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You searched for subject:(distributed optimization in power system). Showing records 1 – 30 of 169355 total matches.

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Penn State University

1. Ahmadi, Hesamoddin. On the Analysis of Data-driven and Distributed Algorithms for Convex Optimization Problems.

Degree: PhD, Industrial Engineering, 2016, Penn State University

 This dissertation considers the resolution of three optimization problems. Of these, the first two problems are closely related and focus on solving optimization problems in… (more)

Subjects/Keywords: Optimization and learning; distributed optimization in power system; convex optimization; augmented Lagrangian

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APA (6th Edition):

Ahmadi, H. (2016). On the Analysis of Data-driven and Distributed Algorithms for Convex Optimization Problems. (Doctoral Dissertation). Penn State University. Retrieved from https://etda.libraries.psu.edu/catalog/29502

Chicago Manual of Style (16th Edition):

Ahmadi, Hesamoddin. “On the Analysis of Data-driven and Distributed Algorithms for Convex Optimization Problems.” 2016. Doctoral Dissertation, Penn State University. Accessed October 20, 2019. https://etda.libraries.psu.edu/catalog/29502.

MLA Handbook (7th Edition):

Ahmadi, Hesamoddin. “On the Analysis of Data-driven and Distributed Algorithms for Convex Optimization Problems.” 2016. Web. 20 Oct 2019.

Vancouver:

Ahmadi H. On the Analysis of Data-driven and Distributed Algorithms for Convex Optimization Problems. [Internet] [Doctoral dissertation]. Penn State University; 2016. [cited 2019 Oct 20]. Available from: https://etda.libraries.psu.edu/catalog/29502.

Council of Science Editors:

Ahmadi H. On the Analysis of Data-driven and Distributed Algorithms for Convex Optimization Problems. [Doctoral Dissertation]. Penn State University; 2016. Available from: https://etda.libraries.psu.edu/catalog/29502


Carnegie Mellon University

2. Guo, Junyao. Distributed Optimization in Electric Power Systems: Partitioning, Communications, and Synchronization.

Degree: 2018, Carnegie Mellon University

 To integrate large volumes of renewables and use electricity more efficiently, many industrial trials are on-going around the world that aim to realize decentralized or… (more)

Subjects/Keywords: asynchronous optimization; distributed optimization; nonconvex optimization; optimal power flow; power system partitioning; smart grid communications

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APA (6th Edition):

Guo, J. (2018). Distributed Optimization in Electric Power Systems: Partitioning, Communications, and Synchronization. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/1140

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Guo, Junyao. “Distributed Optimization in Electric Power Systems: Partitioning, Communications, and Synchronization.” 2018. Thesis, Carnegie Mellon University. Accessed October 20, 2019. http://repository.cmu.edu/dissertations/1140.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Guo, Junyao. “Distributed Optimization in Electric Power Systems: Partitioning, Communications, and Synchronization.” 2018. Web. 20 Oct 2019.

Vancouver:

Guo J. Distributed Optimization in Electric Power Systems: Partitioning, Communications, and Synchronization. [Internet] [Thesis]. Carnegie Mellon University; 2018. [cited 2019 Oct 20]. Available from: http://repository.cmu.edu/dissertations/1140.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Guo J. Distributed Optimization in Electric Power Systems: Partitioning, Communications, and Synchronization. [Thesis]. Carnegie Mellon University; 2018. Available from: http://repository.cmu.edu/dissertations/1140

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Louisiana State University

3. Nazaripouya, Hamidreza. Fault observability in distributed power system.

Degree: MSEE, Electrical and Computer Engineering, 2013, Louisiana State University

 Fault observability as well as fault location algorithms in distributed power system are studied in this thesis. The importance of finding the fault location in… (more)

Subjects/Keywords: Distributed Power System; Fault Observability; Optimization; Fault Location; PMU

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APA (6th Edition):

Nazaripouya, H. (2013). Fault observability in distributed power system. (Masters Thesis). Louisiana State University. Retrieved from etd-06152013-213900 ; https://digitalcommons.lsu.edu/gradschool_theses/982

Chicago Manual of Style (16th Edition):

Nazaripouya, Hamidreza. “Fault observability in distributed power system.” 2013. Masters Thesis, Louisiana State University. Accessed October 20, 2019. etd-06152013-213900 ; https://digitalcommons.lsu.edu/gradschool_theses/982.

MLA Handbook (7th Edition):

Nazaripouya, Hamidreza. “Fault observability in distributed power system.” 2013. Web. 20 Oct 2019.

Vancouver:

Nazaripouya H. Fault observability in distributed power system. [Internet] [Masters thesis]. Louisiana State University; 2013. [cited 2019 Oct 20]. Available from: etd-06152013-213900 ; https://digitalcommons.lsu.edu/gradschool_theses/982.

