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[Principal] [Résumé/CV] [Material docente] [Operations Management] [Mathematical Methods] [Operations Research] [Técnicas de Optimización de Sistemas] [Modelado y Simulación de Sistemas] [Applied Optimization] [Statistics II] [Quantitative Decision Methods] [Optimization Techniques] [Deterministic Optimization] [Stochastic Optimization] [Investigación] [Open Models] [openSDUC] [openTEPES] [TEPES] [ROM] [StarNet] [FLOP] [iMetro]

Modelo ROM (Modelo de Explotación y Fiabilidad para la Generación Renovable)
ROM Model (Reliability and Operation Model for Renewable Energy Sources)

El objetivo del modelo es determinar el impacto técnico y económico de la generación intermitente (Variable Renewable Energy VRE) y otros tipos de tecnologías emergentes (gestión activa de la demanda, vehículos eléctricos, generación termosolar, generación fotovoltaica) en la operación del sistema a medio plazo incluyendo la fiabilidad. Los resultados son la producción de los generadores incluyendo vertido eólico, utilización de las centrales hidráulicas y de bombeo y medidas de fiabilidad. Los beneficios derivados de mejoras en las predicciones de la VRE se pueden determinar cambiando los errores de predicción y reejecutando el modelo.

A continuación se listan las principales características del modelo:

  • Modelo de optimización estocástica diaria seguido por una simulación horaria secuencial
    En este modelo de programación diaria estocástica se incluyen restricciones de operación detalladas como mínimo técnico, rampas de subida y bajada y mínimo tiempo de funcionamiento y de parada de los grupos térmicos. La simulación horaria se ejecuta para el mismo día para considerar los errores de predicción de la VRE y de la demanda y el fallo de los grupos y reevaluar los resultados anteriores. Este modelado del sistema en doble etapa reproduce el mecanismo habitual de decisión del operador del sistema.
    La red de transporte se representa mediante un flujo de cargas en DC con las pérdidas óhmicas aproximadas mediante una poligonal.
  • Una ejecución cronológica para evaluar cada día del año
    Las decisiones por encima de este alcance como la gestión de la operación del bombeo semanal se hacen internamente en el modelo mediante criterios heurísticos. La gestión anual de las centrales hidráulicas viene decidida por modelos de jerarquía superior como, por ejemplo, un modelo de coordinación hidrotérmica.
  • La estocasticidad de la VRE y de las aportaciones hidráulicas se considera para múltiples escenarios mediante simulación de Monte Carlo

El esquema del modelo basado en una secuencia diaria de planificación y simulación es similar al de un control en ciclo abierto utilizado en teoría de control.

Descripción del modelo ROM (ver en Deliverable 2.2 del proyecto MERGE, sección 4 de "FUNCTIONAL SPECIFICATION FOR TOOLS TO ASSESS STEADY STATE AND DYNAMIC BEHAVIOUR IMPACTS, IMPACT ON ELECTRICITY MARKETS AND IMPACT OF HIGH PENETRATION OF EV ON THE RESERVE LEVELS")

Este modelo está originalmente basado en el modelo MEMPHIS desarrollado para Red Eléctrica de España en el proyecto de investigación "Modelado del impacto de la generación intermitente en la operación del sistema".

ROM está escrito en GAMS con Microsoft Excel como interfaz de entrada/salida y requiere licencia de algún optimizador conectado con GAMS. Algunos optimizadores son gratis para universidades, pero deben estar registrados como instituciones académicas.

Este modelo está siendo utilizado y mejorado en algunos proyectos nacionales o europeos:

The model objective is to determine the technical and economic impact of intermittent generation (IG) and other types of emerging technologies (active demand response, electric vehicles, concentrated solar power, and solar photovoltaic) into the medium-term system operation including reliability assessment. Results consist of generation output including IG surplus, pumped storage hydro and storage hydro usage, and adequacy reliability measures. The benefits associated to improve IG predictions can also be determined by changing the forecast error distributions and re-running the model.

