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Master Thesis on optimal location of electric vehicle fast charging stations

Fri, 07/18/2014 - 23:26 — admin

AndinaMiss Andina R. Brown defended last February 2014 the master thesis A multi-objective approach to infrastructure planning in the early stages of EV introduction. This thesis was developped at the Energy Economics Research Group of the Catalonia Institute for Energy Research (IREC) and the advisor were Dr. Cristina Corchero (IREC) and professor F.-Javier Heredia (GNOM). This study deals with the problem of a central planner wishing to install fast charging stations for electric vehicles applying a multi-objective approach to a real-case instance of the city of Barcelona.

A multi-objective approach to infrastructure planning in the early stages of EV introduction

Fri, 07/18/2014 - 22:44 — admin
Publication TypeTesis de Grau i Màster // BSc and MSc Thesis
Year of Publication2014
AuthorsAndina Rosalia Brown
DirectorF.-Javier Heredia; Cristina Corchero
Tipus de tesiMSc Thesis
TitulacióMaster in Statistics and Operations Research
CentreFaculty of Mathematics and Statistics
Data defensa27/01/2014
Nota // mark9.0
Key WordsMulti-objective Optimisation; Facility Location; Electric Vehicle; Fast Charging Stations; MSc Thesis
AbstractThis study approaches the problem from the perspective of a central planner wishing to install fast charging stations. A multi-objective approach is used to simultaneously consider two conflicting objectives in the optimisation problem. The first objective is to minimise the distance that potential consumers would need to deviate from their normal journeys in order to reach their nearest fast charging station, and thus minimise the associated inconvenience. The second objective is to minimise the set up costs associated with the installation of the stations, which differ according to the number of facilities installed and their location. These objectives are normalised using a function transformation and then combined into a single objective function. A mathematical model is formulated and implemented using GAMS to obtain results for the case study of Barcelona, building on the existing literature. Using the weighted sums method, multiple Pareto optimal solutions are found by solving for different relative weights combinations applied to the two objectives. These solutions are used to depict the Pareto front, offering insight into the nature of the trade-offs between the objectives and aiding the decision making process. This study develops the existing methodology used for the EV infrastructure problem, and shows how the application of a multi-objective formulation can offer useful insight to decision makers, particularly when preferences are unclear a priori.
DOI / handlehttp://hdl.handle.net/2099.1/20851
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Stochastic optimal bid to electricity markets with environmental risk constraints

Wed, 03/27/2013 - 11:21 — admin
Publication TypeTesis de Grau i Màster // BSc and MSc Thesis
Year of Publication2012
AuthorsJulian Cifuentes Rubiano
DirectorF.-Javier Heredia
Tipus de tesiMSc Thesis
TitulacióMaster in Statistics and Operations Research
CentreFaculty of Mathematics and Statistics
Data defensa21/12/2012
Nota // mark9.5/10
Key Wordsteaching; stochastic programming; electricity markets; CO2 allowances; environment; emission limits; emission risk; CVaR; CEaR; modeling languages; MSc Thesis
AbstractThere are many factors that influence the day-ahead market bidding strategies of a generation company (GenCo) in the current energy market framework. Environmental policy issues have become more and more important for fossil-fuelled power plants and they have to be considered in their management, giving rise to emission limitations. This work allows to investigate the influence of both the allowances and emission reduction plan, and the incorporation of the derivatives medium-term commitments in the optimal generation bidding strategy to the day-ahead electricity market. Two different technologies have been considered: the coal thermal units, high-emission technology, and the combined cycle gas turbine units, low-emission technology. The Iberian Electricity Market and the Spanish National Emissions and Allocation Plans are the framework to deal with the environmental issues in the day-ahead market bidding strategies. To address emission limitations, some of the standard risk management methodologies developed for financial markets, such as Value-at-Risk (VaR) and Conditional Value at Risk (CVaR), have been extended. This study offers to electricity generation utilities a mathematical model to determinate the individual optimal generation bid to the wholesale electricity market, for each one of their generation units that maximizes the long-run profits of the utility abiding by the Iberian Electricity Market rules, the environmental restrictions set by the EU Emission Trading Scheme, as well as the restrictions set by the Spanish National Emissions Reduction Plan. The economic implications for a GenCo of including the environmental restrictions of these National Plans are analyzed and the most remarkable results will be presented.. The problem to be solved in this project will provide generationutilities with a mathematical tool to find the individual optimal generation bid for each one of theirgeneration units that maximizes the long-run profits of the utility abiding by the Iberian ElectricityMarket rules, the environmental restrictions of the EU Emission Trading Scheme and also by theSpanish National Emissions Reduction Plan
DOI / handlehttp://hdl.handle.net/2099.1/17485
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Master thesis on electricity market optimization under environmental regulation.

