Publication Type	Tesis de Grau i Màster // BSc and MSc Thesis
Year of Publication	2023
Authors	Andrea Iglesias Munilla
Director	F.-Javier heredia
Tipus de tesi	MSc Thesis
Titulació	Master in Data Science
Centre	Facultat d'Informàtica de Barcelona
Data defensa	30/06/2023
Nota // mark	9.5
Key Words	teaching; unit commitment; quantum computing; QUBO
Abstract	This thesis explores the application of quantum computing techniques to solve Quadratic Unconstrained Binary Optimization problems, with a focus on the Unit Commitment problem. The thesis provides an introduction to quantum computing, including its mathematical foundation and the distinction between classical and quantum systems. It then discusses Variational Quantum Algorithms and explores various quantum computing platforms. Then a novel formulation of the Unit Commitment problem is presented, along with its implementation using the Qiskit library. The results obtained from the implementation are summarized, highlighting the process of using quantum computing for solving optimization problems.
DOI / handle	http://hdl.handle.net/2117/394532
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Last July 4 2022 I was invited at the EURO 2022 conference , Aalto University, Espoo, near Helsinki, to present the work Multistage stochastic programming for the optimal bid of a wind-thermal power production pool with battery storage, which is a continuation of the MSc  and PhD thesis of Mr. Ignasi Manyé and Ms. Marlyn D. Cuadrado respectively. This work tackles with an extensive study along a complete timespan of on year analyzing the benefits of a joint operation of a wind and thermal generation system in the elecrticity markets and bilateral contracts. Numerical results show that the total profit increases by  13% in average, but that it can be as high as 77%, with a reduction of the thermal operation costs of 61%.

Publication Type	Conference Paper
Year of Publication	2022
Authors	F.-Javier Heredia; Ignasi Mañé; Marlyn Dayana Cuadrado Guevara
Conference Name	EURO 2022
Conference Date	03-06/07/2022
Conference Location	Espoo, Finland.
Type of Work	Invited presentation
ISBN Number	978-951-95254-1-9
Key Words	research; multistage stochastic programming; virtual power plants; unit commitment
Abstract	In this study we present a multistage stochastic programming model to find the joint optimal bid to electricity markets of a pool of dispatchable (thermal) and non-dispatchable (wind) production units with battery storage facilities. The assumption is that these programming units are operated by the same utility that, previous to the market clearing, has to dispatch some bilateral contracts with the joint production of the production pool. The multistage model mimics the multimarket bidding process in the Iberian Electricity Market (MIBEL). First, the utility has to decide how to cover the energy of the bilateral contracts with the available units. Second, the production capacity of each unit, not allocated to the bilateral contracts, must be offered to the seven consecutives spot markets (day-ahead and six intraday markets) plus the secondary reserve market (the most relevant ancillary services market). The stochasticity of the electricity clearing prices and the hourly generation of the wind-power units is considered. The stochastic process associated to this multistage decision-making process is modelled through multistage scenario trees with thirty-four stages that are built from forecasting models based on real data of the Iberian Electricity Market. The numerical results show the advantage of the joint operation of the pool of production units with an increase of the overall expected profits, mainly due to a strong reduction of the operational costs.
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