index.json

[{"authors":["admin"],"categories":null,"content":"My name is Felipe Maldonado, I am a Lecturer (Assistant Professor) at the School of Mathematics, Statistics, and Actuarial Science, at the University of Essex. Before that I was a Postdoctoral Researcher at the Technical University of Munich (Department of Informatics) working with Martin Bichler on electricity market design.\nBefore moving to Germany, I did my PhD studies at the Australian National University (School of Computer Science), working with Pascal Van Hentenryck and Gerardo Berbeglia. During my stay in Australia I was also part of CSIRO-Data61. Prior to that I worked for 2 years at the University of Concepcion as a fixed-term lecturer. Before that I studied Mathematical Engineering at the University of Chile, and I worked with Roberto Cominetti on my final thesis about myopic agents with adaptive behaviour.\n","date":-62135596800,"expirydate":-62135596800,"kind":"term","lang":"en","lastmod":1622234960,"objectID":"2525497d367e79493fd32b198b28f040","permalink":"http://felipemaldonado.github.io/author/felipe-maldonado/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/author/felipe-maldonado/","section":"authors","summary":"My name is Felipe Maldonado, I am a Lecturer (Assistant Professor) at the School of Mathematics, Statistics, and Actuarial Science, at the University of Essex. Before that I was a Postdoctoral Researcher at the Technical University of Munich (Department of Informatics) working with Martin Bichler on electricity market design.","tags":null,"title":"Felipe Maldonado","type":"authors"},{"authors":["Bichler, Martin","Knörr, Johannes","Felipe Maldonado"],"categories":[],"content":"","date":1657315725,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1657315725,"objectID":"2ce7033d7931bf5dc1f73ff1418bc03c","permalink":"http://felipemaldonado.github.io/publication/2022-infor-systems/","publishdate":"2022-07-08T21:28:45Z","relpermalink":"/publication/2022-infor-systems/","section":"publication","summary":"A Walrasian competitive equilibrium defines a set of linear and anonymous prices where no coalition of market participants wants to deviate. Walrasian prices do not exist in nonconvex markets in general, with electricity markets as an important real-world example. However, the availability of linear and anonymous prices is important for derivatives markets and as a signal for scarcity. Prior literature on electricity markets assumed price-inelastic demand and introduced numerous heuristics to compute linear and anonymous prices on electricity markets. At these prices, market participants often make a loss. As a result, market operators provide out-of-market side-payments (so-called make-whole payments) to cover these losses. Make-whole payments dilute public price signals and are a significant concern in electricity markets. Moreover, demand-side flexibility becomes increasingly important with growing levels of renewable energy sources. Demand response implies that different flexibility options come at different prices, and the proportion of price-sensitive demand that actively bids on power exchanges will further increase. We show that with price-inelastic demand there are simple pricing schemes that are individually rational (participants do not make a loss), clear the market, support an efficient solution, and do not require make-whole payments. With the advent of demand-side bids, budget balanced prices (no subsidies are necessary) cannot exist anymore, and we propose a pricing rule that minimizes make-whole payments. We describe design desiderata that different pricing schemes satisfy and report results of experiments that evaluate the level of subsidies required for linear and anonymous prices on electricity spot markets with price-sensitive demand.","tags":["Non-convexities","Pricing","Demand flexibility","Electricity market design"],"title":"Pricing in Nonconvex Markets: How to Price Electricity in the Presence of Demand Response","type":"publication"},{"authors":["Felipe Maldonado","Saumweber, Andrea"],"categories":[],"content":"","date":1655933325,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1655933325,"objectID":"5c6089b7333ef48efa2e2a99cb2dd9cb","permalink":"http://felipemaldonado.github.io/publication/2022-ev-pricing/","publishdate":"2022-06-22T21:28:45Z","relpermalink":"/publication/2022-ev-pricing/","section":"publication","summary":"The energy transition, a process in which fossil fuels are being replaced by cleaner sources of energy, comes with many challenges. The intrinsic uncertainty associated with renewable energy sources has led to a search for complementary technologies to tackle those issues. In recent years, the use of electric vehicles (EVs) has been studied as an alternative for storage, leading to a much more complex market structure. Small participants are now willing to provide energy, helping to keep the desired balance of supply and demand. In this paper, we analyse the electricity spot market, providing a model where EVs decide to participate depending on the underlying conditions. We study pricing rules adapted from versions currently in