Council of Science Editors:

Nazaripouya H. Fault observability in distributed power system. [Masters Thesis]. Louisiana State University; 2013. Available from: etd-06152013-213900 ; https://digitalcommons.lsu.edu/gradschool_theses/982


University of Manitoba

4. Goulkhah, Mohammad (Monty). Waveform relaxation based hardware-in-the-loop simulation.

Degree: Electrical and Computer Engineering, 2014, University of Manitoba

 This thesis introduces an alternative potentially low cost solution for hardware-in-the-loop (HIL) simulation based on the waveform relaxation (WR) method. The WR tech-nique is extended… (more)

Subjects/Keywords: Waveform Relaxation; Hardware-in-the-Loop simulation; Waveform Relaxation convergence; HIL simulation stability; Power system equipment testing; Waveform Relaxation convergence acceleration; Distributed HIL simulation; Real-Time Player/Recorder; Controller optimization

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APA (6th Edition):

Goulkhah, M. (. (2014). Waveform relaxation based hardware-in-the-loop simulation. (Thesis). University of Manitoba. Retrieved from http://hdl.handle.net/1993/31012

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Goulkhah, Mohammad (Monty). “Waveform relaxation based hardware-in-the-loop simulation.” 2014. Thesis, University of Manitoba. Accessed October 20, 2019. http://hdl.handle.net/1993/31012.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Goulkhah, Mohammad (Monty). “Waveform relaxation based hardware-in-the-loop simulation.” 2014. Web. 20 Oct 2019.

Vancouver:

Goulkhah M(. Waveform relaxation based hardware-in-the-loop simulation. [Internet] [Thesis]. University of Manitoba; 2014. [cited 2019 Oct 20]. Available from: http://hdl.handle.net/1993/31012.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Goulkhah M(. Waveform relaxation based hardware-in-the-loop simulation. [Thesis]. University of Manitoba; 2014. Available from: http://hdl.handle.net/1993/31012

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Texas – Austin

5. -0333-3981. Model-based dynamic relaying for power system protection under uncertainty.

Degree: PhD, Electrical and Computer Engineering, 2019, University of Texas – Austin

 Several major cascading outages have involved mis-operation or mis-coordination of protective relays during stressed system conditions that resulted in a vulnerable network. Such stressed conditions… (more)

Subjects/Keywords: Power system protection; Power system fault analysis; Distributed generation; Supervised learning; Mixed-integer programming; Stochastic optimization

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APA (6th Edition):

-0333-3981. (2019). Model-based dynamic relaying for power system protection under uncertainty. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/2692

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Chicago Manual of Style (16th Edition):

-0333-3981. “Model-based dynamic relaying for power system protection under uncertainty.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed October 20, 2019. http://dx.doi.org/10.26153/tsw/2692.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7th Edition):

-0333-3981. “Model-based dynamic relaying for power system protection under uncertainty.” 2019. Web. 20 Oct 2019.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-0333-3981. Model-based dynamic relaying for power system protection under uncertainty. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2019 Oct 20]. Available from: http://dx.doi.org/10.26153/tsw/2692.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-0333-3981. Model-based dynamic relaying for power system protection under uncertainty. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/2692

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete


University of Waterloo

6. BUSNAINA, JAMAL. Zone-Distributed Optimization System for Energy Management in Smart Grids.

Degree: 2017, University of Waterloo

 Energy management system (EMS) is an important component of smart grid operation. A proper EMS is the key to the integration of smart grid (SG)… (more)

Subjects/Keywords: smart grid; energy management system; semi definite programming; distributed; zoning; optimization; optimal power flow

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APA (6th Edition):

BUSNAINA, J. (2017). Zone-Distributed Optimization System for Energy Management in Smart Grids. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/12202

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

BUSNAINA, JAMAL. “Zone-Distributed Optimization System for Energy Management in Smart Grids.” 2017. Thesis, University of Waterloo. Accessed October 20, 2019. http://hdl.handle.net/10012/12202.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

BUSNAINA, JAMAL. “Zone-Distributed Optimization System for Energy Management in Smart Grids.” 2017. Web. 20 Oct 2019.

Vancouver:

BUSNAINA J. Zone-Distributed Optimization System for Energy Management in Smart Grids. [Internet] [Thesis]. University of Waterloo; 2017. [cited 2019 Oct 20]. Available from: http://hdl.handle.net/10012/12202.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

BUSNAINA J. Zone-Distributed Optimization System for Energy Management in Smart Grids. [Thesis]. University of Waterloo; 2017. Available from: http://hdl.handle.net/10012/12202

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of New South Wales

7. Zhang, Cuo. Robustly optimal operation and planning of distributed energy resources in active distribution networks.

Degree: Electrical Engineering & Telecommunications, 2018, University of New South Wales

Distributed energy resources (DERs) with nature of flexible allocation bring significant technical and economic benefits to modern power systems. DERs include distributed generation (DG) units,… (more)

Subjects/Keywords: Active distribution network; Robust optimization; Distributed energy resources; Microgird; Power system operation and Planning

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APA (6th Edition):

Zhang, C. (2018). Robustly optimal operation and planning of distributed energy resources in active distribution networks. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/60072

Chicago Manual of Style (16th Edition):

Zhang, Cuo. “Robustly optimal operation and planning of distributed energy resources in active distribution networks.” 2018. Doctoral Dissertation, University of New South Wales. Accessed October 20, 2019. http://handle.unsw.edu.au/1959.4/60072.

MLA Handbook (7th Edition):

Zhang, Cuo. “Robustly optimal operation and planning of distributed energy resources in active distribution networks.” 2018. Web. 20 Oct 2019.

Vancouver:

Zhang C. Robustly optimal operation and planning of distributed energy resources in active distribution networks. [Internet] [Doctoral dissertation]. University of New South Wales; 2018. [cited 2019 Oct 20]. Available from: http://handle.unsw.edu.au/1959.4/60072.