Sat, 12/01/2012 - 23:41 — admin


Efficient frontier of the Conditional Emission at RiskMr. Julian Cifuentes Rubiano, student of the master in Statistics and Operations Research and research assistant of the GNOM research group, defended on 12 November 2012 the master Thesis Stochastic Optimal Bid to Electricity Markets with Environmental Risk Constraints . In this thesis the  stochastic programming models for the optimal bidding strategies with emission allowances introduced in a previous work (doi: 10.1109/EEM.2012.6254676) was improved with the consideration of risk measures related with both environmental damages and financial losses. This thesis has been partially supported by the MINECO research project grant DPI2008-02153 and the  CRM grant for master research projects.

Optimal Management of Microgrids

Thu, 07/19/2012 - 21:10 — admin
Publication TypeTesis de Grau i Màster // BSc and MSc Thesis
Year of Publication2012
AuthorsLucia Igualada González
DirectorF.-Javier Heredia; Cristina Corchero
Tipus de tesiTesi Final Màster // MSc Thesis
TitulacióMaster in Statistics and Operations Research
CentreFaculty of Mathematics and Statistics
Data defensa04/07/2012
Nota // mark10 MH // 10/10
Key Wordsresearch; teaching; smartgrids; microgrid; migrogrid central controller; electric vehicle; MSc Thesis
AbstractSmart grids and microgrids are the key in the near future where a decentralization of energy generation is expected. From the point of view of microgrid energy management, economic scheduling for generation devices, storage systems and loads is a crucial problem. Performance an optimization process is necessary to minimize the operating costs while several operational constraints are taken into account. Energy management is carried out by MCC (Microgrid Central Controller) in three steps: tertiary, secondary and primary controls. Tertiary control is executed one day-ahead and has two objectives. The first is an economic optimization using a program based on an Economic Dispatch and an Unit Commitment problem. The second objective is to improve the por tability of the supply and demand balance by interacting with the grid and taking advantage of the V2G (vehicle-to-grid) capability of the charging spot, and to generate a schedule over all components of the microgrid. The secondary control receives the scheduling plan created by tertiary control and taking into account current data, corrects the power outputs of generation units. Exchanged power with the grid and storage states of charge programmed by the tertiary control are ensured. This Energy Management System has been tested over different scenarios. One of them is based on a smart house with a photovoltaic module, a micro wind turbine and one electric vehicle charging spot. The other scenario is based on a large building where one micro gas turbine and one storage device have been added to the rest of units. After analysing the results, several conclusions have been deduced such as a change in curve of load and a lower cost for the user. Generally, the consumption over peak periods is decreased or is almost zero in some test cases, while the demand overnight is increased.
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Programació Matemàtica // Mathematical Programming

