the external grid and the total payment made to customers towards procurement of ILs. The proposed model is tested on the IEEE 13-node test feeder. Results show that the proposed IL program is able to reduce costs and aid in feeder operation during peak load periods in the context of smart grids.
{"title":"Modeling, optimal selection and scheduling of interruptible loads in smart distribution systems","authors":"I. Sharma, Kankar Bhattacharya","doi":"10.1109/ENERGYTECH.2013.6645329","DOIUrl":"https://doi.org/10.1109/ENERGYTECH.2013.6645329","url":null,"abstract":"This paper presents modeling of interruptible loads (ILs) in an unbalanced distribution system. These ILs are then incorporated in the local distribution company's (LDC's) operational framework so as to optimally select the location (node and phase) and amount of IL for a given incentive rate offered by the LDC. The ILs are selected from the contracted customers from the LDC's perspective of minimizing the total cost of energy drawn from the external grid and the total payment made to customers towards procurement of ILs. The proposed model is tested on the IEEE 13-node test feeder. Results show that the proposed IL program is able to reduce costs and aid in feeder operation during peak load periods in the context of smart grids.","PeriodicalId":154402,"journal":{"name":"2013 IEEE Energytech","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128643399","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 : 2013-05-21DOI: 10.1109/ENERGYTECH.2013.6645354
Nicholas R. Wheeler, L. Bruckman, Junheng Ma, Ethan Wang, Carl K. Wang, Ivan Chou, Jiayang Sun, R. French
To optimize and extend the lifetime of photovoltaic (PV) modules, a better understanding of the modes and rates of their degradation is necessary. Lifetime and degradation science (L&DS) is used to better understand degradation modes, mechanisms and rates of materials, components and systems in order to predict lifetime of PV modules. Statistical analytic methods were used to investigate the relationships between various subsystem characteristics related to suspected degradation pathways, as well as their impact on changes in module performance. A PV module lifetime and degradation science (PVM L&DS) model developed in this way is an essential component to predict lifetime and mitigate degradation of PV modules. Previously published accelerated testing data from Underwriter Labs, featuring measurements taken on 18 modules with fluoropolymer, polyester and EVA (FPE) backsheets, were used to develop the analytical methodology. To populate this dataset, three performance characteristics for each module were tracked over a maximum of 4000 hours while the modules were exposed to stressful conditions. Two of the eighteen modules' performance characteristics were measured with no exposure to stress, and then dissassembled immediately to provide baseline measurements. Eight of the sixteen remaining modules were exposed to 85% relative humidity at 85°C (Damp Heat, DH) and the final eight were exposed to 80W/m2 of ultraviolet light at 280-400nm wavelengths and 60°C (UV). Four of the sixteen modules being exposed (two from DH conditions and two from UV conditions) were removed at each 1000 hour time point and disassembled to provide observations for eleven component level experiments, six directly related to degradation mechanisms and five to material performance characteristics. The resulting dataset comprised of coincident observations of 15 variables (time, three system-level performance variables, and eleven component-level variables) was statistically analyzed using the developed methodology. Limitations in the quantity of coincident observations constrained the statistical study to require the use of domain knowledge to pre-select a subset of variables for analysis, which introduced undesirable bias and prevented the full development of a prognostic model from this dataset alone. The results and lessons learned help guide the experimental design for better structuring further accelerated and real-world experiments, providing necessary insight in order to sample data effectively and efficiently, obtain maximum information for identifying statistically significant relationships between variables, and develop a PVM L&DS model construction methodology to determine degradation modes and pathways present in modules and their effects on module performance over lifetime.
