15 research outputs found
The impact of the spot price modeling on the electricity portfolio optimization problem
No full textPrevious studies in the literature have suggested that, in deregulated markets, large consumers may adopt stochastic programming for the optimization of their electricity portfolio. Nevertheless, there may be several modeling approaches, characterized by different assumptions on the stochastic behavior of the spot price. Such different approaches could lead to different solutions of the electricity portfolio optimization problem. Besides, these solutions could vary also because of the impact of the risk aversion of each large consumer. In this paper, we then investigate how different spot prices model can lead to different solutions, generalizing the Value of the Stochastic Solution (VSS). Our aim is to build a decision support system that suggests the optimal procurement policy by using the most suitable spot prices model, based on the risk aversion of the decision maker. We evaluate our technique in a realistic case study in which the portfolio optimization problem is modeled as a two-stage problem solved with the Sample Average Approximation method
Integrating multi-stage stochastic programming and machine learning for the evaluation of policies in the electricity portfolio problem
No full textMulti-stage stochastic programming can support large consumers in developing electricity portfolios that balance the expected total cost and the risk level. Nevertheless, the adoption of multi-stage stochastic programming in real-world problems is often made difficult by the high computational burden required. In this paper, we present an innovative approach, called General Policy Function Approximation, that provides good solutions to the electricity portfolio problem in a limited computational time, owing to the integration of multi-stage stochastic programming and machine learning. Our approach improves the Policy Function Approximation (PFA) approach proposed by Defourny et al. [(2012). Multi-stage stochastic programming: A scenario tree-based approach to planning under uncertainty. Decision Theory Models for Applications in Artificial Intelligence (L. E. Sucar, E. Morales, F. Eduardo & J. Hoey eds). vol. 6. Hershey: IGI Global, pp. 97–144], by developing a single policy function generated from a larger amount of data. Owing to a realistic computational campaign, we show that our approach outperforms PFA both in terms of quality of the policy obtained, and in terms of time required
Job shop scheduling problem with human operators in manufacturing process
No full textThis work deals with complex job shop scheduling problems, in which each task requires two different resources, i.e., machines and human operators. While a machine is specified for each task, there are in general more operators enabled to performing it. The problem is to assign and sequence the tasks for each operator and sequence them on each machine in order to minimize a certain objective function. We address both makespan minimization, for which we propose two different euristics, and the related cyclic scheduling problem, proposing a new MILP formulation
Energy management practices: quantitative models for a large consumer in the Italian electricity market
No full textThe liberalization of energy market has allowed the development of energy management strategies that aim to reduce the total cost, guaranteeing an adequate service level with a minimum risk. Nowadays, these strategies are developed, above all, by Large Consumers (LC), which have at disposal several levers for the optimization of their energy consumption. In particular, several energy intensive LCs, such as telecommunication companies, could focus on the optimization of their purchasing process in the electricity market. Contract management consists of creating the best portfolio of energy contracts, choosing among flexible bilateral contracts, structured derivative instruments, and bids in the day ahead market. In particular, this thesis focus on a typical midterm electricity portfolio problem faced by an electricity intensive LC in the Italian electricity market. Its aim is to reduce the total cost of electricity contracts, guaranteeing an adequate service level with a minimum risk. Thanks to Multistage Stochastic programming (MSP) approach, a LC may define an adequate procurement policy, composed by an initial move (decisions to be taken in the present) and by a subsequent strategy that rebalances the portfolio during the subsequent stages within time horizon, following the evolution of the underlying uncertainty (Carrion et al., 2007). More specifically, the inference based research reported in this thesis aims at investigating quantitative mathematical models for energy management problems of a LC in the Italian market. All the mathematical models proposed in this thesis are built using real data: all the statistical models for the electricity spot and forward market are estimated using historical prices of the from 2009 to 2014. The internal demand that a LC must satisfy has been defined using historical energy consumption information from a real LC in the telecommunication sector.
