European electric vehicle fleet: driving and charging behaviors

The electrification of vehicles would be a reality in the coming decades. Statistical results on real electric vehicle usage data is a key point in the development of the electro mobility. A large collection of electric vehicles and charging points have been monitored during three years and the results about the driving and charging patterns are shown in this work. These results may help to develop future policies on, for instance, charging infrastructure location, end-users incentives, or to allow different type of economic analysis such as an evaluation of the electric vehicle integration in the grid, smart-charge impact…Peer ReviewedPostprint (published version

Short - Term Bidding Strategies for a Generation Company in the Iberian Electricity Market

La posada en marxa del Mercat Ibèric de l'Electricitat va introduir al sector elèctric espanyol un seguit de nous mecanismes de participació que han forçat els agents a renovar les seves polítiques de gestió. D'aquesta nova situació sorgeix l'oportunitat d'estudiar noves estratègies d'oferta a curt termini per a companyies de generació price-taker que participin diàriament al Mercat Ibèric de l'Electricitat. Aquestes estratègies se centraran al mercat diari, ja que és aquí on es negocia un 80% de l'electricitat que es consumeix diàriament a Espanya i on s'integren gran part de la resta de mecanismes de participació. La liberalització dels mercats elèctrics obre a noves tècniques d'optimització els problemes clàssics de gestió de l'energia. En particular, atesa la incertesa que l'existència del mercat ocasiona als preus, les tècniques de programació estocàstiques es converteixen en la forma més natural per abordar aquests problemes. Als mercats elèctrics el preu es fixa horàriament com a resultat d'un procés de casació , és a dir que quan l'agent ha d'efectuar la seva oferta desconeix el preu al qual li vindrà remunerada l'energia. Aquesta incertesa fa imprescindible l'ús de tècniques estadístiques per obtenir informació del mercat i introduir-la als models d'optimització. En aquest aspecte, una de les contribucions d'aquesta tesi és l'estudi dels preus del mercat de l'electricitat a Espanya i el seu modelat mitjançant models factorials. D'altra banda, s'hi es descriuen els nous mecanismes presents al Mercat Ibèric de l'Electricitat que afecten directament la producció física de les unitats. En particular, s'inclou el modelat detallat dels contractes de futurs físics i bilaterals i de la seva inclusió a l'oferta del mercat diari per part de les companyies de generació. Als models presentats, es tenen en compte explícitament les regles del mercat, així com les clàssiques restriccions d'operació de les unitats, tant tèrmiques com de cicle combinat. A més, es deriva i es demostra l'expressió de la funció d'oferta. Per tant, els models construïts són una eina per decidir l'assignació de les unitats, la generació dels contractes de futurs físics i bilaterals a través seu i l'oferta òptima d'una companyia de generació. Un cop s'han cobert aquests objectius, es presenta una millora dels models mitjançant la inclusió de la seqüència de mercats de molt curt termini per tal de modelar la influència que tenen en l'oferta al mercat diari. Aquests mercats es casen just abans i durant el dia en què l'energia ha de ser consumida, i això permetrà veure com la possibilitat d'augmentar els beneficis participant-hi afecta directament les estratègies d'oferta òptima del mercat diari. Els models presentats en aquest treball han estat provats amb dades reals provinents del Mercat Ibèric de l'Electricitat i d'una companyia de generació que hi opera. Els resultats obtinguts són adequats i es discuteixen al llarg del documentLa puesta en marcha del Mercado Ibérico de la Electricidad introdujo en el sector eléctrico español una serie de nuevos mecanismos de participación que han forzado a los agentes a renovar sus políticas de gestión. De esta nueva situación surge la oportunidad de estudiar nuevas estrategias de oferta para las compañías de generación. Esta tesis se enmarca en las estrategias de oferta a corto plazo para compañías de generación price-taker que participen diariamente en el Mercado Ibérico de la Electricidad. Estas estrategias se centraran en el mercado diario ya que es donde se negocia un 80% de la electricidad consumida diariamente en España y es donde se integran gran parte del resto de los mecanismos de participación. La liberalización de los mercados eléctricos permite aplicar nuevas técnicas de optimización a los problemas clásicos de gestión de la energía. En concreto, dada la incertidumbre en el precio existente en el mercado, las técnicas de programación estocástica se convierten en la forma más natural para abordar estos problemas. En los mercados eléctricos el precio se fija horariamente como resultado de un proceso de casación, es decir, cuando el agente debe