Council of Science Editors:

Zhang C. Robustly optimal operation and planning of distributed energy resources in active distribution networks. [Doctoral Dissertation]. University of New South Wales; 2018. Available from: http://handle.unsw.edu.au/1959.4/60072


University of Waterloo

8. Rajaei, Nazila. Fault Current Management in Power Systems using Inverter Based Distributed Generators.

Degree: 2015, University of Waterloo

Distributed generator (DG) connection to power systems has attained special attention in recent years because it provides a number of operational and economic benefits for… (more)

Subjects/Keywords: Power system protection; Distributed generators

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APA (6th Edition):

Rajaei, N. (2015). Fault Current Management in Power Systems using Inverter Based Distributed Generators. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/9264

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Rajaei, Nazila. “Fault Current Management in Power Systems using Inverter Based Distributed Generators.” 2015. Thesis, University of Waterloo. Accessed October 20, 2019. http://hdl.handle.net/10012/9264.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Rajaei, Nazila. “Fault Current Management in Power Systems using Inverter Based Distributed Generators.” 2015. Web. 20 Oct 2019.

Vancouver:

Rajaei N. Fault Current Management in Power Systems using Inverter Based Distributed Generators. [Internet] [Thesis]. University of Waterloo; 2015. [cited 2019 Oct 20]. Available from: http://hdl.handle.net/10012/9264.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Rajaei N. Fault Current Management in Power Systems using Inverter Based Distributed Generators. [Thesis]. University of Waterloo; 2015. Available from: http://hdl.handle.net/10012/9264

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of New South Wales

9. Haghdadi, Navid. Data-driven Assessment of Aggregate Distributed Photovoltaic Generation and its Impacts on Electricity Network Planning.

Degree: Photovoltaics & Renewable Energy Engineering, 2017, University of New South Wales

 Photovoltaics (PV) has emerged as a globally significant source of electricity generation over the past decade. Distributed PV systems in particular have significant implications for… (more)

Subjects/Keywords: Planning; Distributed photovoltaic; Power system

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APA (6th Edition):

Haghdadi, N. (2017). Data-driven Assessment of Aggregate Distributed Photovoltaic Generation and its Impacts on Electricity Network Planning. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/58955 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:48032/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Haghdadi, Navid. “Data-driven Assessment of Aggregate Distributed Photovoltaic Generation and its Impacts on Electricity Network Planning.” 2017. Doctoral Dissertation, University of New South Wales. Accessed October 20, 2019. http://handle.unsw.edu.au/1959.4/58955 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:48032/SOURCE02?view=true.

MLA Handbook (7th Edition):

Haghdadi, Navid. “Data-driven Assessment of Aggregate Distributed Photovoltaic Generation and its Impacts on Electricity Network Planning.” 2017. Web. 20 Oct 2019.

Vancouver:

Haghdadi N. Data-driven Assessment of Aggregate Distributed Photovoltaic Generation and its Impacts on Electricity Network Planning. [Internet] [Doctoral dissertation]. University of New South Wales; 2017. [cited 2019 Oct 20]. Available from: http://handle.unsw.edu.au/1959.4/58955 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:48032/SOURCE02?view=true.

Council of Science Editors:

Haghdadi N. Data-driven Assessment of Aggregate Distributed Photovoltaic Generation and its Impacts on Electricity Network Planning. [Doctoral Dissertation]. University of New South Wales; 2017. Available from: http://handle.unsw.edu.au/1959.4/58955 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:48032/SOURCE02?view=true


Carnegie Mellon University

10. Craig, Michael T. Economic and Environmental Costs, Benefits, and Trade-offs of Low-carbon Technologies in the Electric Power Sector.

Degree: 2017, Carnegie Mellon University

 Motivated by the role of decarbonizing the electric power sector to mitigate climate change, I assess the economic and environmental merits of three key technologies… (more)

Subjects/Keywords: carbon capture and sequestration; climate change; distributed photovoltaic; grid-scale battery; power system optimization; power systems

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APA (6th Edition):

Craig, M. T. (2017). Economic and Environmental Costs, Benefits, and Trade-offs of Low-carbon Technologies in the Electric Power Sector. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/1099

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Craig, Michael T. “Economic and Environmental Costs, Benefits, and Trade-offs of Low-carbon Technologies in the Electric Power Sector.” 2017. Thesis, Carnegie Mellon University. Accessed October 20, 2019. http://repository.cmu.edu/dissertations/1099.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Craig, Michael T. “Economic and Environmental Costs, Benefits, and Trade-offs of Low-carbon Technologies in the Electric Power Sector.” 2017. Web. 20 Oct 2019.

Vancouver:

Craig MT. Economic and Environmental Costs, Benefits, and Trade-offs of Low-carbon Technologies in the Electric Power Sector. [Internet] [Thesis]. Carnegie Mellon University; 2017. [cited 2019 Oct 20]. Available from: http://repository.cmu.edu/dissertations/1099.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Craig MT. Economic and Environmental Costs, Benefits, and Trade-offs of Low-carbon Technologies in the Electric Power Sector. [Thesis]. Carnegie Mellon University; 2017. Available from: http://repository.cmu.edu/dissertations/1099

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Georgia Tech

11. Sandoval Zapata, Marcelo Francisco. Valuation methodology of distributed energy resources portfolios based on an electric grid business model innovation framework for renewable energy integration.