1) Integrating multi-stage stochastic programming and machine learning for the evaluation of policies in the electricity portfolio problem
In stochastic multi-stage problems, the development of a policy and its assessment on out-of-sample scenarios can be obtained through the adoption of a Rolling Horizon Approach (RHA). This approach requires, at each decision stage, to solve a new scenario-based multi-stage stochastic model, using updated information about the uncertainty and the decision process (Conejo et al., 2010). The first stage optimal solution of this new problem is then implemented, new optimization model is build and so on. Using this approach, the initial move corresponds to the first implemented solution, while the purchasing strategy is composed by the sequential first stage decisions obtained by solving the appropriate multi-stage problems. However, there are no theoretical guarantees about the optimality of the policy obtained, and the computational time required for the policy development and assessment could be very high (Shapiro et al., 2009). An alternative approach, which could be called Nearest Neighbour Approach (NNA), can be based on solving the problem on a single scenario tree, obtaining an optimized decision for each node of the tree. Then, a policy can be defined by simulating an out-of-sample scenario, detecting its nearest scenario in the tree, and applying the corresponding decisions. Nevertheless, Nearest Neighbour Approach produces “unstable” policies, in the sense that their quality is strictly dependent on the starting scenario tree (Thiene & Vial , 2008).
Research Question 1 (RQ1): How can a LC define and assess good decision policy for the energy portfolio problem?
In this thesis, an innovative approach for the development and the assessment of a LC procurement policy is introduced (Murgia and Sbrilli, 2014). Thanks to the application of machine learning techniques, our approach could develop and assess a non-linear policy in a short time. Defourny et al. (2013) propose a similar approach, called Policy Function Approximation (PFA), which is based on the development of a family of policies, each one obtained starting from the decisions at all stages in a single scenario tree. Then, these policies are ranked thanks to their assessment on out-of-sample scenarios. Differently, the proposed approach, called General Policy Function Approximation (GPFA), is based on the development of a single policy, which is obtained by the application of neural networks techniques to the decisions at all stages in all scenario trees generated. Thanks to the larger amount of data used for the development of the policy, I obtained policies that, when assessed on out-ofsample scenarios, show a lower mean and variance than those obtained through other approaches previously proposed in literature. The application of our approach in electricity procurement problem allows LC management to easily define and evaluate different policies. In particular, LC management could take into account the effect of its risk aversion, thanks to the development of Pareto frontiers that show the trade-off between the expected procurement cost and the level of risk.
2) The impact of the spot price modelling on the electricity portfolio optimization problem SP models for energy portfolio management start from the definition of a set of discrete scenarios that represent the possible future values of the uncertainty. As a consequence, in order to build an adequate portfolio model, it’s necessary to define and estimate an adequate statistical model for the description of the evolution of the electricity spot price. The obtained statistical model should be able to handle the strong uncertainty that generally affects the electricity spot price. In particular, in the long term electricity prices are often characterized by a specific trend, seasonal cycles, and mean reversion, while in the short term they could be affected by weekly and daily cycles, volatility and spikes. Stochastic programming literature provides several models for electricity spot price, which are characterized by a specific way to consider the long term seasonal (LTSC) and the short term component. These components are generally analysed separately so to obtain more detailed and appropriate results (Most and Keles, 2010).
The combination of models for LTSC and the stochastic component supports LC in forecasting electricity spot prices, but also in pricing electricity forward contracts. In fact, the price of an electricity forward contract is related to the expected spot prices in its delivery period. Because the delivery period of a forward contract is generally equal or higher than one month, the correct forecasting of LTSC represents a more crucial, but also more difficult, issue for a LC. So, the analysis of the statistical performance of the forecasting models for electricity spot prices, and especially
for LTSC, could increase the LCs awareness in the development of their electricity procurement policies. Nevertheless, the agreement about the performance of these forecasting models for
electricity spot prices is not unanimous in the literature, given that they could produce very different results, even when analysing the same historical price series. Moreover, the forecast performance of these models in a given market and in a given period can be evaluated beyond doubt only ex-post. The choice of an inadequate model could lead a LC to implement an electricity procurement policy based on incorrect forecasts of forward and spot prices, which could induce LC to a too low (or too high) hedging level and, consequently, to high financial losses. The choice of the most appropriate among a set of candidate forecasting models for an uncertain process could be affected by the well-known model uncertainty, which has been widely analysed in finance literature, especially in the last decades.
