research

Multistage stochastic bid model for a wind-thermal power producer

Publication TypeTesis de Grau i Màster // BSc and MSc Thesis
Year of Publication2021
AuthorsIgnasi Mañé Bosch
DirectorF-Javier Heredia
Tipus de tesiMSc Thesis
TitulacióMaster in Statistics and Operations Reseafrch
CentreFacultat de matemàtiques i Estadística
Data defensa18/10/2021
Nota // mark9.5
Key Wordsteaching; electricity markets; multistage stochastic programming
AbstractFor many political and economic reasons, over the last decades, electricity markets in developed countries have been liberalised. Markets regulated by governments in which prices were set by the competent authority are now the exception. In this new setting, electricity agents, both consumers and producers, compete to maximise their pro tability in a series of auctions designed to eciently match supply and demand. Many energy producers manage together wind and thermal generation units to meet their contractual obligations such as bilateral contracts, as well as bid on the electric market to sell their production capacity. This master thesis explore di erent multi-stage stochastic programming models for generation companies to nd optimal bid functions in electric spot markets. The explored models not only capture the uncertainty of electric prices of di erent markets and fi nancial products, but also couples together wind and thermal generation units, offering producers that combine both technologies a more suitable approach to nd their best possible bidding strategy among the space of possible actions.
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Participation in the 31st European Conference on Operational Research.

Last July 21th, the work "Multistage Scenario Trees Generation for Electricity Markets Optimization" was presentated at the 31st European Conference on Operational Research  in an invited session of the stream "Stochastic and Robust Optimization". This study is a result of the PH.D. Thesis of Ms. Marlyn D. Cuadrado on scenarios trees generation for multistage stochastic programming in optimal electricity bid problems.

Ph D. Thesis on multistage scenario tree generation for renewable energies.

 On November 30th 2020 took place the defense of the Ph.D. Thesis entittled "Multistage Scenario Trees Generation for Renewable Energy Systems Optimization", authored by Ms. Marlyn D. Cuadrado Guevara and advised by prof. F.-Javier Heredia. In this thesis a new methodology to generate and validate probability scenario trees for multistage stochastic programming problems arising in two different energy systems with renewables are proposed. The first problem corresponds to the optimal bid to electricity markets of a virtual power plant that consists on a wind-power plant plus a battery storage energy systems. The second one is the optimal operation of a distribution grid with some photovoltaic production.

Critical evaluation of European balancing markets to enable the participation of Demand Aggregators

Publication TypeJournal Article
Year of Publication2020
AuthorsMattia Barbero; Cristina Corchero; Lluc Canals; Lucia Igualada; F.-Javier Heredia
Journal TitleApplied Energy
Volume264
Journal Date04/2020
PublisherElsevier
ISSN Number0306-2619/
Key WordsDemand Aggregator; Regulatory framework; Ancillary Services; Demand Response; Tertiary building management; research; paper
AbstractEuropean Directives are incentivizing consumers to play an active role in the electricity system and to collaborate to maintain its stability, which has been historically provided by large generation power plants. However, it is not easy for the System Operator to handle the coexistence of consumers and generators in the same markets. Under these circumstances, a new actor allows small residential and commercial consumers to participate in flexibility markets: The Demand Aggregator. However, balancing markets opened to Demand Aggregators still present several barriers that do not allow their practical participation. This study analyzes barriers and enablers of four European electricity markets and proposes a new market framework that would enhance Demand Aggregators’ participation. To validate the proposed market and to understand the economic potentials of aggregated small tertiary buildings, a Demand Aggregator is simulated using real building’s consumption data. Results show that technical requirements to participate in balancing markets such as the minimum bid size, the symmetricity of the offer and the product resolution strongly affect incomes for Demand Aggregators. However, neither in the proposed market, the creation of a Demand Aggregator whose business model is focused on small tertiary buildings does not seem realistic due to low incomes in comparison to the fixed costs necessary to enable Demand Response, especially if only the air conditioning system is considered.
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DOI10.1016/j.apenergy.2020.114707
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A MIP formulation of a Hybrid AC-DC offshore wind power plant topology

Publication TypeConference Paper
Year of Publication2018
AuthorsCristina Corchero; Josep Homs-Moreno; F.-Javier Heredia; Lucia Igualada; Mikel de Prada
Conference Name23th International Symposium on Mathematical Programming
Conference Date01-06/07/2018
Conference LocationBordeaux
Type of Workcontributed presentation
Key Wordsresearch; hybrid AC-DC; offshore wind power plant; local branching
AbstractThe current study analyses a hybrid o↵shore wind farm design in which individual wind turbine power converters are removed from wind turbines and are installed on intermediate o↵shore collector platforms. In this study a compact and small-sized mixedinteger linear optimisation model makes four decisions with the goal of minimising installation and operation costs: the location and the number of o↵shore platforms and power converters to be installed, the optimal wind farm cable layout and the cluster optimal operating frequency of each wind turbine. The solutions found either for small and large o↵shore wind farms improve notoriously real-world designs, reducing up to 8 percent installation and maintenance costs. On the optimization technical results, a variant of Local Branching has been developed, reducing in some cases more than half of computing time with respect to default Local Branching. The model developed serves as a mathematical tool to provide rigorous evidences of the suitability of the hybrid design versus traditional o↵shore wind farm designs.
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New paper published in Computers and Operations Research