efectuar sus ofertas desconoce el precio al que la energía le será pagada. Esta incertidumbre hace imprescindible el uso de técnicas estadísticas para obtener información del mercado e introducirla en los modelos de optimización. En este aspecto, una de las contribuciones de esta tesis es el estudio del precio de la electricidad en España y su modelado mediante modelos factoriales. Se describen los nuevos mecanismos presentes en el Mercado Ibérico de la Electricidad que afectan directamente a la producción física de las unidades. En particular, se incluye una modelización detallada de los contratos de futuros físicos y bilaterales y su inclusión en la oferta enviada al mercado diario por las compañías de generación. En los modelos presentados se tiene en cuenta explícitamente las reglas del mercado así como las clásicas restricciones de operación de las unidades, tanto térmicas como de ciclo combinado. La expresión de la función de oferta óptima se deriva y se demuestra. Por lo tanto, los modelos construidos son una herramienta para decidir la asignación de unidades, la generación de los contratos de futuros físicos y bilaterales a través de ellas y la oferta óptima de una compañía de generación. Una vez alcanzados estos objetivos, se presenta una mejora del modelo con la inclusión de la secuencia de mercados de muy corto plazo. El objetivo es modelar la influencia que esta tiene en la oferta al mercado diario. Estos mercados se casan justo antes y durante el día en el que la energía va a ser consumida y se verá cómo la posibilidad de aumentar los beneficios participando en ellos afecta a las estrategias de oferta óptima del mercado diario. Los modelos presentados en este trabajo se han probado con datos reales procedentes del Mercado Ibérico de la Electricidad y de una compañía de generación que opera en él. Los resultados obtenidos son adecuados y se discuten a lo largo del documento.The start-up of the Iberian Electricity Market introduced a set of new mechanisms in the Spanish electricity sector that forced the agents participating in the market to change their management policies. This situation created a great opportunity for studying the bidding strategies of the generation companies in this new framework. This thesis focuses on the short-term bidding strategies of a price-taker generation company that bids daily in the Iberian Electricity Market. We will center our bidding strategies on the day-ahead market because 80% of the electricity that is consumed daily in Spain is negotiated there and also because it is the market where the new mechanisms are integrated. The liberalization of the electricity markets opens the classical problems of energy management to new optimization approaches. Specifically, because of the uncertainty that the market produces in the prices, the stochastic programming techniques have become the most natural way to deal with these problems. Notice that, in deregulated electricity markets the price is hourly fixed through a market clearing procedure, so when the agent must bid its energy it is unaware of the price at which it will be paid. This uncertainty makes it essential to use some statistic techniques in order to obtain the information coming from the markets and to introduce it in the optimization models in a suitable way. In this aspect, one of the main contributions of this thesis has been the study the Spanish electricity price time series and its modeling by means of factor models. In this thesis, the new mechanism introduced by the Iberian Market that affects the physical operation of the units is described. In particular, it considers in great detail the inclusion of the physical futures contracts and the bilateral contracts into the day-ahead market bid of the generation companies. The rules of the market operator have been explicitly taken into account within the mathematical models, along with all the classical operational constraints that affect the thermal and combined cycle units. The expression of the optimal bidding functions are derived and proved. Therefore, the models built in this thesis provide the generation company with the economic dispatch of the committed futures and bilateral contracts, the unit commitment of the units and the optimal bidding strategies for the generation company. Once these main objectives were fulfilled, we improved the previous models with an approach to the modeling of the influence that the sequence of very short markets have on optimal day-ahead bidding. These markets are cleared just before and during the day in which the electricity will be consumed and the opportunity to obtain benefits from them changes the optimal day-ahead bidding strategies of the generation company, as it will be shown in this thesis. The entire models presented in this work have been tested using real data from a generation company and Spanish electricity prices. Suitable results have been obtained and discussed