{"title":"Statistical and domain analytics for informed study protocols","authors":"Nicholas R. Wheeler, L. Bruckman, Junheng Ma, Ethan Wang, Carl K. Wang, Ivan Chou, Jiayang Sun, R. French","doi":"10.1109/ENERGYTECH.2013.6645354","DOIUrl":"https://doi.org/10.1109/ENERGYTECH.2013.6645354","url":null,"abstract":"To optimize and extend the lifetime of photovoltaic (PV) modules, a better understanding of the modes and rates of their degradation is necessary. Lifetime and degradation science (L&DS) is used to better understand degradation modes, mechanisms and rates of materials, components and systems in order to predict lifetime of PV modules. Statistical analytic methods were used to investigate the relationships between various subsystem characteristics related to suspected degradation pathways, as well as their impact on changes in module performance. A PV module lifetime and degradation science (PVM L&DS) model developed in this way is an essential component to predict lifetime and mitigate degradation of PV modules. Previously published accelerated testing data from Underwriter Labs, featuring measurements taken on 18 modules with fluoropolymer, polyester and EVA (FPE) backsheets, were used to develop the analytical methodology. To populate this dataset, three performance characteristics for each module were tracked over a maximum of 4000 hours while the modules were exposed to stressful conditions. Two of the eighteen modules' performance characteristics were measured with no exposure to stress, and then dissassembled immediately to provide baseline measurements. Eight of the sixteen remaining modules were exposed to 85% relative humidity at 85°C (Damp Heat, DH) and the final eight were exposed to 80W/m2 of ultraviolet light at 280-400nm wavelengths and 60°C (UV). Four of the sixteen modules being exposed (two from DH conditions and two from UV conditions) were removed at each 1000 hour time point and disassembled to provide observations for eleven component level experiments, six directly related to degradation mechanisms and five to material performance characteristics. The resulting dataset comprised of coincident observations of 15 variables (time, three system-level performance variables, and eleven component-level variables) was statistically analyzed using the developed methodology. Limitations in the quantity of coincident observations constrained the statistical study to require the use of domain knowledge to pre-select a subset of variables for analysis, which introduced undesirable bias and prevented the full development of a prognostic model from this dataset alone. The results and lessons learned help guide the experimental design for better structuring further accelerated and real-world experiments, providing necessary insight in order to sample data effectively and efficiently, obtain maximum information for identifying statistically significant relationships between variables, and develop a PVM L&DS model construction methodology to determine degradation modes and pathways present in modules and their effects on module performance over lifetime.","PeriodicalId":154402,"journal":{"name":"2013 IEEE Energytech","volume":"94 1-2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133139326","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 : 2013-05-21DOI: 10.1109/ENERGYTECH.2013.6645315
H. Musa, S. S. Adamu
This paper presents an enhanced particle swarm optimization (PSO) algorithm for Distributed Generation (DG) placement and sizing using multi-objective optimization concept. It is based on the combination of Evolutionary Programming (EP) and PSO. The merits of EP and PSO are combined together so as to achieve faster convergence and accuracy of the DG sizes. The quality of the solution is improved by exploring the less crowded area in the existing solution space to obtain more non-dominated solutions. The proposed approach was tested on standard IEEE 33 -Bus test system. Result obtained shows the ability of the proposed algorithm towards production of well-distributed Pareto optimal non-dominated solution of the multi-objective DG sizing problem.
{"title":"Enhanced PSO based multi-objective distributed generation placement and sizing for power loss reduction and voltage stability index improvement","authors":"H. Musa, S. S. Adamu","doi":"10.1109/ENERGYTECH.2013.6645315","DOIUrl":"https://doi.org/10.1109/ENERGYTECH.2013.6645315","url":null,"abstract":"This paper presents an enhanced particle swarm optimization (PSO) algorithm for Distributed Generation (DG) placement and sizing using multi-objective optimization concept. It is based on the combination of Evolutionary Programming (EP) and PSO. The merits of EP and PSO are combined together so as to achieve faster convergence and accuracy of the DG sizes. The quality of the solution is improved by exploring the less crowded area in the existing solution space to obtain more non-dominated solutions. The proposed approach was tested on standard IEEE 33 -Bus test system. Result obtained shows the ability of the proposed algorithm towards production of well-distributed Pareto optimal non-dominated solution of the multi-objective DG sizing problem.","PeriodicalId":154402,"journal":{"name":"2013 IEEE Energytech","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131642873","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 : 2013-05-21DOI: 10.1109/ENERGYTECH.2013.6645321
Jawad Ghorbani, S. Chouhan, M. Choudhry, A. Feliachi
In this paper a hybrid multi agent system approach for fast power restoration in power distribution systems is presented. Hybrid structure of MAS provides the capability of solving the restoration problem with taking the advantages of both centralized and distributed agent structures. Bottom-up order of agents constructing the MAS is zone agents, feeder and substation agents. In this architecture, agents have the permission to execute a function based on their hierarchy level and the control central supervisory is not always required. After the fault location and isolation, agents start communicating with their higher level agents to initiate the reconfiguration and restoration plans. According to the algorithm, agents try to restore the un-faulted zones as much as possible considering the restoration constraints. An existing Mon Power distribution system with 5 feeders is selected for computer simulation to test the effectiveness of proposed approach. The simulation results show that the proposed multi agent approach is effective and promising.
