4 resultados para electricity market opening

em AMS Tesi di Dottorato - Alm@DL - Università di Bologna


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This thesis is a collection of essays about the instrumental use of commitment decisions to facilitate the completion of the European internal electricity market. European policy can shape markets in many ways, two most evident being regulation and competition enforcement. The interplay between these two instruments attracts a lot of scholarly attention. One of the major concerns in the competition vs. regulation debate is the instrumental use of competition rules. It has been observed that competition enforcement is triggered not only as a response to an anticompetitive harm occurring in the market, but that it sometimes becomes a powerful tool in the European Commission’s hands to pursue regulatory goals. This thesis looks for examples of such instrumentalisation in the context of electricity markets and finds that the Commission is very pragmatic in using all the possible instruments it has at hand to push forward its project of creating the internal electricity market. This includes regulation, competition enforcement and all sorts of political pressure. To the extent that commitment decisions accelerate sector-specific regulation and overcome political deadlocks, they contribute to the Commission’s energy policy goals. However, instrumentalisation of competition rules comes at a certain cost to competition policy, energy policy and, most importantly, to electricity markets themselves. Markets might be negatively affected either indirectly, by application of sector-specific regulation or competition policy building on previous commitment decisions, or directly, through the implementation of inadequate commitments in individual cases. Concluding, commitment decisions generally contributed to achieving the policy objectives of the internal electricity market, but their use for that purpose does not come without cost. Given that this cost is ultimately borne by the internal electricity market, the Commission should take a more balanced approach to the instrumental use of commitment decisions so that it does not do more harm than good.

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This paper analyzes the effect that different designs in the access to fnancial transmission rights has on spot electricity auctions. In particular, I characterize the equilibrium in the spot electricity market when financial transmission rights are assigned to the grid operator and when financial transmission rights are assigned to the firm that submits the lowest bid in the spot electricity auction. When financial transmission rights are assigned to the grid operator, my model, in contrast with the models available in the literature, works out the equilibrium for any transmission capacity. Moreover, I have found that an increase in transmission capacity not only increases competition between markets but also within a single market. When financial transmission rights are assigned to the firm that submits the lowest bid in the spot electricity auction, firms compete not only for electricity demand, but also for transmission rights and the arbitrage profits derived from its hold. I have found that introduce competition for transmission rights reduces competition in spot electricity auctions.

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La disciplina pubblicistica dell’energia elettrica presenta specificità rilevanti rispetto ad altri settori della regolazione economica. Il settore energetico si caratterizza infatti per una complessa regolazione, dovuta sia alle specificità dell’oggetto della disciplina, cioè l’energia elettrica come bene immateriale, sia alla molteplicità degli interessi pubblici coinvolti, che si innestano su fallimenti di mercato (i.e. il sistema a rete non duplicabile), sia agli obiettivi di politica internazionale e di sicurezza nazionale, che intercettano delicate interrelazioni con l’ambiente e il clima, come tutelati nel Green Deal, nelle normative europee e nazionali e negli accordi internazionali sulla decarbonizzazione e sullo sviluppo sostenibile. Inoltre, la filiera elettrica è “verticalmente integrata”, cioè suddivisa in attività diverse, cioè la produzione, il dispacciamento, la trasmissione, la distribuzione, la vendita all’ingrosso e al dettaglio di energia. Queste sono esercitate in regimi di mercato differenti: monopolio naturale (dovuto al carattere sub-additivo dei costi) per il dispacciamento, la trasmissione e la distribuzione di energia; libera concorrenza per la produzione e la vendita. L’esigenza di assicurare la concorrenza nel mercato energetico si contempera con la necessità di rispettare gli obblighi di servizio pubblico, in un delicato bilanciamento tra esigenze contrapposte. La Direttiva U.E. del 13 luglio 2009 n. 2009/72/Cee, all’art. 3, qualifica infatti la fornitura di energia elettrica come un servizio universale, attribuendo agli utenti il diritto di ricevere la fornitura e di mantenere prezzi ragionevoli, facilmente e chiaramente comparabili, trasparenti e non discriminatori.

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Let’s put ourselves in the shoes of an energy company. Our fleet of electricity production plants mainly includes gas, hydroelectric and waste-to-energy plants. We also sold contracts for the supply of gas and electricity. For each year we have to plan the trading of the volumes needed by the plants and customers: better to fix the price of these volumes in advance with the so-called forward contracts, instead of waiting for the delivery months, exposing ourselves to price uncertainty. Here’s the thing: trying to keep uncertainty under control in a market that has never shown such extreme scenarios as in recent years: a pandemic, a worsening climate crisis and a war that is affecting economies around the world have made the energy market more volatile than ever. How to make decisions in such uncertain contexts? There is an optimization problem: given a year, we need to choose the optimal planning of volume trading times, to meet the needs of our portfolio at the best prices, taking into account the liquidity constraints given by the market and the risk constraints imposed by the company. Algorithms are needed for the generation of market scenarios over a finite time horizon, that is, a probabilistic distribution that allows a view of all the dates between now and the end of the year of interest. Algorithms are needed to solve the optimization problem: we have proposed more than one and compared them; a very simple one, which avoids considering part of the complexity, moving on to a scenario approach and finally a reinforcement learning approach.