Next there is a list of the main characteristics of the model:

  • A daily stochastic optimization model followed by a sequential hourly simulation
    This system modeling in two phases reproduces the usual decision mechanism of the system operator. Detailed operation constraints such as minimum load, ramp-rate, minimum uptime and downtime of thermal units and power reserve provision are included into the daily stochastic unit commitment model. The hourly simulation is run for the same day to account for IG production errors, demand forecast errors and unit failure and therefore revising the previous planned schedule.
    The transmission network is represented by a DC load flow with ohmic losses approximated by a piecewise linear function.
  • A chronological approach to sequentially evaluate every day of a year
    Decisions above this scope as the weekly scheduling of pumped storage hydro plants are done internally in the model by heuristic criteria. Yearly hydro scheduling of storage hydro plants is done by higher hierarchy models, as for example, a hydrothermal scheduling model.
  • Monte Carlo simulation of many yearly scenarios that deal with IG or hydro inflows stochasticity

The model scheme based on a daily sequence of planning and simulation is similar to an open-loop feedback control used in control theory.

Description of the ROM model (see Deliverable 2.2 of MERGE project section 4 of "FUNCTIONAL SPECIFICATION FOR TOOLS TO ASSESS STEADY STATE AND DYNAMIC BEHAVIOUR IMPACTS, IMPACT ON ELECTRICITY MARKETS AND IMPACT OF HIGH PENETRATION OF EV ON THE RESERVE LEVELS")

This model was originally based on the MEMPHIS model developed for Red Eléctrica de España under the research project "Modelado del impacto de la generación intermitente en la operación del sistema".

ROM is written in GAMS with a Microsoft Excel input/output interface and requires a licence for one of the optimization solvers linked with GAMS. Some of the optimization solvers are free for academics, but must be registered with a degree-issuing academic institution.

This model is currently being used and improved in some Spanish or European research projects:

Algunas publicaciones relacionadas con ROM / Some ROM related publications

J. Chaves-Ávila, F. Banez-Chicharro, A. Ramos The impact of support schemes and market rules on renewable electricity generation and system operation: application to the Spanish case IET Renewable Power Generation 11 (3), 22, 238-244, Feb 2017 10.1049/iet-rpg.2016.0246

K. Dietrich, J.M. Latorre, L. Olmos, A. Ramos Modelling and assessing the impacts of self supply and market-revenue driven Virtual Power Plants Electric Power Systems Research 119: 462-470, Feb 2015 10.1016/j.epsr.2014.10.015

A. Ramos, K. Dietrich, F. Banez-Chicharro, L. Olmos, J.M. Latorre Analysis of the impact of increasing shares of electric vehicles on the integration of RES generation in the book M.A. Sanz (ed.) Use, Operation and Maintenance of Renewable Energy Systems. pp. 371-385 Springer 2014 ISBN 9783319032238

B. Dupont, K. Dietrich, C. De Jonghe, A. Ramos, R. Belmans Impact of residential demand response on power system operation: a Belgian case study Applied Energy 122: 1-10, June 2014 10.1016/j.apenergy.2014.02.022

F. Banez-Chicharro, J.M. Latorre, A. Ramos Smart charging profiles for electric vehicles Computational Management Science 11 (1): 87-110, Jan 2014 10.1007/s10287-013-0180-8

K. Dietrich, J.M. Latorre, L. Olmos, A. Ramos The Role of Flexible Demands in Smart Energy Systems in the book V. Papp, M. Carvalho and P. Pardalos (eds.) Optimization and Security Challenges in Smart Power Grids. Springer 2013 ISBN 9783642381331

B. Dollinger and K. Dietrich Storage Systems for Integrating Wind and Solar Energy in Spain International Conference on Renewable Energy Research and Applications (ICRERA). Madrid, Spain, October 2013.