Research Question 2 (RQ2): Which is the impact of the choice of the spot price statistical model on the developed decision policy?
In order to test the impact of model uncertainty on a LC procurement policy, I performed a set of experiments, each defined by two main parameters: LTSC models, chosen among the most reliable models developed in the literature and LC risk aversion, chosen among four different levels.
Given a level of LC risk aversion, I varied the level of market risk and the LTSC models used for spot price forecasting. So, for each configuration i, I defined a set of scenarios wi and infer a decision policy fi. Besides, for each configuration i, I computed the optimal value of the cost functional θi. Starting from these values, I built a comparison matrix, whose element (i, j) represents the Cross Value of the Stohastic Solution (CVSS). This indicator measures the relative distance from the
value of the cost functional, obtained by evaluating the decision policy fi on the validation scenarios wj, and LBi. This value indicates the loss that a LC faces when its strategy has been developed by using a configuration i, while the price uncertainty is instead described by a configuration j. When the configuration i and j differ for the choice of LTSC model (the level of risk premium), CVSS could support a LC to evaluate the impact of the alternative LTSC models (the alternative levels of risk
premium) on its procurement policy. In this way, a LC could detect and choose the configuration that minimises the maximum regret, which could be considered as the most robust. Results show that a wrong estimation of the LTSC of the statistical model may have a very strong impact on the procurement policy. I aim to deepen this insight by increasing the number of LTSC models under analysis. Finally, I aim to evaluate also the impact of the level of LC risk aversion, by comparing the results obtained in the four levels under investigation.
3) The Approximate Second Order Stochastic Dominance criteria for Long term contract management
In the technical literature about mathematical models in energy finance, the risk aversion of the decision maker is introduced using the so-called mean risk (MR) framework. This approach requires that the performance of the purchasing strategy should be evaluated on the basis of two factors: the expected value of the costs to be incurred for energy purchasing and a risk functional directly proportional to the variability of the chosen strategy. In current practice, one of the most widely used functional risk is the Conditional Value at Risk at a given confidence levelα For the problem under consideration, the CVaRα corresponds to the expected value of the costs incurred in the (1 − α)% of the worst scenarios. Intuitively, this value quantifies the costs in a subset of extreme scenarios, that identifies the right tail of the distribution of the costs. The popularity of CVaR comes from its computational tractability: in fact, that this indicator can be determined as the solution of a convex optimization problem, then can be easily included in a linear programming model. Hence, mean-risk based models are very convenient from the computational point of view. However, in the
mean-risk approach the risk aversion of the decision maker is simply included in the model through a parameter that weighs the risk component: the higher the weight associated with risk the greater the risk aversion of the decision maker. Despite its intuitiveness, this approach may underestimate the complexity of the decisionmaking process. On the contrary, Second-order Stochastic dominance (SSD) has been widely recognized as a sounder criteria of choice, due to its close relation with the utility theory. In particular, thanks to SSD it’s possible to express the preference of any risk-averse decision maker without explicitly specify a utility function. Using the SSD criteria it’s possible to improve MR solutions. Indeed, SSD-efficient solutions are not dominated by MR-efficient solutions with respect to the expected value and show a lover CVaRα for all the possible confidence levels, i.e less risky. This underlines the importance of choosing SSD efficient solutions.
Research Question 3 (RQ3): How can a LC find contract portfolios that are (approximately) SSD efficient?