 The work On optimal participation in the electricity markets of wind power plants with battery energy storage systems  has been published in the journal Computers and Operations Research.  We present in this study a multi-stage stochastic programming model to find the optimal operation of a VPP in the day-ahead, intraday and secondary reserve markets hile taking into account uncertainty in wind power generation and clearing prices (day-ahead, secondary reserve, intraday markets and system imbalances). A case study with real data from the Iberian electricity market is presented. Preprint available at http://hdl.handle.net/2117/118479

On optimal participation in the electricity markets of wind power plants with battery energy storage systems

Publication TypeJournal Article
Year of Publication2018
AuthorsF.-Javier Heredia; Marlyn D. Cuadrado; Cristina Corchero
Journal TitleComputers and Operations Research
Volume96
Pages316-329
Journal Date08/2018
PublisherElsevier
ISSN Number0305-0548
Key Wordsresearch; Battery energy storage systems; Electricity markets; Ancillary services market; Wind power generation; Virtual power plants; Stochastic programming; paper
AbstractThe recent cost reduction and technological advances in medium- to large-scale battery energy storage systems (BESS) makes these devices a true alternative for wind producers operating in electricity markets. Associating a wind power farm with a BESS (the so-called virtual power plant (VPP)) provides utilities with a tool that converts uncertain wind power production into a dispatchable technology that can operate not only in spot and adjustment markets (day-ahead and intraday markets) but also in ancillary services markets that, up to now, were forbidden to non-dispatchable technologies. What is more, recent studies have shown capital cost investment in BESS can be recovered only by means of such a VPP participating in the ancillary services markets. We present in this study a multi-stage stochastic programming model to find the optimal operation of a VPP in the day-ahead, intraday and secondary reserve markets while taking into account uncertainty in wind power generation and clearing prices (day-ahead, secondary reserve, intraday markets and system imbalances). A case study with real data from the Iberian electricity market is presented.
URLClick Here
DOI10.1016/j.cor.2018.03.004
Preprinthttp://hdl.handle.net/2117/118479
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Optimising data analytics for industry 4.0

Publication TypeConference Paper
Year of Publication2018
AuthorsF.-Javier Heredia
Conference NameMaths for Industry 4.0
Conference Date19/02/2018
Conference LocationBarcelona
Type of WorkRound table
Key Wordsresearch,; industrial mathematics; industry 4.0; BGSMath
Abstract“Maths for Industry 4.0” will showcase how academic excellence at BGSMath is helping companies becoming digital. Join us to learn about successful collaborative initiatives, such as industrial doctoral theses, as well as the range of expertise you could benefit from. The workshop will be closed by a round table on Data Analytics. Our experts will discuss common challenges and trends across sectors, and how mathematical creativity enable solutions for supply chain, risk management, control and monitoring. This activity belongs to the Mobile Week Barcelona and it’s an open space for reflexion on digital transformation through art, science and technology.
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Maths for Industry 4.0

Maths for Industry 4.0The Barcelona Graduate School of Mathematics (BGSMath ) organized last February 19 2018 the workshop "Maths for Industry 4.0 " to showcase how academic excellence at BGSMath is helping companies becoming digital through several successful collaborative initiatives, such as industrial doctoral theses or consultancy and development projects of the BGSMaths's research groups in Data Science and Optimization. The workshop will be closed by the round table "Optimising data analytics for industry 4.0" where I was invited to participate as expert in supply chain optimization. This activity is embedded into the Mobile Week Barcelona and it's an open space for reflexion on digital transformation through art, science and technology. More photos of the event at this link .

Stochastic optimal generation bid to electricity markets with emissions risk constraints.

Publication TypeJournal Article
Year of Publication2018
AuthorsF.-Javier Heredia; Julián Cifuentes-Rubiano; Cristina Corchero
Journal TitleJournal of Environmental Management
Volume207
Issue1
Pages12
Start Page432
Journal DateFebruary 2018
PublisherElsevier
ISSN Number0301-4797
Key Wordsresearch; OR in Energy; Stochastic Programming; Risk Management; Electricity market; Emissions reduction; paper
AbstractThere are many factors that influence the day-ahead market bidding strategies of a generation company (GenCo) within the framework of the current energy market. Environmental policy issues are giving rise to emission limitation that are becoming more and more important for fossil-fueled power plants, and these must be considered in their management. This work investigates the influence of the emissions reduction plan and the incorporation of the medium-term derivative commitments in the optimal generation bidding strategy for the day-ahead electricity market. Two different technologies have been considered: the high-emission technology of thermal coal units and the low-emission technology of combined cycle gas turbine units. The Iberian Electricity Market (MIBEL) and the Spanish National Emissions Reduction Plan (NERP) defines the environmental framework for dealing with the day-ahead market bidding strategies. To address emission limitations, we have extended some of the standard risk management methodologies developed for financial markets, such as Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR), thus leading to the new concept of Conditional Emission at Risk (CEaR). This study offers electricity generation utilities a mathematical model for determining the unit’s optimal generation bid to the wholesale electricity market such that it maximizes the long-term profits of the utility while allowing it to abide by the Iberian Electricity Market rules as well as the environmental restrictions set by the Spanish National Emissions Reduction Plan. We analyze the economic implications for a GenCo that includes the environmental restrictions of this National Plan as well as the NERP’s effects on the expected profits and the optimal generation bid.
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DOI10.1016/j.jenvman.2017.11.010
Preprinthttp://hdl.handle.net/2117/114024
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