K. Dietrich, J.M. Latorre, L. Olmos, A. Ramos Demand Response Mechanism Design and the Impact of Crucial Parameters on its Effectiveness IIT-13-027A.pdf

K. Dietrich and A. Lopez-Pena, Is the European 2050 emissions path viable for Spain? How much renewables are needed? Is the power system able to deal with it? International Conference Challenges on Climate Change. Madrid, Spain, February 2013

K. Dietrich, J.M. Latorre, L. Olmos, A. Ramos Demand Response in an Isolated System with high Wind Integration IEEE Transactions on Power Systems 27 (1): 20-29 Feb 2012 10.1109/TPWRS.2011.2159252

A. Ramos, J.. Latorre, F. Banez, A. Hernández, G. Morales-España, K. Dietrich, L. Olmos Modeling the Operation of Electric Vehicles in an Operation Planning Model 17th Power Systems Computation Conference (PSCC 2011). Stockholm, Sweden August 2011 (Presentation)

C. Fernandes, P. Frías Análisis del impacto en España de la generación renovable en el período 2020-2050 Anales de Mecánica y Electricidad. Julio-Agosto 2011.

K. Dietrich, J.M. Latorre, L. Olmos, and A. Ramos Demand Response and Its Sensitivity to Participation Rates and Elasticities 7th International Conference on the European Energy Market (EEM 11). Zagreb, Croatia May 2011

K. Dietrich, J.M. Latorre, L. Olmos, A. Ramos How can the use of electric vehicles affect the curtailment of renewable generation? ENERDAY 6th Conference on Energy Economics and Technology Dresden, Germany April 2011 (Presentation)

K. Dietrich, J.M. Latorre, L. Olmos, A. Ramos Using flexible load shape objectives for demand response and its impact in system operation Young Energy Economists and Engineers Seminar (YEEES) Dresden, Germany April 2011

K. Dietrich, J.M. Latorre, L. Olmos, A. Ramos Adequate Regulation Reserve Levels in Systems with large wind integration using Demand Response 11th IAEE European Conference Vilnius, Lithuania August 2010

C. Fernandes, P. Frías, L. Olmos, A. Ramos, T. Gómez A Long-Term Prospective for the Spanish Electricity System 7 International Conference on the European Energy Market (EEM 10). Madrid, Spain June 2010

C. Fernandes, P. Frías, L. Olmos, A. Ramos, T. Gómez Economic Impact of Plug-In Hybrid Electric Vehicles on Power Systems Operation IAEE'S Rio 2010 International Conference. Rio de Janeiro, Brazil June 2010

K. Dietrich, J.M. Latorre, L. Olmos, A. Ramos Demand Response in an Isolated System with high Wind Integration IIT-10-009A

K. Dietrich, J.M. Latorre, L. Olmos, A. Ramos Stochastic Unit Commitment Considering Uncertain Wind Production in an Isolated System International Workshop on Large-Scale Integration of Wind Power into Power Systems Bremen, Germany October 2009 (Presentation)

A. Ramos, K. Dietrich, J.M. Latorre, L. Olmos, I.J. Pérez-Arriaga Sequential Stochastic Unit Commitment for Large-Scale Integration of RES and Emerging Technologies 20th International Symposium of Mathematical Programming (ISMP) Chicago, IL, USA August 2009 (Presentation)

K. Dietrich, J.M. Latorre, L. Olmos, A. Ramos, I.J. Pérez-Arriaga Stochastic Unit Commitment Considering Uncertain Wind Production in an Isolated System ENERDAY 4th Conference on Energy Economics and Technology Dresden, Germany April 2009 (Presentation)

A. Ramos, L. Olmos, J. Latorre, I. Pérez-Arriaga Modeling Medium Term Hydroelectric System Operation with Large-Scale Penetration of Intermittent Generation XIV Latin Ibero-American Congress on Operations Research (CLAIO 2008) Cartagena de Indias, Colombia September 2008 (Presentation)


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