In this thesis, I propose a new model for the optimization of the energy portfolio of a LC based on the concept of SDD . In particular, exploiting the link between second order stochastic dominance and conditional value at risk it is possible to define a multi-objective approach to find SSD-efficient solutions. Since the resulting model turns out to be intractable from the computational point of view, I propose an approximation numerically tractable, called Approximate Second Order Stochastic Dominance (ASSD). The proposed model is applied to a realistic case study regarding the long-term management of energy contracts portfolio of a LC in the Italian market. The case study highlights the difference of the obtained portfolio with respect to the MR solutions. Results shows that the proposed model may be useful for the risk assessment of the decision maker in a real case
A job shop scheduling problem with human operators in handicraft production
No full textThis paper deals with complex job shop scheduling problems. A (typically large) number of elementary tasks has to be carried out, according to precedence constraints defined by a task graph. As typical of production environments such as handicraft production and task processing requires two different resources, i.e. machines and human operators. While for each operation a given machine is specified, there are in general more human operators capable of performing it. The problem is to assign the tasks to the operators, sequence them on each operator and sequence them on each machine so that the overall makespan is minimised. This scheduling problem is NP-hard even if the task graph consists of three chains (three-job job shop), and there are two fully skilled operators. We propose two heuristics for this scheduling problem, based on two different ways of decomposing the problem. An extensive computational experience allows a comparison between the heuristic solutions and the one obtained solving a mixed-integer programming formulation of the problem. The experiments show that close-to-optimal solutions can be obtained in reasonable time on a PC. Our model is applied to a case study from leather manufacturing, and we also show its use as a decision support tool in skill planning
A Wall of Dates: How a Work of Art Can Make the 20th Century Readable, Audible and Traversable
No full textThe confrontation between the individual and history is at the heart of a work by the Italian, Berlin based artist, Daniela Comani: It Was Me. Diary 1900-1999, presented also at the LIV Venice Biennale.
Comani’s activity is oriented towards gender stereotypes, cultural habits, memory, and expressed through photographs, drawings, videos, installations, publishing.
It Was Me recounts the 20th century by concentrating a selection of epochal events in a virtual year of 366 days, without listing them in chronological order. The work has three versions: it can be listened to as a radio chronicle, in various languages; it can be read by leafing through a book; it can be looked at, printed on a large canvas, as a wall of dates and words. In the audio version, listening goes from January 1st to December 31st which correspond, respectively, to the foundation of the German Communist Party (1919) and to the escape from Cuba of the dictator Batista (1958).
In the book and in the display, access to data and dates is not necessarily sequential: the reader can go from one date to another, according to personal paths, curiosity, suggestions, checking the year of the event on the chronology provided.
The peculiarity of this selection lies in the fact that all the events reported are told by the author in the first person female: the artist expresses herself as if everything - two world wars, the fall of secular empires, Holocaust, dictatorial regimes, weapons of mass destruction, colonialism, capitalism, feminism, protest, hope for a better world - had happened to her, as if she were Hirohito or Einstein or Woolf or an anonymous survivor to terroristic attacks.
A short-circuit is triggered between the enormity of the facts and the individual, who assumes responsibility and - by means of artistic impact – is led to reflect on crucial issues in history
Tre puntate su Fortuna. Ventagli, libri-oracolo e web
No full textL'articolo analizza l'iconografia della fortuna dai rebus seicenteschi di Della Bella (proponendo una nuova interpretazione per un rigo del Rebus sulla Fortuna) all'immaterialità delle opere digitali, passando per i procedimenti creativi legati al caso nell'arte contemporanea e nei sistemi di ricerca.I. In the 17th century, the Florentine engraver Stefano Della Bella (1610-1664) realized two fans, one dedicated to Love and the other to Fortune. Both are in form of rebus – alternating letters and images – and illustrate Italian proverbs about the two topics. Fortune though, appears on the fan always as a woman with wheel or sail: the name of the goddess must be pronounced entire, whereas the other words are obtained by means of images and upper-case letters. In this paper, the third proverb on the fan is fully explained thanks to an interview with Carlo Lapucci (author of a dictionary of Italian proverbs 2007) who indicated the correct name of the part of the key ("ingegno") represented in the image.
II. A divination game with an old Penguin copy of Wuthering heighst by Emily Brontë, visible in the 1997 Mike Leighs' movie Career Girls, is one of the most recent examples of the tradition of bibliomancy, testified also in fictional literature. Excerpts of significant passages of novels in which books are consulted as oracle are collected and discussed, focusing on the creative aspects of this practice that, in 20th century – with the idea of chance – involves artistic movements such as Dada and Fluxus.