Planificació tèrmica mitjançant una aplicació en VBA per Excel

La Planificació Tèrmica a curt termini és un dels problemes a resoldre en la gestió de les companyies elèctriques. La solució indica com distribuir i assignar la generació d’energia elèctrica a les centrals tèrmiques actives durant un període concret, que a curt termini varia entre un dia i una setmana, de forma que és minimitzi la despesa per consum de combustible. En l’optimització a curt termini, la previsió horària de càrrega s’ha de cobrir, satisfent alhora diversos requeriments de reserva rodant fixats per tenir en compte els errors en la previsió de càrrega i les avaries de les màquines. El període d’estudi queda dividit en intervals temporals d’una hora, partint d’unitats enceses o apagades. En aquests intervals considerem conegudes totes les dades, tenint com a variables de decisió la generació d’energia de cada una de les centrals tèrmiques

Problema del període òptim d'oferta d'una unitat tèrmica

L’objectiu d’aquest projecte és l’estudi de l’aplicació de les tècniques de programació estocàstica en l’ajut a l’elaboració de l’oferta de les compayies productores d’energia al mercat diari espanyol d’energia elèctrica. L’assoliment d’aquest objectiu ha fet necessari: - Definir, aplicant tècniques de programació estocàstica, un model d’optimització per obtenir un patró d’engegades i aturades per una unitat tèrmica de forma que el benefici esperat sigui màxim, tenint en compte l’aleatorietat d’aquests beneficis. - Estudiar l’estructura dels preus del Mercat Elèctric Espanyol per tal de poder incloure’ls als models d’optimització abans esmentats

A Stochastic Programming Model for the Thermal Optimal Day-Ahead Bid Problem with Physical Futures Contracts

The reorganization of the electricity industry in Spain completed a new step with the start-up of the Derivatives Market. One main characteristic of MIBEL’s Derivatives Market is the existence of physical futures contracts; they imply the obligation to settle physically the energy. The market regulation establishes the mechanism for including those physical futures in the day-ahead bidding of the Generation Companies. The goal of this work is to optimize coordination between physical futures contracts and the Day-Ahead bidding which follow this regulation. We propose a stochastic quadratic mixed-integer programming model which maximizes the expected profits, taking into account futures contracts settlement. The model gives the simultaneous optimization for the Day-Ahead Market bidding strategy and power planning production (unit commitment) for the thermal units of a price-taker Generation Company. The uncertainty of the day-ahead market price is included in the stochastic model through a set of scenarios. Implementation details and some first computational experiences for small real cases are presented

A stochastic programming model for the thermal optimal day-ahead bid problem with physical futures contracts

The reorganization of the electricity industry in Spain completed a new step with the start-up of the Derivatives Market. One main characteristic of MIBEL’s Derivatives Market is the existence of physical futures contracts; they imply the obligation to physically settle the energy. The market regulation establishes the mechanism for including those physical futures in the day-ahead bidding of the Generation Companies. The goal of this work is to optimize coordination between physical futures contracts and the day-ahead bidding which follow this regulation. We propose a stochastic quadratic mixed-integer programming model which maximizes the expected profits, taking into account futures contracts settlement. The model gives the simultaneous optimization for the Day-Ahead Market bidding strategy and power planning production (unit commitment) for the thermal units of a price-taker Generation Company. The uncertainty of the Day-Ahead Market price is included in the stochastic model through a set of scenarios. Implementation details and some first computational experiences for small real cases are presented.Postprint (published version