Thu, 07/19/2012 - 17:05 — admin
Publication TypeDocència // Teaching
Year of Publication2012
Quadrimestre // Term2012-13 Q1
AuthorsF.-Javier Heredia; Ma Paz Linares; Jordi Castro
Coordinator?no
Codi // Code200152 - PM
Idioma // LanguageCatalà
Key Wordsteaching; UPC; FME; GM; mathematical programming; PM
Abstractteaching; UPC; FME; GM; mathematical programming
URLClick Here
Titolació // StudiesGrau en Matemàtiques // Degree in Mathematics.
Centre // Faculty Facultat de Matemàtiques i Estadística (FME)
Institució // InstitutionUniversitat Politècnica de Catalunya (UPC)
Horaris // ScheduleWed. 15:00-17:00, Fri. 15:00 - 17:00, room 100 (FME)
ECTS7.5
Consultes // tutoringContact.
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Optimització en enginyeria // Optimization in Engineering

Thu, 07/19/2012 - 17:02 — admin
Publication TypeDocència // Teaching
Year of Publication2012
Quadrimestre // Term2012-13 Q2
AuthorsF.-Javier Heredia; Ma Paz Linares
Coordinator?yes
Codi // Code361226
Idioma // LanguageCatalà
Key Wordsteaching; UPC; UB; FME; GE; programació lineal; programació entera; assignatures; courses; OI
Abstract

Objectius de l'assignatura:

  • Conèixer els models de la investigació operativa habituals en optimització en enginyeria i usar amb correctament la terminologia pròpia de l’àrea.
  • Formular matemàticament i resoldre computacionalment mitjançant l’ús de llenguatges de modelització per a
    programació matemàtica problemes d’optimització en enginyeria de diverses àrees.
  • Interpretar els resultats dels models d’optimització en enginyeria i ser capaç d’elaborar informes i presentacions on s’exposin els resultats.
URLClick Here
Titolació // StudiesGrau Interuniversitari d'Estadística, UB-UPC.
Centre // FacultyFaultat d'Economia i Empresa (EEE), UB. Facultat de Matemàtiques i Estadística UPC.
Institució // InstitutionUniversitat de Barcelona -Universitat Politècnica de Catalunya.
Horaris // ScheduleDilluns de 13:00 a 14:00, dimarts i dijous de 13:00 a 14:30Facultat d'Economia i Empresa aula 103 (teoria) i I9 (laboratori).
ECTS6
Consultes // tutoringContact.
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Programació Lineal i Entera // Linear and Integer Programming

Thu, 07/19/2012 - 16:56 — admin
Publication TypeDocència // Teaching
Year of Publication2012
Quadrimestre // Term2012-13 Q2
AuthorsF.-Javier Heredia
Coordinator?yes
Codi // Code361226
Idioma // LanguageCatalà
Key Wordsteaching; UPC; UB; FME; GE; programació lineal; programació entera; assignatures; courses; PLE
Abstract

Objectius referits a coneixements

  • Conèixer els models de presa de decisió més importants de la investigació operativa en diversos camps d'aplicació.
  • Analitzar problemes de presa de decisió amb l'objectiu de formular i resoldre computacionalment el model d'optimització més adient.
  • Comprendre les propietats matemàtiques dels problemes de programació lineal i dels seus algorismes de resolució, així com de les tècniques d'anàlisi de sensibilitat.
  • Comprendre les propietats matemàtiques dels problemes de programació lineal entera i dels seus algorismes de resolució.

Objectius referits a habilitats, destreses

  • Aplicar sense ajut computacional els algorismes estudiats de programació lineal a problemes acadèmics de dimensió reduïda.
  • Resoldre problemes pràctics mitjançant l'aplicació de tècniques d'anàlisi de sensibilitat a models de programació lineal.
  • Aplicar, sense ajut computacional, els algorismes estudiats de programació lineal entera a problemes acadèmics de dimensió reduïda.
  • Resoldre problemes reals de presa de decisió mitjançant l'ús d'algun programari d'optimització de referència corresponent als diferents algorismes d'optimització estudiats al llarg del curs.
URLClick Here
Titolació // StudiesGrau Interuniversitari d'Estadística, UB-UPC.
Centre // FacultyFaultat d'Economia i Empresa (EEE), UB. Facultat de Matemàtiques i Estadística UPC.
Institució // InstitutionUniversitat de Barcelona -Universitat Politècnica de Catalunya.
Horaris // ScheduleDilluns i dijous de 13:00 a 14:30, dimarts i dijous de 13:00 a 14:00. Facultat d'Economia i Empresa aula 103 (teoria) i I9 (laboratori).
ECTS6
Consultes // tutoringContact.
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Modelització en Programació Matemàtica // Modelization in Mathematical programming

