OPERATIONAL DECISION MAKING IN COMPOUND ENERGY SYSTEMS USING MULTI-LEVEL MULTI PARADIGM SIMULATION BASED OPTIMIZATION

Persistent Link:
http://hdl.handle.net/10150/203489
Title:
OPERATIONAL DECISION MAKING IN COMPOUND ENERGY SYSTEMS USING MULTI-LEVEL MULTI PARADIGM SIMULATION BASED OPTIMIZATION
Author:
Mazhari, Esfandyar M.
Issue Date:
2011
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
A two level hierarchical simulation and decision modeling framework is proposed for electric power networks involving PV based solar generators, various storage, and grid connection. The high level model, from a utility company perspective, concerns operational decision making and defining regulations for customers for a reduced cost and enhanced reliability. The lower level model concerns changes in power quality and changes in demand behavior caused by customers' response to operational decisions and regulations made by the utility company at the high level. The higher level simulation is based on system dynamics and agent-based modeling while the lower level simulation is based on agent-based modeling and circuit-level continuous time modeling. The proposed two level model incorporates a simulation based optimization engine that is a combination of three meta-heuristics including Scatter Search, Tabu Search, and Neural Networks for finding optimum operational decision making. In addition, a reinforcement learning algorithm that uses Markov decision process tools is also used to generate decision policies. An integration and coordination framework is developed, which details the sequence, frequency, and types of interactions between two models. The proposed framework is demonstrated with several case studies with real-time or historical for solar insolation, storage units, demand profiles, and price of electricity of grid (i.e., avoided cost). Challenges that are addressed in case studies and applications include 1) finding a best policy, optimum price and regulation for a utility company while keeping the customers electricity quality within the accepted range, 2) capacity planning of electricity systems with PV generators, storage systems, and grid, and 3) finding the optimum threshold price that is used to decide how much energy should be bought from sold to grid to minimize the cost. Mathematical formulations, and simulation and decision modeling methodologies are presented. A grid-storage analysis is performed for arbitrage, to explore if in future it is going to be beneficial to use storage systems along with grid, with future technological improvement in storage and increasing cost of electrical energy. An information model is discussed that facilitates interoperability of different applications in the proposed hierarchical simulation and decision environment for energy systems.
Type:
text; Electronic Dissertation
Keywords:
MULTI-LEVEL SIMULATION; MULTI PARADIGM SIMULATION; OPERATIONAL DECISION MAKING; SIMULATION BASED OPTIMIZATION; Systems & Industrial Engineering; COMPOUND ENERGY SYSTEMS; MULTI-LEVEL MULTI PARADIGM SIMULATION
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Graduate College; Systems & Industrial Engineering
Degree Grantor:
University of Arizona
Advisor:
Son, Young-Jun

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleOPERATIONAL DECISION MAKING IN COMPOUND ENERGY SYSTEMS USING MULTI-LEVEL MULTI PARADIGM SIMULATION BASED OPTIMIZATIONen_US
dc.creatorMazhari, Esfandyar M.en_US
dc.contributor.authorMazhari, Esfandyar M.en_US
dc.date.issued2011-
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractA two level hierarchical simulation and decision modeling framework is proposed for electric power networks involving PV based solar generators, various storage, and grid connection. The high level model, from a utility company perspective, concerns operational decision making and defining regulations for customers for a reduced cost and enhanced reliability. The lower level model concerns changes in power quality and changes in demand behavior caused by customers' response to operational decisions and regulations made by the utility company at the high level. The higher level simulation is based on system dynamics and agent-based modeling while the lower level simulation is based on agent-based modeling and circuit-level continuous time modeling. The proposed two level model incorporates a simulation based optimization engine that is a combination of three meta-heuristics including Scatter Search, Tabu Search, and Neural Networks for finding optimum operational decision making. In addition, a reinforcement learning algorithm that uses Markov decision process tools is also used to generate decision policies. An integration and coordination framework is developed, which details the sequence, frequency, and types of interactions between two models. The proposed framework is demonstrated with several case studies with real-time or historical for solar insolation, storage units, demand profiles, and price of electricity of grid (i.e., avoided cost). Challenges that are addressed in case studies and applications include 1) finding a best policy, optimum price and regulation for a utility company while keeping the customers electricity quality within the accepted range, 2) capacity planning of electricity systems with PV generators, storage systems, and grid, and 3) finding the optimum threshold price that is used to decide how much energy should be bought from sold to grid to minimize the cost. Mathematical formulations, and simulation and decision modeling methodologies are presented. A grid-storage analysis is performed for arbitrage, to explore if in future it is going to be beneficial to use storage systems along with grid, with future technological improvement in storage and increasing cost of electrical energy. An information model is discussed that facilitates interoperability of different applications in the proposed hierarchical simulation and decision environment for energy systems.en_US
dc.typetexten_US
dc.typeElectronic Dissertationen_US
dc.subjectMULTI-LEVEL SIMULATIONen_US
dc.subjectMULTI PARADIGM SIMULATIONen_US
dc.subjectOPERATIONAL DECISION MAKINGen_US
dc.subjectSIMULATION BASED OPTIMIZATIONen_US
dc.subjectSystems & Industrial Engineeringen_US
dc.subjectCOMPOUND ENERGY SYSTEMSen_US
dc.subjectMULTI-LEVEL MULTI PARADIGM SIMULATIONen_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.disciplineSystems & Industrial Engineeringen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorSon, Young-Junen_US
dc.contributor.committeememberLiu, Jianen_US
dc.contributor.committeememberSimmons, Joseph H.en_US
dc.contributor.committeememberSon, Young-Junen_US
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