{"title":"Hybrid multi agent approach for power distribution system restoration","authors":"Jawad Ghorbani, S. Chouhan, M. Choudhry, A. Feliachi","doi":"10.1109/ENERGYTECH.2013.6645321","DOIUrl":"https://doi.org/10.1109/ENERGYTECH.2013.6645321","url":null,"abstract":"In this paper a hybrid multi agent system approach for fast power restoration in power distribution systems is presented. Hybrid structure of MAS provides the capability of solving the restoration problem with taking the advantages of both centralized and distributed agent structures. Bottom-up order of agents constructing the MAS is zone agents, feeder and substation agents. In this architecture, agents have the permission to execute a function based on their hierarchy level and the control central supervisory is not always required. After the fault location and isolation, agents start communicating with their higher level agents to initiate the reconfiguration and restoration plans. According to the algorithm, agents try to restore the un-faulted zones as much as possible considering the restoration constraints. An existing Mon Power distribution system with 5 feeders is selected for computer simulation to test the effectiveness of proposed approach. The simulation results show that the proposed multi agent approach is effective and promising.","PeriodicalId":154402,"journal":{"name":"2013 IEEE Energytech","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131053769","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 : 2013-05-21DOI: 10.1109/ENERGYTECH.2013.6645291
D. Echternacht, Daniel Heuberger, C. Breuer, C. Linnemann, A. Moser
A rising penetration of renewable energies and the resulting changes in the generation system render extensive grid reinforcements throughout Europe inevitable. Up till now grid reinforcements are mostly done using HVAC technology but for future extensions as for example in Germany HVDC technology is on the rise. To optimally integrate these future HVDC links into the existing AC networks the terminal positions have to be chosen wisely to mitigate grid congestions. This paper presents an approach to identify optimal terminal positions based on two technical criterions. To demonstrate the effectiveness the presented methodology is applied on a European grid model in a prospective scenario for the year 2022.
{"title":"Advantageous positions for HVDC terminals in Europe","authors":"D. Echternacht, Daniel Heuberger, C. Breuer, C. Linnemann, A. Moser","doi":"10.1109/ENERGYTECH.2013.6645291","DOIUrl":"https://doi.org/10.1109/ENERGYTECH.2013.6645291","url":null,"abstract":"A rising penetration of renewable energies and the resulting changes in the generation system render extensive grid reinforcements throughout Europe inevitable. Up till now grid reinforcements are mostly done using HVAC technology but for future extensions as for example in Germany HVDC technology is on the rise. To optimally integrate these future HVDC links into the existing AC networks the terminal positions have to be chosen wisely to mitigate grid congestions. This paper presents an approach to identify optimal terminal positions based on two technical criterions. To demonstrate the effectiveness the presented methodology is applied on a European grid model in a prospective scenario for the year 2022.","PeriodicalId":154402,"journal":{"name":"2013 IEEE Energytech","volume":"207 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133820359","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 : 2013-05-21DOI: 10.1109/ENERGYTECH.2013.6645349
P. Christopher
Gerard O'Neill's outstanding satellite solar array concepts are updated from geostationary systems to include sun synchronous low earth orbits and Brandon Molniya orbits. The low earth orbits would offer low cost and Brandon orbits would offer the convenience of stationary ground antennas. Ten micron laser links are studied for low cost and low cloud attenuation.
