smart cities

MSc Thesis on distributed battery energy storage systems in energy retail markets

 Distributed BESS in a neighborhood. Image from Mr. M. Sisovs's MSc Thesis report.Last September 16 2016 Mr Maksims Sisovs, student of the "KIC InnoEnergy" Master of Science in Smart Electrical Networks and Systems defended their MSc Thesis A Study on Feasibility of the Distributed Battery Energy Storage Systems in Spanish Retail Electricity Market. This project was proposed by Minsait, an advanced technological consultancy from the Indra's group, and developed under my academical supervision. The objective of the study was to analyse the business opportunity of distributed battery energy storage systems deployed in residential neighbourhoods (LiIon batteries, both static devices and mobile through electrical vehicle). The methodology applied was based on the adaptation of the mathematical optimization model presented in the paper Economic analysis of battery electric storage systems operating in electricity markets (Heredia et al. 2015) to the data of the smart meters deployed by several electrical utilities (more than 20 millions of consumption readings). This work deserved the maximum grade, A+ with honours.

A Study on Feasibility of the Distributed Battery Energy Storage Systems in Spanish Retail Electricity Market

Publication TypeTesis de Grau i Màster // BSc and MSc Thesis
Year of Publication2016
AuthorsMaksims Sisovs
DirectorF.-Javier Heredia
Tipus de tesiMSc Thesis
Titulació"KIC InnoEnergy" Master of Science in Smart Electrical Networks and Systems
CentreEscola Tècnica Superior d'Enginyeria Industrial de Barcelona (ETSEIB)
Data defensa16/09/2016
Nota // mark10 MH (A+ with honours)
Key Wordsteaching; BEES; battery energy storage systems; electrical vehicle; smart meters; retail energy market; MSc Thesis
AbstractThe main focus of this master thesis project is to evaluate the economic, technical and regulatory feasibility of distributed battery energy storage systems (BESS) and the potential opportunity of electricity companies to increase their pro ts through advanced operation in energy services, such as electric energy time-shift, ancillary or electric vehicle incentives in Spanish electricity market. To assess the feasibility, an optimization tool has been developed. This tool simulates energy trading between diff erent market participants with particular features extracted from data analysis and literature. Load consumption pro les had been developed from smart meter real data by applying several data mining techniques. This part had been guided by external collaborating entity Minsait. Electricity market analysis includes the overview of its functionality principles and regulatory side regarding storage adaptation and speci fic service applicability. Market historical prices were used for further electricity trading simulation. A brief technical insight explains current storage situation and tells about high-potential technologies in emerging markets. Benchmark analysis covers several products of battery manufacturers with relevant technical and price information. Spanish electricity market showed low adaptability to distributed BESS solutions: energy arbitrage incomes have resulted being insuficient. Ancillary services, despite promising economic gures, are to a large extent prohibited to be provided by distributed storage. Electric vehicle incentives, though, resulted being of a high interest due to absence of direct investment.
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A multi-objective approach to infrastructure planning in the early stages of EV introduction

Publication TypeTesis de Grau i Màster // BSc and MSc Thesis
Year of Publication2014
AuthorsAndina Rosalia Brown
DirectorF.-Javier Heredia; Cristina Corchero
Tipus de tesiMSc Thesis
TitulacióMaster in Statistics and Operations Research
CentreFaculty of Mathematics and Statistics
Data defensa27/01/2014
Nota // mark9.0
Key WordsMulti-objective Optimisation; Facility Location; Electric Vehicle; Fast Charging Stations; MSc Thesis
AbstractThis study approaches the problem from the perspective of a central planner wishing to install fast charging stations. A multi-objective approach is used to simultaneously consider two conflicting objectives in the optimisation problem. The first objective is to minimise the distance that potential consumers would need to deviate from their normal journeys in order to reach their nearest fast charging station, and thus minimise the associated inconvenience. The second objective is to minimise the set up costs associated with the installation of the stations, which differ according to the number of facilities installed and their location. These objectives are normalised using a function transformation and then combined into a single objective function. A mathematical model is formulated and implemented using GAMS to obtain results for the case study of Barcelona, building on the existing literature. Using the weighted sums method, multiple Pareto optimal solutions are found by solving for different relative weights combinations applied to the two objectives. These solutions are used to depict the Pareto front, offering insight into the nature of the trade-offs between the objectives and aiding the decision making process. This study develops the existing methodology used for the EV infrastructure problem, and shows how the application of a multi-objective formulation can offer useful insight to decision makers, particularly when preferences are unclear a priori.
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