use in electricity markets, and focus on two of them for our experimental settings: integer programming (IP) and extended locational marginal (ELM) pricing. We particularly pay attention to the properties those prices might satisfy, and numerically test them under some scenarios representing different levels of participation of EVs and an active demand side. Our results suggest that IP pricing generally derives larger individual uplift payments and further produces public prices that are not well aligned with the final payments of market participants, leading to distortions in the market.","tags":["Electric vehicles","Pricing rules","Electricity spot market"],"title":"Why Do Pricing Rules Matter? Electricity Market Design with Electric Vehicle Participants","type":"publication"},{"authors":["Bichler, Martin","Buhl, Hans Ulrich","Knörr, Johannes","Felipe Maldonado","Schott, Paul","Waldherr, Stefan","Weibelzahl, Martin"],"categories":[],"content":"","date":1641418125,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1641418125,"objectID":"6e002f33d496f109bef5e06602109d16","permalink":"http://felipemaldonado.github.io/publication/2021-call-to-arms/","publishdate":"2022-01-05T21:28:45Z","relpermalink":"/publication/2021-call-to-arms/","section":"publication","summary":"Europe’s clean energy transition is imperative to combat climate change and represents an economic opportunity to become independent of fossil fuels. As such, the energy transition has become one of the most important, but also one of the most challenging economic and societal projects today. Electricity systems of the past were characterized by price-inelastic demand and only a small number of large electricity generators. The transition towards intermittent renewable energy sources changes this very paradigm. Future electricity systems will consist of many thousands of electricity generators and consumers that actively participate in markets, offering flexibility to balance variable electricity supply in markets with a high spatial and temporal resolution. These structural changes have ample consequences for market operators, generators, industrial consumers as well as prosumers. While a large body of the literature is devoted to the energy transition in engineering and the natural sciences, it has received relatively little attention in the recent business research literature, even though many of the central challenges for a successful energy transition are at the core of business research. Therefore, we provide an up-to-date overview of key questions in electricity market design and discuss how changes in electricity markets lead to new research challenges in business research disciplines such as accounting, business \u0026 information systems engineering, finance, marketing, operations management, operations research, and risk management.","tags":["Renewable energy sources","Energy transition","Demand response","Electricity market design"],"title":"Electricity Markets in a Time of Change: A Call to Arms for Business Research","type":"publication"},{"authors":null,"categories":null,"content":"","date":1627084800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1627084800,"objectID":"4f6c355240c71d652b765dc8d776f61c","permalink":"http://felipemaldonado.github.io/project/supply-chain/","publishdate":"2021-07-24T00:00:00Z","relpermalink":"/project/supply-chain/","section":"project","summary":"Project page for this project.","tags":["Reinforcement Learning, Supply Chain, Incomplete Information"],"title":"Monte Carlo Tree Search on Supply Chain","type":"project"},{"authors":["Ashour Novirdoust, Amir","Bichler, Martin","Bojung, Caroline","Buhl, Hans Ulrich","Fridgen, Gilbert","Gretschko, Vitali","Hanny, Lisa","Knörr, Johannes","Felipe Maldonado","Neuhoff, Karsten","Neumann, Christoph","Ott, Marion","Richstein, Jörn C.","Rinck, Maximilian","Schöpf, Michael","Schott, Paul","Sitzmann, Amelie","Wagner, Johannes","Wagner, Jonathan","Weibelzahl, Martin"],"categories":[],"content":"","date":1614115725,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1614115725,"objectID":"e9bb38b7b890689e0b9b210eedc6ef2c","permalink":"http://felipemaldonado.github.io/publication/2020-synergie-electricity/","publishdate":"2021-02-23T21:28:45Z","relpermalink":"/publication/2020-synergie-electricity/","section":"publication","summary":"Driven by the climate conference in Paris in December 2015 countries worldwide are confronted with the question of how to shape their power system and how to establish alternative technologies to reduce harmful CO2 emissions. The German government plans that even before the year 2050, all electricity generated and consumed in Germany should be greenhouse gas neutral [1]. To successfully integrate renewable energies, a future energy system must be able to handle the intermittent nature of renewable energy sources such as wind and solar. One important means to address such electricity production variability is demand-side flexibility. Here, industry plays a major role in responding to variable electricity supply with adequate flexibility. This is where the Kopernikus project SynErgie comes in