Degree: PhD, Electrical and Computer Engineering, 2018, Georgia Tech

 Adoption of distributed energy resources (DERs) such as solar photovoltaic generators, energy storage, demand response devices, energy efficiency and electric vehicles is expected to grow… (more)

Subjects/Keywords: Distributed energy resources; Power systems economics; Integrated grid planning; Risk-averse two-stage stochastic optimization; Power system architecture; Locational value analysis

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APA (6th Edition):

Sandoval Zapata, M. F. (2018). Valuation methodology of distributed energy resources portfolios based on an electric grid business model innovation framework for renewable energy integration. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/59887

Chicago Manual of Style (16th Edition):

Sandoval Zapata, Marcelo Francisco. “Valuation methodology of distributed energy resources portfolios based on an electric grid business model innovation framework for renewable energy integration.” 2018. Doctoral Dissertation, Georgia Tech. Accessed October 20, 2019. http://hdl.handle.net/1853/59887.

MLA Handbook (7th Edition):

Sandoval Zapata, Marcelo Francisco. “Valuation methodology of distributed energy resources portfolios based on an electric grid business model innovation framework for renewable energy integration.” 2018. Web. 20 Oct 2019.

Vancouver:

Sandoval Zapata MF. Valuation methodology of distributed energy resources portfolios based on an electric grid business model innovation framework for renewable energy integration. [Internet] [Doctoral dissertation]. Georgia Tech; 2018. [cited 2019 Oct 20]. Available from: http://hdl.handle.net/1853/59887.

Council of Science Editors:

Sandoval Zapata MF. Valuation methodology of distributed energy resources portfolios based on an electric grid business model innovation framework for renewable energy integration. [Doctoral Dissertation]. Georgia Tech; 2018. Available from: http://hdl.handle.net/1853/59887

12. Wu, Xiaofan. Sparsity-promoting optimal control of power networks.

Degree: PhD, Electrical/Computer Engineering, 2016, University of Minnesota

 In this dissertation, we study the problems of structure design and optimal control of consensus and synchronization networks. Our objective is to design controller that… (more)

Subjects/Keywords: control; distributed systems; optimization; power systems

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APA (6th Edition):

Wu, X. (2016). Sparsity-promoting optimal control of power networks. (Doctoral Dissertation). University of Minnesota. Retrieved from http://hdl.handle.net/11299/185164

Chicago Manual of Style (16th Edition):

Wu, Xiaofan. “Sparsity-promoting optimal control of power networks.” 2016. Doctoral Dissertation, University of Minnesota. Accessed October 20, 2019. http://hdl.handle.net/11299/185164.

MLA Handbook (7th Edition):

Wu, Xiaofan. “Sparsity-promoting optimal control of power networks.” 2016. Web. 20 Oct 2019.

Vancouver:

Wu X. Sparsity-promoting optimal control of power networks. [Internet] [Doctoral dissertation]. University of Minnesota; 2016. [cited 2019 Oct 20]. Available from: http://hdl.handle.net/11299/185164.

Council of Science Editors:

Wu X. Sparsity-promoting optimal control of power networks. [Doctoral Dissertation]. University of Minnesota; 2016. Available from: http://hdl.handle.net/11299/185164

13. Cherry, Derrick Dewayne. OPTIMAL PLACEMENT OF DISTRIBUTED GENERATION ON A POWER SYSTEM USING PARTICLE SWARM OPTIMIZATION.

Degree: PhD, Electrical and Computer Engineering, 2012, Mississippi State University

  In recent years, the power industry has experienced significant changes on the distribution power system primarily due to the implementation of smart-grid technology and… (more)

Subjects/Keywords: PSO Optimal DG; artificial intelligence in power system; distributed generation; optimal distributed generation placement; impact of distributed generation; particle swarm optimization in power system

…techniques have become popular in solving power system optimization problems to obtain a global or… …power network is in need of major upgrades. Upgrades to the power system tend to encounter… …instrumental in optimizing the power system, but DG tends to be more economical and provides… …Three main components of a typical power system [7] Introduction to Distributed… …and security of the electrical system. Distributed generation on a power system affects the… 

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APA (6th Edition):

Cherry, D. D. (2012). OPTIMAL PLACEMENT OF DISTRIBUTED GENERATION ON A POWER SYSTEM USING PARTICLE SWARM OPTIMIZATION. (Doctoral Dissertation). Mississippi State University. Retrieved from http://sun.library.msstate.edu/ETD-db/theses/available/etd-07082011-012449/ ;

Chicago Manual of Style (16th Edition):

Cherry, Derrick Dewayne. “OPTIMAL PLACEMENT OF DISTRIBUTED GENERATION ON A POWER SYSTEM USING PARTICLE SWARM OPTIMIZATION.” 2012. Doctoral Dissertation, Mississippi State University. Accessed October 20, 2019. http://sun.library.msstate.edu/ETD-db/theses/available/etd-07082011-012449/ ;.

MLA Handbook (7th Edition):

Cherry, Derrick Dewayne. “OPTIMAL PLACEMENT OF DISTRIBUTED GENERATION ON A POWER SYSTEM USING PARTICLE SWARM OPTIMIZATION.” 2012. Web. 20 Oct 2019.