{"title":"Satellite solar array with laser downlink to denver","authors":"P. Christopher","doi":"10.1109/ENERGYTECH.2013.6645349","DOIUrl":"https://doi.org/10.1109/ENERGYTECH.2013.6645349","url":null,"abstract":"Gerard O'Neill's outstanding satellite solar array concepts are updated from geostationary systems to include sun synchronous low earth orbits and Brandon Molniya orbits. The low earth orbits would offer low cost and Brandon orbits would offer the convenience of stationary ground antennas. Ten micron laser links are studied for low cost and low cloud attenuation.","PeriodicalId":154402,"journal":{"name":"2013 IEEE Energytech","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123813581","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 : 2013-05-21DOI: 10.1109/ENERGYTECH.2013.6645290
Hassan Shirzeh, F. Naghdy, P. Ciufo, M. Ros
A smart grid can be considered as an unstructured network of distributed interacting nodes represented by renewable energy sources, storage and loads. The nodes emerge or disappear in a stochastic manner due to the intermittent nature of natural sources such as wind speed and solar irradiation. Prediction and stochastic modelling of electrical energy flow is a critical characteristic in such a network to achieve load balancing and/or peak shaving in order to minimise the fluctuation between off peak and peak demand by power consumers. Before contributing energy to the network, a node acquires information about other nodes in the grid and the state of the grid in order to adjust its power injection to or consumption from the grid. The unpredictable behaviour of nodes in a smart grid is modelled and administered through a scheduling strategy control and learning algorithm using the historical data collected from the system. The stochastic model predicts future power consumption/injection to determine the power required for storage components. In the proposed stochastic model and the deployed learning and adaptation processes, two indicators, based on moving averages of different subsets of the time series are implemented to satisfy two objectives. The first objective is to predict the most efficient state of electrical energy flow between a distribution network and nodes. Whereas the second objective is to minimise the peak demand and off peak consumption of acquiring electrical energy from the main grid by using ant colony search algorithm (ACSA). The performance of the indicators is validated against limited autoregressive integrated moving average (LARIMA) and second order Markov Chain model. It is shown that proposed method outperforms both LARIMA and Markov Chain model.
{"title":"Adaptive stochastic energy flow balancing in smart grid","authors":"Hassan Shirzeh, F. Naghdy, P. Ciufo, M. Ros","doi":"10.1109/ENERGYTECH.2013.6645290","DOIUrl":"https://doi.org/10.1109/ENERGYTECH.2013.6645290","url":null,"abstract":"A smart grid can be considered as an unstructured network of distributed interacting nodes represented by renewable energy sources, storage and loads. The nodes emerge or disappear in a stochastic manner due to the intermittent nature of natural sources such as wind speed and solar irradiation. Prediction and stochastic modelling of electrical energy flow is a critical characteristic in such a network to achieve load balancing and/or peak shaving in order to minimise the fluctuation between off peak and peak demand by power consumers. Before contributing energy to the network, a node acquires information about other nodes in the grid and the state of the grid in order to adjust its power injection to or consumption from the grid. The unpredictable behaviour of nodes in a smart grid is modelled and administered through a scheduling strategy control and learning algorithm using the historical data collected from the system. The stochastic model predicts future power consumption/injection to determine the power required for storage components. In the proposed stochastic model and the deployed learning and adaptation processes, two indicators, based on moving averages of different subsets of the time series are implemented to satisfy two objectives. The first objective is to predict the most efficient state of electrical energy flow between a distribution network and nodes. Whereas the second objective is to minimise the peak demand and off peak consumption of acquiring electrical energy from the main grid by using ant colony search algorithm (ACSA). The performance of the indicators is validated against limited autoregressive integrated moving average (LARIMA) and second order Markov Chain model. It is shown that proposed method outperforms both LARIMA and Markov Chain model.","PeriodicalId":154402,"journal":{"name":"2013 IEEE Energytech","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115924110","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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