with more than 80 project partners from academia, industry, governmental, and non-governmental organizations as well as energy suppliers and network operators. The Kopernikus project SynErgie investigates how to best leverage demand-side flexibility in the German industry. The current electricity market design in Germany is not well suited to deal with increasing levels of re- newable energy, and it does not embrace demand-side flexibility. Almost 6 GW of curtailed power in 2019 provide evidence that changes are needed with respect to the rules governing electricity markets. These rules were designed at a time when electricity generation was concentrated on a few large and dispatchable conventional power plants and demand was considered inelastic. The SynErgie Cluster IV investigates how a future-proof electricity market design should be organized. The corresponding Work Package IV.3.1 more specifically deals with analyzing and designing allocation and pricing rules on electricity spot markets. The resulting design must be well suited to accommodate demand-side flexibility and address the intermittent nature of important renewable energy sources. This whitepaper is the result of a fruitful collaboration among the partners involved in SynErgie Cluster IV which include Germany’s leading research organizations and practitioners in the field. The collaboration led to an expert workshop in October 2020 with participation from a number of international energy market experts such as Mette Bjørndal (NHH), Endre Bjørndal (NHH), Peter Cramton (University of Maryland and University of Cologne), and Raphael Heffron (University of Dundee). The whitepaper details the key recommendations from this workshop. In particular, the whitepaper recommends a move to a locational, marginal price-based system together with new bidding formats allowing to better express flexibility. We argue in favor of a one-step introduction of locational, marginal prices instead of repeatedly splitting existing zones. Frequent zone splitting involves recurring political debates as well as short- and long-run instabilities affecting the basis for financial con- tracts, for example. Importantly, the definition of stable prize zones is very challenging with increasing levels of distributed and renewable energy sources. The recommendation is the outcome of an intense debate about advantages and downsides of different policy alternatives. However, such a transition to locational, marginal prices is not without challenges, and it is a call to arms for the research community, policymak- ers, and practitioners to develop concepts on how to best facilitate the transition and ensure a reliable and efficient electricity market of the future. ","tags":["Renewable energies","Demand response","Electricity market design"],"title":"Whitepaper:ELECTRICITY SPOT MARKET DESIGN 2030-2050","type":"publication"},{"authors":["Felipe Maldonado"],"categories":[],"content":"","date":1610496000,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1610496000,"objectID":"28b1589ce14bbf86700152cd8609aac9","permalink":"http://felipemaldonado.github.io/teaching/dynammic-programming-and-reinforcement-learning/","publishdate":"2021-01-13T00:00:00Z","relpermalink":"/teaching/dynammic-programming-and-reinforcement-learning/","section":"teaching","summary":"Machine learning has become a prominent tool in data analytics. One major category of it, i.e. the reinforcement learning/adaptive learning, has been widely used in industry to maximize the notion of cumulative reward. This module is concerned with the conceptual background of reinforcement learning, i.e. Markov decision process (MDP) and dynamic programming.\nModern reinforcement learning approaches and typical applications will also be covered throughout the teaching and laboratory practices.\nAdaptive learning/ reinforcement learning, has been covered under Dynamic Programming for decades. DP is designed on the divide-and-conquer basis which fits well into the computing concepts for MSc Optimization and Analytics and MSc Data Science. The stochastic version of DP links closely with the stochastic process, with the similar idea of describing the problem status by stages, states and transition matrices, but allowing decisions in the whole process. So this module fits naturally well into the current course structure, whereas compensates what we are offering by linking several topics (maths and computing, deterministic and stochastic) together.\nThis module can certainly be used, at least as an option, by the computational pathway of G100. It will create one more compulsory module to the MSc Optimization and Data Analytics, and one more optional for MSc Data Science (the largest MSc program we are having so far).