Vancouver:

Cherry DD. OPTIMAL PLACEMENT OF DISTRIBUTED GENERATION ON A POWER SYSTEM USING PARTICLE SWARM OPTIMIZATION. [Internet] [Doctoral dissertation]. Mississippi State University; 2012. [cited 2019 Oct 20]. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-07082011-012449/ ;.

Council of Science Editors:

Cherry DD. OPTIMAL PLACEMENT OF DISTRIBUTED GENERATION ON A POWER SYSTEM USING PARTICLE SWARM OPTIMIZATION. [Doctoral Dissertation]. Mississippi State University; 2012. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-07082011-012449/ ;


University of New South Wales

14. Sadinezhad, Iman. Development of numerical optimization algorithms for power system real-time estimation tools.

Degree: Electrical Engineering & Telecommunications, 2012, University of New South Wales

 The estimation of voltage/current phasors and local frequency are key parts to operate and control the ever evolving electricity networks. Phasor and frequency can be… (more)

Subjects/Keywords: Estimation; Power System; Optimization

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APA (6th Edition):

Sadinezhad, I. (2012). Development of numerical optimization algorithms for power system real-time estimation tools. (Doctoral Dissertation). University of New South Wales. Retrieved from http://handle.unsw.edu.au/1959.4/51791 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10458/SOURCE02?view=true

Chicago Manual of Style (16th Edition):

Sadinezhad, Iman. “Development of numerical optimization algorithms for power system real-time estimation tools.” 2012. Doctoral Dissertation, University of New South Wales. Accessed October 20, 2019. http://handle.unsw.edu.au/1959.4/51791 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10458/SOURCE02?view=true.

MLA Handbook (7th Edition):

Sadinezhad, Iman. “Development of numerical optimization algorithms for power system real-time estimation tools.” 2012. Web. 20 Oct 2019.

Vancouver:

Sadinezhad I. Development of numerical optimization algorithms for power system real-time estimation tools. [Internet] [Doctoral dissertation]. University of New South Wales; 2012. [cited 2019 Oct 20]. Available from: http://handle.unsw.edu.au/1959.4/51791 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10458/SOURCE02?view=true.

Council of Science Editors:

Sadinezhad I. Development of numerical optimization algorithms for power system real-time estimation tools. [Doctoral Dissertation]. University of New South Wales; 2012. Available from: http://handle.unsw.edu.au/1959.4/51791 ; https://unsworks.unsw.edu.au/fapi/datastream/unsworks:10458/SOURCE02?view=true


University of Texas – Austin

15. Chirapongsananurak, Pisitpol. Distribution circuit multi-time-scale simulation tool for wind turbine and photovoltaic integration analysis.

Degree: PhD, Electrical and Computer Engineering, 2016, University of Texas – Austin

Power system phenomena can be characterized into three types according to their time scales. Firstly, electromagnetic transient phenomena, such as the effects of capacitor switching… (more)

Subjects/Keywords: Distributed power generation; Power system modeling; Power system simulation; Solar power generation; Wind power generation

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Chirapongsananurak, P. (2016). Distribution circuit multi-time-scale simulation tool for wind turbine and photovoltaic integration analysis. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68247

Chicago Manual of Style (16th Edition):

Chirapongsananurak, Pisitpol. “Distribution circuit multi-time-scale simulation tool for wind turbine and photovoltaic integration analysis.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed October 20, 2019. http://hdl.handle.net/2152/68247.

MLA Handbook (7th Edition):

Chirapongsananurak, Pisitpol. “Distribution circuit multi-time-scale simulation tool for wind turbine and photovoltaic integration analysis.” 2016. Web. 20 Oct 2019.

Vancouver:

Chirapongsananurak P. Distribution circuit multi-time-scale simulation tool for wind turbine and photovoltaic integration analysis. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2019 Oct 20]. Available from: http://hdl.handle.net/2152/68247.

Council of Science Editors:

Chirapongsananurak P. Distribution circuit multi-time-scale simulation tool for wind turbine and photovoltaic integration analysis. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/68247


University of Melbourne

16. Gholami, Sasan. Control of electronically-coupled distributed energy resources in microgrids.

Degree: 2017, University of Melbourne

 The current power grid is going through a paradigm shift due to large scale integration of renewable energy sources. The safe, secure and reliable operation… (more)

Subjects/Keywords: microgrid; power system; distributed energy resources

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APA (6th Edition):

Gholami, S. (2017). Control of electronically-coupled distributed energy resources in microgrids. (Doctoral Dissertation). University of Melbourne. Retrieved from http://hdl.handle.net/11343/191723

Chicago Manual of Style (16th Edition):

Gholami, Sasan. “Control of electronically-coupled distributed energy resources in microgrids.” 2017. Doctoral Dissertation, University of Melbourne. Accessed October 20, 2019. http://hdl.handle.net/11343/191723.

MLA Handbook (7th Edition):

Gholami, Sasan. “Control of electronically-coupled distributed energy resources in microgrids.” 2017. Web. 20 Oct 2019.

Vancouver:

Gholami S. Control of electronically-coupled distributed energy resources in microgrids. [Internet] [Doctoral dissertation]. University of Melbourne; 2017. [cited 2019 Oct 20]. Available from: http://hdl.handle.net/11343/191723.