Thu, 07/19/2012 - 16:51 — admin
Publication TypeDocència // Teaching
Year of Publication2012
Quadrimestre // Term2012-13 Q1
AuthorsF.-Javier Heredia; Jordi Castro
Coordinator?no
Codi // Code26339 - MPM
Idioma // LanguageCatalà
Key Wordsteaching; UPC; FME; MEIO; IO; assignatures; courses; modelització; modeling; AMPL; CPLEX; MINOS; MPM
Abstract

The overall objective of the course is for students to acquire the knowledge and the ability necessary for solving practical
decision-making problems, formulated as problems of mathematical programming, which may arise during a professional
or research career.

  • Learn the mathematical formulation of some of the main mathematical programming models and develop the ability to formulate new ones.
  • Acquire the ability to determine the most appropriate algorithm and the optimization software for solving these problems numerically.
  • The ability to interpret correctly the results provided by the optimization software.

Skills to be learned

  • Learn and understand some of the most important problems in linear, integer and nonlinear programming as well as network flows.
  • Given the description of a new decision-making problem, be able to formulate the associated optimization problem correctly.
  • The ability to implement and obtained the optimum solution for decision-making problems by selecting the most appropriate algorithm and optimization software in each particular case.
URLClick Here
Titolació // StudiesFacultat de matemàtiques i Estadística (FME)
Centre // FacultyFacultat de matemàtiques i Estadística (FME)
Institució // InstitutionUniversitat Politècnica de Catalunya (UPC) - Universitat de Barcelona (UB)
Horaris // ScheduleTues. 15.00 - 17.00 and Wed. 17.00 - 19.00 room PC03, FME.
ECTS6
Consultes // tutoringContact.
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Programació Matemàtica // Mathematical Programming

Thu, 07/19/2012 - 16:44 — admin
Publication TypeDocència // Teaching
Year of Publication2011
Quadrimestre // Term2011-12 Q1
AuthorsF.-Javier Heredia; Jordi Castro; Elena Fernández; Ma Paz Linares
Coordinator?no
Codi // Code200152 - PM
Key Wordsteaching; UPC; FME; GM; mathematical programming; PM
AbstractIntroduir a l'estudiant en els fonaments i les aplicacions de la Programació Matemàtica.
  • Que l'estudiant adquireixi una panoràmica dels models de la Programació Matemàtica i de les seves aplicacions.
  • Que l'estudiant conegui la metodologia de construcció dels models de la Programació Matemàtica i llur paper en els
  • processos de presa de decisions quantitatives.
  • Que l'estudiant conegui les àrees bàsiques de la Programació Matemàtica, com ara la programació lineal i entera, els problemes de fluxos en xarxes, i la programació no lineal.
  • Que l'estudiant conegui els fonaments teòrics de les classes de models considerades.
  • Que l'estudiant conegui els principals procediments algorísmics per a resolució de les classes de models considerades.
  • Que l'estudiant pugui aplicar de forma pràctica dels algorismes estudiats mitjançant el software de Programació Matemàtica disponible a la Facultat.
URLClick Here
Titolació // StudiesGrau en Matemàtiques // Degree in Mathematics.
Centre // Faculty Facultat de Matemàtiques i Estadística (FME)
Institució // InstitutionUniversitat Politècnica de Catalunya (UPC)
Horaris // ScheduleWed. 15:00-17:00, Fri. 15:00 - 17:00, room 100 (FME)
ECTS7.5
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