\nActually this module can be taken by any MSc students with or without optimization background, because the divide-and-conquer idea behind it is straightforward to get at the very beginning (even without knowing Linear Programming), whereas the later contents will be largely linked to statistics (e.g. regression to approximate the value-to-go), machine learning (e.g. neural networks to predict what's going to happen in later stages) and stochastic process (e.g. stochastic dynamic programming where information reveals as time going). DP also has wide applications in Finance so we can also make it available as an option for MSc Maths and Finance.","tags":["Markov Decision Processes","Monte Carlo Tree Search","Q-Learning","Inventory Optimisation"],"title":"Dynammic Programming and Reinforcement Learning (MA338) - University of Essex","type":"teaching"},{"authors":["Felipe Maldonado","Pascal Van Hentenryck","Gerardo Berbeglia"],"categories":[],"content":"","date":1608499725,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1608499725,"objectID":"eb3a9675948504f81fcb2741831eca3a","permalink":"http://felipemaldonado.github.io/publication/2019-pricing-networks/","publishdate":"2020-12-20T21:28:45Z","relpermalink":"/publication/2019-pricing-networks/","section":"publication","summary":"We study the problem of pricing under a Multinomial Logit model where we incorporate network effects over the consumer’s decisions. We analyse both cases, when sellers compete or collaborate. In particular, we pay special attention to the overall expected revenue and how the behaviour of the no purchase option is affected under variations of a network effect parameter. Where for example we prove that the market share for the no purchase option, is decreasing in terms of the value of the network effect, meaning that stronger communication among costumers increases the expected amount of sales. We also analyse how the customer’s utility is altered when network effects are incorporated into the market, comparing the cases where both competitive and monopolistic prices are displayed. We use tools from stochastic approximation algorithms to prove that the probability of purchasing the available products converges to a unique stationary distribution. We model that the sellers can use this stationary distribution to establish their strategies. Finding that under those settings, a pure Nash Equilibrium represents the pricing strategies in the case of competition, and an optimal (that maximises the total revenue) fixed price characterise the case of collaboration.","tags":["Network Effects","Pricing","Robbins–Monro algorithms","Competition"],"title":"Pricing Strategies Under a Consumer Choice Model with Network Effects","type":"publication"},{"authors":["Felipe Maldonado","Martin Bichler","Johannes Knoerr"],"categories":null,"content":"","date":1603184400,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1603184400,"objectID":"6ade655b3f782988a9ce96d120795c82","permalink":"http://felipemaldonado.github.io/talk/synergie/","publishdate":"2020-10-20T09:00:00Z","relpermalink":"/talk/synergie/","section":"talk","summary":"","tags":[],"title":"Pricing in electricity markets - an overview.","type":"talk"},{"authors":["Felipe Maldonado","Gerardo Berbeglia","Pascal Van Hentenryck"],"categories":null,"content":"","date":1561546800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1561546800,"objectID":"bcdfe72e8c4bb3fb22ff65dc99dab0ea","permalink":"http://felipemaldonado.github.io/talk/euro2019/","publishdate":"2019-06-26T11:00:00Z","relpermalink":"/talk/euro2019/","section":"talk","summary":"","tags":[],"title":"Pricing under network effects","type":"talk"},{"authors":["Felipe Maldonado","Pascal Van Hentenryck","Gerardo Berbeglia","Franco Berbeglia"],"categories":[],"content":"","date":1524259725,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1524259725,"objectID":"3a5cd166647ea516e4f0c6e56a277b8f","permalink":"http://felipemaldonado.github.io/publication/2018-popularity-signals/","publishdate":"2018-04-20T21:28:45Z","relpermalink":"/publication/2018-popularity-signals/","section":"publication","summary":"This paper considers trial-offer markets where consumer preferences are modelled by a multinomial logit with social influence and position bias. The social signal for a product is given by its current market share raised to power r (or, equivalently, the number of purchases raised to the power of r). The paper shows that, when r is strictly between 0 and 1, and a static position assignment (e.g., a quality ranking) is used, the market converges to a unique equilibrium where the market shares depend only on product quality, not their initial appeals or the early dynamics. When r is greater than 1, the market becomes unpredictable. In many cases, the market goes to a monopoly for some product: which product becomes a monopoly depends on the initial conditions of the market. These theoretical results are complemented by an agent-based simulation which indicates that convergence is fast when r is between 0 and 1, and that the quality ranking dominates the well-known popularity ranking in terms of market efficiency. These results shed a new light on the role of social influence which is often blamed for unpredictability, inequalities, and inefficiencies in markets. In contrast, this paper shows that, with a proper social signal and position assignment for the products, the market becomes predictable, and inequalities and inefficiencies can be controlled appropriately.","tags":["Social