Council of Science Editors:

Gholami S. Control of electronically-coupled distributed energy resources in microgrids. [Doctoral Dissertation]. University of Melbourne; 2017. Available from: http://hdl.handle.net/11343/191723


University of Illinois – Urbana-Champaign

17. Robbins, Brett Andrew. Architectures and algorithms for voltage control in power distribution systems.

Degree: PhD, Electrical & Computer Engr, 2015, University of Illinois – Urbana-Champaign

 In this thesis, we propose a hierarchical control architecture for voltage in power distribution networks where there is a separation between the slow time-scale, in… (more)

Subjects/Keywords: Power Systems; Power Distribution Systems; Voltage Regulation; Optimization; Distributed Optimization; Optimal Power Flow; Convex Relaxation; Distributed Energy Resources

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Robbins, B. A. (2015). Architectures and algorithms for voltage control in power distribution systems. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/78592

Chicago Manual of Style (16th Edition):

Robbins, Brett Andrew. “Architectures and algorithms for voltage control in power distribution systems.” 2015. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed October 20, 2019. http://hdl.handle.net/2142/78592.

MLA Handbook (7th Edition):

Robbins, Brett Andrew. “Architectures and algorithms for voltage control in power distribution systems.” 2015. Web. 20 Oct 2019.

Vancouver:

Robbins BA. Architectures and algorithms for voltage control in power distribution systems. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2015. [cited 2019 Oct 20]. Available from: http://hdl.handle.net/2142/78592.

Council of Science Editors:

Robbins BA. Architectures and algorithms for voltage control in power distribution systems. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2015. Available from: http://hdl.handle.net/2142/78592


Carnegie Mellon University

18. Dai, Wei. Learning with Staleness.

Degree: 2018, Carnegie Mellon University

 A fundamental assumption behind most machine learning (ML) algorithms and analyses is the sequential execution. That is, any update to the ML model can be… (more)

Subjects/Keywords: Large Scale Machine Learning; Distributed Optimization Method; Distributed System; Parameter Server

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APA (6th Edition):

Dai, W. (2018). Learning with Staleness. (Thesis). Carnegie Mellon University. Retrieved from http://repository.cmu.edu/dissertations/1209

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Dai, Wei. “Learning with Staleness.” 2018. Thesis, Carnegie Mellon University. Accessed October 20, 2019. http://repository.cmu.edu/dissertations/1209.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Dai, Wei. “Learning with Staleness.” 2018. Web. 20 Oct 2019.

Vancouver:

Dai W. Learning with Staleness. [Internet] [Thesis]. Carnegie Mellon University; 2018. [cited 2019 Oct 20]. Available from: http://repository.cmu.edu/dissertations/1209.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Dai W. Learning with Staleness. [Thesis]. Carnegie Mellon University; 2018. Available from: http://repository.cmu.edu/dissertations/1209

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Michigan Technological University

19. Cook, Michael D. DECENTRALIZED OPTIMAL EXERGY DESTRUCTION CONTROL STRATEGY FOR DC AND AC MICROGRIDS.

Degree: PhD, Department of Mechanical Engineering-Engineering Mechanics, 2017, Michigan Technological University

  The primary goal of the research presented in this dissertation is the development of a decentralized control method for both dc and ac inverter… (more)

Subjects/Keywords: power system control; optimal control; decentralized control; distributed control; reduced order model; hardware in the loop; Energy Systems

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Cook, M. D. (2017). DECENTRALIZED OPTIMAL EXERGY DESTRUCTION CONTROL STRATEGY FOR DC AND AC MICROGRIDS. (Doctoral Dissertation). Michigan Technological University. Retrieved from http://digitalcommons.mtu.edu/etdr/418

Chicago Manual of Style (16th Edition):

Cook, Michael D. “DECENTRALIZED OPTIMAL EXERGY DESTRUCTION CONTROL STRATEGY FOR DC AND AC MICROGRIDS.” 2017. Doctoral Dissertation, Michigan Technological University. Accessed October 20, 2019. http://digitalcommons.mtu.edu/etdr/418.

MLA Handbook (7th Edition):

Cook, Michael D. “DECENTRALIZED OPTIMAL EXERGY DESTRUCTION CONTROL STRATEGY FOR DC AND AC MICROGRIDS.” 2017. Web. 20 Oct 2019.

Vancouver:

Cook MD. DECENTRALIZED OPTIMAL EXERGY DESTRUCTION CONTROL STRATEGY FOR DC AND AC MICROGRIDS. [Internet] [Doctoral dissertation]. Michigan Technological University; 2017. [cited 2019 Oct 20]. Available from: http://digitalcommons.mtu.edu/etdr/418.

Council of Science Editors:

Cook MD. DECENTRALIZED OPTIMAL EXERGY DESTRUCTION CONTROL STRATEGY FOR DC AND AC MICROGRIDS. [Doctoral Dissertation]. Michigan Technological University; 2017. Available from: http://digitalcommons.mtu.edu/etdr/418

20. Weerasinghe, Handuwala Dewage Dulan Jayanatha. Planning optimal load distribution and maximum renewable energy from wind power on a radial distribution system.