III. New media and the web offer up-to-date versions of bibliomancy: classical sacred books, as well as Tarot cards have been "transferred" into digital, allowing immediate interrogations. Even the 15th century Libro delle Sorti by Lorenzo Spirito Gualtieri can be consulted on line, through virtual dice rolls. The web, nevertheless, enhances the idea of fortune, of chance, of random (see the 'random article' in Wikipedia homepage), of serendipity
Marisa Volpi. Legami a doppio filo fra pittura, scrittura, lettura
No full textIl contributo presenta la figura della critica e storica dell'arte Marisa Volpi (1928-2015), personalità di spicco della critica d'arte degli anni Sessanta e Settanta, nonché scrittrice (premio Viareggio 1986) e autrice di racconti ispirati alle vite d'artista. Con alcuni esempi, viene messo in luce lo stretto legame fra l'attività di ricerca storica, l'elaborazione critica e la scrittura di Marisa Volpi.The contribute focuses on the intellectual figure of Marisa Volpi (1928-2015): art historian, professor, art critic, curator and writer (Viareggio Prix 1986). The author of this contribute runs the website www.marisavolpi.it, with the patronage of the Department of Art History and Performing media at Sapienza University, where Marisa Volpi's archive is situated
Dipinti che cambiano nome. Pirandello e la cultura dell'attribuzionismo
No full textL'articolo "Dipinti che cambiano nome. Pirandello e la cultura dell'attribuzionismo", propone un confronto tra una pagina de Il fu Mattia Pascal – in discussione è se l'autore di un dipinto esposto agli Uffizi sia Perugino o Raffaello – e la diffusione del metodo attribuzionistico di Giovanni Morelli, sullo sfondo di una cultura in cui il tema, politico e istituzionale, della nuova registrazione anagrafica dei cittadini italiani si intreccia con il pensiero, letterario e filosofico, dell'identità e delle sue incertezze.
Nello specifico, nell'articolo è proposto un rapporto fra l’episodio museale de Il fu Mattia Pascal e la cultura dell’attribuzionismo, diffusa in Europa nella seconda metà dell’Ottocento e di cui Pirandello poteva essere a conoscenza grazie al suo sodalizio con il critico e storico dell’arte Ugo Fleres. La pagina del romanzo pirandelliano è messa a confronto con alcuni passi dell’edizione italiana del volume Della pittura italiana. Studii storico-critici di Giovanni Morelli, figura di spicco della connoisseurship del secondo Ottocento.In the novel The Late Mattia Pascal (Il fu Mattia Pascal, 1904) by Luigi Pirandello, the protagonist, after escaping from his town and family, discovers that he has been by mistake declared dead. Blessed with the sudden chance to start a completely new life, he has assumed a new name (Adriano Meis) and settled down in Rome. A guest in the house where he lives notices that he frequently touchs his annular finger, as if he had a wedding ring: having to face her curiosity, Mattia Pascal/Adriano Meis invents an explanation. When he was twelve years old, he had visited Uffizi Gallery in Florence with his grandfather, an art expert. Looking at a Renaissance painting, the young boy had proposed that the author were not Perugino, as the label declared, but Raphael. Approving his “attribution”, the grandfather had rewarded him with a little ring, bought on one of the Ponte Vecchio shops. The essay Paintings that change their names proposes to connect this episode with the connoisseurship culture, diffused in Europe in the second half of 19th Century, and based on close observation of paintings’ details, such as noses, nails, fingers shapes, as involuntary marks and clues of artistic identity. One of the most important exponent of this method was Giovanni Morelli, whose new attributions of artworks changed the state of the art of European museums’ catalogues. The scene in The Late Mattia Pascal is compared with the first pages of art historian Giovanni Morelli volume on Italian Painting (a copy of it was in the library of Sigmund Freud), where an old Italian gentleman explains paintings to young visitors in Florence museums (a topos in the ékphrasis tradition since Filostrato) inviting to observe signs of the individual style of each painter.The connection is supported by the fact that Pirandello himself had been a painter, an art critic and an art historian, a close friend of Ugo Fleres (director of the National Gallery of Modern Art in Rome since 1908). Very interested in Renaissance painting, he had visited Perugia, observing Perugino and Raphael style. Attribution and change of identity, anagraphical documents, signature, baptism, close observation of details: these features are present both in Pirandello’s masterpiece as in art history of the period, suggesting affinity, relationship, a shape of time