Two-stage stochastic programming model for the thermal optimal day-ahead bid problem with physical future contracts

The reorganization of electricity industry in Spain has finished a new step with the start-up of the Derivatives Market. Nowadays, all electricity transactions in Spain and Portugal are managed jointly through the MIBEL by the Day-Ahead Market Operator and the Derivatives Market Operator. This new framework requires important changes in the short-term optimiza- tion strategies of the Generation Companies. One main characteristic of MIBEL's Derivatives Market is the existence of physical futures contracts; they imply the obligation to settle physically the energy. The market regulation establishes the mechanism for including those physical futures in the day-ahead bidding of the Generation Companies. Thus, the participation in the derivatives market changes the incomes function and it could imply changes in the optimal planning, both in the optimal bidding and in the unit commitment. The goal of this work is the optimization of the coordination between the physical futures contracts and the Day-Ahead bidding following this regulation. We propose a stochastic quadratic mixed-integer programming model which maximizes the expected profits taking into account futures contracts settlement. The model gives the simultaneous optimization for the Day-Ahead Market bidding strategy and power planning production (unit commitment) for the thermal units of a price-taker Generation Company. The uncertainty of the day-ahead market price is included in the stochastic model through a scenario set. There has been applied both simulation and reduction techniques for building this scenario set from a time series ARIMA model. The implementation of the model is done with the modeling language AMPL. Implementation details and some first computational experiences for small real cases are presented

Comparison between economic and environmental drivers for demand side aggregator

© 2020 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Demand-side flexibility is a promising source of the energy system that might enhance renewable energy penetration and help to democratize the electricity sector. However, it is not clear what is the best strategy to adopt for Demand Aggregators, especially when flexibility is provided by residential and tertiary buildings. This study compares two Demand Aggregators strategies in the framework of the SABINA (H2020) and the REFER research projects and analyses the effect of CO2 prices on the Demand Aggregator business model. Results show that Demand Response activities reduce both the costs and the building CO2 emissions independently from the strategy adopted.Peer ReviewedPostprint (author's final draft

Reviewing and exploring the qualitative impacts that different market and regulatory measures can have on encouraging energy communities based on their organizational structure

The emergence of energy communities represents a promising option to democratize the energy system by empowering consumers to take a more active role. This can aid in achieving energy and environmental goals as well as encouraging more equitable distribution of costs and revenues between all parties on the energy system. Despite this potential, energy communities are still a nascent solution, the success of which is heavily influenced by regulations. As a result, there are a wide variety of organizational structures for energy communities at this time. This paper provides a review of the policy landscape in Spain as it relates to energy communities. This work also presents a formalized method for characterizing different energy community structures and provides a qualitative assessment of the impacts of different measures to encourage energy communities with respect to their organizational structure. Findings suggest that many market-focused measures, including wholesale, local flexibility, capacity, and multisector market measures favor larger, more integrated communities, while regulatory, legal, and organizational measures, including peer-to-peer trading, aggregation, and self-consumption favor smaller, more distributed communities. Additionally, when developing policies to encourage the growth of energy communities, policymakers should be cognizant of the progression of policies in the context of the desired outcomes for energy community growth specific to the region or country and its goals.Peer ReviewedPostprint (published version

Potential externalities savings due to electric vehicle smart charge

This work focuses on the analysis developed in order to demonstrate how smart charging, using tailored control algorithms, contributes to minimize the environmental impact and economic costs associated to the electric vehicles under an LCA perspective. The analysis considers the Spanish grid mix profile and specific charging patterns.The LCA methodology adopted implies a comprehensive assessment of the impacts and costs occurring upstream and downstream the charging event. For the environmental analysis, the LCA impact categories are considered, while for the economic assessment, data regarding the costs associated to the electricity price and the pollutants generation have been adopted.Postprint (published version