Degree: PhD, Electrical and Computer Engineering, 2015, Kansas State University

 Optimizing renewable distributed generation in distribution systems has gained popularity with changes in federal energy policies. Various studies have been reported in this regard and… (more)

Subjects/Keywords: Distributed wind generation; Distribution system; Distributed energy storage system; Optimization; Electrical Engineering (0544)

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Weerasinghe, H. D. D. J. (2015). Planning optimal load distribution and maximum renewable energy from wind power on a radial distribution system. (Doctoral Dissertation). Kansas State University. Retrieved from http://hdl.handle.net/2097/28714

Chicago Manual of Style (16th Edition):

Weerasinghe, Handuwala Dewage Dulan Jayanatha. “Planning optimal load distribution and maximum renewable energy from wind power on a radial distribution system.” 2015. Doctoral Dissertation, Kansas State University. Accessed October 20, 2019. http://hdl.handle.net/2097/28714.

MLA Handbook (7th Edition):

Weerasinghe, Handuwala Dewage Dulan Jayanatha. “Planning optimal load distribution and maximum renewable energy from wind power on a radial distribution system.” 2015. Web. 20 Oct 2019.

Vancouver:

Weerasinghe HDDJ. Planning optimal load distribution and maximum renewable energy from wind power on a radial distribution system. [Internet] [Doctoral dissertation]. Kansas State University; 2015. [cited 2019 Oct 20]. Available from: http://hdl.handle.net/2097/28714.

Council of Science Editors:

Weerasinghe HDDJ. Planning optimal load distribution and maximum renewable energy from wind power on a radial distribution system. [Doctoral Dissertation]. Kansas State University; 2015. Available from: http://hdl.handle.net/2097/28714


Texas A&M University

21. Amba, Tushar. Genetic Algorithm Based Damage Control For Shipboard Power Systems.

Degree: 2010, Texas A&M University

 The work presented in this thesis was concerned with the implementation of a damage control method for U.S. Navy shipboard power systems (SPS). In recent… (more)

Subjects/Keywords: Damage control; genetic algorithm; integrated power system; integrated fight through power; optimization; power system dynamics; power system restoration; shipboard power system

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APA (6th Edition):

Amba, T. (2010). Genetic Algorithm Based Damage Control For Shipboard Power Systems. (Thesis). Texas A&M University. Retrieved from http://hdl.handle.net/1969.1/ETD-TAMU-2009-05-282

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Amba, Tushar. “Genetic Algorithm Based Damage Control For Shipboard Power Systems.” 2010. Thesis, Texas A&M University. Accessed October 20, 2019. http://hdl.handle.net/1969.1/ETD-TAMU-2009-05-282.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Amba, Tushar. “Genetic Algorithm Based Damage Control For Shipboard Power Systems.” 2010. Web. 20 Oct 2019.

Vancouver:

Amba T. Genetic Algorithm Based Damage Control For Shipboard Power Systems. [Internet] [Thesis]. Texas A&M University; 2010. [cited 2019 Oct 20]. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-05-282.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Amba T. Genetic Algorithm Based Damage Control For Shipboard Power Systems. [Thesis]. Texas A&M University; 2010. Available from: http://hdl.handle.net/1969.1/ETD-TAMU-2009-05-282

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Newcastle

22. Luo, Fengji. Advanced analysis methods for power system with high renewable penetrations.

Degree: PhD, 2014, University of Newcastle

Research Doctorate - Doctor of Philosophy (PhD)

In recent years, power system has been undergoing rapid development. One of the most significant trends of modern… (more)

Subjects/Keywords: power system; renewable energy; wind power; distributed computing; cloud computing

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Luo, F. (2014). Advanced analysis methods for power system with high renewable penetrations. (Doctoral Dissertation). University of Newcastle. Retrieved from http://hdl.handle.net/1959.13/1042442

Chicago Manual of Style (16th Edition):

Luo, Fengji. “Advanced analysis methods for power system with high renewable penetrations.” 2014. Doctoral Dissertation, University of Newcastle. Accessed October 20, 2019. http://hdl.handle.net/1959.13/1042442.

MLA Handbook (7th Edition):

Luo, Fengji. “Advanced analysis methods for power system with high renewable penetrations.” 2014. Web. 20 Oct 2019.

Vancouver:

Luo F. Advanced analysis methods for power system with high renewable penetrations. [Internet] [Doctoral dissertation]. University of Newcastle; 2014. [cited 2019 Oct 20]. Available from: http://hdl.handle.net/1959.13/1042442.

Council of Science Editors:

Luo F. Advanced analysis methods for power system with high renewable penetrations. [Doctoral Dissertation]. University of Newcastle; 2014. Available from: http://hdl.handle.net/1959.13/1042442


Virginia Tech

23. Thandi, Gurjit Singh. Modeling, Control and Stability Analysis of a PEBB Based DC Distribution Power System.

Degree: MS, Electrical Engineering, 1997, Virginia Tech

Power Electronic Building Block (PEBB) concept is to provide generic building blocks for power conversion, regulation and distribution with control intelligence and autonomy. A comprehensive… (more)

Subjects/Keywords: power conversion; distributed power system

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Thandi, G. S. (1997). Modeling, Control and Stability Analysis of a PEBB Based DC Distribution Power System. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/36788

Chicago Manual of Style (16th Edition):

Thandi, Gurjit Singh. “Modeling, Control and Stability Analysis of a PEBB Based DC Distribution Power System.” 1997. Masters Thesis, Virginia Tech. Accessed October 20, 2019. http://hdl.handle.net/10919/36788.

MLA Handbook (7th Edition):

Thandi, Gurjit Singh. “Modeling, Control and Stability Analysis of a PEBB Based DC Distribution Power System.” 1997. Web. 20 Oct 2019.

