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Microgrid Central Controller (MGCC)

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A stochastic programming model for the tertiary control of microgrids

Thu, 09/03/2015 - 10:25 — admin
Publication TypeProceedings Article
Year of Publication2015
AuthorsLeire Citores; Cristina Corchero; F.-Javier Heredia
Conference Name12th International Conference on the European Energy Market (EEM15)
Pagination1-6
Conference Start Date19-22/05/2015
PublisherIEEE
Conference LocationLisbon, Portugal.
ISBN Number978-1-4673-6691-5
Key WordsMicrogrids; Optimization; Production; Stochastic processes; Uncertainty; Wind power generation; Wind speed; energy system optimization; microgrid; scenario generation; stochastic programming; paper; research
AbstractIn this work a scenario-based two-stage stochastic programming model is proposed to solve a microgrid's tertiary control optimization problem taking into account some renewable energy resource's uncertainty as well as uncertain energy deviation prices in the electricity market. Scenario generation methods for wind speed realizations are also studied. Results show that the introduction of stochastic programming represents a significant improvement over a deterministic model.
URLClick Here
DOI10.1109/EEM.2015.7216761
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Energy Management System para una microrred domestica con participación en los servicios auxiliares de red

Thu, 11/27/2014 - 16:32 — admin
Publication TypeTesis de Grau i Màster // BSc and MSc Thesis
Year of Publication2014
AuthorsIrune Etxarri Urtasun
DirectorF.-Javier Heredia, Cristina Corchero
Tipus de tesiMSc Thesis
TitulacióMaster in Statistics and Operations Reseafrch
CentreFaculty of Mathematics and Statistics
Data defensa27/06/2014
Nota // mark**
Key Wordsteaching; research; microgrids; stochastic programming; electricity market; secondary reserve; MSc Thesis
AbstractEn este proyecto se ha propuesto un modelo estocástico de dos etapas para la gestión de energía en una microrred doméstica, introduciendo la participación en el mercado de banda de regulación. El objetivo del modelo es determinar la potencia que se oferta al mercado diario, teniendo en cuenta la participación en el mercado de banda de regulación. Se ha introducido estocasticidad en los precios de este mercado y en los precios y probabilidades del requerimiento a subir y a bajar de la energía de regulación secundaria. Se han comparado los beneficios de la microrred en caso de participar o no en el mercado de banda de regulación, y se ha visto que la participación en dicho mercado produce grandes beneficios para sus usuarios.
DOI / handlehttp://hdl.handle.net/2099.1/23233
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Optimal energy management for a residential microgrid including a vehicle-to-grid system

Mon, 11/18/2013 - 16:34 — admin
Publication TypeReport
Year of Publication2013
AuthorsLucía Igualada; Cristina Corchero; Miguel Cruz-Zambrano; F.-Javier Heredia
Pages9
Date11/2013
ReferenceResearch report DR 2013/05, Dept. of Statistics and Operations Research. E-Prints UPC, http://hdl.handle.net/2117/20642. Universitat Politècnica de Catalunya
Prepared forPublished at IEEE Transactions on Smart Grids (DOI: 10.1109/TSG.2014.2318836)
Key Wordsresearch; optimal management; smart grids; vehicle-to-grid; renewable generation; microgrids
AbstractAn optimization model is proposed to manage a residential microgrid including a charging spot with a vehicle-to-grid system and renewable energy sources. In order to achieve a realistic and convenient management, we take into account: (1) the household load split into three different profiles depending on the characteristics of the elements considered; (2) a realistic approach to owner behavior by introducing the novel concept of range anxiety; (3) the vehicle battery management considering the mobility profile of the owner and (4) different domestic renewable energy sources. We consider the microgrid operated in grid-connected mode. The model is executed one-day-ahead and generates a schedule for all components of the microgrid. The results obtained show daily costs in the range of 2.82€ to 3.33€; the proximity of these values to the actual energy costs for Spanish households validate the modeling. The experimental results of applying the designed managing strategies show daily costs savings of nearly 10%.
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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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