influence","Stochastic dynamics","Robbins–Monro algorithms","Popularity signals","Ranking policies"],"title":"Popularity Signals in Trial-Offer Markets with Social Influence and Position Bias","type":"publication"},{"authors":["Andres Abeliuk","Gerardo Berbeglia","Felipe Maldonado","Pascal Van Hentenryck"],"categories":[],"content":"","date":1468022400,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1468022400,"objectID":"eb32b06b5b467b5b23403b699b696f84","permalink":"http://felipemaldonado.github.io/publication/2016-performance-ranking/","publishdate":"2016-07-09T00:00:00Z","relpermalink":"/publication/2016-performance-ranking/","section":"publication","summary":"We study dynamic trial-offer markets, in which par- ticipants first try a product and later decide whether to purchase it or not. In these markets, social influence and position biases have a greater effect on the decisions taken in the sampling stage than those in the buying stage. We consider a myopic policy that maximizes the market efficiency for each incoming participant, taking into account the inherent quality of products, position biases, and social influence. We prove that this myopic policy is optimal and predictable asymptotically.","tags":["Quality vs Popularity","Ranking policies"],"title":"Asymptotic Optimality of Myopic Optimization in Trial-Offer Markets with Social Influence","type":"publication"},{"authors":["Andres Abeliuk","Franco Berbeglia","Gerardo Berbeglia","Felipe Maldonado","Pascal Van Hentenryck"],"categories":[],"content":"","date":1463443200,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1463443200,"objectID":"b6f6d91d72d36efe7d6e58a5bf7eb863","permalink":"http://felipemaldonado.github.io/publication/2016-aligning-pop/","publishdate":"2016-05-17T00:00:00Z","relpermalink":"/publication/2016-aligning-pop/","section":"publication","summary":"Social influence is ubiquitous in cultural markets and plays an important role in recommendations for books, songs, and news articles to name only a few. Yet social influence is often presented in a bad light, often because it supposedly increases market unpredictability. Here we study a model of trial-offer markets, in which participants try products and later decide whether to purchase. We consider a simple policy which re- covers product quality and ranks the products by quality when presenting them to market participants. We show that, in this setting, market efficiency always benefits from social influ- ence. Moreover, we prove that the market converges almost surely to a monopoly for the product of highest quality, mak- ing the market both predictable and asymptotically optimal. Computational experiments confirm that the quality ranking policy quickly identifies “blockbusters”, outperforms other policies, and is highly predictable.","tags":["Quality vs Popularity","Ranking policies"],"title":"Aligning Popularity and Quality in Online Cultural Markets","type":"publication"},{"authors":null,"categories":null,"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":1622234960,"objectID":"6f2ae24689dd626422f36a03d187ca38","permalink":"http://felipemaldonado.github.io/featured/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/featured/","section":"","summary":"Publications","tags":null,"title":"","type":"widget_page"},{"authors":["Felipe Maldonado"],"categories":[],"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":-62135596800,"objectID":"c125d2dc06f1c8295ae38f44dbafb0a4","permalink":"http://felipemaldonado.github.io/teaching/auction-theory-and-market-design/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/teaching/auction-theory-and-market-design/","section":"teaching","summary":"The field of market design studies how to construct rules for allocating resources or to structure successful marketplaces. It draws on the tools of game theory and mechanism design to identify why certain market rules or institutions succeed and why others fail. The field has become popular in the recent years with many applications in the sale of spectrum licenses, electricity markets, or the assignment of students to courses. After participating in the course, the participants understand methods and game-theoretical models of auctions as well as the fundamental problems in the design of combinatorial auctions. They are able to assess the properties of different auction formats, and the results of theoretical and experimental analyses. ","tags":["Combinatorial Auctions","Game Theory and Mechanism Design","Matching Markets"],"title":"Auction Theory and Market Design (IN2211)- Technical University of Munich","type":"teaching"},{"authors":["Felipe Maldonado"],"categories":[],"content":"","date":-62135596800,"expirydate":-62135596800,"kind":"page","lang":"en","lastmod":-62135596800,"objectID":"89af6f96d741afb983657dc2e6bfa717","permalink":"http://felipemaldonado.github.io/teaching/computational-economics/","publishdate":"0001-01-01T00:00:00Z","relpermalink":"/teaching/computational-economics/","section":"teaching","summary":"","tags":["Markov Chain"],"title":"Computational Economics (ECON4414)- Australian National University","type":"teaching"}]