Vancouver:

Thandi GS. Modeling, Control and Stability Analysis of a PEBB Based DC Distribution Power System. [Internet] [Masters thesis]. Virginia Tech; 1997. [cited 2019 Oct 20]. Available from: http://hdl.handle.net/10919/36788.

Council of Science Editors:

Thandi GS. Modeling, Control and Stability Analysis of a PEBB Based DC Distribution Power System. [Masters Thesis]. Virginia Tech; 1997. Available from: http://hdl.handle.net/10919/36788


Anna University

24. Umayal SP. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.

Degree: Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems, 2014, Anna University

In developing countries electricity consumption is increasing rapidly newlineand there is always a mismatch between power generation and the load newlinedemand Utilization of available resources… (more)

Subjects/Keywords: lack of funds; Power system optimization problems

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

SP, U. (2014). Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/28521

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

SP, Umayal. “Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.” 2014. Thesis, Anna University. Accessed October 20, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/28521.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

SP, Umayal. “Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.” 2014. Web. 20 Oct 2019.

Vancouver:

SP U. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. [Internet] [Thesis]. Anna University; 2014. [cited 2019 Oct 20]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/28521.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

SP U. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/28521

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Anna University

25. Umayal SP. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.

Degree: Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems, 2014, Anna University

In developing countries electricity consumption is increasing rapidly newlineand there is always a mismatch between power generation and the load newlinedemand Utilization of available resources… (more)

Subjects/Keywords: lack of funds; Power system optimization problems

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

SP, U. (2014). Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/28523

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

SP, Umayal. “Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.” 2014. Thesis, Anna University. Accessed October 20, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/28523.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

SP, Umayal. “Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.” 2014. Web. 20 Oct 2019.

Vancouver:

SP U. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. [Internet] [Thesis]. Anna University; 2014. [cited 2019 Oct 20]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/28523.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

SP U. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/28523

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Anna University

26. Umayal SP. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.

Degree: Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems, 2014, Anna University

In developing countries electricity consumption is increasing rapidly newlineand there is always a mismatch between power generation and the load newlinedemand Utilization of available resources… (more)

Subjects/Keywords: lack of funds; Power system optimization problems

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

SP, U. (2014). Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/28526

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

SP, Umayal. “Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.” 2014. Thesis, Anna University. Accessed October 20, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/28526.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

SP, Umayal. “Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.” 2014. Web. 20 Oct 2019.

Vancouver:

SP U. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. [Internet] [Thesis]. Anna University; 2014. [cited 2019 Oct 20]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/28526.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

SP U. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/28526

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Anna University

27. Umayal SP. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.

Degree: Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems, 2014, Anna University

In developing countries electricity consumption is increasing rapidly newlineand there is always a mismatch between power generation and the load newlinedemand Utilization of available resources… (more)

Subjects/Keywords: lack of funds; Power system optimization problems

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

SP, U. (2014). Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/28527

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

SP, Umayal. “Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.” 2014. Thesis, Anna University. Accessed October 20, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/28527.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

SP, Umayal. “Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.” 2014. Web. 20 Oct 2019.

Vancouver:

SP U. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. [Internet] [Thesis]. Anna University; 2014. [cited 2019 Oct 20]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/28527.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

SP U. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/28527

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Anna University

28. Umayal SP. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.

Degree: Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems, 2014, Anna University

In developing countries electricity consumption is increasing rapidly newlineand there is always a mismatch between power generation and the load newlinedemand Utilization of available resources… (more)

Subjects/Keywords: lack of funds; Power system optimization problems

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

SP, U. (2014). Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/28528

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

SP, Umayal. “Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.” 2014. Thesis, Anna University. Accessed October 20, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/28528.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

SP, Umayal. “Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.” 2014. Web. 20 Oct 2019.

Vancouver:

SP U. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. [Internet] [Thesis]. Anna University; 2014. [cited 2019 Oct 20]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/28528.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

SP U. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/28528

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Anna University

29. Umayal SP. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.

Degree: Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems, 2014, Anna University

In developing countries electricity consumption is increasing rapidly newlineand there is always a mismatch between power generation and the load newlinedemand Utilization of available resources… (more)

Subjects/Keywords: lack of funds; Power system optimization problems

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

SP, U. (2014). Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/28529

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

SP, Umayal. “Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.” 2014. Thesis, Anna University. Accessed October 20, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/28529.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

SP, Umayal. “Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.” 2014. Web. 20 Oct 2019.

Vancouver:

SP U. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. [Internet] [Thesis]. Anna University; 2014. [cited 2019 Oct 20]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/28529.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

SP U. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/28529

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Anna University

30. Umayal SP. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.

Degree: Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems, 2014, Anna University

In developing countries electricity consumption is increasing rapidly newlineand there is always a mismatch between power generation and the load newlinedemand Utilization of available resources… (more)

Subjects/Keywords: lack of funds; Power system optimization problems

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

SP, U. (2014). Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/28533

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

SP, Umayal. “Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.” 2014. Thesis, Anna University. Accessed October 20, 2019. http://shodhganga.inflibnet.ac.in/handle/10603/28533.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

SP, Umayal. “Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;.” 2014. Web. 20 Oct 2019.

Vancouver:

SP U. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. [Internet] [Thesis]. Anna University; 2014. [cited 2019 Oct 20]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/28533.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

SP U. Particle swarm optimization technique To solve stochastic multi objective Power system optimization problems;. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/28533

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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